Big Data. Big Decisions
InformationWeek
Special Coverage Series


Bank Hacks: 7 Misunderstood Facts

As security researchers review recent bank hacks--affecting Bank of America, JPMorgan Chase, PNC, U.S. Bank, and Wells Fargo--claims made by supposed hacktivists don't all add up.

Who's behind the recent online attacks against multiple financial institutions including Bank of America, JPMorgan Chase, PNC, U.S. Bank, and Wells Fargo? In recent weeks, all have bit hit by large-scale distributed denial-of-service (DDoS) attacks. Cue website outages and customer outrage.

A self-described hacktivist group, the Cyber fighters of Izz ad-din Al qassam, has taken credit for organizing the related Operation Ababil, which it claims is a grassroots campaign to protest the recent release of a film that mocked the founder of Islam.

More Insights

Webcasts

More >>

White Papers

More >>

Reports

More >>

But as information security researchers review the attacks and tools used, they're finding that the claims made by the supposed hacktivist group don't all appear to add up. Here are seven facts about what's currently known about recent and forthcoming banking attacks.

1. Hacktivist Tool Claims Remain Unverified

Was a hacktivist group really behind the bank attacks, or--as some former U.S. government officials have alleged in anonymous interviews--might the government of Iran be to blame?

"In its postings, Cyber fighters of Izz ad-din Al Qassam published several attack tools including the Mobile LOIC Apache Killer version," said Ronen Kenig, director of product marketing for security products at Radware, in a blog post. "That tool was not present in the observed attack traffic, however, meaning it is possible that the Cyber fighters of Izz ad-din Al Qassam group was not behind the attack after all, or that it didn't manage to recruit supporters to its attack who were willing to use the mobile LOIC attack tool."

[ Criminals are tripling down on attack infrastructure. See Online Criminals' Best Friends: Malnets. ]

2. Servers, Not Botnets, Disrupted Bank Sites

What the attackers lacked in grassroots support, they made up for in attack strength, since they successfully disrupted the websites of leading banks, even after publicizing in advance the date and time of their attacks. Their attack power came from the use of server-infecting malware. "The majority of the attack traffic was not generated from a botnet, but rather from servers," said Carl Herberger, VP of security solutions at Radware, via phone. "The servers were compromised by the attackers prior to the attack."

Using server malware is unusual, and according to Arbor Networks researchers, the attacks don't resemble any previously seen hacktivism campaigns. "These are high-bandwidth servers that have obviously been compromised," said Dan Holden, director of security for the Arbor security engineering and respo nse team, speaking by phone. "So you're talking about probably hosting websites that have been compromised or used."

Recent hacktivist attacks have involved botnets of infected PCs--not servers. "For years and years, there have been botnets used for DDoS," said Holden. "Then you had opt-in hacktivism activity, and the 'hive mind' type of feature set. And now this is almost back to the future, where you're going back to the 1990s style of servers being leveraged, because of course they have very high bandwidth."

3. Attack Toolkit Positively Identified

One of the DDoS toolkits used in the attacks--and it may be the only one--has been identified as the 'itsoknoproblembro' tool kit. According to Prolexic Technologies, the toolkit has been used to launch "sustained floods" that have peaked at 70 Gbps and 30 million packets per second.

The tool can also be used to launch blended DDoS attacks. "The itsoknoproblembro toolkit includes multiple infrastructure and application-layer attack vectors, such as SYN floods, that can simultaneously attack multiple destination ports and targets, as well as ICMP, UDP, and SSL encrypted attack types," according to Prolexic. In addition, the toolkit can also be used to take out domain name system (DNS) infrastructure via UDP floods.

4. Banks Knocked Offline Via Encrypted SSL Floods

Beyond the volume of attacks generated, the banking website disruptions were also successful because they included SSL attacks, which can be generated by tools such as Dirt Jumper.

"Every SSL DDoS attack that we've seen has been an HTTP GET flood that's been encrypted," said Radware's Herberger. "It's been a very simple flood ... [but] the infrastructures that are in place to prevent SSL attacks are designed against intrusion events, not DDoS attacks."

Unfortunately, devices that provide SSL intrusion prevention can themselves become DDoS targets and be successfully shut down using relatively little traffic. "In one case in the last two weeks, we saw a financial services organization with 40 gigabits of external link that was taken down with 30 megabits of SSL attack," Herberger said.

 1 | 2  | Next Page »


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.