Martijn Lammerts
My own digital place with a little of everything

Use-after-free (UAF) Vulnerability CVE-2018-8373 in VBScript Engine Affects Internet Explorer to Run Shellcode

15 August 2018

We discovered a high-risk Internet Explorer (IE) vulnerability in the wild on July 11, just a day after Microsoft’s July Patch Tuesday. We immediately sent Microsoft the details to help fix this flaw. While this vulnerability, now designated as CVE-2018-8373, affects the VBScript engine in the latest versions of Windows, Internet Explorer 11 is not vulnerable since VBScript in Windows 10 Redstone 3 (RS3) has been effectively disabled by default.

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Use-after-free (UAF) Vulnerability CVE-2018-8373 in VBScript Engine Affects Internet Explorer to Run Shellcode

15 August 2018

We discovered a high-risk Internet Explorer (IE) vulnerability in the wild on July 11, just a day after Microsoft’s July Patch Tuesday. We immediately sent Microsoft the details to help fix this flaw. While this vulnerability, now designated as CVE-2018-8373, affects the VBScript engine in the latest versions of Windows, Internet Explorer 11 is not vulnerable since VBScript in Windows 10 Redstone 3 (RS3) has been effectively disabled by default.

The post Use-after-free (UAF) Vulnerability CVE-2018-8373 in VBScript Engine Affects Internet Explorer to Run Shellcode appeared first on .

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Ransomware as a Service Princess Evolution Looking for Affiliates

9 August 2018

We have been observing a malvertising campaign via Rig exploit kit delivering a cryptocurrency-mining malware and the GandCrab ransomware since July 25. On August 1, we found Rig's traffic stream dropping a then-unknown ransomware. Delving into this seemingly new ransomware, we checked its ransom payment page in the Tor network and saw it was called Princess Evolution (detected by Trend Micro as RANSOM_PRINCESSLOCKER.B), and was actually a new version of the Princess Locker ransomware that emerged in 2016. Based on its recent advertisement in underground forums, it appears that its operators are peddling Princess Evolution as a ransomware as a service (RaaS) and are looking for affiliates.

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Ransomware as a Service Princess Evolution Looking for Affiliates

9 August 2018

We have been observing a malvertising campaign via Rig exploit kit delivering a cryptocurrency-mining malware and the GandCrab ransomware since July 25. On August 1, we found Rig's traffic stream dropping a then-unknown ransomware. Delving into this seemingly new ransomware, we checked its ransom payment page in the Tor network and saw it was called Princess Evolution (detected by Trend Micro as RANSOM_PRINCESSLOCKER.B), and was actually a new version of the Princess Locker ransomware that emerged in 2016. Based on its recent advertisement in underground forums, it appears that its operators are peddling Princess Evolution as a ransomware as a service (RaaS) and are looking for affiliates.

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How Machine Learning Can Help Identify Web Defacement Campaigns

9 August 2018

Website defacement — the act of visibly altering the pages of a website, notably in the aftermath of a political event to advance the political agenda of a threat actor— has been explored in our various research works. We broke down top defacement campaigns in a previous paper and, in another post, emphasized how machine learning in our security research tool can help Computer Emergency Readiness Teams (CERTs)/Computer Security Incident Response Teams (CSIRTs) and web administrators prepare for such attacks. The latter took off from the analysis done in our most recent paper, Web Defacement Campaigns Uncovered: Gaining Insights From Deface Pages Using DefPloreX-NG. Here we expound on why machine learning (ML) was an ideal method for our analysis to better understand how web defacers operate and organize themselves.

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Malware Targeting Bitcoin ATMs Pops Up in the Underground

7 August 2018

With the increasing popularity and real-world use of cryptocurrencies and the fact that cybercriminals will always try to exploit something that can make money for them, it shouldn’t come as a surprise that malware targeting Bitcoin ATMs have started appearing in underground markets.

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Adversarial Sample Generation: Making Machine Learning Systems Robust for Security

2 August 2018

The history of antimalware security solutions has shown that malware detection is like a cat-and-mouse game. For every new detection technique, there’s a new evasion method. When signature detection was invented, cybercriminals used packers, compressors, metamorphism, polymorphism, and obfuscation to evade it. Meanwhile, API hooking and code injection methods were developed to evade behavior detection. By the time security solutions started using machine learning (ML)-based detection technologies, it was already expected that cybercriminals would develop new tricks to evade ML.

To be one step ahead of cybercriminals, one method of enhancing an ML system to counter evasion tactics is generating adversarial samples, which are input data modified to cause an ML system to incorrectly classify it. Interestingly, while adversarial samples can be designed to cause ML systems to malfunction, they can also, as a result, be used to improve the efficiency of ML systems.

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