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SANS Tip of the Day - Fri, 11/13/2015 - 00:00
Make sure each of your accounts has a separate, unique password. Can't remember all of your passwords/passphrases? Consider using a password manager to securely store all of them for you.

Spam and phishing in Q3 2015

Malware Alerts - Thu, 11/12/2015 - 05:58

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Spam: features of the quarter Online dating

The dating theme is typical for spam emails, but in the third quarter of 2015 we couldn’t help but notice the sheer variety appearing in these types of mailings. We came across some rather interesting attempts to deceive recipients and to bypass filters, as well as new types of spam mailings that were bordering on fraud.

The main aim of spammers exploiting the dating theme is usually to advertise recently created dating sites that are still relatively unknown. The owners of these sites resort to spamming to attract the largest possible audience to their resource. The messages often address different categories of recipients, for example, dating sites for older people, married people or the religious.

Yet another type of advert is for marriage agencies offering a selection of brides (mainly from Russia and Ukraine) to foreign suitors. This type of spam is usually distributed in the English-language segment of the Internet. The messages contain an invitation to register on a site, a short text promising to find the perfect life partner and a link leading to the advertised site.

Q3 2015, the percentage of spam in email traffic accounted for 54.2% #KLReport #infosec

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Similar emails can also be sent from a “bride”. This type of spam is closer to the fraudulent tactics used by ‘Nigerian letters’. The email is supposedly written by a girl who provides a few details about herself, about how hard her life is in the Russian hinterland, and her dreams of meeting Prince Charming. A photo is often attached, though not necessarily a photo of the “bride” – it could easily be taken from someone’s social networking page and attached to make the message look more convincing. That’s why emails from different girls may contain the same photos. However, the messages vary: a host of synonyms are used to bypass spam filters. The usual channel for receiving feedback is via email. The address is different for each email – they are obviously created in large quantities on free email services for each mass mailing. After replying, the user will, at best, receive a notification that the address is non-existent. The worst case scenarios will see his address targeted by further spam mailings and he may even get caught up in a scam where the girl asks for money to buy a ticket to come and see him. Once she gets the money, she disappears without a trace.

A similar method is used to advertise dating sites “for adults”. The emails contain either an invitation to register on the site and a promise of intimate dating, or a message from a girl who is looking for a partner for intimate relations plus a link to the resource with her alleged profile. This type of spam is often disguised as personal notifications on social networking sites, as well as image or audio files sent via instant messengers. As a result, the site is hidden, and the user cannot clearly identify what it is until he follows all the links. Of course, the contents of these messages aim to arouse the recipient’s interest and make him click the links, often due to the flirty content or heavy hints and intimate photos.

And finally, yet another type of spam we detected in Q3 was quite blatantly fraudulent. During the quarter we observed a mass mailing that prompted recipients to send a text message to a specific telephone number; in return a girl promised to send intimate photos of herself. The text of the emails varied, as did the mobile numbers specified in them. We sent messages to some of the numbers and found that they were not premium-rate numbers as might be expected, and users were not charged for sending a text message. We got a reply from a girl, but after a couple of answers it became clear we were dealing with a robot whose task was to make us download an application so we could continue chatting and receive the promised photos. As a result, we received several text messages containing short links that led to an article about useful mobile apps that appeared in a well-known American newspaper. During the redirect to the article an archive with mobile malware was downloaded to the user’s phone.

Seasonal malicious spam

The amount of seasonal spam traditionally increases in summer. This is true for both advertising and malicious spam. The holiday season saw spam with a travel theme: fake notifications from booking services, airlines and hotels were used to spread malicious programs.

Fake notifications from major international airlines and booking services were detected by Kaspersky Lab as Trojan-Downloader.JS.Agent.hhy and Trojan-Downloader.Win32.Upatre.

We came across similar emails supposedly sent by popular airlines that had messages in French. The text informed recipients that the attachment contained an e-ticket. In fact, the ZIP archive contained Trojan.Win32.Xtrat Trojan and the DDoS bot Nitol (the module used to organize DDoS attacks).

In July, fraudsters tried to trick users by sending fake notifications on behalf of hotels. The message thanked the recipients for staying in their hotel and asked them to view the attached bill. The attached archive actually contained Trojan-Downloader.Win32.Upatre.dhwi, which in turn downloaded and ran Trojan- Banker.Win32.Dyre (viewed as 98. ***. **. 39/cv17.rar) by clicking the links written in the body of the downloader.

In addition to fake emails sent on behalf of well-known companies we observed a message in English from an individual. The email contained a request to change a room booking because some friends had cancelled.

The text in the email could easily be seen as a legitimate request from a client; however, the ZIP attachment contained Trojan-Downloader.JS.Agent.hhi that downloaded Backdoor.Win32.Androm.

Spammer tricks

The text in a standard phishing email is usually in the body of the message, while personal information is entered on a web page that opens after clicking a fraudulent link in the text, or in the HTML fields of a page attached to the email, or is sent back in a reply email. The latter is most typical when asking recipients to confirm the address and the password for an email account.

Q3 2015, Top 3 biggest sources of spam globally were the #USA, #Vietnam & #China #KLReport

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In Q3 2015, cybercriminals came up with a new way of distributing phishing emails and bypassing spam filters. The text of the phishing email and the fake link were included in a PDF document attached to the email. After clicking the link, a standard phishing page opened and the user was asked to enter his personal information. The majority of emails utilizing the new technique imitated bank notifications. The body of these messages usually contained a short text describing the problem; sometimes there was no text at all.

It should be noted that the spammers used well-known phrases and tricks in the text of the emails: notifications about an account being blocked, the need to pass a verification procedure, security issues, an investigation into phishing incidents, etc. As usual, the fraudulent links were masked by legitimate links and text fragments.

However, there were emails with detailed text in the message body providing genuine links to official bank resources. The phishing notification was included in the PDF attachment.

Our colleagues also came across a different type of phishing message using Mediabox objects in attached PDF files.

A Mediabox object is a document opened by a mouse click and used to redirect the user to a phishing website.

Statistics Proportion of spam in email traffic

Percentage of spam in email traffic, April-September 2015

After some relatively stable months in the second quarter the percentage of spam in global email traffic began to change again. A slight growth in July and August of 2015 was followed by a noticeable drop in September. As a result, the average percentage of spam in Q3 amounted to 54.19% – slightly higher than the average for the previous quarter.

Sources of spam by country

Sources of spam by country, Q3 2015

The US (15.34%) remained the biggest source of spam in Q3. Vietnam was second with 8.42% of global spam, compared to 3.38% in the previous quarter. China rounded off the Top 3 (7.15%) – its share remained unchanged from the previous quarter.

Russia’s share (5.79%) dropped by 2.03 p.p., pushing it from second to fourth position. It was followed by Germany (4.39%) and France (3.32%) – their shares changed only slightly compared to Q2.

Spam email size

Spam email size distribution, Q2 2015 and Q3 2015

The most commonly distributed emails were very small – up to 2 KB (79.05%). The proportion of these emails grew from the previous quarter (13.67 p.p.), while the share of emails sized 20-50 KB (3.32%) fell by approximately the same number of percentage points. The share of all other emails saw no significant change from Q2 of 2015.

Malicious email attachments

Top 10 malicious programs sent by email, Q3 2015

Trojan-Spy.HTML.Fraud.gen remained the most popular malicious program sent by email. This program is a fake HTML page sent via email that imitates an important notification from a large commercial bank, online store, or software developer, etc.

Second and ninth places in the Top 10 are occupied by Trojan-Downloader.JS.Agent.hhi and Trojan-Downloader.JS.Agent.hfq, respectively. Both are an obfuscated Java-script. The downloaders use ADODB.Stream technology that allows them to download and run DLL, EXE and PDF files.

Trojan-Downloader.VBS.Small.lj and Trojan-Downloader.VBS.Agent.aqp came third and sixth, respectively. These VBS scripts, which also use the ADODB.Stream technology, download ZIP archives and run malware extracted from them.

Q3 2015, Upatre was the most common malware family sent by email #KLReport

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Trojan-Downloader.MSWord.Agent.oq came fourth. This malicious program is a DOC file with embedded VBS macros that run when the document is opened. The macros download another malicious VBS script from the cybercriminals’ site and run it on the victim’s computer.

Email-Worm.Win32.Mydoom.l rounds off the Top 5. This network worm is spread as an email attachment via file-sharing services and writable network resources. It harvests email addresses from infected computers so they can be used for further mass mailings. The worm also enables attackers to remotely control the infected computer.

Trojan-Downloader.HTML.Meta.ay, Trojan-Downloader.HTML.Agent.aax and Trojan-Downloader.HTML.Meta.aq were seventh, eighth and tenth in the rating, respectively. They all are HTML pages which, when opened, redirect users to a rigged site. Once there, a victim usually encounters a phishing page or is asked to download a program – Binbot, a binary option trading bot. The three malicious programs spread via email attachments and the only difference between them is the link which redirects users to the rigged sites.

Malware families

As in the previous two quarters, Upatre (9.46%) was the most common malware family. Malware from this family downloads the Trojan banker known as Dyre, Dyreza, Dyzap.

The MSWord.Agent family (5.55%) remained in second position. To recap, these malicious programs are DOC files with an embedded macro written in Visual Basic for Applications (VBA), which runs on opening the document. It downloads and runs other malware, such as malicious programs from the Andromeda family.

In third place was the VBS.Agent (5.44%) family. Unlike MSWord.Agent, the malicious programs of this family use the embedded VBS script. To download and run other malware on the user’s computer they use the ADODB.Stream technology.

Countries targeted by malicious mailshots

Distribution of email antivirus verdicts by country, Q3 2015

There were some significant changes in the Top 3 countries targeted most often by mailshots in Q3 2015. Russia’s appearance in third place (7.56%) was the biggest surprise: its share grew by 2.82 p.p., pushing it up two places from fifth.

Germany (18.47%) remained on top, although its contribution dropped by 1.12 p.p. compared to Q2. Brazil ended the quarter in second place (11.7%) – the amount of malicious spam originating from there almost doubled compared to Q2.

The UK (4.56%), which was second in Q2, ended Q3 in sixth place.

Special features of malicious spam

In spam traffic at the beginning of September we came across a large-scale malicious mass mailing containing emails imitating a non-delivery auto-reply sent by an email server. The text and subject of the message looked very similar to an automatic notification; however, the sender address belonged to an individual, which raised doubts about the legitimacy of the email. The attached ZIP archive named Google_drive_1711 was also suspicious because notifications from email services do not normally contain attachments. Closer inspection revealed that the archive included Trojan Trojan-Downloader.JS.Agent.hhi, which in turn downloaded Backdoor.Win32.Androm.

At the beginning of the third quarter cybercriminals were actively sending out emails in French containing macro viruses. The macros that we detected belonged to a category of Trojan downloaders and were used to download and install the banking Trojan Dridex on victim computers. To deceive the recipient, the fraudsters imitated a notification about the receipt of an order or an invoice.

In July, spammers exploited the theme of loans to spread malicious files that are now traditional for advertising spam. Some scammer emails offered a loan attracting potential customers with very favorable terms, low interest rates, etc. Other messages notified the recipient that his loan application had been approved. Interestingly, this content can also be seen in ordinary advertising spam, but malicious spam usually contains an attachment masquerading as detailed information about the loan.

Interestingly, malicious emails with Trojan-Downloader.Win32.Upatre in the attachment were sent to employees at different companies.

Phishing

In Q3 2015, the Anti-Phishing system was triggered 36,300,537 times on computers of Kaspersky Lab users, which is 6 million times more than the previous quarter. Of them, 15,764,588 attempts were blocked by our heuristic detection components and 20,535,949 by signature detection components. 839,672 phishing wildcards were added to the Kaspersky Lab databases.

The country where the largest percentage of users is affected by phishing attacks was once again Brazil (21.7%). In Q3 2015, the share of those attacked increased by 11.33 p.p., meaning Brazil returned to the same sort of figures last seen in Q1.

Geography of phishing attacks*, Q3 2015

* Number of users on whose computers the Anti-Phishing system was triggered as a percentage of the total number of Kaspersky Lab users in the country

The percentage of attacked users in Japan and China also grew considerably (+10.9 p.p. and +7.85 p.p., respectively), which saw these countries ranked second and third in the rating.

Top 10 countries by percentage of users attacked:

Country % of users 1 Brazil 21.07 2 Japan 16.86 3 China 15.08 4 Vietnam 14.5 5 Bangladesh 13.32 6 Nigeria 13.05 7 Russia 12.91 8 Kazakhstan 12.85 9 India 12.44 10 Columbia 12.25 Organizations under attack

The statistics on phishing targets is based on detections of Kaspersky Lab’s anti-phishing component. It is activated every time a user enters a phishing page while information about it is not included in Kaspersky Lab databases. It does not matter how the user enters this page – by clicking the link contained in a phishing email or in the message in a social network or, for example, as a result of malware activity. After the activation of the security system, the user sees a banner in the browser warning about a potential threat.

In the third quarter of 2015, the ‘Global Internet portals’ category (30.93%) topped the rating of organizations attacked by phishers although its share decreased by 11.42 p.p. from the previous quarter. The share of ‘Social networking sites’ (21.44%) increased by 6.69 p.p. In third place came ‘Banks’ with 18.07% (+4.65 p.p.). The ‘Online games’ category also increased by half and accounted for 4.02%.

Distribution of organizations affected by phishing attacks, by category, Q3 2015

The proportion of phishing attacks on organizations in the ‘Cloud data storage’ category increased by 0.26 p.p. and amounted to 1.06%. Users are increasingly using cloud storage technology, thus attracting the attention of cybercriminals. The stolen information is used for blackmail, sold to third parties or used in targeted attacks.

This type of phishing is often distributed via email or social networks in the form of a message inviting users to download a document allegedly uploaded to a popular cloud service. Messages can arrive from a compromised account from a user’s friend list or, in the case of email, on behalf of a cloud service administrator.

Q3 2015, Anti-Phishing system was triggered more than 36M times on computers of @Kaspersky Lab users #KLReport

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Phishing pages imitating well-known cloud storage sites are used to distribute various malicious programs. In such cases, a user automatically downloads a malicious program to his computer by clicking the link on the page.

Below is an example of an attack where the user is asked to download an important PDF document. The link in the email leads to a phishing page imitating the site of the popular cloud service Dropbox.

Example of a phishing attack targeting users of Dropbox

In addition to stealing data stored in the cloud and spreading malware, cybercriminals often use the Dropbox name to steal the victim’s email account data.

Example of a phishing page using the Dropbox brand

Here is yet another example of phishing, with the scammers trying to steal the user’s AppleID and password for iCloud.

Example of a phishing attack on iCloud users

Among other things, if successful, the attackers gain access to any content purchased by the user as well as his email account.

Top 3 organizations attacked

Fraudsters continue to focus the greatest part of their non-spear phishing attacks on the most popular brands. In this way they are trying to increase the chances of success for their latest phishing attack. In more than half of cases the heuristic component of Anti-Phishing is triggered when a user follows a link to phishing pages hiding behind the names of more than 30 well-known companies.

The Top 3 organizations most often attacked by phishers account for 26.39% of all phishing links detected in Q3 2015.

Organization % of all detected phishing links 1 Yahoo! 15.38 2 VKontakte 9.44 3 Facebook 8.95

In Q3 2015, the leading three organizations targeted by phishers saw a few changes. Yahoo! remained top with 15.38%, although its share almost halved (-13.65 p.p.). The Russian social networking site VKontakte (9.44%) came second. Facebook (8.95%) fell by 1.49 p.p. and moved from second to third place.

Conclusion

In Q3 of 2015, the percentage of spam in email traffic accounted for 54.2%, a 0.8 p.p. drop from the previous quarter. The Top 3 biggest sources of spam distributed worldwide were: the US (15.3%), Vietnam (8.4%) and China (7.2%).

The holiday season saw an increase in tourism-related malicious spam. Cybercriminals sent out fake notifications from well-known booking services, airlines and hotels, as well as emails from individuals. They typically included attached archives with different Trojan downloaders.

Trojan-Spy.HTML.Fraud.gen remained the most popular malicious program sent by email. As in the previous two quarters, the rating of the most popular malware families was topped by Upatre. Germany topped the ranking of countries whose users were most often targeted by mailshots – 18.5% of antivirus detections were registered there.

A particular feature of Q3 was a new trick used in phishing emails – in order to bypass spam filters they placed the text of the email and fraudulent link in an attached PDF document rather than in the message body.

In Q3, Kaspersky Lab solutions blocked more than 36 million attempts to follow links to phishing pages, which is 6 million more than in the previous quarter. The country where the largest percentage of users is affected by phishing attacks was once again Brazil (21.7%).

When Away

SANS Tip of the Day - Thu, 11/12/2015 - 00:00
Leaving your seat? Ctrl--Alt--Delete! Make sure you lock your workstation or laptop while you are away from it. On a Mac? Try Control--Shift--Eject/Power.

Beaches, carnivals and cybercrime: a look inside the Brazilian underground

Malware Alerts - Wed, 11/11/2015 - 09:58

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Introduction

The Brazilian criminal underground includes some of the world’s most active and creative perpetrators of cybercrime. Like their counterparts in China and Russia, their cyberattacks have a strong local flavor. To fully understand them you need spend time in the country and understand its language and culture.

The Brazilian underground generates quite a lot of cyberthreats – mainly banking Trojans and phishing campaigns. These attacks can be quite creative and are designed to reflect the local landscape. In 2014, Brazil was ranked the most dangerous country for financial attacks, and the Brazilian banking Trojan, the ChePro family, was ranked the second most widespread Trojan after ZeuS.

Countries most affected by banking Trojans in 2014

The picture for phishing attacks is not that different, with Brazil also ranked in first place worldwide. Not surprisingly, quite a number of the brands and companies that feature in the most frequently attacked list are Brazilian.

