Big Data. Big Decisions
InformationWeek
Special Coverage Series


Fast Flux Botnet Nets Fraudsters $78 Million

Security report offers new details on financial hackers, warns that automated clearing house payment channels could be next target of increasingly sophisticated attacks.

Who Is Hacking U.S. Banks? 8 Facts
Who Is Hacking U.S. Banks? 8 Facts
(click image for larger view and for slideshow)
What does it take to build a cutting-edge, highly automated series of attacks against banking systems, powered by financial malware and bulletproof hosting services? For starters, it helps to have extensive experience using the Zeus and SpyEye financial malware toolkits.

That's just one finding from "Operation High Roller Revisited," a new report released this week by McAfee and Guardian Analytics, which provides greater insights into the gangs that appear to be behind a massive number of attacks launched against financial institutions from servers located in Russia, Albania and China.

More Insights

Webcasts

More >>

White Papers

More >>

Reports

More >>

[ Apparently, even hacktivists need a holiday. Read U.S. Bank Hackers Promise DDoS Pause. ]

The criminals have stolen an estimated $78 million, in part by using financial malware. "These campaigns, like many other attempts at fraud, originated in Eastern Europe, so it is not surprising that the actors had an extensive history of Zeus and SpyEye activity," read the report, which was written by Ryan Sherstobitoff, a threat researcher at McAfee.

But the attackers' sophistication has also continued to increase. "Prior to conceiving Operation High Roller, our data shows that the fraudsters actively participated in early automated transfer systems against consumers and some business accounts and actively used Zeus and SpyEye in these attacks," said Sherstobitoff in a blog post. "These initial efforts were likely their test ground to gain knowledge of financial systems and their various fraud prevention practices." From there, he said, the gangs progressed to more advanced attacks, including launching highly automated transfer system exploits against European banks at the end of 2011. Earlier this year, the attacks were expanded to exploit banks in North America as well.

The new report updates research released in June by McAfee and Guardian Analytics, which first detailed Operation High Roller. A total of 12 different criminal gangs appear to be involved in the attacks, which have been launched against financial institutions of every size, from credit unions to large banks. Most of the attacks documented in that report used Zeus and SpyEye malware to attempt to transfer money out of accounts located in the United States and the Netherlands.

The groups behind Operation High Roller have tended to focus only on certain industries. "Typically these campaigns have no precise target other than high net worth businesses with significant cash flow," according to the report. Interestingly, however, the U.S. attacks seemed to focus on commercial banking involving businesses in the manufacturer and import/export industries, as well as state and local governments.

Their attacks mix manual exploits with quite sophisticated automated attacks, which were launched against thousands of financial institutions in Europe and North America. To help avoid detection, criminals launched their automated attacks not from compromised PCs that were part of a botnet but from servers. These servers appeared to be leased from so-called bulletproof hosting providers, predominantly located in Russia, China, or other parts of Asia, which offer quite lenient "acceptable use" policies and terms of service for their systems.

Now the researchers have found that the criminals involved in Operation High Roller had previously used elements of the same infrastructure to launch a series of prior attacks that involved automated transfer system attack tools, which are designed to automatically drain targeted bank accounts.

In the past, malware such as Zeus might use Web injection files to modify target websites, then attempt to trick users into inputting their credentials, at which point attackers could manually steal their money by transferring it into another account. Automated transfer systems, however, take users out of the equation because they "allow cybercriminals to automatically transfer funds from victims' accounts to their own ones without leaving traces of their presence," according to Trend Micro threat researcher Loucif Kharouni. "Instead of merely passively stealing information, [they] allow cybercriminals to instantly carry out financial transactions that could deplete users' bank accounts without their knowledge."

McAfee's Sherstobitoff said that researchers had traced some of the attacks to a server located in Kemerovo, Russia. But that server pointed to other servers, some located in China and one in San Jose, Calif. "These connections were the first indication that this was a 'fast-flux' botnet with many levels of complication," he said. "The fast-flux technique allows malware to hide itself in an array of compromised servers and increase its lifespan."

Going forward, expect the gangs involved in Operation High Roller to continue pushing the malicious-banking-attack state of the art. "Financial institutions, regulators, and security researchers should expect the likely next target to be Automated Clearing House payment channels," said Sherstobitoff. "The fraudsters will build on the methods, malware, and infrastructure employed in Operation High Roller, laced with new ideas and locations to be discovered. We should be looking for any signs of 'test cases' against these systems and tracking interactions to uncover malicious sites and infrastructure."

Organizations challenged by meeting the requirements of multiple regulatory mandates are increasingly looking at the alignment of governance, risk, and compliance under a unified framework, GRC.In our report, A Security Pro's Guide To GRC, we examine where the security professionals figure into the mix and recommend the steps organizations should take to align IT GRC with existing security programs and processes. (Free registration required.)



