Dark Reading is part of the Informa Tech Division of Informa PLC

This site is operated by a business or businesses owned by Informa PLC and all copyright resides with them.Informa PLC's registered office is 5 Howick Place, London SW1P 1WG. Registered in England and Wales. Number 8860726.

Attacks/Breaches

Microsoft Silverlight Exploit Kit Attacks Spike

While crimeware authors continue gunning for outdated plug-ins, researchers report that businesses are finding and stopping related intrusions more quickly.

Beware a surge in attacks that target outdated versions of the Microsoft Silverlight plug-in.

That warning was issued Monday by Cisco, which has traced a recent surge in attacks targeting Microsoft Silverlight vulnerabilities to Angler, among other exploit kits. Oftentimes, these exploits are delivered via "malvertising," when attackers manage to sneak malicious code into ads displayed by otherwise legitimate advertising networks.

"Silverlight exploits are the drive-by flavor of the month," said Cisco information security researcher Levi Gundert in a blog post, noting that a related spike in attacks began April 23. "In this particular Angler campaign, the attack is more specifically targeted at Flash and Silverlight vulnerabilities, and though Java is available and an included reference in the original attack landing pages, it's never triggered."

According to Gundert, attackers are successfully compromising a large number of outdated and vulnerable versions of Silverlight. "Unfortunately, we observe extensive global DNS requests for the Angler landing pages, indicating that this campaign is largely succeeding... due to [each victim's] failure to upgrade their system's applications."

Silverlight, which offers Flash-like functionality, was ignored by exploit kit writers prior to last year, according to a security report published Wednesday by Trustwave. But then two different flaws -- CVE-2013-0074 and CVE-2013-3896 -- drew attackers' attention.

"Trustwave did not see evidence of any Silverlight vulnerabilities in exploit kits until these two flaws were coupled together and integrated into virtually all active exploit kits in 2013," according to the report. "Within a month, Silverlight became the most popular target for exploitation. To make matters worse, integrating this exploit into a kit was so simple that developers could use the same .dll file across all versions. They merely added their own methods of obfuscation and evasion to the code."

Silverlight, of course, isn't the only plug-in to be targeted by attackers, nor is Angler the most pervasive crimeware kit, according to Trustwave's report, which is based on almost 700 breach investigations conducted by the firm in 2013, as well as threat intelligence data gathered by the company's networking products.

But plug-ins remain potent enterprise security weak points. In 2013, 85% of the breaches investigated by Trustwave involved exploits of third-party plug-ins such as Java, Adobe Flash, Adobe Acrobat and Reader, and Microsoft Silverlight.

Throughout 2013, most of these malware-based exploits traced to the Blackhole crimeware kit, which accounted for 49% of all exploit-kit-based attacks -- at least prior to Russian police busting botnet mastermind "Paunch" in October. "The arrest of its creator and a lack of updates to the kit spurred a 15% decline in Blackhole's prevalence," according to Trustwave's report. "We expect the second-most prevalent exploit kit, Magnitude at 31%, to fill the gap." Other popular exploit kits include Cool and Redkit (each 6%), while 8% of crimeware traffic collectively traced to Angler, BleedingLife, DotkaChef, Eleonore, Gondad, Neutrino, and SofosFO.

Trustwave's study also offers further details about how many businesses are being compromised. Nearly one-third of all 2013 breaches investigated by Trustwave, for example, involved attackers being able to compromise weak passwords. SQL injection (8% of attacks) and phishing (6%) were also potent exploit vectors.

One hopeful finding from Trustwave's study is that within 10 days of a breach being discovered, two-thirds of organizations were able to contain it. Furthermore, 71% of organizations were able to contain a breach within six months, up from 56% in 2012.

Most businesses, however, still don't know if or when they've been breached. In only 29% of the breaches investigated by Trustwave, for example, did the business discover the breach itself. Everyone else was informed by a third party: regulators, card brands, or merchant banks (in 60% of cases); another third party (7%); the public (3%); or a law enforcement agency (3%).