Countries most attacked by phishing attacks in 2014

Brazilian cybercriminals are adopting techniques that they have imported from Eastern Europe, inserting it into local malware to launch a series of geo-distributed attacks. These can include massive attacks against ISPs and modems and network devices or against popular, nationwide payment systems such as Boletos.

To understand what is going on in the Brazilian cybercriminal underground, we would like to take you on a journey into their world, to explore their attack strategy and their state of mind. We will look at the underworld market for stolen credit cards and personal data, the new techniques used in local malware and the ways in which they are cooperating with criminal in other countries.

For many people, Brazil is a country famous for its culture, beaches, samba and carnivals. For security professionals, it is equally renown as a prominent source of Banking Trojans.

Like Bonnie and Clyde: living the crazy life

The first impression you get is that Brazilian criminals like to flaunt how much money they have stolen and the high life they lead as a result of this. They compare themselves to Robin Hood: stealing from the ‘rich’ (in their eyes the banks, the financial systems and the government), in favor of the ‘poor’ (themselves). This is a widely-held conviction: they don’t regard themselves as stealing from individuals who bank online, but from the banks, since, according to local laws financial institutions are obliged to reimburse the victim for any money lost through theft.

There is a widespread sense of impunity, especially because, until recently cyber-crime was not legally defined as criminal activity under Brazilian law. The Carolina Dieckman law (named after a famous actress whose nude pictures were stolen from her computer) was approved in 2013, but the law is not very effective in punishing cybercriminals as the penalties are too lenient and the judicial system is very slow. It is very common for attackers to be arrested three or four times only to be released again without charge. The lack of effective legislation to combat cybercrime and high levels of police corruption provide the icing on the cake.

A strong indicator of just how immune to prosecution the cyber-criminals feel can be seen in the fact that it’s very easy to find videos and pictures of them online or to access their profiles on social networking sites. Invariably, they can be seen flaunting what appears to be stolen money, celebrating the high life, paying for prostitutes in Rio during the carnival, and more.

Brazil has achieved worldwide notoriety as a place where many ‘Bonnie and Clyde’ types are living decadent lives. How much do they steal? Quite a lot. According to the Brazilian Federation of Banks (FEBRABAN), in 2012 local banks lost 1.4 billion of reais (around US$500 million) paying for fraud perpetrated via Internet banking, by telephone, or through credit card cloning.

The target audience for cybercrime in Brazil is significant: the country has more than 100 million Internet users, 141 million citizens eligible to use Brazil’s e-voting system and more than 50 million people who use Internet banking services daily.

There are online videos celebrating the criminal life, like this song, the “Hacker’s Rap”. The lyrics celebrate the life of the criminals who use their knowledge to steal bank accounts and passwords:

The lyrics say: “I’m a virtual terrorist, a criminal; on the internet I spread terror, have nervous fingers; I’ll invade your PC, so heads up; you lose ‘playboy’, now your passwords are mine”.

Card-skimmers also celebrate and flaunt their profits in the “Cloned credit card rap”, also available on Youtube:

The lyrics include the words: “You work or you steal, we cloned the cards, I’m a 171, a professional fraudster and cloner, we steal from the rich, like Robin Hood, I’m a Raul…”

Recently the Brazilian Federal Police arrested the owner of a three million reais luxury mansion bought with funds stolen using Boleto malware. In Brazil, cybercrime pays, and pays very well.

C2C: Cybercrime to Cybercrime

As is the case with other underground fraternities, Brazilian cybercriminals are organized in small or medium-sized groups, each with their own expertise, selling their services to each other or working together. ‘Independent’ criminals are also common, but in general, most need to collaborate to do business.

The most common channels used by the Brazilian underworld to negotiate, buy and sell services or malware are Internet Relay Chat (IRC) channels. Some of them also use social networks such as Twitter and Facebook, but most of the juicy content is hidden inside IRC channels and closed forums that you can only join by invitation or with endorsement from an existing member. In these IRC chats criminals exchange data about attacks, hire out services among themselves, and sell personal data from hacked websites, while coders sell their malware and spammers sell their databases and services. These are true C2C (Cybercrime to Cybercrime) operations. The two most popular IRC networks used for such activity are FullNetwork and SilverLords.

However, a very common problem among the criminal fraternity is what it calls “calote” or deadbeats – those people who steal from the thieves, who buy criminal services or software underground without paying the seller. Revenge is taken quickly and in one of two ways. Firstly, the bad player may be “doxed”: their real identity published with the aim of alerting Law Enforcement. Secondly, they may find their name added to a big reputation database of bad and good debtors. This ‘black’ and ‘white’ list enables the ‘community’ to protect itself by checking out the reputation of a customer before doing business with them.

An underground reputation system from Fullnetwork.org: protection against deadbeats

“Doxing” and other attacks on competing gangs are common among the Brazilian underground – some groups even celebrate the arrest of other cyber-crooks. That’s what happened with Alexandre Pereira Barros, responsible for the SilverLords network. He and three other cybercriminals were arrested by the Brazilian Federal Police in April 2013 after a series of fraud attacks against financial systems, credit card cloning, hacktivism attacks, and more. The group owned a lottery retailer in the state of Goias, responsible for theft of $250.000. To ‘celebrate’ their arrest, other criminals posted a video on Youtube, in revenge for unpaid debts:

Brazilian cybercriminals arrested in 2013 – unfortunately, they did not end up in jail after all

A typical Brazilian cybercrime group include four or five members, but some groups can be bigger than that. Each member has their own role. The main character in this scenario is the “coder”, the person responsible for developing the malware, buying exploits, creating a quality assurance system for the malware and building a statistical system that will be used by the group to count victims; and then putting everything in a package that can be easily negotiated and used by other criminals. Some coders don’t limit themselves to a single group and may work with several, and most prefer to not get their hands dirty with any stolen money. Their earnings come from selling their creations to other criminals. A coder could be a leader of a group, but this is not common. They are rarely arrested.

Every group has one or two spammers, responsible for buying mailing lists, buying VPSs and designing the “engenharia” (the social engineering used in the mail messages sent to the victims). Their role also involves spreading the infection as widely as possible. It´s common to find spammers with experience in the defacement of web servers that then allow them to insert a malicious iframe into infected websites. Spammers don’t have a fixed salary: their earnings come from the number of people infected. That is why the coder needs to build a victim-counter into the malware, as this information is used to calculate how much the spammer will receive.

The group also has a recruiter, responsible for hiring the money mules (also known as “laranjas”). This is a very important task because this person will be in direct contact with people or hold responsibility for external activities, such as for coordinating the things necessary for transferring the money or withdrawing it from ATMs, paying the bills (generally at a lottery house) or receiving the products bought online with the stolen credit cards – do the “correria” (foray). It´s common for the people in this role to recruit their own family members to work as money mules, as they can earn up to 30% of the sums stolen and distributed among the money mule accounts. Generally, the money mules are the first to be arrested in police operations, followed by the recruiter.

The real leader of the group is responsible for coordinating the other members and all the activites, negotiating new “KLs” (keyloggers) with a coder, requesting a new “engenharia” from the spammers, or do the “correria” with recruiters. They are also responsible for recruiting new members to the group and negotiating their wares in with other criminal groups. Roles are not fixed; some members may perform a number of functions and work with more than one group, and their earnings may vary. Some criminals prefer to work independently, selling their services and goodies to several groups.

And some criminals have opened web stores to sell their goods and promote their services in a better and more user-friendly way. In these stores one can buy cryptors, hosting services, coding services for new Trojans, etc. That was the purpose of the “BlackStore” (now offline). Let’s check the prices of their ‘goodies’:

A “crypter” 100% undetected, R$ 100 (U$ 30.00)

  • Compatible with Delphi and VB
  • 100% undetected by 30 AVs
  • Compatible with more than 98 RATs
  • Compatible with more than 73 botnets
  • 30 days of crypter services

Hosting: US$17
A perfect place to host your phishing attack or malware, or even a malicious script.

  • Fast hosting
  • Unlimited MySQL
  • Domain already included
  • Mail accounts
  • 24/7 support

Coding services: US$170
“We turn your idea in something concrete. Just bring us what you have in mind, your project or application, we’ll code it! We work with:
coding from desktop
web programming
compatible with all OSs
compatible with all browsers
system free of bugs
license system”

    Tester of stolen credit cards: US$130
    “Check out the most recent and updated credit card tester, made for the CCS test, without the CVV data”

    • Test Visa, Master, Diners, Elo
    • Clean and beautiful design
    • Source code clean, without bugs

    Check out the pictures of the application on our database!”

    DNS Network US$1500
    Most advanced system. The change of the DNS allows for real-time changes on the victim’s computer

    • Open popup when accessing a website
    • Open a fake page when visiting a certain website
    • Sniff all the communication server-client
    • Insert iframes with Adsense
    • Insert banners to of fakecredit card giveaways
    • Complete admin panel

    Malicious Java applet: US$25
    System most used to infect. Using Java applets you can infect dozens of people easily.

    • Control panel
    • Stats
    • More than 10 domains with direct link
    • 100% undetected

    Viral Facebook: US$20
    New viral on Facebook, the most versatile system to “Like” + “Share”. Spread a malicious link fast, using few “share” your viral spread quickly. We offer a complete pack + domain + hosting

      VPS Spam sender: US$20
      “The most powerful system to send spam at the moment. VPS sending 30.000 messages in 30 minutes.”

      • all configurations possible
      • reboot, format and turning off options
      • include scripts to send spam

      SPAM PHP system: US$10
      Spam PHP for those who want to make a small investment, great tool for those who want a basic spamming system, for beginners.

      • 20,000 spam per hour
      • 30 days warranty
      • 80% of messages delivered

      KL (Keylogger): US$ 300
      “Keylogger for those who want quality in stolen banking information. With an admin panel to check all infections, saving the info in your mail”

      Targeted banks:

      • HSBC
      • Itau
      • Caixa

      As a “professional” store, they also offer a receipt for your purchases:

      Honest thieves: proof of your underground purchases

      The professionalization of organized cybercrime, as observed in Eastern Europe, is now adopted by the Brazilian crime underground. Investment in technology and marketing is aimed at increasing their profits. In some closed forums criminals have even started advertising their services in a clear attempt to attract newcomers not used to developing their own tools:

      The text says: “Buying any social engineering kit you also earn kits for banker, credit card and frequent flyer miles. 1 million free spam messages, from Bruno Dias smart solutions”. Other services that are increasingly offered include websites offering “malware as service”, cryptors, FUDs (fully undetected malware) and a complete system to manage information about stolen banking accounts:

      “FUD as a service”, encryption service for already detected trojans

      An “admin panel” manages the complete system that allow attackers to control infected machines, collect banking data, and bypass two-factor authentication (2FA) in any form (SMS, token, OTPs (one-time password cards) and more). Some systems also allow for the control of websites and domains used to spread the malware and to send spam and manage mail lists, all in a single solution.

      Remote access tool sold on the underground intended to bypass the 2FA of Brazilian banks

      The goods on offer also include DDoS attacks. Using the power of thousands of infected computers it’s not difficult to perform a distributed denial of service for other criminals, using SYN flood, amplified UDP, and more. The prices are listed below: 300 seconds: $8.3; 450 seconds: $13; 1000 seconds: $28; 3600 seconds: $40.

      DDoS for hire: takedown your target paying by seconds of attacks

      How much does your credit card cost?

      Credit card dumps are among the most valuable data exchanged among criminals. These have often been cloned in different ways, including chupa cabras (skimmers) on ATMs and point-of-sale terminals, phishing pages, keyloggers installed on victims’ PCs, and more.

      Brazil has one of the highest concentrations of ATM terminals, according to the World Bank. There are more than 160,000 opportunities for fraudsters to install a skimmer (also known as a “Chupa Cabra device”), and they do this all the time. Even during the day you can see them hanging about, wearing flip-flops and beachwear and in a very relaxed mood, installing skimmers in a crowded bank:

      When it comes to credit card cloning, Brazil has some of the most creative and active criminals. Fortunately, most of the cards in use have CHIP and PIN technology built in. Despite recent news revealing some security flaws in this protocol, CHIP and PIN cards are still more secure and harder to clone than magnetic swipe cards. Because these EMV chips are used all over the country, most of the cloning activity happens online, using phishing attacks, fake bank pages, fake giveaways and compromised e-commerce portals, offering an expensive product for very attractive price. If you are engaged in any type of online business, sooner or later your card will be attacked: via phishing or through compromise of the e-commerce portal.

      These highly sought-after dumps are sold online through specialized websites or even through IRC channels. And it’s not just carders and cybercriminals who are involved in this underground business, but many ‘traditional’ criminals connected to drug trafficking and other illegal activities.

      The price of a cloned credit card depends in the bank, the country of origin, etc.

      • Infinity: flags such as American Express or international cards are sold at $42 apiece
      • Platinum: cards from multinational banks, $40 apiece
      • Black: cards by $30 apiece
      • Gold/ Premier: $25 apiece
      • Classic: from national banks, $22 apiece

      Ad of a criminal selling dumps of stolen credit cards: you can even pay for it with your own credit card

      Data breach incidents fueling cyberattacks

      The Brazilian underground is hungry for personal data – and this allows cybercriminals to monetize identity theft, offering opportunities to buy products using “laranjas” or money mules, or even collect this data to empty your bank account, as several online services ask for personal data to confirm a customer’s identity.

      Unfortunately, the country does not yet have specific laws in place to protect personal data – at this time politicians are still evaluating their options. As a result, data breaches in government organizations and private companies are widespread. Affected businesses currently are not obligated by law to contact customers affected by the breach or even to inform them that an incident has taken place.

      Recently, we observed some very serious data breach incidents affecting major websites, and involving databases from the government, Receita Federal (IRS) and other institutions. It is common to find leaked databases being sold underground, such as the database of DETRAN (Traffic Department), with data on five million citizens costing only US$50:

      Flaws on government websites are critical. In 2011 two very serious flaws in the Labor Ministry website exposed an entire database with six months’ worth of data on every citizen in the country. A flaw in the website’s security left sensitive data out in the open, with only a CPF number (Brazilian SSN) required to obtain further information about a person.

      The CPF is one of the most important documents for anyone living in Brazil. The number is unique and is a prerequisite for a series of tasks like opening bank accounts, to get or renew a driver’s license, buy or sell real estate, obtain loans, apply for a jobs (especially in the public sector), and to get a passport or credit cards. Leaked data makes it possible for a cybercriminal to impersonate the victim and to steal their identity in order to, for example, get a loan from a bank.

      This is a case of where a data leak meets the phishers. Information of such quality can only be obtained through data leak incidents. Not surprisingly, it is common for the Brazilian media to spot criminals selling CDs carrying data from the Brazilian IRS system which includes a lot of sensitive data, including the CPF numbers. You can find criminals selling CDs full of leaked database from several sources for a mere $100. As a result of such data breaches, Brazilian phishers have created attacks with messages displaying the complete name and the CPF number of the victim in an attempt to add legitimacy to a fake message. Attacks such this one have happened regularly since 2011:

      A phishing message displaying the complete name of the victim and their CPF number

      The abundance of personal data leaked from several sources has allowed Brazilian criminals to establish online services offering a searchable database with personal data from millions of citizens. Despite the efforts of the authorities to take down such websites, new services are created every month.

      Having the CPF number is enough to find all your personal data

      The problem of data brokers

      Another problem related to the bad management of personal data is “Data brokers”, companies that collect information and then sell it on to companies that use it to target advertising and marketing at specific groups; or to verify a person’s identity for the purpose of fraud detection; or to sell to individuals and organizations so they can research particular individuals.

      Local companies such as Serasa (now acquired by Experian) are a common target of phishers and malware authors. As they offer the biggest database in the country regarding fraud protection, and carry a complete profile of personal data for every citizen, the stolen credentials to access this database are valuable among fraudsters.

      So, not surprisingly many fraudsters resell the results of their access to data broker services using stolen customer credentials, in packs that cost US$30 per 15 days or US$50 for 30 days of full access:

      Other criminals go further, and build their own data broker services. Owners of these services market them to other fraudsters, offering a comprehensive package to search databases leaked from the government as well as those obtained from private sources. Such widespread activity gives the impression that in Brazil cybercrime will always be able to reach you, one way or another.

      Govern and Data broker’s database together in the same underground service

      To advertise their services, fraudsters use all channels, even social networks like Facebook. In a dossier published by Tecmundo they found evidence of public employees involved in the scheme, selling databases and credentials.

      Access to stolen data service advertised on Facebook

      How phishing attack compromised the Amazon forest

      Could you imagine a phishing attack compromising the biggest rainforest in the world? That is what happened with IBAMA, the Brazilian Institute of Environment and Renewable Natural Resources. IBAMA is responsible for limiting the cutting of hardwood trees in the Amazon region, ensuring that only authorized companies are able to do that.

      In a series of attacks against IBAMA’s employees (probably using phishing emails like the one below), Brazilian criminals were able to steal credentials and break into IBAMA’s online system. Then they unlocked 23 companies previously suspended for environmental crimes, allowing them to resume extracting wood from the forest. In just 10 days these companies extracted $11million in wood. The number of trees cut illegally was enough to fill 1,400 trucks.

      Phishing page of IBAMA: to steal credentials and cut woods in the forest

      Underground cooperation with Eastern Europe

      We have sufficient evidence that Brazilian criminals are cooperating with the Eastern European gangs involved with ZeuS, SpyEye and other banking Trojans created in the region. This collaboration directly affects the quality and threat-level of local Brazilian malware, as its authors are adding new techniques to their creations.

      It’s not unusual to find Brazilian criminals on Russian underground forums looking for samples, buying new crimeware and ATM/PoS malware, or negotiating and offering their services. The first result of this cooperation can be seen in the development of new attacks such the one affecting Boletos payments in Brazil.

