Big Data. Big Decisions
InformationWeek
Special Coverage Series

Commentary

Mathew J. Schwartz

Mathew J. Schwartz



Shady RAT No China Smoking Gun

Kudos to McAfee for discovering attacks that go undiscovered too often, but questions about attack severity, sophistication, or nation-state backing remain.

Is Shady RAT one of the "the biggest series of cyberattacks in history," as some media outlets have claimed?

McAfee's revelation of the long-running attacks, which have operated on the sly since at least 2006 and compromised more than 70 organizations, was timed to coincide with the publication last week of a related expose in Vanity Fair, as well as the start of the annual Black Hat security conference. McAfee's security researchers have been investigating the attacks-which they dubbed Shady RAT for their use of stealthy remote access tools-for some time.

More Insights

Webcasts

More >>

White Papers

More >>

Reports

More >>

While the tools used in such attacks can steal information, such attacks apparently exist in relatively low volumes, at least compared with the flood of spam, phishing attacks, and generic malware businesses see daily. But that low volume also makes RAT-style attacks difficult to detect when they do get launched.

If this low volume and persistence sound familiar, that's because it recalls the modus operandi for an advanced persistent threat. Of course, APT is a fuzzy concept. As McAfee's own report on Shady RAT notes, "this term lately lost much of its original meaning due to overzealous marketing tactics of various security companies, as well as to the desire by many victims to call anything they discover being successful at compromising their organizations as having been an APT." (Reference: RSA SecurID breach.) Generally, however, security experts define an APT as a threat involving attackers who can launch multiple exploits, advancing the underlying functionality along the way, to steal non-financial information of value, often operating without being detected.

The interesting APT-related angle to Shady RAT is that the attackers failed to update their Trojan software attack functionality for more than a year and failed to encrypt the server used to control the Trojans (often used by Chinese attackers). As a result, they left a trail that McAfee's researchers ultimately spotted and traced to the command-and-control server. The attackers had already installed Web traffic analysis tools on the server, further aiding researchers.

But simply discovering that server was somewhat unusual. "It was great that McAfee was able to get access to this data and show how it works," Joe Stewart, director of malware research for Dell SecureWorks, told me last week at Black Hat.

Some security researchers, however, dispute that Shady RAT would even qualify as an APT. "I would contend that it isn't, especially when you consider the errors made in configuring the servers and the relatively non-sophisticated malware and techniques used in this case," said Symantec researcher Hon Lau in a blog post. "Sure, the people behind it are persistent, but no more so than the myriad of other malware groups out there such as Zeus, Tidserv, and others like them."

While McAfee's discovery of the mechanics behind the Shady RAT attacks was new, the existence of the group was already known. Stewart said it's often referred to as the "Comment Crew," for using HTML comments as a mechanism for communicating with the botnet command-and-control servers the group operates. "They've got lots of infrastructure behind it, stuff we'll never get access to," he said. But the group has left tracks before. "One of the malware families belonging to this group is one that we saw using HTran, and sending its data back to China," Stewart said.

As a result of that traffic flow, security experts suspect the Comment Crew is operating from China. McAfee, while saying that it saw a solo "state actor" behind the attacks, stopped short of pointing fingers. Likewise, Alex Gostev, chief security expert for Kaspersky Lab, said that without hard evidence, people should beware jumping to conclusions about who's behind this attack, especially when it comes to the motives of criminal organizations.

For starters, Gostev said, the circumstances surrounding Shady RAT's discovery make the suggestion of state-sponsored hacking tenuous. "A situation in which a complicated and large-scale corporate espionage operation has alleged to have been undertaken for years but whose sophisticated organizers do not clean up their server access logs after them--this is something that can certainly be described as unusual," he said.

Furthermore, when it comes to how Shady RAT was used, McAfee has assumed--based on logs of connections between Web servers--that large organizations were spied on. But the report doesn't identity data that might have been stolen, or which specific Trojan applications were used, which makes it unclear what type of damage Shady RAT may even have caused, Gostev said.

"Until the information in the McAfee report is backed up by evidence, to talk about the biggest cyberattack in history is premature," he said. "Until then, we will consider it an original way of approaching the start of the annual Black Hat conference in Las Vegas."

The vendors, contractors, and other outside parties with which you do business can create a serious security risk. Here's how to keep this threat in check. Also in the new, all-digital issue of Dark Reading: Why focusing solely on your own company's security ignores the bigger picture. Download it now. (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.