It's important for organizations to self-detect breaches, because it affects response time. "For organizations that do self-detect, they detect quicker and they contain a data breach quicker," said John Yeo, a director at Trustwave, in a phone interview.

Indeed, organizations that self-detected a breach spotted it an average of 32 days after it occurred, compared with 108 days for organizations that learned about the breach from a third party. Similarly, organizations that self-detected took just one day -- on average -- to contain the breach, compared with fourteen days for others.

Mathew Schwartz served as the InformationWeek information security reporter from 2010 until mid-2014. View Full Bio

Comment  | 
Print  | 
More Insights
Comments
Newest First  |  Oldest First  |  Threaded View
COVID-19: Latest Security News & Commentary
Dark Reading Staff 9/25/2020
Hacking Yourself: Marie Moe and Pacemaker Security
Gary McGraw Ph.D., Co-founder Berryville Institute of Machine Learning,  9/21/2020
Startup Aims to Map and Track All the IT and Security Things
Kelly Jackson Higgins, Executive Editor at Dark Reading,  9/22/2020
Register for Dark Reading Newsletters
White Papers
Video
Cartoon
Current Issue
Special Report: Computing's New Normal
This special report examines how IT security organizations have adapted to the "new normal" of computing and what the long-term effects will be. Read it and get a unique set of perspectives on issues ranging from new threats & vulnerabilities as a result of remote working to how enterprise security strategy will be affected long term.
Flash Poll
How IT Security Organizations are Attacking the Cybersecurity Problem
How IT Security Organizations are Attacking the Cybersecurity Problem
The COVID-19 pandemic turned the world -- and enterprise computing -- on end. Here's a look at how cybersecurity teams are retrenching their defense strategies, rebuilding their teams, and selecting new technologies to stop the oncoming rise of online attacks.
Twitter Feed
Dark Reading - Bug Report
Bug Report
Enterprise Vulnerabilities
From DHS/US-CERT's National Vulnerability Database
CVE-2020-15208
PUBLISHED: 2020-09-25
In tensorflow-lite before versions 1.15.4, 2.0.3, 2.1.2, 2.2.1 and 2.3.1, when determining the common dimension size of two tensors, TFLite uses a `DCHECK` which is no-op outside of debug compilation modes. Since the function always returns the dimension of the first tensor, malicious attackers can ...
CVE-2020-15209
PUBLISHED: 2020-09-25
In tensorflow-lite before versions 1.15.4, 2.0.3, 2.1.2, 2.2.1 and 2.3.1, a crafted TFLite model can force a node to have as input a tensor backed by a `nullptr` buffer. This can be achieved by changing a buffer index in the flatbuffer serialization to convert a read-only tensor to a read-write one....
CVE-2020-15210
PUBLISHED: 2020-09-25
In tensorflow-lite before versions 1.15.4, 2.0.3, 2.1.2, 2.2.1 and 2.3.1, if a TFLite saved model uses the same tensor as both input and output of an operator, then, depending on the operator, we can observe a segmentation fault or just memory corruption. We have patched the issue in d58c96946b and ...
CVE-2020-15211
PUBLISHED: 2020-09-25
In TensorFlow Lite before versions 1.15.4, 2.0.3, 2.1.2, 2.2.1 and 2.3.1, saved models in the flatbuffer format use a double indexing scheme: a model has a set of subgraphs, each subgraph has a set of operators and each operator has a set of input/output tensors. The flatbuffer format uses indices f...
CVE-2020-15212
PUBLISHED: 2020-09-25
In TensorFlow Lite before versions 2.2.1 and 2.3.1, models using segment sum can trigger writes outside of bounds of heap allocated buffers by inserting negative elements in the segment ids tensor. Users having access to `segment_ids_data` can alter `output_index` and then write to outside of `outpu...