      Brazilian bad guy writing in (very bad) Russian, selling access to 400 infected PoS devices

      They have also started to use the infrastructure of Eastern European criminals, sometimes buying bulletproof hosting or renting it. “João de Santo Cristo” (a fictional character that appears in a popular Brazilian tune) was one of them, buying and hosting 14 Boleto malware domains in Russia:

      Not surprisingly we have started to see Russian websites hacked into and hosting fake Boleto websites:

      These facts show how Brazilian cybercriminals are adopting new techniques as a result of collaboration with their European counterparts. We believe this is only the tip of the iceberg, as this kind of exchange tends to increase over the years as Brazilian crime develops and looks for new ways to attack businesses and regular people.

      Advances in local malware

      The contact with Eastern European cybercrime affects the quality of Brazilian malware. For example, we found in Boleto malware exactly the same encryption scheme that is used in payloads by ZeuS Gameover.

      Encrypted payload of Boleto malware: the same encryption used by ZeuS

      We also saw, for the first time, Brazilian malware using DGA (Domain Generation Algorithm). Trojan-Downloader.Win32.Crishi was one of them, distributed in messages like this one:

      Further evidence of advances in Brazilian malware due to the cooperation with Eastern European criminals can be seen in the use of fast flux domains in Boleto attacks.

      Conclusion

      Brazil is one of the most dynamic and challenging markets in the world due to its particular characteristics and its important position in Latin America. The constant monitoring of Brazilian cybercriminals’ malicious activities provides IT security companies with a good opportunity to discover new attacks related to financial malware. In some cases these attacks are very unique as happened with the usage of malicious PAC files.

      Message from bad guys in a malicious PAC file to yours truly: reaction due a good detection

      To have a complete understanding of the Brazilian cybercrime scene, antimalware companies need to pay close attention to the reality of the country, collect files locally, build local honeypots, and retain local analysts to monitor the attacks, mostly because it’s common for criminals to restrict the reach of the infection and distribution of their creations to Brazilian users. As happens in Russia and China, Brazilian criminals have created their own, unique reality that’s very hard to understand from the outside.

      Microsoft Security Updates October 2015

      Malware Alerts - Tue, 11/10/2015 - 17:13

      Microsoft posted four critical bulletins today, along with another eight rated Important and lesser. Microsoft’s summary is at the Technet site. All in all, the software maker is patching a large number of vulnerabilities this month, with 37 CVE listed vulnerabilities being fixed with the four critical Bulletins alone. On the bright side, Microsoft claims that none of these exploits are being publicly exploited at the time of notification.

      Software affected with Bulletins rated critical are listed here (MS15-112, MS15-113, MS15-114, MS15-115):

      • Web browsers Microsoft Edge and Internet Explorer
      • Windows Journal
      • Windows’ font handing code

      Software affected with Bulletins rated important are listed here (MS15-116, MS15-117, MS15-118, MS15-119, MS15-120, MS15-121, MS15-122, MS15-123):

      • Microsoft Office
      • Windows NDIS, IPSEC, Schannel, and winsock (network software)
      • Microsoft .NET Framework
      • Kerberos
      • Services on Sharepoint and Office Web Apps
      • Skype for Business and Microsoft Lync

      Of the Bulletins rated “Important”, 16 CVE listed vulnerabilities were being fixed.

       

      For you travelers aware of your own operational security and shunners of pgp, it’s interesting that Bulletin MS15-122 provides fixes against BitLocker-encrypted drive attacks.

      According to Microsoft, “Kerberos fails to check the password change of a user signing into a workstation. An attacker could bypass Kerberos authentication on a target machine and decrypt drives protected by BitLocker.
      An attacker who has physical access to a target machine could bypass Kerberos authentication by connecting a workstation to a malicious Kerberos Key Distribution Center (KDC).

      The following mitigating factors may be helpful in your situation:

      • This bypass can be exploited only if the target system has BitLocker enabled without a PIN or USB key.
      • A domain user must be logged on to the target machine for the attack to succeed.”

      Its reporter, Ian Haken, will be presenting the attack in a couple of days at BlackHat EU in Amsterdam.

      Significant updates today also include Google announcing their deprecation of support for the Chrome browser on Windows XP and Windows Vista, along with Mac OS X 10.6, 10.7, and 10.8. While some organizations in the ICS or health care space may want to continue running their investment into these systems on their plant floors or facilities, this deprecation is another reason to upgrade those systems.

      Disbanding the ‘Zoo’

      Malware Alerts - Tue, 11/10/2015 - 06:00

      Virtualized environments are exceptionally flexible, manageable, fault-tolerant and cost-effective. However, a number of difficulties have to be overcome to protect them from external threats. If this is not done successfully, problems will inevitably arise. This is true of individual virtual machines, as well as the data center as a whole.

      Unfortunately, malware infections are a common occurrence in virtualized systems, particularly in VDI environments: customers’ employees do whatever they like on their virtual workstations without worrying about cyber-hygiene, believing that both their own IT department and the service provider will effectively block any malware.

      It should be noted that, in most cases, the provider is not allowed access to customer machines and has to demand that customers use their own protection. Many customers, though not all, take a responsible approach and install endpoint protection solutions of their choice on their machines.

      Sometimes, however, in spite of the provider’s recurring requests, customers resign themselves to the risk and do absolutely nothing about protection. There is no doubt that the provider will ultimately have to deal with all the problems arising from this approach. As a result, this turns into a major undertaking for the provider, who will have to change its protection strategy completely. (More information about security-related business problems faced by data centers can be found here.)

      In virtualized data centers, information is stored and processed on virtual machines and in data storage systems. These are completely different technologies that require different approaches to protection, each having many subtle aspects.

      The nuances of protecting virtualized environments

      As mentioned above, if the service provider does not provide protection for customers’ virtual machines, customers will do it on their own, each in their own individual way. On the one hand, this is not a bad thing; each customer can choose a security solution that suits their needs. However, in practice, this approach is not only inefficient; the resulting chaotic ‘zoo’ of solutions on customer machines creates numerous problems of its own:

      • Excessive use of hardware resources. The security system on each machine includes a complete set of components: an antivirus engine, a signature database, a firewall, etc. Each takes up its share of CPU time, RAM and disk space.
      • ‘Storms’. If scanning for malware is performed or antivirus databases are updated on several virtual machines at the same time, this leads to a surge in resource consumption, which can result in degradation of the entire platform’s performance or even in denial of service. Security software can of course be manually configured to avoid storms, but the time required to do this for hundreds of virtual machines will be very significant.
      • Panic attacks. A security system is often configured to step up protection when malware is detected on a machine. A ‘paranoid’ set of security rules is activated and out-of-schedule scans are launched. This can increase the load on the host machine’s hardware and negatively affect the performance of neighboring virtual machines.
      • ‘Instant-on’ security gap. Virtual machines often remain inactive until they are started up when the need arises. While a machine is inactive, none of the security system components on it are updated and the machine remains vulnerable during the period from startup until an anti-malware solution update is completed.
      • Incompatibility. Virtual machines are similar to physical computers in many ways, but they are also different in some significant aspects of their operation. For example, they use dynamic hard disks and can migrate from one server to another without shutting down. Standard security systems for physical machines are not designed with virtualized systems in mind. This can lead to delays, faulty operation or even complete inability to operate.

      All these issues will ultimately have to be addressed by the service provider – and on a regular basis. There is only one way to avoid this – prevent this ‘zoo’ from being created in the first place by putting customers in a situation where they have to choose between several proven dedicated security solutions for virtualized environments.

      With or without an agent?

      The key advantage of virtualization security systems like Kaspersky Security for Virtualization lies in the fact that the engine and the anti-malware databases are hosted on a separate virtual machine (Security Virtual Appliance, SVA) which provides protection for all machines running on the hypervisor.

      This solution has obvious advantages: hundreds of machines can be protected by just one anti-malware engine running on the SVA, which operates all the time and receives timely updates. This means all machines receive a high level of protection, while the VM scanning schedule is designed to preclude any excess load on the environment.

      Virtualization security software can be implemented in two substantially different ways: agent-based (light agent) or agentless. Customers have the freedom to choose the one that best suits their needs, or even combine the two.

      The agentless security solution has all of its components running on the SVA, and has a number of serious limitations. It is only designed to operate in environments based on VMware products, and is not capable of working with processes running in virtual machine memories, so it only scans the file system and incoming network traffic. In other words, it can only scan files and block network attacks. In some cases, this is sufficient. An agentless solution also provides almost instant protection of virtual machines immediately after they are launched. No software needs to be installed on the customer’s machines.

      The agentless approach to securing virtual environments, based on the solution Kaspersky Security for Virtualization | Agentless

      The light agent-based security system provides the entire range of security technologies (working with memory processes, application control, web browser protection, etc.) without using up lots of resources, as the scan engine and the databases are hosted on the SVA. Such an approach provides the functionality similar to Endpoint Protection-class solutions, while also being optimized and tested for virtual environments. However, a lightweight agent needs to be installed on each virtual machine so that the security solution has full access to the system. This can be seen as inconvenience, but many virtualization scenarios allow the use VM templates; in this case, the agent can be pre-installed into the template, so every VM spawned from it would have the agent as well, receiving instant protection right after being started.

      The light agent-based approach to securing virtual environments, based on the solution Kaspersky Security for Virtualization | Light Agent

      The choice between these two types of solutions depends on the accompanying circumstances.

      Often the provider cannot guarantee the presence of a security solution at the customer’s facility, which potentially creates a gap in data center security. The customer may also have reasons for not allowing any third-party software to be installed on their machines. In this case, the agentless security solution is the optimal choice.

      In other cases, the provider and the customer agree from the outset that a security solution will be installed on the virtual machines from a shortlist of tested and approved solutions. In this case, it is best to use specialized light agent-based security systems for virtual environments. This will provide the maximum level of security with minimum collateral problems.

      A special case is that of a virtual desktop infrastructure (VDI) hosted in a data center. When virtual machines are used as workstations, each of them is exposed to a multitude of threats during everyday operations. An employee may pick up a malware program when visiting a dangerous website or receive an email with a malicious attachment, while it is not uncommon for malware to spread from a removable media device that has passed between other users.

      When such a broad range of potential infection vectors is present, an agentless solution will be insufficient: with its limited functionality, the risk of infection is much higher. If an infection is detected, it will most probably happen too late to prevent any damage. On the other hand, a light agent-based security system is capable of protecting against a much broader range of threats by checking programs that are launched, preemptively blocking a user’s access to dangerous websites, and controlling the processes running in the system.

      A third, more resource-intensive, protection option for virtual machines also exists – a ‘regular’, full-agent endpoint protection-class security product. This is a viable choice if there is no access to the hypervisor (e.g. in public clouds such as Amazon or Azure), or if a more obscure hypervisor is used at the data center that is incompatible with specialized security solutions. And finally, these ‘regular’ security systems are developed for a broader range of operating systems. For instance, they can be used to protect virtual machines running under Mac OS.

      It should be noted that a security system that is not designed to work in a virtual environment may not be fully compatible with specific virtual machines and may not work properly or may not work at all. Solving these types of issues can take considerable time.

      Taking care of data storages

      An infected network data storage puts the entire data center at risk, and if anything requires anti-malware protection, it is data storage systems. If this need is not fulfilled, an epidemic may break out, especially if not all the machines located at the data center are connected to a security solution for virtual environments.

      Storage Area Networks (SAN) are very easy to protect – all it takes is a security system on the server. This is no different from protecting any other server; in this case, a server solution is implemented, such as Kaspersky Security for File Servers. Things are different with Network Attached Storage (NAS), which all machines in the network are granted instant access to. In this case, a specialized NAS security solution is required.

      Network data storage types

      Data stored on NAS needs to be protected before it is available to customer machines, meaning support on the NAS side is required. Luckily, most NAS support a number of special protocols and are able to work with external security solutions.

      Diagram showing how a NAS protection solution works

      When a customer requests a file from NAS (1), the storage sends it to the security system’s server (2). The server scans the file and reports the result to the storage (3). Depending on the security solution’s verdict, NAS provides the file to the customer or denies access (4). For greater reliability, more than one security server can be present in a network. During normal operation, the data storage itself will balance the load between them.

      Conclusion

      When it comes to securing virtualized data centers, there is no silver bullet solution, nor can there be one, that would ideally solve all problems. What is possible is to choose the optimum security system based on all the relevant factors.

      An agentless solution is best for protecting database servers, intranet web servers and machines that are not allowed to host any software besides a fixed set of applications.

      If the customer has a choice of several specialized security solutions pre-approved by the provider, a light agent solution is the best option. This will meet the needs of protecting web servers, virtual workstations, and sensitive data processing servers.

      Flexibility is particularly relevant when protecting virtual environments, so Kaspersky Lab provides both solutions – the agentless solution and the light agent solution – under one license. This gives the customer a choice between these two variants, and the capability to combine them when necessary, e.g. in environments with different hypervisors, or to address a variety of tasks more efficiently. More detailed information is available here.

      The most important thing is to ensure that protection issues are addressed before any annoying and costly problems arise.

      The Power of V&V

      Malware Alerts - Mon, 11/09/2015 - 04:57

      A secure system – especially a system that is used to provide security – has to be trusted. But what underpins that trust? What proof do we have that the main components of our trusted system are implemented properly and won’t fail at a critical moment? We mentioned this point in our last article about Secure OS and, as promised, we return to it here.

      Verification and validation (V&V) are applied to assure that software (or the whole system or appliance) truly possesses the stated properties. Although these terms (V&V) sound quite similar and are used in conjunction with each other, they have quite different meanings. Let’s recap.

      Verification is the process used to determine whether the outcome of a given stage of product development (i.e. software development) conforms exactly to the requirements set at the beginning of the stage.

      Validation is the process used to determine whether the product (computer program, operating system, appliance etc.) satisfies its intended use and user needs. Requirements, lifecycle processes and other supporting artifacts can also be validated for their conformance to the expected results.

      Put simply, verification asks, “Have we implemented the system properly?” while validation tries to find out “Did we implement the proper system?” And while the second question requires the involvement of an expert (whose opinion forms the basis for the whole scope of validation issues, from requirement validation to the final integration test), the first question has to be addressed mainly using formal methods.

      Indeed, the one cannot exist without the other. The system can only be verified with regard to a concrete property, for example, evidence that the program does not suffer from deadlocks. The fact that this property makes sense should be validated. Furthermore, verification can be performed in a trivial way by restricting the ability to lock resources – but this may disrupt the integrity of those resources. Therefore, we have to validate an additional condition. In some cases the property definition can also be the subject of verification if the expert requirements can be appropriately formalized into the verification goal.

      To envision the process of verification you can try imagining a sort of “magic evaluator” ready at the push of a button to perform an assessment of any given source code: Is the code valid or not? Is it safe or not? And so on. But even this sort of ideal raises a number of questions. The first of them being: what will we actually prove? What statements is verification capable of making evident? The correctness, completeness, data consistency, accuracy and safety of execution… It has been shown that all the properties might be represented as a composition of two basic properties – the ‘safety’ property and the ‘liveness’ property. The safety property stipulates that the system cannot reach a specific (unsafe) state. Put another way, this means “something bad will never happen”. The liveness property, on the other hand, guarantees that after a finite run the system will reach some defined state – in other words, “something good will definitely happen”.

      However, awareness of the decomposition possibility of the verification goal is one thing, while the correct and valid representation of such a decomposed goal without loss of sense is, clearly, another. Sometimes, attempting rule decomposition for a system model results in a negative effect: the model hangs in the safety part of the rule without being able to establish the liveness part. This imposes additional conditions on the decomposition process. In some other realistic scenarios, you have to address the “fairness property” in addition to safety and liveness (just like in real life).

      To formalize the criteria defined in such a manner, classical or temporal logic is often used and, to verify the system properties according to these criteria, the appropriate programming languages. In particular, for classical logic clauses Prolog is quite popular, while for temporal logic the Promela and SPIN languages are used. However, this is not the only way to define verification goals. The formal definition of correct program behavior and verification of this behavior is so specific and of such significance that in 1969 computer scientist and logician C. A. R. Hoare proposed a formal theory intended to establish the correctness of computer programs deductively. The basis of this theory is a set of logical rules defined in a way that imitates the semantics of imperative language constructions. Later, an approach to criteria specification was developed that even more closely resembles programming abstractions and supports further software design – design-by-contract programming.

      Another major issue is the choice of object for verification. Despite the fact that a verification procedure implies a precise evaluation, the right choice of object needs to be made for there to be confidence in the result.

      For example, one may choose a static system configuration – i.e. system parameters, applications and security policy restrictions – to verify. The evaluator accepts this data, performs the verification procedures according to the logical rules (based on expert knowledge) and generates ‘Pass’ or ‘Fail’ output. The evaluator may, for example, ascertain whether a certain kind of attack on the system is possible or if an unprivileged user can obtain unauthorized access to specific resources in the system, etc.

      The verification of system configuration can ensure system behavior is trusted if system components are configured properly. This means that all system services and applications should run as specified and contain no bugs or vulnerabilities that could be exploited to affect the functioning of the whole system.1

      However, the situation is often different in reality. Therefore, software internals need to be verified2. One thing is clear at this point – because software internals have a lot of representation layers, the need to make the right choice once again appears. What object is to be verified – the high-level source code or the sequences of machine instructions? Is it necessary to consider the program environment and how to model this environment? Is examining the specific dependencies of low-level execution from the hardware platform of any value…? And again, the choice depends on the verification goal and on the level of assurance provided for verification. Suppose you need to ensure the absence of a certain type of vulnerability in a piece of software (this example can be interpreted in most cases as the safety problem mentioned above). Testing and static code analysis intended to find typical dangers are not usually considered as formal verification methods3 due to the fact they tend not to cover all possible situations (although exceptions do exist). To solve this problem of the verification method, you need to perform logical computations with code constructions in order to make it evident that any continuous fragment on the program control flow graph (including all non-linear transitions) is not vulnerable to the given exploitation method. All that is required is to formalize, in a general way, the appropriate valid conditions and implement efficient evaluation algorithms for the entire program code.

