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Microsoft has patched two zero-day flaws and over 160 others
Microsoft on Tuesday released updates to address a record 169 security flaws across its product portfolio, including one vulnerability that has been actively exploited in the wild. Of these 169 vulnerabilities, 157 are rated Important, eight are rated Critical, three are rated Moderate, and one is rated Low in severity. Ninety-three of the flaws are
Today is Microsoft's April 2026 Patch Tuesday with security updates for 167 flaws, including 2 zero-day vulnerabilities. [...]
Cybersecurity researchers have unmasked a novel ad fraud scheme that has been found to leverage search engine poisoning (SEO) techniques and artificial intelligence (AI)-generated content to push deceptive news stories into Google's Discover feed and trick users into enabling persistent browser notifications that lead to scareware and financial scams. The campaign, which has been
Adobe has released an emergency security update for Acrobat Reader to fix a vulnerability, tracked as CVE-2026-34621, that has been exploited in zero-day attacks since at least December. [...]
An Adobe Reader zero-day vulnerability is being actively exploited via malicious PDFs, allowing hackers to steal data without user interaction, with no patch available.
Threat actors have been exploiting a previously unknown zero-day vulnerability in Adobe Reader using maliciously crafted PDF documents since at least December 2025. The finding, detailed by EXPMON's Haifei Li, has been described as a highly-sophisticated PDF exploit. The artifact ("Invoice540.pdf") first appeared on the VirusTotal platform on November 28, 2025. A second
Artificial Intelligence (AI) company Anthropic announced a new cybersecurity initiative called Project Glasswing that will use a preview version of its new frontier model, Claude Mythos, to find and address security vulnerabilities. The model will be used by a small set of organizations, including Amazon Web Services, Apple, Broadcom, Cisco, CrowdStrike,&
Anthropic’s Claude AI has helped researchers find a vulnerability in Apache ActiveMQ Classic
Security researchers and red teams adopt workflow automation to cut alert fatigue, enrich data, and scale operations across SOC, intel and recon tasks.
A financially motivated operation codenamed REF1695 has been observed leveraging fake installers to deploy remote access trojans (RATs) and cryptocurrency miners since November 2023. "Beyond cryptomining, the threat actor monetizes infections through CPA (Cost Per Action) fraud, directing victims to content locker pages under the guise of software registration," Elastic
Google on Thursday released security updates for its Chrome web browser to address 21 vulnerabilities, including a zero-day flaw that it said has been exploited in the wild. The high-severity vulnerability, CVE-2026-5281 (CVSS score: N/A), concerns a use-after-free bug in Dawn, an open-source and cross-platform implementation of the WebGPU standard. "Use-after-free in Dawn in Google Chrome prior
New research from Octagon Networks reveals a critical zero-day ImageMagick vulnerability that allows Remote Code Execution (RCE) via simple image uploads affecting Ubuntu, Amazon Linux, and WordPress. This magic byte shift bypasses even the most secure policies.
Google has fixed the fourth Chrome vulnerability exploited in zero-day attacks since the start of the year. [...]
A high-severity security flaw in the TrueConf client video conferencing software has been exploited in the wild as a zero-day as part of a campaign targeting government entities in Southeast Asia dubbed TrueChaos. The vulnerability in question is CVE-2026-3502 (CVSS score: 7.8), a lack of integrity check when fetching application update code, allowing an attacker to distribute a tampered update,
Security researchers from Georgia Tech have observed a surge in reported CVEs for which the flaw was introduced by AI-generated code
Attackers rapidly exploited a critical Oracle WebLogic RCE flaw the same day exploit code was released, according to a CloudSEK honeypot study
Researchers are warning about the risks posed by a low-cost device that can give insiders and hackers unusually broad powers in compromising networks. The devices, which typically sell for $30 to $100, are known as IP KVMs. Administrators often use them to remotely access machines on networks. The devices, not much bigger than a deck of cards, allow the machines to be accessed at the BIOS/UEFI level, the firmware that runs before the loading of the operating system. This provides power and convenience to admins, but in the wrong hands, the capabilities can often torpedo what might otherwise be a secure network. Risks are posed when the devices—which are exposed to the Internet—are deployed with weak security configurations or surreptitiously connected to by insiders. Firmware vulnerabilities also leave them open to remote takeover. Read full article Comments
Mutational grammar fuzzing is a fuzzing technique in which the fuzzer uses a predefined grammar that describes the structure of the samples. When a sample gets mutated, the mutations happen in such a way that any resulting samples still adhere to the grammar rules, thus the structure of the samples gets maintained by the mutation process. In case of coverage-guided grammar fuzzing, if the resulting sample (after the mutation) triggers previously unseen code coverage, this sample is saved to the sample corpus and used as a basis for future mutations. This technique has proven capable of finding complex issues and I have used it successfully in the past, including to find issues in XSLT implementations in web browsers and even JIT engine bugs . However, despite the approach being effective, it is not without its flaws which, for a casual fuzzer user, might not be obvious. In this blogpost I will introduce what I perceive to be the flaws of the mutational coverage-guided grammar fuzzing approach. I will also describe a very simple but effective technique I use in my fuzzing runs to counter these flaws. Please note that while this blogpost focuses on grammar fuzzing, the issues discussed here are not limited to grammar fuzzing as they also affect other structure-aware fuzzing techniques to various degrees. This research is based on the grammar fuzzing implementation in my Jackalope fuzzer , but the issues are not implementation specific. Issue #1: More coverage does not mean more bugs The fact that coverage is not a great measure for finding bugs is well known and affects coverage-guided fuzzing in general, not just grammar fuzzing. However this tends to be more problematic for the types of targets where structure-aware fuzzing (including grammar fuzzing) is typically used, such as in language fuzzing. Let’s demonstrate this on an example: In language fuzzing, bugs often require functions to be called in a certain order or that a result of one function is used as an input to another function. To trigger a recent bug in libxslt two XPath functions need to be called, the document() function and the generate-id() function, where the result of the document() function is used as an input to generate-id() function. There are other requirements to trigger the bug, but for now let’s focus on this requirement. Here’s a somewhat minimal sample required to trigger the bug: ?xml version="1.0"? xsl:stylesheet xml:base= "#" version= "1.0" xmlns:xsl= "http://www.w3.org/1999/XSL/Transform" xsl:template match= "/" xsl:value-of select= "generate-id(document('')/xsl:stylesheet/xsl:template/xsl:message)" / xsl:message terminate= "no" /xsl:message /xsl:template /xsl:stylesheet With the most relevant part for this discussion being the following element and the XPath expression in the select attribute: xsl:value-of select= "generate-id(document('')/xsl:stylesheet/xsl:template/xsl:message)" / If you run a mutational, coverage guided fuzzer capable of generating XSLT stylesh