Related Reading




Currently we allow the following HTML tags in comments:

Single tags

These tags can be used alone and don't need an ending tag.

<br> Defines a single line break

<hr> Defines a horizontal line

Matching tags

These require an ending tag - e.g. <i>italic text</i>

<a> Defines an anchor

<b> Defines bold text

<big> Defines big text

<blockquote> Defines a long quotation

<caption> Defines a table caption

<cite> Defines a citation

<code> Defines computer code text

<em> Defines emphasized text

<fieldset> Defines a border around elements in a form

<h1> This is heading 1

<h2> This is heading 2

<h3> This is heading 3

<h4> This is heading 4

<h5> This is heading 5

<h6> This is heading 6

<i> Defines italic text

<p> Defines a paragraph

<pre> Defines preformatted text

<q> Defines a short quotation

<samp> Defines sample computer code text

<small> Defines small text

<span> Defines a section in a document

<s> Defines strikethrough text

<strike> Defines strikethrough text

<strong> Defines strong text

<sub> Defines subscripted text

<sup> Defines superscripted text

<u> Defines underlined text

BYTE encourages readers to engage in spirited, healthy debate, including taking us to task. However, BYTE moderates all comments posted to our site, and reserves the right to modify or remove any content that it determines to be derogatory, offensive, inflammatory, vulgar, irrelevant/off-topic, racist or obvious marketing/SPAM. BYTE further reserves the right to disable the profile of any commenter participating in said activities.

Disqus Tips To upload an avatar photo, first complete your Disqus profile. | View the list of supported HTML tags you can use to style comments. | Please read our commenting policy.

Follow InformationWeek

By The Numbers

What Are Your Primary Concerns About Using Big Data Software?

Base: 417 respondents at organizations using or planning to deploy data analytics, BI or statistical analysis software
Data: InformationWeek 2013 Analytics, Business Intelligence and Information Management Survey of 541 business technology professionals, October 2012

What Do You Think?

What's your attitude about SQL analysis on top of Hadoop?
We want fast, standard SQL analysis capabilities on Hadoop ASAP
Hadoop is for unstructured data; SQL is for relational databases
We'll give SQL on Hadoop a try, but relational DBs will remain the mainstay
Given strong SQL support on Hadoop, we'd nix the data warehouse
We're not interested in Hadoop
No opinion



Related Content

From Our Sponsor

Five Big Data Challenges and How to Overcome Them with Visual Analytics

Five Big Data Challenges and How to Overcome Them with Visual Analytics

Business leaders often need a visual snapshot of data to quickly grasp and use it. This paper identifies five challenges in presenting data and how visual analytics can resolve them. Solutions are suggested to overcome the challenges of: speed, data clarity, data quality, displaying meaningful results, and dealing with outliers.

Game-Changing Analytics: How IT Executives Can Use Analytics to Create Innovation and Business Success

Game-Changing Analytics: How IT Executives Can Use Analytics to Create Innovation and Business Success

Today's competitive advantage requires a deeper understanding of your business, your market and your customers. As an IT executive, you can drive that knowledge transformation. In this white paper, learn how to make decisions as a strategic business leader and three steps to begin an analytics initiative within your enterprise.

Data Visualization Techniques: From Basics to Big Data with SAS Visual Analytics

Data Visualization Techniques: From Basics to Big Data with SAS Visual Analytics

High-performance data visualization turns sophisticated analyses into meaningful graphics, leading to faster and smarter decision making. In this white paper, learn how visual analytics can transform big data, with additional features such as real-time functionality, mobile compatibility, robust applications for technical groups and accessibility for nontechnical users.

Big Data: Lessons from the Leaders

Big Data: Lessons from the Leaders

Financial performance, competitive advantage, operational efficiency, strategic decision making - every business goal can extract value from big data, and the time for doubt or inaction has long passed. In this Economist Intelligence Unit report, in-depth interviews with data pioneers reveal the link between the effective use of big data and the bottom line among other results.

Decision-Driven Data Management: A Strategy for Better Decisions with Better Data

Decision-Driven Data Management: A Strategy for Better Decisions with Better Data

Which came first, the data or the decision? This white paper makes the case for having a decision in mind, then tailoring big data's volume, variety and velocity to achieve business results such as overcoming customer dissatisfaction or creating well-informed strategies in real time.

Informationweek Reports

Research: The Big Data Management Challenge

Research: The Big Data Management Challenge

The challenge of big data is real, but most organizations don't differentiate 'big data' from traditional data, and nearly 90% of respondents to our survey use conventional databases as the primary means of handling data. We'll help you understand what constitutes big data (it's not just size) and the numerous management challenges it poses.