      The issue may be further complicated by the lack of guarantees that a compiler will save the proven properties for the resultant machine code, and by the necessity of guaranteeing the properties originally defined for the low-level code. It is because of this complexity of verifying program code that the verification methods are applied to the code as simply and concisely as possible. Priority is given to the code of the operating system kernel and the code of the low-level services that underpin the security of the whole system.

      One promising approach to verification is by guaranteeing the security of some code properties (or setting the basis for such a guarantee) when the code is created. By demonstrating that a notation or programming language is capable of imparting the necessary characteristics to the program code, one can avoid the tedious checking procedures at least for these characteristics. Code generation minimizes human error (i.e. bugs) when creating software code. This is quite an effective approach that is currently only used for a limited number of algorithms in a specific context – at least until another more complicated task is solved. This task appears because we do not eliminate the code verification issue, but instead pass it to a higher level – the level of language (or compiler) verification. Therefore, we have to verify that the language is safe, meaning that all the constructions produced with this language are safe in the previous sense. This is a non-trivial task, but after being solved once it addresses verification issues for any code created using previously evaluated methods.

      Another approach to implementing the verifiability of program code as it is created is to use the design-by-contract approach (contract-based programming). In this case, implementation starts by determining precise formal specifications of programming interfaces that prescribe preconditions (obligations accepted by the clients of interfaces), post-conditions (obligations accepted by the interface supplier) and invariants (obligations for saving certain properties related to the interface). Many programming languages support design by contract natively or with third-party extensions (e.g. C and Java languages).

      “Laboratory verification” of the program code may cause complaints if the code behavior is affected to a large extent by the environment. Of course, it would be good if a system made from loosely coupled trusted components with properly defined interfaces could give a 100% guarantee that it will execute properly, but in real systems it is quite difficult to predict what influence the environment will have on individual components. In order to assess the correctness of the system it is necessary to resort to an analysis of the behavior of parallel components. Formal verification of whether a given logical formula is satisfied for the system with parallel execution architecture is referred to as model checking. This method brings together existing knowledge and expertise in the software verification field, and is widely used throughout the world to evaluate existing hardware and software systems. The Turing Award has been given twice for work in the field of model checking. The first time was in 1996 to Amir Pnueli “for seminal work introducing temporal logic into computing science and for outstanding contributions to program and systems verification”. The second time was in 2007 to the three scientists, Clarke, Emerson, and Sifakis “for their role in developing Model-Checking into a highly effective verification technology that is widely adopted in the hardware and software industries”).

      During the Turing Award ceremony in 2007, ACM President Stuart Feldman said about the model checking method: “This is a great example of an industry-transforming technology arising from highly theoretical research.” We can say with some certainty that if the future of all aspects of our life lies with technologies that are safe, secure and smart in all senses of the word, validation and verification methods provide the route to that future.

      It is impossible to cover all aspects of V&V in one article. For those who are particularly interested in the subject, we can recommend a paper by one of the pioneers of the model-checking approach, Edmund M. Clarke, ‘The Birth of Model Checking’, and his book ‘Model Checking’, co-authored with Orna Grumberg and Doron A. Peled, for a more in-depth exploration of the method. The best way to learn about aspects of safety, liveness and the other main properties is to refer to the original works listed in the paper by Ekkart Kindler, ‘Safety and Liveness Properties: A Survey’. The excellent monograph by G. Tel, ‘Introduction to distributed algorithms’, gives a detailed explanation of the formal representation and development of correct and dependable algorithms in complex systems.

      1This is the case when the validation of lifecycle processes (based on an awareness of possible vulnerabilities) may help to reject configuration verification as inappropriate or enter compensating measures (e.g. code analysis) to provide some guarantees for software implementation.

      2It should be noted that configuration verification and software verification are not interchangeable measures. While a check of the program code guarantees that it will be executed as expected, configuration checks ensure conformance to the required policy.

      3They are usually considered as validation methods.

      Surviving in an IoT-enabled world

      Malware Alerts - Thu, 11/05/2015 - 05:59

      Scare stories around the Internet of Things (IoT) conjure up images of bad guys in hoodies, who live for hacking and to make the lives of other people harder, inventing millions of ways to infiltrate your life through your gadgets. But is this perception a good enough reason to stop using smart devices? We don’t think so; we believe that customers should be aware of the potential risks and know how to mitigate them before embracing the IoT-enabled world.

      More than a year ago, our colleague from the Global Research and Analysis Team, David Jacoby looked around his living-room, and decided to investigate how susceptible the devices he owned were to a cyber-attack. He discovered that almost all of them were vulnerable. So, we asked ourselves: was that a coincidence, or are the smart ‘IoT’ products currently on the market really that exposed? To find the answer, earlier this year we gathered up a random selection of connected home devices and took a look at how they work.

      The devices we chose for our experiment were as follows:

      • a USB-dongle for video streaming (Google Chromecast);
      • a smartphone-controlled IP camera;
      • a smartphone-controlled coffee maker; and
      • a home security system, also smartphone-controlled.

      The task we set ourselves was simple: to find out whether any of those products posed a security threat to their owner. The results of our investigation provide much food for thought.

      Google Chromecast. IoT hacking for beginners

      Risk: the content on the victim’s screen is streamed from a source owned by an attacker

      Chromecast, which has been recently updated with a more advanced version, is an interesting device. It’s an inexpensive USB-dongle that allows you to stream media from your smartphone or tablet to a TV- or other display-screen. It works like this: the user connects it to a television’s HDMI in order to switch it on. After that the Chromecast launches its own Wi-Fi-network for initial setup. Once it has established a connection with a smartphone or a tablet, it switches its own Wi-Fi off and connects to the user’s home Wi-Fi network. It’s very convenient and user-friendly.

      But this could become less convenient and decidedly unfriendly if there is a hacker nearby. The famous “rickrolling” vulnerability, discovered by security consultant, Dan Petro, proves that. It allows the content on the victim’s screen to stream from a source owned by an attacker. This is how it works: the attacker floods the device with special ‘disconnect’ requests from a rogue Raspberry Pi-based device and then, as the Chromecast turns on its own Wi-Fi module in response, Google Chromecast is reconnected to the attacker’s device making it stream the content the attacker wants.

      The only way to get rid of this is to switch off the TV, take the dongle out of range of your Wi-Fi hotspot and wait until the attacker gets bored and goes away.

      The only limitation to this attack is that the attacker needs to be within range of the Wi-Fi network to which the target Chromecast is connected. However, we discovered in our own experiment that this not necessarily a restriction if you have a cheap directional Wi-Fi antenna and some Kali Linux software. When we used that, we found that Chromecast can be “rickrolled” across a far greater distance than the normal signal range for domestic Wi-Fi networks. What this means is that, while in the original hack by Dan Petro, the attacker would run the risk of being spotted by an angry Chromecast owner, with a directional antenna that risk no longer exists.

      We don’t regard this “finding” as a new security discovery; it simply extends a previously-known and so far unpatched security issue. It’s an exercise for beginners in IoT hacking, although it could be used in a really harmful way – but we’ll get to that later. First we’ll go through the other findings of our brief research.

      Mitigation: Use in remote parts of your house as this will lower the risk of attacks with a directional antenna

      Status: Not patched

      IP camera Issue one

      Risk: attackers get access to the email addresses of all the camera users who have experienced technical issues

      The IP camera we investigated was positioned by its vendor as a baby monitor. You put the camera in a nursery, download an app on your smartphone, connect the camera to the app and the Wi-Fi, and off you go: you can watch your child whenever you want, from anywhere you like.

      Why would someone want to hack a baby monitor, you may well ask? Actually there are a number of recorded instances of baby monitor abuse dating back as early as 2013 (http://www.cbsnews.com/news/baby-monitor-hacked-spies-on-texas-child/) with a similar issue reported in 2015 (http://www.kwch.com/news/local-news/whitewater-woman-says-her-baby-monitor-was-hacked/32427912). So yes, there are people who, for some reason want to hack baby monitors.

      When we investigated our camera (in the spring of 2015) there were two different apps available for customers that enabled them to communicate with the camera. Both contained security issues. We were later to learn from the vendor that one of these apps was a legacy app, however it was still being used by a number of camera owners. We discovered that this legacy app contained hardcoded credentials to a Gmail account.

      public static final String EMAIL_FROM = “*****@gmail.com”;
          public static final String EMAIL_PASSWORD = “*******”;
          public static final String EMAIL_PORT = “465”;
          public static final String EMAIL_SMTP_HOST = “smtp.gmail.com”;
          public static final String EMAIL_TO;
          public static final String EMAIL_TO_MAXIM = “maximidc@gmail.com”;
          public static final String EMAIL_TO_PHILIPS = “*****@philips.com”;
          public static final String EMAIL_USERNAME = “*****@gmail.com”;

      The vendor later told us that the account was used to collect reports on technical issues from the camera users.

      The problem here is that reports were being sent to this pre-installed account from users’ own email accounts. So an attacker would not even need to buy a camera; all they needed to do was download and reverse-engineer one of the apps to get access to the technical email account and to collect the email addresses of all the camera users who had experienced technical issues. Is it a big issue, that your email could have been exposed to a third party as a result of the exploitation of that vulnerability? It might be. However, realistically-speaking this vulnerability doesn’t appear to be a tempting target for mass-harvesting personal information, mainly because of its relatively small base of victims. Technical issues are rare and the app was old and not really popular at the time of our research. Baby monitors are also a niche product so not many email addresses are stored.

      On the other hand, if you are the owner of a baby monitor, you’re most likely a parent and that fact makes you (and by extension your email address) a much more interesting target should an attacker plan a specific, tailored, fraud campaign.

      In other words, this is not a critical security vulnerability but it could still be used by attackers. But that wasn’t the only vulnerability we found while investigating the camera and the app.

      Status: fixed

      Issue two

      Risk: full control of the camera by an attacker

      After looking at the legacy app we moved on to the more recent version and immediately discovered another interesting issue.

      The application communicates with the camera through a cloud service and communication between the app and the cloud service is https-encrypted. The application uses Session ID for authentication which is changed automatically each time a user initiates a new session. It might sound secure, but it is in fact possible to intercept the Session ID and to control the camera through the cloud or to retrieve the password for local access to the camera.

      Before the app starts streaming data from the camera, it sends an http request to the cloud service:

      type=android&id=APA91bEjfHJc7p6vw3izKmMNFYt7wJQr995171iGq2kk_rD4XaMEHhTXqTmFaAALjWD15bnaVcyMuV2a7zvEFdtV13QXildHQn0PCvQbPikag2CPJwPwOWWsXtP7B0S-Jd3W-7n0JUo-nMFg3-Kv02yb1AldWBPfE3UghvwECCMANYU3tKZCb2A&sessionId=100-U3a9cd38a-45ab-4aca-98fe-29b27b2ce280

      This request contains the Session ID which could be intercepted as the request is unencrypted. The Session ID is then used to retrieve the current password. We found that it could be done by creating a special link with the Session ID in the end.

      https://*****/*****/*****sessionId=100-U3a9cd38a-45ab-4aca-98fe-29b27b2ce280

      In return for this link the cloud service would send the password for the session.

      https:// *****/*****/*****sessionId=100-U3a9cd38a-45ab-4aca-98fe-29b27b2ce280

      … “local_view”:{“password”:”N2VmYmVlOGY4NGVj”,”port”:9090} …

      Using the password it is possible to get full control of the camera, including the ability to watch the streamed video, listen to audio, and play audio on the camera.

      It is important to note that this is not a remote attack – the attacker must be on the same network as the app user in order to intercept the initial request, making exploitation less likely. However, app users should still proceed with caution, especially if they are using large networks that can be accessed by many people. For example, if the app user is connecting to their camera from public Wi-Fi, they could be exposing themselves to risk from an attacker on the same network. In such conditions it would not be hard to imagine a real-life app-usage scenario that involved a third-party.

      Status: fixed

      Issue three

      Risk: god mode – an attacker can do anything with camera firmware

      The third issue we discovered while investigating our smartphone-controlled camera resided not in the app but in the camera itself. And the issue is rather simple: a factory root password for SSH in the firmware. It is simple because the camera is running on Linux and the root password enables god-mode for anyone who has access to the device and knows the password. You can do anything with camera firmware: modify it, wipe it – anything. All the attacker needs to do in order to extract the password is to download and extract the firmware from the vendor’s website (although the attacker would need to be in the same network with the attacked device to get the URL from which the firmware is being downloaded), extract it and follow this path: \\ubifs\\home/.config. There it is: in plain text.

      CONFIG_*******_ROOT_PASSWORD=”sVGhNBRNyE57″

      CONFIG_*******_ROOT_PASSWORD=”GFg7n0MfELfL”

      What’s more worrying is that, unless they are a Linux expert, there is no way for an inexperienced user to remove or change this password by themself.

      Why the SSH password was there is a mystery to us, but we have some suggestions. The root access would be of use to developers and technical support specialists in a situation where a customer encounters an unexpected technical problem that could not be fixed over the phone. In this case, a specialist could connect to the camera remotely, use the SSH password to get root access and fix an issue. Apparently this is a common practice for new models of such devices, which can contain bugs that were not discovered and fixed at the pre-release stage. We looked at the firmware of some other cameras from an alternative vendor and also discovered SSH passwords in there. So the story is: developers leave the SSH password in the firmware in order to have the ability to fix unexpected bugs there and then, and when a stable version of firmware is released they just forget to remove or encrypt the password.

      Our second suggestion is that they just forgot it was there. As we discovered during our research, the part of the device where SSH passwords were found – the chipset – is usually shipped by a third-party vendor. And the third-party vendor leaves the SSH password in the camera by default for convenience, to make sure that the vendor of the end-product (the baby monitor) has the ability to tune up the chipset and to connect it with other hardware and software. So the vendor does this and then just forgets to remove the password. As simple as it sounds.

      Status: fixed

      Communications with the vendor

      It wasn’t hard to discover these vulnerabilities and we have to admit that it wasn’t difficult to report them to the vendor and help them to patch them. The camera we investigated was branded by Philips, but was actually produced and maintained by Gibson Innovations. The representatives of the company were extremely quick to react to our report. As a result all the issues we reported have been patched, both in the camera and in the apps (Android and iOS).

      This autumn, Rapid7 released a very interesting report about vulnerabilities in baby monitors, and a Philips product (a slightly different version of the camera we investigated) was on the list of vulnerable devices, with a number of vulnerabilities noted, some of them similar to those discovered in our research. But judging by the ‘from-discovery-to-patch’ timeline presented in the report, Gibson Innovations is one of only a few IoT vendors to treat security issues in their products seriously and to do so continuously. Kudos to them for such a responsible approach.

      But back to our research.

      One could say that the security issues we’ve discovered in the IP camera require access to the same network as the user of the camera or the camera itself, and they would be right. On the other hand, for an intruder that is not necessarily a major obstacle, especially if the user has another connected device in their network.

      A smartphone-controlled coffee machine What could possibly go wrong?

      Risk: leakage of the password to the home wireless network

      The coffee machine we’ve randomly chosen can remotely prepare a cup of coffee at the exact time you want. You just set the time and when the coffee is ready the app will send you a push-notification. You can also monitor the status of the machine through an app. For instance, it is possible to find out if it is brewing now or not, if it is ready for brewing or if it is time to refill the water container. In other words, a very nice device, which, unfortunately, gives an attacker a way to hijack the password of your local Wi-Fi network.

      Before you use it you have to set it up. It happens like this: when the device is plugged in, it creates a non-encrypted hotspot and listens to UPNP traffic. A smartphone running the application for communicating with the coffee machine connects to this hotspot and sends a broadcast UDP request asking if there are UPNP devices in the network. As our coffee machine is such a device, it responds to this request. After that a short communication containing the SSID and the password to the home wireless network, among other things, is sent from the smartphone to the device.

      This is where we detected a problem. Although the password is sent in encrypted form, the components of the encryption key are sent through an open, non-protected channel. These components are the coffee machine’s Ethernet address and some other unique credentials. Using these components, the encryption key is generated in the smartphone. The password to the home network is encrypted with this key using 128-bit AES, and sent in base64 form to the coffee machine. In the coffee machine, the key is also generated using these components, and the password can be decrypted. Then, the coffee machine connects to the home wireless network and ceases to be a hotspot until it is reset. From this moment on, the coffee machine is only accessible via the home wireless network. But it doesn’t matter, as by then the password is already compromised.

      Status: the vulnerability is still in place

      Communications with vendor

      We’ve reported our findings to the vendor of the coffee machine, and the vendor has acknowledged the issue and provided us with the following statement:

      “Both user experience and security are extremely important to us and we continually strive to strike the right balance between the two. The actual risks associated with the vulnerabilities you mentioned during set-up are extremely low. In order to gain access, a hacker would have to be physically within the radius of the home network at the exact time of set-up, which is a window of only a few minutes. In other words, a hacker would have to specifically target a smart coffee maker user and be around at the exact point of set-up, which is extremely unlikely. Because of this, we do not believe the potential vulnerabilities justify the significant negative impacts it will have on user experience if we make the suggested changes. Though no definite plans to change our set-up procedure are in the works, we are constantly reevaluating and wouldn’t hesitate to make changes if risks become more significant. Should something change in the near future we will let you know.”

      We don’t entirely disagree with this statement and have to admit that the attack window is extremely short. The vulnerability could be patched in several ways, but based on the conclusions of our own analysis, almost all of these ways would involve either hardware changes (the Ethernet port on the coffee machine or a keyboard for the password would solve the problem) or the provision of a unique pin code for each coffee machine including those that have already been sold, which is not easy from a logistical point of view. Such changes would considerably impact the user experience and the set up process would become less straightforward.

      The only software fix we can propose is to implement asymmetric encryption. In this case the coffee maker would have to send out the public encryption key to the user’s smartphone and only after that the sensitive data exchange would start. This, however, would still allow any user in a given Wi-Fi network, including the attacker, to take control of the coffee machine. The public key would be available to everyone, and the first user to receive it and establish the connection with the coffee maker will be able to control it. Nevertheless, the legitimate user of the coffee machine will at least have a clue that something is going wrong, as during/following? a successful attack they wouldn’t be able to communicate with the device. This is not the case with the current software running on the coffee machine.

