MADLIRA - Malware detection using learning and information retrieval for Android

MADLIRA is a tool for Android malware detection. It consists in two components: TFIDF component and SVM learning component. In gerneral, it takes an input a set of malwares and benwares and then extracts the malicious behaviors TFIDF component or computes training model SVM classifier. Then, it...

Denis and Co.

In April 2017, we published a detailed review of a malicious program that used DNS tunneling to communicate to its C&C. That study prompted us to develop a technology to detect similar threats, which allowed us to collect a multitude of malware samples using DNS tunneling. In this article, we wil...

Detonating a bad rabbit: Windows Defender Antivirus and layered machine learning defenses

Windows Defender Antivirus uses a layered approach to protection: tiers of advanced automation and machine learning models evaluate files in order to reach a verdict on suspected malware. While Windows Defender AV detects a vast majority of new malware files at first sight, we always strive to...

Detonating a bad rabbit: Windows Defender Antivirus and layered machine learning defenses

Windows Defender Antivirus uses a layered approach to protection: tiers of advanced automation and machine learning models evaluate files in order to reach a verdict on suspected malware. While Windows Defender AV detects a vast majority of new malware files at first sight, we always strive to...

Investigation Report for the September 2014 Equation malware detection incident in the US

Background In early October, a story was published by the Wall Street Journal alleging Kaspersky Lab software was used to siphon classified data from an NSA employee's home computer system. Given that Kaspersky Lab has been at the forefront of fighting cyberespionage and cybercriminal activities ...

Unpatched Windows Kernel Bug Could Help Malware Hinder Detection

A 17-year-old programming error has been discovered in Microsoft's Windows kernel that could prevent some security software from detecting malware at runtime when loaded into system memory. The security issue, described by enSilo security researcher Omri Misgav, resides in the kernel routine...

Cb Defense Praised in Independent Tests, Product Reviews

Earlier this week, Carbon Black announced the Q3 release of Cb Defense, which features breakthrough streaming ransomware prevention as well as live response capability. Following this announcement, three independent security organizations published reviews and reports confirming the efficacy of C...

Cross site scripting

A vulnerability in the malware detection functionality within Advanced Malware Protection AMP of Cisco AsyncOS Software for Cisco Email Security Appliances ESAs could allow an unauthenticated, remote attacker to cause an email attachment containing malware to be delivered to the end user. The...

An Established Solution for Mobile Threats

As much as smartphones and applications have evolved over the years, so has mobile malware. We’re seeing an increasing number of threats—from mobile ransomware and auto-clicking adware to dangerous backdoors that can compromise your privacy. And there are also legitimate personal applications tha...

Cisco Email Security Appliance Malformed EML Attachment Bypass Vulnerability

A vulnerability in the malware detection functionality within Advanced Malware Protection AMP of Cisco AsyncOS Software for Cisco Email Security Appliances ESAs could allow an unauthenticated, remote attacker to cause an email attachment containing malware to be delivered to the end user. The...

Facebook worries: I didn’t post that

It is my assumption that most Facebook users don’t look at their own profile often. With your own profile, I mean the timeline that shows up when you click your own name or avatar in the Facebook menu. That’s because we think we know exactly what is posted there, so why bother to look at it? Afte...

Serverless, Real-time Malware Detection: BinaryAlert

BinaryAlert is an open-source serverless AWS pipeline where any file uploaded to an S3 bucket is immediately scanned with a configurable set of YARA rules. An alert will fire as soon as any match is found, giving an incident response team the ability to quickly contain the threat before it spread...

AVG AntiVirus < 17.2 Security Bypass Vulnerability - Mac OS X

AVG AntiVirus is prone to a security bypass vulnerability. SPDX-FileCopyrightText: 2017 Greenbone AG Some text descriptions might be excerpted from a referenced sources, and are Copyright C by the respective right holders. SPDX-License-Identifier: GPL-2.0-only CPE = "cpe:/a:avg:anti-virus";...

AVG AntiVirus for MacOS Information Disclosure Vulnerability

AVG AntiVirus for MacOS is an antivirus and anti-backdoor antivirus program for MacOS. scan engine is one of the antivirus scanning engines. A security vulnerability exists in versions of AVG AntiVirus for MacOS prior to scan engine 4668. A remote attacker could exploit the vulnerability to bypas...

Authentication flaw

AVG AntiVirus for MacOS with scan engine before 4668 might allow remote attackers to bypass malware detection by leveraging failure to scan inside disk image aka DMG files...

CVE-2017-9977: Undefined Security Weakness

AVG AntiVirus for MacOS with scan engine before 4668 might allow remote attackers to bypass malware detection by leveraging failure to scan inside disk image aka DMG files...

PT-2017-19315

Name of the Vulnerable Software and Affected Versions AVG AntiVirus for MacOS with scan engine before 4668 Description The issue allows remote attackers to bypass malware detection by leveraging the failure to scan inside disk image aka DMG files. Recommendations For AVG AntiVirus for MacOS with...

Watchguard Firebox / XTM XXE Injection Vulnerability

Watchguard's Firebox and XTM appliances suffer from XML external entity injection and XML-RPC user enumeration vulnerabilities. Watchguardas Firebox and XTM are a series of enterprise grade network security appliances providing advanced security services like next generation firewall, intrusion...

CVE-2015-8986

CVE-2015-8986 is described as a sandbox-detection evasion vulnerability in McAfee/Intel Security Advanced Threat Defense (MATD) versions up to 3.4.2.32. The issue allows malware to detect the sandbox environment and bypass malware detection, resulting in false negatives. The available sources ide...

PT-2017-7517

Name of the Vulnerable Software and Affected Versions McAfee Advanced Threat Defense versions 3.4.2.32 and earlier Description A sandbox detection evasion issue allows attackers to detect the sandbox environment and bypass proper malware detection, resulting in a failure to detect malware files v...