      So we can say that to some degree we understand the vendor logic: the level of risk this issue brings doesn’t match the level of complexity of measures that must be implemented in order to eliminate the issue. Besides that, it would be wrong to say that the vendor didn’t think about the security of their product at all: as we said earlier, the password is transmitted in protected form, and you have to hold the antenna in a special way.

      However, the vulnerability still exists and for a smart criminal it wouldn’t be a problem to exploit it to obtain your Wi-Fi password. The situation is interesting: if you are a user of this coffee maker, every time you change the password for your home Wi-Fi network in order to make it more secure, you’re actually exposing this new password, because each time you implement a new password you have to set up the coffee machine again. And you would never know whether someone had sniffed your password or not. For some people this may not be an issue, but for others it is most certainly a security problem.

      For this reason, we will not disclose the vendor or model so as not to draw unwanted attention to the vulnerable product. However, if you are a user of a smartphone-controlled coffee maker and you’re worried about this issue, do not hesitate to contact the vendor and ask them if our findings have something to do with the product that you own, or are planning to purchase.

      Onto the final chapter of our journey into the insecure world of IoT.

      Home security system vs physics

      Risk: bypassing security sensors with no alarms

      App-controlled home security systems are pretty popular nowadays. The market is full of different products intended to secure your home from physical intrusion. Usually such systems include a hub that is connected to your home network and to your smartphone, and a number of battery-powered sensors that communicate wirelessly with the hub. The sensors are usually door/window contact sensors that would inform the owner if the window or door they guard has been opened; motion sensors; cameras.

      When we initially got our hands on a smart home security system we were excited. Previously we’d seen a lot of news about researchers finding severe vulnerabilities in such products, like the research from HP or another awesome piece of research on the insecurity of the ZigBee protocol used by such products, presented at this year’s Black Hat. We prepared ourselves for an easy job finding multiple security issues.

      But that wasn’t the case. The more we looked into the system the better we understood that, from a cyber-security perspective, it is a well-designed device. In order to set up the system, you have to connect the hub directly to your Wi-Fi router, and in order to make the app communicate with the hub, you have to create an account on the vendor’s website, provide your phone number and enter the secret pin code that is sent to you via SMS. All communications between the app and the system are routed through the vendor’s cloud service and everything is done over https.

      When looking at how the hub downloads new versions of firmware, we found that the firmware is not signed, which is a bit of an issue as it potentially allows you to download any firmware onto the device. But at the same time, in order to do so you’d have to know the password and the login of the user account. Also, when on the same network as the security system it is possible to send commands to the hub, but to understand what kind of commands it is possible to send, you’d need to reverse-engineer the hub firmware which is not really security research, but aggressive hacking. We’re not aggressive hackers.

      So from a software point of view – if you’re not intending to hack a device at all costs – the home security system we investigated was secure.

      But then we looked at the sensors.

      Defeating contact sensors with their own weapon

      Intrusion or contact sensors, included in the package, consist of three main parts: the magnet (the part that you put on a door or on the moving part of a window), the radio transmitter, and the magnetic field sensor. It works as follows: the magnet emits a magnetic field and the magnetic field sensor registers it. If the door or window is opened, the sensor will stop registering the magnetic field and will send a notification to the hub, indicating that the door/window is open. But if the magnetic field is there, it will send no alarms, which means that all you need to bypass the sensor is a magnet powerful enough to replace the magnetic field. In our lab we put a magnet close to the sensor, and then we opened the window, got in, closed the window and removed the magnet. No alarms and no surprises.

      One could say that it would only work with windows, where you can be lucky enough to locate easily the exact place where the sensor is placed. But magnetic fields are treacherous and they can walk through walls, and the simplest magnetic field detection app for the smartphone will locate a sensor precisely, even if you don’t have visual contact. So doors (if they’re not made of metal) are vulnerable too. Physics wins!

      Motion sensor

      Encouraged by an easy victory over contact sensors we moved on to the motion sensor and disassembled it to discover that it was a rather simple infrared sensor that detects the movement of a warm object. This means that if an object is not warm the sensor doesn’t care. As we discovered during our experiment, one would only need to put on a coat, glasses, a hat and/or a mask in order to become invisible to the sensor. Physics wins again!

      Protection strategies

      The bad news is that magnetic field sensor-based devices and low quality infrared motion sensors are used not only by the home security system we investigated. They’re pretty standard sensors which can be found in a number of other similar products. Just search the IoT e-shops and you’ll see for yourself. There is more bad news: it is impossible to fix the issue with a firmware update. The problem is in the technology itself.

      The good news is that it is possible to protect yourself from the burglars who didn’t bunk off Physics in school. The basic rules here are as follows:

      1. Do not rely only on contact sensors when protecting your home if you are using a system of the kind described above. Smart home security system vendors usually offer additional devices, like motion- and audio-sensing cameras, which are impossible to bypass with magnets. So it would be wise to supplement the contact sensors with some smart cameras even though it may cost more. Using contact sensors alone will turn your home security system into what is essentially a high-tech ‘toy’ security system.
      2. If you’re using infrared motion sensors, try to put them in front of a radiator in rooms a burglar will have to walk through, should they make their way into your home. In this case the intruder, no matter what clothes they are wearing, will overshadow the radiator and the sensor will notice the change and report it to your smartphone.
      Conclusions

      Based on what we discovered during our brief experiment, vendors are doing their best not to forget about the cyber-security of the devices they’re producing, which is good. Nevertheless, any connected, app-controlled device that is usually called an IoT device is almost certain to have at least one security issue. However, the probability that they will be critical is not that high.

      At the same time, the low severity of such security issues doesn’t guarantee that they won’t be used in an attack. At the beginning of this article we promised to describe how the safe and funny “rickrolling” vulnerability could be used in a dangerous attack. Here it is.

      Just imagine that one day a TV with a Chromecast device connected to it, both belonging to an inexperienced user, starts showing error messages which report that, in order to fix this issue, the user has to reset their Wi-Fi router to factory settings. That means the user would have to reconnect all their devices, including their Wi-Fi-enabled coffee machine. The user resets the router and reconnects all the devices. After that the Chromecast works normally again as do all the other devices in the network. What the user doesn’t notice is that someone new has connected to the router, and then jumped to the baby monitor camera or other connected devices, ones that have no critical vulnerabilities but several non-critical ones.

      From an economic perspective it is still unclear why cybercriminals would attack connected home devices. But as the market of the Internet of Things takes off, and technologies are being popularized and standardized, it is only a matter of time before black hats find a way to monetize an IoT attack. Ransomware is obviously a possible way to go, but it’s certainly not the only one.

      Besides that, cybercriminals are not the only ones who might become interested in IoT. For instance, this summer the Russian Ministry of Interior Affairs ordered (RU) to research possible ways of collecting forensic data from devices built with the use of smart technologies. And the Canadian military recently published a procurement request for a contractor that can “find vulnerabilities and security measures” for cars and will “develop and demonstrate exploits”.

      This doesn’t mean that people should avoid using the IoT because of all the risks. The safe option is to choose wisely: consider what IoT device or system you want, what you plan to use it for and where.

      Here is the list of suggestions from Kaspersky Lab:

      1. Before buying an IoT device, search the Internet for news of any vulnerabilities. The Internet of Things is a very hot topic now, and a lot of researchers are doing a great job finding security issues in products of this kind: from baby monitors to app controlled rifles. It is likely that the device you are going to purchase has been already examined by security researchers and it is possible to find out whether the issues found in the device have been patched.
      2. It is not always a great idea to buy the most recent products released on the market. Along with the standard bugs you get in new products, recently-launched devices might contain security issues that haven’t yet been discovered by security researchers. The best choice is to buy products that have already experienced several software updates.
      3. When choosing what part of your life you’re going to make a little bit smarter, consider the security risks. If your home is the place where you store many items of material value, it would probably be a good idea to choose a professional alarm system that will replace or complement your existing app-controlled home alarm system; or set-up the existing system in such a way that any potential vulnerabilities would not affect its operation. Also, when choosing the device that will collect information about your personal life and the lives of your family, like a baby monitor, maybe it would be wise to choose the simplest RF-model, capable only of transmitting an audio signal, and without Internet connectivity. If that is not an option, than follow our first piece of advice – choose wisely!

      As for the vendors of IoT-devices, we have only one, but important suggestion: to collaborate with the security community when creating new products and improving old ones. There are initiatives like Builditsecure.ly or OWASP Internet of Things project that could actually help to build an awesome connected device with no serious security issues. At Kaspersky Lab, we will also continue our research to get more information about connected devices and to find out how to protect people against the threats that such devices pose.

      Kaspersky DDoS Intelligence Report Q3 2015

      Malware Alerts - Tue, 11/03/2015 - 06:03

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      Q3 events

      Of all the Q3 2015 events in the world of DDoS attacks and the tools used to launch them, we picked out those that, in our opinion, best illustrate the main trends behind the evolution of these threats.

      • DDoS attacks targeting financial organizations for the purpose of extortion;
      • new techniques to increase the intensity of attacks by manipulating web pages;
      • active development of Linux-based botnets for DDoS attacks.
      Attacks on financial organizations

      In Q3 2015, there was increased activity by the cybercriminal group “DD4BC” responsible for a number of attacks on major banking organizations around the world. The group has been targeting banks, media groups and gaming companies since September, threatening to take down their customer websites unless they pay a ransom. The owner of the targeted resource is asked to pay between 25 and 200 bitcoins ($6,500 – $52,500), or have their servers disabled. Some of the first victims included organizations in Australia, New Zealand and Switzerland, while a warning was received by major financial institutions in Hong Kong. The Bank of China and the Bank of East Asia also reported that they were targeted by illegal activity. In the third quarter, a number of Russian financial institutions also received notifications from cybercriminals asking for a specific sum in cryptocurrency to terminate an attack.

      Unusual attack scenario

      The company CloudFlare reported a DDoS attack with an unusual scenario. A site belonging to one of CloudFlare’s customers was being subjected to an attack made up of 275,000 HTTP requests per second. Of particular interest was the fact that the attackers made use of malicious JavaScript embedded in adverts. An iframe with a malicious advert that contained the JavaScript was run on the browsers of lots of users, resulting in their workstations sending XHR requests to the victim. Experts believe that these malicious ads can also display some legitimate applications.

      XOR DDoS bot activity

      The specialists at Akamai Technologies witnessed growth in the capacity of a DDoS botnet consisting of Linux-based computers whose victims were mostly Asian sites belonging to educational institutions and gaming communities. A distinctive feature of the bot is the use of XOR-encryption both in the malicious program and for communication with the C&C servers. At the same time, in order to self-propagate the bot brute-forces passwords to the root account in Linux systems. Linux is often used as a server operating system, which means that the server also has the channel and computing resources that the attackers can use to launch DDoS attacks. Using SYN and DNS floods, this botnet has been successfully carrying out attacks with a capacity of 109-179 Gbps.

      The proportion of DDoS attacks from Linux-based botnets in Q3 2015 was 45.6% #KLReport

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      According to Kaspersky Lab data, the botnets from Linux-based servers infected by the XOR DDoS bot actively attacked resources located in China.

      DDoS availability

      On the one hand, the software that is used for DDoS attacks is becoming more complicated; on the other hand, the tools for DDoS attacks are becoming more freely available and easier to use. As a result, setting up and launching a DDoS attack no longer requires any special technical knowledge. A fairly competent criminal could easily unleash a powerful attack.

      This fact is confirmed by attacks on the educational portal of the Republic of Tatarstan carried out by students attempting to block communication between teachers and parents. Throughout the year the attackers repeatedly tried to bring down the portal, which was protected by Kaspersky DDoS Protection. All their attempts were unsuccessful, but their persistence did succeed in attracting the attention of Kaspersky Lab’s experts.

      The longest DDoS attack in Q3 2015 lasted for 320 hours #KLReport

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      The availability and ease of use of the tools for DDoS attacks has resulted in the range of targets growing. It is generally accepted that DDoS attacks are mainly focused on financial institutions, government agencies, businesses and the media. Now, however, any resource that has attracted the ire of an unscrupulous web user could be subjected to a DDoS attack – even an educational portal.

      Statistics of botnet-assisted DDoS attacks Methodology

      The DDoS Intelligence system (part of Kaspersky DDoS Protection) is designed to intercept and analyze commands sent to bots from command and control (C&C) servers, and does not have to wait until user devices are infected or cybercriminal commands are executed in order to gather data.

      In this report, a single (separate) DDoS attack is defined as an incident during which any break in botnet activity lasts less than 24 hours. If the same web resource was attacked by the same botnet after a break of more than 24 hours, this is regarded as a separate DDoS attack. Attacks on the same web resource from two different botnets are also regarded as separate attacks.

      In Q3 2015, 91.6% of resources, targeted by DDoS attacks, were located in 10 countries #KLReport

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      The geographical distribution of DDoS victims and C&C servers is determined according to their IP addresses. In this report, the number of DDoS targets is calculated based on the number of unique IP addresses reported in the quarterly statistics.

      It is important to note that DDoS Intelligence statistics are limited to those botnets that were detected and analyzed by Kaspersky Lab. It should also be highlighted that botnets are just one of the tools used to carry out DDoS attacks; therefore, the data presented in this report does not cover every DDoS attack that has occurred within the specified time period.

      Q3 Summary
      • In Q3 2015, botnet-assisted DDoS attacks targeted victims in 79 countries around the world.
      • 91.6% of targeted resources were located in 10 countries.
      • The largest numbers of DDoS attacks targeted victims in China, the US and South Korea.
      • The longest DDoS attack in Q3 2015 lasted for 320 hours (or 13.3 days).
      • SYN DDoS, TCP DDoS and HTTP DDoS were the most common DDoS attack scenarios.
      • Linux-based bots are actively used by cybercriminals; the proportion of DDoS attacks from Linux-based botnets in the third quarter was 45.6%.
      Geography of attacks

      In Q3, the targets of DDoS attacks were located in 79 countries around the world. 91.6% of attacked resources were located in 10 countries.

      Distribution of unique DDoS attack targets by country, Q3 vs Q2 2015

      China still leads the Top 10 ranking: in Q3 of 2015, 34.5% of DDoS attack targets were located there, an increase of 4.6 percentage points (p.p.) on the previous quarter. The US came second with 0.8%. South Korea remained in third place (17.7%) although its share increased considerably – by 7.9 p.p.

      The Netherlands (1.1%) re-entered the Top 10. A newcomer to the rating was Japan whose share accounted for 1.3% of all attacked resources. Germany (1.0%) and Hong Kong (0.9%) left the Top 10.

      If we look at the number of reported attacks, 92.3% of all attacks (an increase of 14.7 p.p. on Q2) had targets within the same Top 10 countries:

      Distribution of DDoS attack by countries, Q3 vs Q2 2015

      In the third quarter, China (37.9%), the US (22.7%) and South Korea (14.1%) remained in the leading three places. The Netherlands (1.1%) and Japan (1.3%) pushed France (0.9%) and Hong Kong (0.9%) out of the Top 10 in terms of the number of attacks. The biggest increase in the proportion of DDoS attacks in Q3 was observed in the US – the share of attacks grew by 5.4 p.p.

      In Q3 2015, the largest numbers of DDoS attacks targeted victims in China, the US & South Korea #KLReport

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      The figures for the leading three countries in both rankings – the number of attacks and the number of targets – increased by more than they did for the other Top 10 countries. The continued leadership of China and the US in the rankings is due to cheap web hosting in those countries, which explains why so many targeted web resources are located there.

      The absolute leader in terms of the number of attacks was an IP address allegedly belonging to a data center in Hong Kong: throughout the quarter it was attacked 22 times.

      Changes in DDoS attack numbers

      In Q3 2015, DDoS activity was distributed unevenly, with two peaks: the first fell in mid-July, the second in late September. The quietest period was from early August to mid-September.

      Number of DDoS attacks over time* in Q3 2015.

      * DDoS attacks may last for several days. In this timeline, the same attack may be counted several times, i.e. one time for each day of its duration.

      The peak number of attacks in one day was 1344, recorded on 24 September.

      Tuesday was the most active day of the week in terms of DDoS attacks.

      Distribution of DDoS attack numbers by days of the week

      The fact that Tuesday leads is probably due to a dramatic rise in the number of DDoS attacks on that day of the week on 14 July and on 22 September. Particularly active on those two days were botnets from Linux-based servers infected by the XOR DDoS bot that attacked resources in China.

      Types and duration of DDoS attacks

      99.3% of DDoS targets in Q3 2015 (vs. 98.2% in Q2) were attacked by bots belonging to one family.

      In only 0.7% of all cases cybercriminals launched attacks using bots from two different families (or the clients used the services of several attack agents). In 0.2% of cases, three or more bots were used.

      In Q3 2015, SYN DDoS (51.7%) remained the most popular attack method. TCP DDoS (16.4%) and HTTP DDOS (14.9%) were second and third respectively. ICMP-DDoS, whose contribution doubled over the last two quarters and accounted for 5.1%, was fourth.

      The distribution of DDoS attacks by types

      Once again, most attacks lasted no longer than 24 hours in Q3 2015. However, the number of attacks that lasted a week or longer increased considerably.

      The distribution of DDoS attacks by duration (hours)

      The longest DDoS attack in the previous quarter lasted for 205 hours (8.5 days); in Q3, this record was beaten by an attack that lasted 320 hours (13.3 days).

      C&C servers and botnet types

      In Q3 2015, South Korea took the lead in terms of the number of C&C servers located on its territory; its share grew from 34% to 56.6%. Noticeably, in South Korea this quarter the number of C&C servers that control Nitol bots increased significantly. Nitol began to use Dynamic DNS services more actively, in particular, no-ip.org and codns.com. As mentioned above, the percentage of DDoS attacks targeting resources located in South Korea also increased.

      The proportion of C&C servers located in the US and China dropped significantly – from 21% to 12.4% and from 14% to 6.9% respectively.

      Distribution of botnet C&C servers by countries in Q3 2015

      The activity of Windows and Linux botnets continued to fluctuate. After the previous quarter’s reduction in the share of Linux-based botnets, in Q3 they regained ground – the proportion of attacks by Linux bots grew from 37.6% to 45.6%.

      Correlation between attacks launched from Windows and Linux botnets

      The increase in the proportion of Linux bot activity was most probably down to insufficient protection for Linux-based machines and, quite importantly, their higher Internet speeds. This makes Linux more attractive to cybercriminals despite the relative complexity in developing, acquiring and exploiting Linux bots.

      Attacks on banks

      The third quarter of 2015 saw the return of DDoS extortionists to the cybercrime scene. A number of major banking institutions in a variety of countries were targeted by DDoS attacks that were then followed by demands for a large payment in cryptocurrency to stop the attack. This particular aspect of the attacks suggests they are the work of the cybercriminal group DD4BC (Distributed Denial of Service for Bitcoin), which demands bitcoin ransoms.

      It appears the group has now reached Russia, where a number of financial institutions were also attacked. Some of the Russian banks that were targeted were either protected by Kaspersky DDoS Protection or quickly connected to the service as soon as the DDoS attacks began. This meant they avoided any damage and the banks’ websites and online banking systems continued to function smoothly.

      Kaspersky Lab registered a wave of lengthy DDoS attacks on the online banking systems of eight well-known financial institutions, with some banks repeatedly targeted.

      SYN DDoS, TCP DDoS and HTTP DDoS were the most common DDoS attack scenarios in Q3 2015 #KLReport

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      For all attacks the cybercriminals used a complex combination of amplification attacks that disable online resource with minimal effort.

      Three types of attack were used to overload the channel: NTP amplification, SSDP amplification and RIPv1 amplification which reached 40 Gbps. In some cases, the attacks were supplemented by a HTTPS flood attack that reached 150 Mbps from a botnet with about 2,000 attacking hosts.

      The attacks lasted from one to four hours.

      The attackers not only demanded a bitcoin ransom but also threatened the banks with unprecedented terabit attacks. However, these threats have not been implemented in practice.

      We can assume that the peak attack parameters registered at the end of September were the attackers’ maximum – Kaspersky Lab experts recorded this particular aggregate capacity in simultaneous attacks on several banks.

      Unfortunately, this does mean the power of attacks will not increase in the future.

      Conclusion

      The correlation between the number of attacks launched from Windows and Linux botnets marks an interesting trend, with criminals starting to actively use botnets from infected servers. There are several reasons for this.

      Firstly, servers have a significantly bigger Internet channel than domestic machines, making it possible to organize powerful attacks with only a few C&C servers.

      Secondly, the level of server protection is not always very high, leaving them vulnerable to hacking. If security patches are not regularly installed on the server, it quickly becomes an easy prey for cybercriminals: it does not take them long to discover such servers and exploit any known vulnerabilities. Then there is the expanded arsenal of available exploits that have appeared after a number of vulnerabilities were detected in open-source products such as exploits for the ghost vulnerability, which is still in use.

      Thirdly, the power of a server botnet can be increased by renting additional servers.

      In these circumstances, timely installation of security patches on servers becomes critical. For the owners of web resources, effective protection from DDoS attacks originating from server botnets is strongly recommended.

      Back up Your Files

      SANS Tip of the Day - Tue, 11/03/2015 - 00:00
      Eventually, we all have an accident or get hacked. And when we do, backups are often the only way to recover. Backups are cheap and easy; make sure you are backing up all of your personal information (such as family photos) on a regular basis.

      IT threat evolution in Q3 2015

      Malware Alerts - Mon, 11/02/2015 - 05:31

       Download PDF version

      Q3 in figures
      • According to KSN data, Kaspersky Lab solutions detected and repelled a total of 235,415,870 malicious attacks from online resources located all over the world.
      • 75,408,543 unique URLs were recognized as malicious by web antivirus components.
      • Kaspersky Lab’s web antivirus detected 38,233,047 unique malicious objects: scripts, exploits, executable files, etc.
      • There were 5,686,755 registered notifications about attempted malware infections that aim to steal money via online access to bank accounts.
      • Kaspersky Lab’s file antivirus detected a total of 145,137,553 unique malicious and potentially unwanted objects.
      • Kaspersky Lab mobile security products detected:
        • 1,583,094 malicious installation packages;
        • 323,374 new malicious mobile programs;
        • 2516 mobile banker Trojans.
      Overview Targeted attacks Turla’s ‘eye in the sky’

      We’ve written about Turla several times over the last year or so (our initial report, follow-up analysis and campaign overview can be found on securelist.com). The group behind this cyber-espionage campaign has been active for more than eight years, infecting hundreds of computers in more than 45 countries. The organizations targeted include government agencies, embassies, military, education, research and pharmaceutical companies.

      The Turla group profiles its victims, using watering-hole attacks in the initial stages. However, as outlined in our latest report, for subsequent operations the group makes use of satellite communications to manage its C2 (Command-and-Control) traffic.

      Most people think of satellite communications as a means of broadcasting TV, but they are also used to provide Internet access. Typically, this is done in remote locations where other types of Internet access are slow, unstable or unavailable. One of the most widespread and least expensive means of obtaining satellite-based access is through a downstream-only connection.

      Turla gang turns to satellites for #cybercrime #KLRreport

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      The method used by Turla to hijack downstream satellite links does not require a valid satellite Internet subscription. The key benefit is that it’s anonymous – it’s very hard to identify the attackers. The satellite receivers can be located anywhere within the area covered by the satellite (typically a wide area) and the true location and hardware of the C2 server can’t be easily identified or physically seized. It’s also cheaper than purchasing a satellite-based link and easier than hijacking traffic between the victim and the satellite operator and injecting packets along the way.

      In order to attack satellite-based Internet connections, both the legitimate users of these links, as well as the attackers’ own satellite dishes, point to the specific satellite that is broadcasting the traffic. The attackers exploit the fact that packets are unencrypted. Once an IP address that is routed through the satellite’s downstream link has been identified, the attackers start listening for packets coming from the Internet to this specific IP. Once a packet has been identified, they identify the source and spoof a reply packet back to the source using a conventional Internet line. At the same time, the legitimate user of the link just ignores the packet as it goes to an otherwise unused port (for instance, port 80 or 10080). You can find a graphical explanation of how Turla uses satellite links here.

      The Turla group tends to focus on satellite Internet providers located in the Middle East and Africa, including Congo, Lebanon, Libya, Niger, Nigeria, Somalia and the UAE. Satellite broadcasts from these countries don’t normally cover European and North American countries, making it very hard for security researchers to investigate such attacks.

      The use of satellite-based Internet links is an interesting development. The hijacking of downstream bandwidth is cheap (around $1,000 for the initial investment and around $1,000 per year in maintenance), easy to do and offers a high degree of anonymity. On the downside, it’s not always as reliable as more traditional methods such as bullet-proof hosting, multiple proxy levels and hacked web sites – all of which Turla also uses. This makes it less likely that it will be used to maintain extensive botnets. Nevertheless, if this method becomes widespread among APT groups or cybercriminals, it will pose a serious problem for the IT security industry and law enforcement agencies.

      Darkhotel extends its ‘guest’ list

      In November 2014, we reported on the Darkhotel APT. These attacks were characterized by the misuse of stolen certificates, the deployment of HTA files using multiple methods and the infiltration of hotel Wi-Fi networks to place backdoors on targets’ computers.

      Recently we published an update on Darkhotel. While the attackers behind this APT continue to use the above methods, they have also supplemented their armoury. They have shifted their attention more towards spear-phishing of their chosen victims. As well as using HTA files, they are also deploying infected RAR files, using the RTLO (right to left override) mechanism to mask the real extension of the file. The attackers also use Flash exploits, including a zero-day exploit leaked as a result of the Hacking Team security breach.

      In 2015, Darkhotel extended its geographic reach, to include victims in North Korea, Russia, South Korea, Japan, Bangladesh, Thailand, India, Mozambique and Germany.

      Blue Termite

      In August, we reported on the Blue Termite APT, a targeted attack campaign focused on stealing information from organizations in Japan. These include government agencies, local government bodies, public interest groups, universities, banks, financial services, as well as companies working in sectors such as energy, communication, heavy industry, chemical, automotive, electrical, news media, information services, health care, real estate, food, semiconductor, robotics, construction, insurance, transportation, and more. One of the most high profile targets was the Japan Pension Service.

      The malware is customized according to the specific victim. The Blue Termite backdoor stores data about itself – including C2, API name, strings for anti-analysis, values of mutexes, as well as the MD5 checksum of backdoor commands and the internal proxy information. The data are stored in encrypted form, making analysis of the malware more difficult – a unique decryption key is required for each sample.

      The main method of infection, as with so many targeted attack campaigns, is via spear-phishing e-mails. However, we have detected other methods of infection. These include drive-by downloads using a Flash exploit (CVE-2015-5119) – one of the exploits leaked following the Hacking Team security breach. Several Japanese web sites were compromised this way. We also found some watering-hole attacks, including one on a web site belonging to a prominent member of the Japanese government.

      Malware stories End of the line for CoinVault?

      On 14 September 2015, Dutch police arrested two men for suspected involvement in CoinVault ransomware attacks, following a joint effort by Kaspersky Lab, Panda Security and the Dutch National High Tech Crime Unit (NHTCU) – highlighting the benefit of collaboration between police and security researchers. This malware campaign started in May 2014 and continued into this year, targeting victims in more than 20 countries, with the majority of victims in the Netherlands, Germany, the United States, France and Great Britain. They successfully encrypted files on more than 1,500 Windows-based computers, demanding payment in bitcoin to decrypt data on victims’ machines.

      The cybercriminals responsible for this ransomware campaign modified their creations several times to keep on targeting new victims. We published our first analysis of CoinVault in November 2014, soon after the first sample of the malicious program appeared. The campaign then stopped until April 2015, when we found a new sample. In the same month, Kaspersky Lab and the Dutch NHTCU launched a web site to act as a repository of decryption keys. In addition, we also made available online a decryption tool to help victims recover their data without having to pay the ransom.

      Arrests made in #CoinVault #ransomware attacks by Dutch Authorities with assist from @Kaspersky #KLReport

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      After publishing the site, Kaspersky Lab was contacted by Panda Security, which had found information about additional malware samples. We were able to confirm that the samples were related to CoinVault. We passed this information to the Dutch NHTCU.

      You can find our analysis of the twists and turns employed by the CoinVault authors here.

      Ransomware has become a notable fixture of the threat landscape. While this case shows that collaboration between researchers and law enforcement agencies can lead to positive results, it’s essential for consumers and businesses alike to take steps to mitigate the risks of this type of malware. Ransomware operations rely on their victims paying up. On top of anti-malware protection, it’s important to make regular backups of data, to avoid data loss and the need to make such ransom payments.

      A serpent in Apple’s walled garden

      The recent appearance of malicious apps in the App Store has made it clear that, contrary to what many people believe, iOS is not immune to malware.

      The malware, called ‘Xcodeghost’, infected dozens of apps, including WeChat, NetEase’s music download app, business card scanner CamCard and Didi Kuadi’s car-hailing app. The Chinese versions of Angry Birds 2 were also infected.

      The attackers didn’t hack the App Store, but hosted a malicious version of Apple’s Xcode. Xcode is a free suite of tools used by software developers to create iOS apps. It is officially distributed by Apple, but also unofficially by third parties: someone in China hosted a version of Xcode that contained XcodeGhost. Some Chinese developers choose to download development tools such as this from local servers because it is much quicker.

      Any apps created using the modified version of Xcode would be infected. The infected apps steal data from their victims and send it to the attackers. It was initially believed that 39 infected apps had bypassed Apple’s scanning process and had been successfully uploaded to the App Store. Infected apps have been removed by Apple. However, the compromised version of Xcode has been available for around six months, so the total number of infected apps could be much higher, not least because the source code for XcodeGhost has been published on Github.

      You can find an analysis of XcodeGhost by researchers at Palo Alto Networks here.

      The incident highlights the danger of programs being infected at source if tools used by developers are compromised.

      The Gaza cyber-gang

      At the end of September we reported on the activities of another regional APT, the Gaza cyber-gang. This is a politically motivated Arabic group operating in the MENA region (Middle East and North Africa) – mainly focused on Egypt, the UAE and Yemen. The group is interested in government agencies – especially embassies, where security and IT operations might not be well-established or reliable. The Gaza cyber-gang has been active since 2012, but became particularly active in the second quarter of 2015.

      The gang actively sends malware to IT and Incident Response (IR) staff in target organizations: the file names they use reflect IT functions and IR tools used to investigate cyber-attacks. It’s not hard to work out why. IT staff typically have greater access rights than other employees, because it’s their job to manage the corporate infrastructure. IR employees are likely to have access to sensitive data related to ongoing cyber-investigations, as well as extended access rights to help them look for suspicious activities across the network. This means the attackers not only gain access to the target organization but also extend their reach across the network.

      The main infection modules used by the group are widely used remote access Trojans (RATs): XtremeRAT and PoisonIvy. Their activities are heavily reliant on social engineering. They use filenames related to IT and IR functions and content and domain names that are likely to be of interest to their victims (e.g. ‘.gov.uae.kim’).

      Statistics

      All the statistics used in this report were obtained using Kaspersky Security Network (KSN), a distributed antivirus network that works with various anti-malware protection components. The data was collected from KSN users who agreed to provide it. Millions of Kaspersky Lab product users from 213 countries and territories worldwide participate in this global exchange of information about malicious activity.

      Mobile threats

      Displaying adverts to users is still the main method of making money from mobile threats. The number of programs displaying intrusive advertising on mobile devices (adware) continued to grow in the third quarter and accounted for more than half of all detected mobile objects.

      We have also observed a growing number of programs that use advertising as the main monetization method while also using other methods from the virus writers’ arsenal. They often root the device of a victim and use superuser privileges, making it very difficult, if not impossible, to combat them. In Q3 2015, these Trojans accounted for more than half of the Top 20 most popular mobile malware.

      In Q3, @Kaspersky mobile security products detected 323,374 new malicious mobile programs #klreport

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      SMS Trojans are still relevant as a monetization method, especially in Russia. These programs send paid messages from an infected device without the user’s knowledge. Although their overall traffic share among mobile threats continues to fall, the malicious mobile Trojan-SMS still leads in terms of the number of new samples detected in the third quarter.

      The pursuit of profit is not limited to displaying adverts or sending paid text messages – cybercriminals are also very interested in users’ bank accounts. In Q3 2015, the total share of mobile bankers and spyware designed to steal personal information exceeded that of SMS Trojans in new mobile malware traffic by 0.7 p.p.

      The number of new mobile threats

      In Q3 2015, Kaspersky Lab mobile security products detected 323,374 new malicious mobile programs – a 1.1-fold increase on Q2 2015 and a 3.1-fold increase on Q1.

      The number of malicious installation packages detected was 1,583,094 – this is 1.5 times more than in the previous quarter.

      Number of malicious installation packages and new malicious mobile programs detected
      (Q1 2015 – Q3 2015)

      Distribution of mobile malware by type

      Distribution of new mobile malware by type, Q2 and Q3 2015

      Potentially unwanted advertising programs (adware) headed the ranking of detected objects for mobile devices in Q3 2015. In the previous quarter this category of programs occupied second place with 19%; in Q3 their share grew considerably and reached 52.2%.

      Second came RiskTool. The programs in this category are legitimate applications that are potentially dangerous for users – if used carelessly or manipulated by a cybercriminal, they could lead to financial losses. RiskTool was knocked off top spot after its share decreased by 16.6 p.p. from the previous quarter.

      The percentage of SMS Trojans in the overall flow of mobile threats decreased by another 1.9 p.p. and amounted to 6.2%. Despite this, they are still among the leading mobile malicious programs.

      SMS Trojans were followed by Spy Trojans (5.4%). These programs steal personal data from users, including incoming text messages (mTANs) from banks.

      Q3 2015, @kaspersky detected 2,516 #mobile banker Trojans, which is a 4X increase on the previous quarter #KLReport

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      In the third quarter of 2015, the biggest growth rates were demonstrated by Trojan-Banker whose share more than doubled and accounted for 1.5% compared to 0.6% in the previous quarter. In Q2, 630 of these programs were detected, while Q3 saw their number increase four-fold and exceed 2500.

      Top 20 malicious mobile programs

      Please note that the ranking of malicious programs does not include potentially dangerous or unwanted programs such as RiskTool or adware.

      Name % of attacked users* 1 DangerousObject.Multi.Generic 46.6 2 Trojan.AndroidOS.Rootnik.d 9.9 3 Trojan-SMS.AndroidOS.Podec.a 7.4 4 Trojan-Downloader.AndroidOS.Leech.a 6.0 5 Trojan.AndroidOS.Ztorg.a 5.5 6 Exploit.AndroidOS.Lotoor.be 4.9 7 Trojan-Dropper.AndroidOS.Gorpo.a 3.3 8 Trojan-SMS.AndroidOS.Opfake.a 3.0 9 Trojan.AndroidOS.Guerrilla.a 2.9 10 Trojan-SMS.AndroidOS.FakeInst.fz 2.6 11 Trojan-Ransom.AndroidOS.Small.o 2.3 12 Trojan-Spy.AndroidOS.Agent.el 2.1 13 Trojan.AndroidOS.Ventica.a 1.9 14 Trojan.AndroidOS.Ztorg.b 1.9 15 Trojan.AndroidOS.Ztorg.pac 1.8 16 Trojan.AndroidOS.Fadeb.a 1.6 17 Trojan-SMS.AndroidOS.Smaps.a 1.5 18 Trojan.AndroidOS.Iop.a 1.5 19 Trojan.AndroidOS.Guerrilla.b 1.5 20 Trojan-SMS.AndroidOS.FakeInst.fi 1.4

      * Percentage of users attacked by the malware in question, relative to all users attacked.

      The top position in the rankings was occupied by DangerousObject.Multi.Generic (46.6%). This is how new malicious applications are detected by the KSN cloud technologies, which help our products to significantly shorten the response time to new and unknown threats. The proportion of DangerousObject.Multi.Generic increased almost three-fold: from 17.5% in Q2 to 46.6% in Q3.

      The number of Trojans that use advertising as the main means of monetization significantly increased from the previous quarter. In the second quarter of 2015 this Top 20 included six of these programs, while in Q3 their number increased to 11: three programs belong to the Trojan.AndroidOS.Ztorg family, and two each belong to the Trojan.AndroidOS.Guerrilla, Trojan.AndroidOS.Rootnik.d, Trojan-Downloader.AndroidOS .Leech.a, Trojan-Dropper.AndroidOS.Gorpo.a, Trojan-Spy.AndroidOS.Agent.el, Trojan.AndroidOS.Ventica.a and Trojan.AndroidOS.Fadeb.a families.

      Unlike the usual advertising modules, these programs do not contain any useful functionality. Their goal is to deliver as many adverts as possible to the recipient using a variety of methods, including the installation of new advertising programs. These Trojans can use superuser privileges to conceal their presence in the system folder, from where it will be very difficult to remove them.

      Of special note is Trojan-Spy.AndroidOS.Agent.el, which is even encountered in the official firmware of some developers.

      Trojan-SMS.AndroidOS.Podec.a (7.4%) has been among the Top 3 malicious mobile programs for four quarters in a row due to how actively it is spread. It is worth mentioning that the functionality of the latest versions of this Trojan has changed and no longer includes the sending of text messages. The Trojan is now fully focused on paid subscriptions, making use of CAPTCHA recognition.

      Seventeenth place is occupied by Trojan-SMS.AndroidOS.Smaps.a. Some of its versions are able to send spam upon receiving a command from the server via the Viber app if it is installed on the victim’s device. No special permission or actions on the part of the user are required by the Trojan to do this.

      The geography of mobile threats

      The geography of mobile malware infection attempts in Q3 2015 (percentage of all users attacked)

      Top 10 counties attacked by mobile malware (ranked by percentage of users attacked)

      Country* % of users attacked ** 1 Bangladesh 22.57 2 China 21.45 3 Nigeria 16.01 4 Tanzania 15.77 5 Iran 13.88 6 Malaysia 13.65 7 Algeria 12.73 8 Nepal 12.09 9 Kenya 11.17 10 Indonesia 10.82

      * We eliminated countries from this ranking where the number of users of Kaspersky Lab’s mobile security product is lower than 10,000.
      ** Percentage of unique users attacked in each country relative to all users of Kaspersky Lab’s mobile security product in the country.

      Most secure country v. #Mobile #Malware Japan (1.13%) Where does your country rank? #KLReport

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      The most secure countries in this respect are:

      Country % of users attacked ** 1 Japan 1.13 2 Canada 2.87 3 Denmark 3.20 4 Sweden 3.45 5 Australia 3.48

      Although Australia is included in the Top 5 most secure countries, when it comes to mobile malware infections the situation is not as safe as would be expected: in the third quarter of 2015, users in Australia were attacked by mobile banker Trojans more often than users in other countries (see below.).

      Mobile banker Trojans

      In Q3 2015, we detected 2,516 mobile banker Trojans, which is a four-fold increase on the previous quarter.

      Number of mobile banker Trojans detected by Kaspersky Lab’s solutions (Q4 2014 – Q3 2015)

      Geography of mobile banking threats in Q3 2015 (number of users attacked)

      The number of attacked users depends on the overall number of users within each individual country. To assess the risk of a mobile banker Trojan infection in each country, and to compare it across countries, we made a country ranking according to the percentage of users attacked by mobile banker Trojans.

      Top 10 counties attacked by mobile banker Trojans (ranked by percentage of users attacked)

      Country* % of users attacked by mobile bankers** 1 Australia 0.85 2 Republic of Korea 0.40 3 Russia 0.32 4 Cyprus 0.32 5 Czech Republic 0.31 6 Austria 0.27 7 Kyrgyzstan 0.26 8 Bulgaria 0.24 9 Romania 0.23 10 Uzbekistan 0.23

      * We eliminated countries from this ranking where the number of users of Kaspersky Lab’s mobile security product is lower than 10,000.
      ** Percentage of unique users in each country attacked by mobile banker Trojans, relative to all users of Kaspersky Lab’s mobile security product in the country.

      Australia, which was ranked eighth in the previous quarter, took the lead in Q3 2015. The percentage of users attacked by mobile bankers in Australia increased six-fold (from 0.14% to 0.85%). Such significant growth was caused by fraudsters making active use of Trojan-Banker.AndroidOS.Agent.ad. This Trojan steals credentials used to enter the online banking system of one of Australia’s largest banks. It also tries to steal users’ credit card details (cardholder’s name, card number, CVV, card expiry date).

      At the same time, Korea, which topped the Q2 rating, saw its share decrease six-fold (from 2.37% to 0.4%) and dropped to second place in the ranking.

      Top 10 countries by the percentage of users attacked by mobile bankers relative to all attacked users

      An indication of how popular mobile banker Trojans are with cybercriminals in each country can be provided by the percentage of users who were attacked at least once by mobile banker Trojans during the quarter, relative to all users in the same country whose mobile security product was activated at least once in the reporting period. This ranking differs from the one above:

      Country* % of users attacked by mobile bankers, relative to all attacked users ** 1 Australia 24.31 2 Austria 7.02 3 Montenegro 5.92 4 Republic of Korea 5.69 5 France 5.66 6 Cyprus 5.56 7 Russia 5.09 8 Czech Republic 4.98 9 Sweden 4.81 10 Finland 4.56

      * We eliminated countries from this ranking where the number of users of Kaspersky Lab’s mobile security product is lower than 10,000.
      ** Percentage of unique users in each country attacked by mobile banker Trojans, relative to all unique users attacked by mobile malware in the country.

      In Australia, which topped the ranking, slightly less than a quarter of all users attacked by mobile malware were targeted by mobile bankers.

      The share of bankers among all mobile malware attacks in Russia halved – from 10.35% to 5.09%. This was due to a significant drop in the activity of the Trojan-Banker.AndroidOS.Marcher family which was one of the most popular in the country. In the third quarter the number of attacks using this malware fell almost ten-fold compared to the previous quarter.

      Vulnerable applications used by cybercriminals

      The ranking of vulnerable applications below is based on information about the exploits blocked by our products. These exploits were used by cybercriminals in Internet attacks and in attempts to compromise local applications, including those installed on mobile devices.

      Distribution of exploits used in attacks by type of application attacked, Q3 2015

      Compared to Q2 2015, the following changes have taken place:

      1. The proportion of Adobe Flash Player exploits has risen by 2 percentage points (p.p.).
      2. The proportion of Adobe Reader exploits has decreased by 5 p.p.

      In Q3, just like the rest of the year, exploits for Adobe Flash Player were in demand. Their share was only 5%, but there are more of them ‘in the wild’ and at the current time nearly all exploit packs are using vulnerabilities in this software. As was the case in the previous quarter, the share of Java exploits (11%) has continued to decrease in Q3. We have not observed any exploits for this software included in recent exploit packs.

      In Q3, the most common exploit packs included exploits for the following vulnerabilities:

      1. CVE-2015-5560 (Adobe Flash; this exploit was described in a Kaspersky Lab article)
      2. CVE-2015-2419 (Internet Explorer)
      3. CVE-2015-1671 (Silverlight)

      The previous quarter saw a dramatic increase in the number of spam messages containing malicious PDF documents. This quarter, the number of these messages decreased significantly, so the proportion of Adobe Reader exploits also decreased.

      The overall trend so far for 2015 has continued in Q3: exploits for Adobe Flash Player and Internet Explorer are most popular with cybercriminals. In the pie chart above, the latter falls into the ‘Browsers’ category; the landing pages from which the exploits spread are also classified here.

      Online threats (Web-based attacks)

      The statistics in this section were derived from web antivirus components that protect users from attempts to download malicious objects from a malicious/infected website. Malicious websites are created deliberately by malicious users; infected sites include those with user-contributed content (such as forums), as well as compromised legitimate resources.

      Online threats in the banking sector

      These statistics are based on the detection verdicts returned by the antivirus module, received from users of Kaspersky Lab products who have consented to provide their statistical data.

      In Q3 2015, Kaspersky Lab solutions blocked attempts to launch malware capable of stealing money via online banking on the 625,669 computers. This number is 17.2 p.p. lower than in Q2 2015 (755,642). A year ago, in Q3 2014 this number was 591,688.

      Kaspersky Lab’s solutions produced a total of 5,686,755 notifications about attempted malware infections aimed at stealing money via online access to bank accounts in Q3 2015.

      Number of attacks by financial users, Q3 2015

      Geography of attacks

      To evaluate and compare the degree of risk of being infected by banking Trojans which user computers are exposed to worldwide, we calculate the percentage of Kaspersky Lab product users who encountered this type of threat during the reporting period in the country, relative to all users of our products in the county.

      Geography of banking malware attacks in Q3 2015 (percent of attacked users)

      Top 10 countries by the percentage of attacked users

      Country* % attacked users** 1 Austria 4.98 2 Singapore 4.23 3 Turkey 3.04 4 Namibia 2.91 5 New Zealand 2.86 6 Hong Kong 2.81 7 Australia 2.78 8 Lebanon 2.60 9 United Arab emirates 2.54 10 Switzerland 2.46

      * We excluded those countries in which the number of Kaspersky Lab product users is relatively small (less than 10,000).
      ** Unique users whose computers have been targeted by web attacks as a percentage of all unique users of Kaspersky Lab products in the country.

      In Q3 2015, Austria became the leader in terms of the percentage of Kaspersky Lab users who were attacked by banking Trojans. Singapore, last quarter’s leader, is now in second place. It should be noted that most countries in the Top 10 have significant numbers of online banking users, and this attracts the cybercriminals.

      In Russia, 0.71% of users encountered a banking Trojan at least once in Q3; this number is little different from the Q2 figure of 0.75%. In the US, the figure was 0.59%, which is 0.3 p.p. lower than in Q2. The countries of Western Europe also saw a small decrease in the percentages of users attacked by banking malware compared to Q2: Spain stood at 1.95%, or 0.07 p.p. less than in Q2; the UK (1.24%) was down 0.34 p.p.; Italy (1.16%) saw a decrease of 0.41 p.p.; while Germany (1.03%) was 0.13 p.p. lower.

      The Top 10 banking malware families

      The table below shows the Top 10 malware families most commonly used in Q3 2015 to attack online banking users:

      Name* Percentage of attacks** 1 Trojan-Downloader.Win32.Upatre 63.13 2 Trojan-Spy.Win32.Zbot 17.86 3 Trojan-Banker.JS.Agent 1.70 4 Trojan-Banker.Win32.ChePro 1.97 5 Backdoor.Win32.Caphaw 1.14 6 Trojan-Banker.Win32.Banbra 1.93 7 Trojan-Banker.AndroidOS.Faketoken 0.90 8 Trojan-Banker.AndroidOS.Agent 0.57 9 Trojan-Banker.Win32.Tinba 1.93 10 Trojan-Banker.AndroidOS.Marcher 0.55

      *These statistics are based on the detection verdicts returned by Kaspersky Lab’s products, received from users of Kaspersky Lab products who have consented to provide their statistical data.
      **Unique users whose computers have been targeted by the malicious program, as a percentage of all unique users targeted by financial malware attacks.

      The majority of the Top 10 malicious programs work by injecting random HTML code in the web page displayed by the browser and intercepting any payment data entered by the user in the original or inserted web forms.

      The Trojan-Downloader.Win32.Upatre family of malicious programs remains at the top of the ranking. The malware is no larger than 3.5 KB in size, and is limited to downloading the payload to the victim computer, most typically a banker Trojan from the Dyre/Dyzap/Dyreza family. The first malicious program from this family was detected in June 2014, and its main aim is to steal the user’s payment details. Dyre does this by intercepting the data from a banking session between the victim’s browser and the online banking web app. In the summer of 2015, however, Trojan-Downloader.Win32.Upatre was spotted on compromised home routers, which is a testimony to how cybercriminals make use of this multiple-purpose malware.

      Trojan-Spy.Win32.Zbot, in second place, has become a permanent resident of this ranking, and it is no coincidence that it consistently occupies a leading position. The Trojans of the Zbot family were among the first to use web injections to compromise the payment details of online banking users and to modify the contents of banking web pages. They encrypt their configuration files at several levels; the decrypted configuration file is never stored in the memory in its entirety, but is instead loaded in parts. This gives the Trojans of the Trojan-Spy.Win32.Zbot family a technological edge over other malware programs.

      Third place in the Q3 ranking was occupied by the Trojan-Banker.JS.Agent family. This is the malicious JavaScript code that results from an injection into an online banking page. The aim of this code is to intercept payment details that the user enters into online banking forms.

      Of particular interest is the fact that three families of mobile banking Trojans are present in this ranking: Trojan-Banker.AndroidOS.Faketoken, Trojan-Banker.AndroidOS.Marcher (we wrote about these two in in the Q2 report), and a newcomer to this ranking – Trojan-Banker.AndroidOS.Agent. The malicious programs belonging to the latter family steal payment details from Android devices.

      The Top 10 operating systems attacked by banker Trojans

      In Q3, users of Windows operating systems encountered the largest number of financial malware attacks (which comes as no surprise given how widespread Windows devices are). That said, users of Windows 7 x64 Edition encountered banking Trojans more often, accounting for 42.2% of all banking Trojan attacks. Android also made it into the list of attacked operating systems.

      Operating system Percentage of attacks* Windows 7 x64 Edition 42.2 Windows 7 11.6 Windows 7 Home x64 Edition 5.5 Windows XP Professional 7.0 Windows 8.1 Home x64 Edition 3.7 Windows 8.1 x64 Edition 2.3 Windows 7 Home 1.3 Windows 10 x64 Edition 1.2 Android 4.4.2 0.6 Windows NT 6.3 x64 Edition 0.7

      *These percentage numbers are relative to all financial malware attacks detected on the computers of unique users who have consented to provide their statistical data.

      It should be noted that although the family of Mac OS X operating systems did not make it to the Top 10, users of this operating system should not see themselves as being immune: in Q3 2015, computers running under Mac OS X were attacked 12,492 times.

      TOP 20 malicious objects detected online

      In the third quarter of 2015, Kaspersky Lab’s web antivirus detected 38,233,047 unique malicious objects (scripts, exploits, executable files, etc.) and reported 75,408,543 unique URLs as malicious.

      In Q3 2015, @Kaspersky Lab's web antivirus detected 38,233,047 unique malicious objects #KLReport

      Tweet

      Of all malicious or potentially unwanted objects, we identified the 20 most active. These 20 accounted for 95% of all attacks on the Internet.

      Top 20 malicious objects detected online

      Name* % of all attacks** 1 Malicious URL 53.63 2 AdWare.JS.Agent.bg 16.71 3 AdWare.Script.Generic 7.14 4 Trojan.Script.Generic 6.30 5 Trojan.Script.Iframer 3.15 6 Trojan.Win32.Generic 1.52 7 AdWare.Win32.SoftPulse.heur 1.31 8 AdWare.JS.Agent.bt 1.09 9 AdWare.Win32.OutBrowse.heur 0.84 10 Trojan-Downloader.Win32.Generic 0.63 11 AdWare.NSIS.Vopak.heur 0.46 12 Exploit.Script.Blocker 0.46 13 Trojan-Downloader.JS.Iframe.diq 0.30 14 AdWare.Win32.Amonetize.aqxd 0.30 15 Trojan-Downloader.Win32.Genome.tqbx 0.24 16 AdWare.Win32.Eorezo.abyb 0.23 17 Hoax.HTML.ExtInstall.a 0.19 18 Trojan-Clicker.HTML.Iframe.ev 0.17 19 AdWare.Win32.Amonetize.bgnd 0.15 20 Trojan.Win32.Invader 0.14

      * These statistics represent the detection verdicts of the web antivirus module. Information was provided by users of Kaspersky Lab products who consented to share their local statistical data.
      ** The percentage of all web attacks recorded on the computers of unique users.

      The Top 20 is largely made up of verdicts assigned to objects used in drive-by attacks, as well as adware programs. This quarter, adware verdicts occupied nine positions in this ranking.

      Of interest is the verdict Hoax.HTML.ExtInstall.a, assigned to a web page which blocks the browser and urges the user to install a Chrome extension. When the user tries to close the page, the voice file ‘voice.mp3’ is often played – “Click on the ‘Add’ button to close this page”.

      Web page urging users to install a Chrome extension
      (translation: “Press ‘Add’ to continue”)

      The extensions that are offered do not cause any harm to users. However, the prompt is very intrusive and it is practically impossible for the user to reject it. This is why Kaspersky Lab products detect the corresponding web page with its popup window as malicious. There is a partnership program that uses this method to distribute the extension.

      Top 10 countries where online resources are seeded with malware

      The following statistics are based on the physical location of the online resources that were used in attacks and blocked by our antivirus components (web pages containing redirects to exploits, sites containing exploits and other malware, botnet command centers, etc.). Any unique host could be the source of one or more web attacks.

      In order to determine the geographical source of web-based attacks, domain names are matched up against their actual domain IP addresses, and then the geographical location of a specific IP address (GEOIP) is established.

      The #USA is top country with malicious web-based attack resources in Q3 #KLReport

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      In Q3 2015, Kaspersky Lab solutions blocked 235,415,870 attacks launched from web resources located in various countries around the world. 80% of notifications on blocked web attacks were triggered by attacks coming from web resources located in 10 countries.

      Distribution of web attack sources by country, Q3 2015

      Q3 saw the US take over first place (with 26.9%) from Russia (18.8%). The Virgin Islands and Singapore have fallen out of the Top 10, while there are two newcomers – Sweden (1.43%) and Canada (1.42%).

      Countries where users faced the greatest risk of online infection

      In order to assess the risk of online infection faced by users in different countries, we calculated the percentage of Kaspersky Lab users in each country who encountered detection verdicts on their machines during the quarter. The resulting data provide an indication of the aggressiveness of the environment in which computers work in different countries.

      Country* % of unique users attacked** 1 Russia 38.20 2 Nepal 36.16 3 Kazakhstan 33.79 4 Ukraine 33.55 5 Syria 32.10 6 Azerbaijan 32.01 7 Belarus 30.68 8 Vietnam 30.26 9 China 27.82 10 Thailand 27.68 11 Armenia 27.65 12 Brazil 26.47 13 Algeria 26.16 14 Turkey 25.13 15 Mongolia 25.10 16 Kyrgyzstan 23.96 17 Macedonia 23.84 18 Lithuania 23.59 19 Bangladesh 23.56 20 Moldavia 23.36

      These statistics are based on the detection verdicts returned by the web antivirus module, received from users of Kaspersky Lab products who have consented to provide their statistical data.

      *These calculations excluded countries where the number of Kaspersky Lab users is relatively small (fewer than 10,000 users).
      **Unique users whose computers have been targeted by web attacks as a percentage of all unique users of Kaspersky Lab products in the country.

      The leader of this ranking remained unchanged – it is still Russia with 38.2%. Since the previous quarter, Georgia, Croatia, Qatar, Bosnia and Herzegovina and Greece have left the Top 20. Newcomers to the ranking are Nepal, which went straight in at number two (36.16%), Brazil in 12th place (26.47%), Turkey in 14th (25.13%), Lithuania in 18th (23.59%), and Bangladesh (23.56%) in 19th.

      23.4% of computers connected to the Internet globally were subjected to at least one web attack during Q3 #KLReport

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      The countries with the safest online surfing environments included Switzerland (17%), the Czech Republic (16%), the US (16.3%), Singapore (15%), Hungary (13.8%), Norway (13%), Ireland (12.2%), and Sweden (10.8%).

      On average, 23.4% of computers connected to the Internet globally were subjected to at least one web attack during the three months. This is a 0.5 p.p. decrease on Q2.

      Local threats

      Local infection statistics for users computers are a very important indicator: they reflect threats that have penetrated computer systems using means other than the Internet, email, or network ports.

      Data in this section is based on analyzing statistics produced by antivirus scans of files on the hard drive at the moment they were created or accessed, and the results of scanning removable storage media.

      In Q3 2015, Kaspersky Lab’s file antivirus modules detected 145,137,553 unique malicious and potentially unwanted objects.

      Top 20 malicious objects detected on user computers

      Name* % of unique users attacked** 1 DangerousObject.Multi.Generic 19.76 2 Trojan.Win32.Generic 14.51 3 Trojan.WinLNK.StartPage.gena 5.56 4 WebToolbar.JS.Condonit.a 4.98 5 AdWare.Script.Generic 4.97 6 WebToolbar.Win32.Agent.azm 4.48 7 RiskTool.Win32.GlobalUpdate.dx 3.63 8 WebToolbar.JS.AgentBar.e 3.63 9 WebToolbar.JS.CroRi.b 3.32 10 Downloader.Win32.Agent.bxib 3.20 11 AdWare.Win32.OutBrowse.heur 3.13 12 Adware.NSIS.ConvertAd.heur 3.08 13 AdWare.Win32.Generic 3.06 14 Downloader.Win32.MediaGet.elo 2.98 15 Trojan.Win32.AutoRun.gen 2.92 16 AdWare.Win32.BrowseFox.e 2.91 17 WebToolbar.Win32.MyWebSearch.si 2.82 18 AdWare.Win32.MultiPlug.heur 2.66 19 Virus.Win32.Sality.gen 2.61 20 RiskTool.Win32.BackupMyPC.a 2.57

      *These statistics are compiled from malware detection verdicts generated by the on-access and on-demand scanner modules on the computers of those users running Kaspersky Lab products who have consented to submit their statistical data.
      **The proportion of individual users on whose computers the antivirus module detected these objects as a percentage of all individual users of Kaspersky Lab products on whose computers a file antivirus detection was triggered.

      In line with the established practice, this ranking represents the verdicts assigned to adware programs or their components, and to worms distributed on removable drives.

      The only virus in the rankings – Virus.Win32.Sality.gen – continues to lose ground. The proportion of user machines infected by this virus has been diminishing for a long time. In Q3 2015, Sality was in 19th place with 2.61%, which is a 0.25 p.p. decrease on Q2.

      Countries where users faced the highest risk of local infection

      For each of the countries, we calculated the percentage of Kaspersky Lab product users on whose computers the file antivirus had been triggered during the quarter. These statistics reflect the level of personal computer infection in different countries.

      Top 20 countries with the highest levels of computer infection

      Country* % of unique users** 1 Bangladesh 64.44 2 Vietnam 60.20 3 Nepal 60.19 4 Georgia 59.48 5 Somalia 59.33 6 Laos 58.33 7 Russia 57.79 8 Armenia 57.56 9 Afghanistan 56.42 10 Ethiopia 56.34 11 Rwanda 56.21 12 Syria 55.82 13 Mozambique 55.79 14 Yemen 55.17 15 Cambodia 55.12 16 Algeria 55.03 17 Iraq 55.01 18 Kazakhstan 54.83 19 Mongolia 54.65 20 Ukraine 54.19

      These statistics are based on the detection verdicts returned by on-access and on-demand antivirus modules, received from users of Kaspersky Lab products who have consented to provide their statistical data. The data include detections of malicious programs located on users’ computers or on removable media connected to the computers, such as flash drives, camera and phone memory cards, or external hard drives.

      * These calculations exclude countries where the number of Kaspersky Lab users is relatively small (fewer than 10,000 users).
      ** The percentage of unique users in the country with computers that blocked local threats as a percentage of all unique users of Kaspersky Lab products.

      The newcomers to this ranking are Mozambique in 13th position (55.8%), and Yemen in 14th (55.2%).

      42.2% of computers globally faced at least one local threat during Q3 2015 #KLReport

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      The safest countries in terms of local infection risks were Sweden (21.4%), Denmark (19.8%) and Japan (18.0%).

      An average of 42.2% of computers globally faced at least one local threat during Q3 2015, which is 2.2% p.p. more than in Q2 2015.

      Go With Passphrases

      SANS Tip of the Day - Mon, 11/02/2015 - 00:00
      Passphrases are the strongest type of passwords and the easiest to remember. Simply use an entire sentence for your password, such as "What time is coffee?" By using spaces and punctuation, you create a long password that is hard to guess but easy to remember.

      0xHACKED: Brown University Accounts Distributing Phishing Emails

      Malware Alerts - Wed, 10/28/2015 - 09:56

      “Ido, we will address this compromise with Miss. XXXX directly. Thank you for notifying us,” said the last email received from Miss. Patricia Falcon, Information Security Policy & Awareness Specialist at the University of Brown, Rhode Island. Suspected spear phishing campaign attempting to steal users’ credentials by sending phishing emails masquerading as Google recovery.

      From the beginning:

      When the first email arrived in one of my Gmail inboxes I thought it was just another phishing scam – report it and toss it into the trash. But then I thought, hold on… it made its way through all the Gmail spam filters, so why not take a quick look.

      That was on 5 October, an email with a “NO REPLY.” alias in the Sender field was marked as unread and after clicking it, a Google recovery email opened. Next to its subject was a profile picture of a person I didn’t know. Well, I thought, hackers don’t tend to post their pictures on their own phishing emails. So I checked the details and it was an email from Brown University, located in Rhode Island, United States.

      Could it be a spear phishing campaign against the university?

      On second thoughts, it was only one email. Maybe the person was lured by some appealing content into clicking a link where he simply entered his username and password to a fake form that hijacked his credentials.

      First incident: Yet another phishing email

      Browsing through the body of the email, I got the impression that it was very well written and was not some first-timer’s attempt. Not many obvious mistakes. Can you spot any?

      Fake email from Brown University compromised account

      1. Funny – the old Google logo is used.
      2. First line after “Hello” has a space before the first sentence starts.
      3. “The Google Accounts team“? Who are they? And a capital ‘T’, surely?
      4. Close my account because info is missing and then verify existing info to continue using it? Where’s the logic in that?
      5. The button should say “Verify Account Details” not “Verify Email Address”, right?

      We could spot some more, but that’s enough for now.

      With all that in mind, the picture is the first thing that immediately draws your attention. It’s because this is a valid Gmail account of a person named Ph****p P**g. This person works for Brown University and brown.edu email servers are actually hosted by Google. That means that the compromised account can initially send phishing emails to any Gmail user account without them hitting the spam folder – not until it’s being reported as spam.

      After trying to notify Mr. P**g in every possible medium he existed in online, I finally gave up. We reported the phishing attempt registered as an ow.ly short link that redirects to a domain named after a song by a Nigerian rapper, and hosted on GoDaddy.

      Two domain names have been identified so far; however, the IP address indicates massive use of phishing and even kits available for direct download and use. One of the domains found was the initial redirection URL from the malicious email short link and the other one was embedded in a PHP form action attribute, located within the phishing website’s /index.html page, masquerading as a legitimate Google recovery form.

      Fake Google recovery form

      Here is the chain of events from the victim’s point of view:

      1. Compromised Gmail account sends a message to the Gmail victim – Not spam.
      2. Victim clicks the fake “Verify” button and the embedded short link executes.
      3. Short link becomes a long link redirecting to hxxp://shokiti-bobo-crew[.]net/<your ip>/index.html. (Fake Gmail Recovery)
      4. The page sends a fake Javascript alert() that the victim’s Gmail account has been logged out.
      5. Clicking OK reveals a form similar to the Gmail login page, only with additional fields, such as recovery email, phone and date of birth.
      6. Submitting the PHP form sends the data to another malicious server – hxxp://owo-ni-boiz[.]net/auth.php
      7. After submitting the form, the page redirects back to Gmail – which was logged in the whole time – persuading the victim that the fake logout alert() message from step (4) was real.
      The second [Co]incident

      20 October, 8:00AM, another email arrived. To my surprise, it had the same origin – brown.edu – but a different victim.

      It was now a woman. Her name is Q***h T**n, a former employee of the university and a current LinkedIn employee. Her account was immediately deleted after we reported the scam to LinkedIn.

      LinkedIn employee account deleted after Gmail account was compromised in the attack

      This email was different, suggesting that our threat actors have many templates at their disposal. However, the domains were the same. Since she is a former employee, it might mean her account was taken over while her account was disabled. It’s possible that the attackers took over a server that has modified privileges and they have managed to reactivate the dormant accounts of former employees.

      Second fake email to come from a former Brown University employee

      Issues spotted:

      1. No “Hello” this time – straight to the point.
      2. Non-US spelling: “take a look at the help centre or watch the video“
      3. Capital ‘R’ in ‘required’ is missing from subject.
      4. Russian? <img alt=”Логотип (Google Диск)” border=”0″>
      5. under “to bcc” there is a tiny button that was supposed to display a Google logo. Instead, it is broken and the HTML attributes are in Russian. “Logotip (Google Disk)”, says the alt.
      6. Lastly, this redirection is using bit.ly, not ow.ly

      This time the navigation is the other way around. If the first instance was redirecting to hxxp://shokiti-bobo-crew[.]net/ to submit a form that was sent to hxxp://owo-ni-boiz[.]net/, then this time the address hxxp://owo-ni-boiz[.]net/, redirects to hxxp://shokiti-bobo-crew[.]net/mission/xconactc.php

      We were the first to submit the URL to Virus Total, meaning it’s still fresh. No anti-viruses identified the link as malicious.

      Conclusions:

      OWO NI BOYS and SHOKITI BOBO are both songs by Nigerian rappers. This suggests that the attackers are influenced by rappers such as Olamide and Kida Kudz or are trying to create this false sense for analysts.

      The second piece of information was the Russian Google Drive logo found in second incident. Both creates assumptions about threat actors way of thinking, either by injecting false information or by making terrible mistakes.

      One thing is for sure – Brown University is suffering from a few compromised accounts and this attack is still active.

      Secure Your Home Wi-Fi Network

      SANS Tip of the Day - Wed, 10/28/2015 - 01:00
      Be aware of all the devices connected to your home network, including baby monitors, gaming consoles, TVs, appliances or even your car. Ensure all those devices are protected by a strong password and/or are running the latest version of their operating system.

      On the trail of Stagefright 2

      Malware Alerts - Fri, 10/23/2015 - 09:03

      In early October, it was announced that a critical vulnerability had been found in the libutils library. The libutils library is part of Android OS; it implements various primitive elements that can be used by other applications. The least harmful result that exploiting this vulnerability could lead to is the software that uses the stagefright library and handles MP3/MP4 files crashing.

      Although exploits for newly discovered vulnerabilities take a while to appear ‘in the wild’, we believe we should be prepared to detect them even if there have been no reports, as yet, of any such exploits being found. Since a working exploit is needed to develop protection functionality, PoC files are commonly used to implement detection.

      In this case, developing detection logic that would cover possible exploits for the vulnerability was complicated by the fact that no PoC files were readily available. Because of this, we decided to do the research and generate a PoC file on our own.

      We are going to omit some technical details when discussing our work to prevent cybercriminals from using this information.

      We began by looking at the changes made to the source code of libutils in order to close the vulnerability. As it turned out, the following change was among the latest:

      Checking input parameters in allocFromUTF8 function of String8 class

      It can be seen in the code that if len = SIZE_MAX, this will cause an integer overflow when allocating memory.

      We assumed that the following had to be done to cause software that handles MP3 files to malfunction: pass a number equal to SIZE_MAX as the second parameter to the allocFromUTF8 function. The function is called from several places in the String8 class. If you analyze the implementation of the String8 object, you will see that the function of interest to us is called in the following places:

      1. in the String8 class’s constructor (two implementations are possible);
      2. in the setTo method (two implementations are possible).

      It is also worth noting that in one of the two implementations of the constructor and in one of the two implementations of the setTo method, an input parameter is passed that is subsequently passed to allocFromUTF8. This leads us to another conclusion: we are interested in the code that creates the String8 object and explicitly passes the string length in the class’s constructor or calls the setTo method (specifying the string length).

      Based on what we know, the vulnerability is exploited when handling MP3 files. This means that it makes sense to look at the way the String8 class is used in the code responsible for handling MP3 files. This code is easy to find in the following branch: \media\libstagefright\MP3Extractor.cpp.

      Use of the String8 class in MP3Extractor.cpp code

      One of the first times the class is used is when parsing the MP3 file’s COMM tag (the tag stores information on comments to the MP3 file):

      Reading comments from an MP3 file using the vulnerable String8 class

      It can be seen in the code that another class, ID3, which is responsible for parsing ID3 data, is used to read strings (we are interested in the getString method).

      Before looking at this component’s code, have a look at the COMM tag’s structure (information on this can be found in official documentation — http://id3.org/d3v2.3.0).

      Example of the COMM tag from a regular MP3 file

      Based on the documentation, we have the following:

      COMM – Frame ID
      00 00 00 04 – size
      00 00 – flags
      00 – text encoding
      00 00 00 – Language
      00 – null terminated short description
      74 65 73 74 (test) – actual text

      Next, let’s look at the ID3 parser code:

      void ID3::Iterator::getString(String8 *id, String8 *comment) const { getstring(id, false); // parse short description if (comment != NULL) { getstring(comment, true); } } void ID3::Iterator::getstring(String8 *id, bool otherdata) const { id-&gt;setTo(""); const uint8_t *frameData = mFrameData; if (frameData == NULL) { return; } uint8_t encoding = *frameData; if (mParent.mVersion == ID3_V1 || mParent.mVersion == ID3_V1_1) { ..... } size_t n = mFrameSize - getHeaderLength() - 1; // error, overflow possible !!! if (otherdata) { // skip past the encoding, language, and the 0 separator frameData += 4; int32_t i = n - 4; while(--i &gt;= 0 &amp;&amp; *++frameData != 0) ; int skipped = (frameData - mFrameData); if (skipped &gt;= (int)n) { return; } n -= skipped; } if (encoding == 0x00) { // ISO 8859-1 convertISO8859ToString8(frameData + 1, n, id); } else if (encoding == 0x03) { // UTF-8 id-&gt;setTo((const char *)(frameData + 1), n); } else if (encoding == 0x02)

      It can be seen in the code that, under certain conditions, we can call the setTo method of the String8 class, which will in turn call allocFromUTF8 with a pre-calculated value of n.

      It only remains to find out whether we can influence the value of n in any way. And, more specifically, whether we can make certain that -1 (0xFFFFFFFF) is written to n as a result of calculations.

      The size of the header depends on the version of the ID3 format.

      Now we only need to sort out mFrameSize. The amount of code used to calculate this parameter is sufficiently large. It was established by trial and error that the value of the mFrameSize variable when parsing a file also depends on the COMM tag and the version of the file being parsed.

      It follows from this that we have the means to influence the values of two variables from the following expression:

      size_t n = mFrameSize — getHeaderLength() – 1

      By changing data in the COMM tag, we can influence mFrameSize. Using simple math, we can make certain that the following expression is true:

      mFrameSize — getHeaderLength() – 1 = -1

      As a result of execution, the following value will be written to the n variable: -1 (0xFFFFFFFF).

      Now, all we have to do is pass this value to the setTo function. It can be seen in the code that this method will be called if the encoding field in the COMM tag header has certain values.

      Calling the setTo method and passing data size to it

      If these conditions are met, we get an MP3 file with a malformed COMM tag. Processing it will result in the stock browser and music player crashing:

      Stack trace of a crash when processing an MP3 file with a malformed COMM tag

      This means we have successfully created a PoC exploit for the vulnerability in question.

      Kaspersky Lab products detect this exploit as HEUR:Exploit.AndroidOS.Stagefright.b.