FISA

Cybersecurity researchers identified a large-scale malware campaign targeting job seekers through fake online interview platforms. The operation distributes a credential-stealing trojan known as JobStealer, which is disguised as legitimate video conferencing software for remote interviews. The campaign specifically targets Windows and macOS systems and focuses heavily on stealing browser credentials, cryptocurrency wallet data, authentication tokens, and sensitive personal information. The attack demonstrates how threat actors are increasingly exploiting remote work culture and employment-related social engineering to compromise victims. The attack begins with threat actors contacting victims through fake recruitment offers and interview invitations. Victims are directed to professionally designed websites pretending to host online interview platforms. Researchers identified multiple fake platform names such as MeetLab, Meetix, Juseo, and Carolla, while some sites directly impersonate...

Cybersecurity researchers uncovered an active malware campaign targeting software developers through fake installation pages impersonating Anthropic’s Claude Code platform. The operation relies heavily on social engineering and malicious search advertisements to trick victims into downloading or executing malware disguised as legitimate AI development tooling. The campaign demonstrates a growing trend where attackers exploit the popularity and rapid adoption of AI-assisted coding tools to compromise developer environments and steal sensitive browser data. The attack typically begins when a developer searches online for terms such as “install Claude Code” or “Claude Code CLI.” Attackers purchase sponsored search advertisements that appear above legitimate results, redirecting victims to convincing lookalike websites that closely mimic official Claude documentation pages. These fake pages replicate branding, layouts, installation guides, and command-line instructions in order to appear ...

  Cybersecurity researchers disclosed a critical Linux kernel vulnerability chain known as “Dirty Frag,” a local privilege escalation exploit capable of granting root access across most major Linux distributions released since 2017. The vulnerability quickly gained attention due to its high reliability, the public release of proof-of-concept exploit code, and the absence of immediate patches at the time of disclosure. Security analysts have compared Dirty Frag to previous high-profile Linux vulnerabilities such as Dirty Pipe and Copy Fail because of its ability to manipulate kernel memory structures and achieve deterministic privilege escalation. Dirty Frag is not a single vulnerability but a chained exploitation technique involving weaknesses in Linux kernel networking components related to xfrm-ESP and RxRPC functionality. By abusing flaws in the page cache handling logic, attackers can modify protected memory-backed files without appropriate permissions. This enables unprivilege...

Cybersecurity researchers reported a serious abuse of the digital certificate issuance process involving DigiCert, one of the world’s largest certificate authorities. Threat actors successfully obtained legitimate code-signing certificates and used them to digitally sign malicious software, allowing malware samples to appear trusted by operating systems and security solutions. The incident highlights the growing misuse of trusted digital infrastructure in modern cyberattacks and demonstrates how attackers increasingly exploit weaknesses in verification and identity validation processes rather than relying solely on technical vulnerabilities. Digital certificates are designed to establish trust between software publishers, operating systems, and users. When software is signed using a valid certificate, security mechanisms such as Microsoft SmartScreen and antivirus products are more likely to treat the application as legitimate. By obtaining valid certificates, attackers can bypass secu...

Cybersecurity researchers have uncovered a critical vulnerability in Ollama, one of the most widely used platforms for running large language models locally, that could allow a remote, unauthenticated attacker to read and steal the server's entire process memory. Tracked as CVE-2026-7482 and dubbed "Bleeding Llama" by the researchers at Cyera who discovered it, the flaw carries a CVSS score of 9.1 and is estimated to affect more than 300,000 publicly exposed servers worldwide. What Is Ollama? Ollama is a popular open-source framework that enables developers and organizations to run AI language models locally rather than relying on cloud services. The project has over 171,000 stars on GitHub, making it one of the most widely adopted tools in the self-hosted AI space. How the Vulnerability Works The flaw is an out-of-bounds heap read located in Ollama's GGUF model loader specifically in a function called WriteTo() within the model creation pipeline. GGUF is the sta...

Security researchers have disclosed a total of twelve vulnerabilities in vm2 , a widely used open-source Node.js library, several of which carry the maximum possible CVSS score of 10.0. All affected versions up to and including 3.11.1 are impacted, and users are strongly urged to upgrade to the newly released version 3.11.2 immediately. What Is vm2? vm2 is a Node.js sandbox library designed to safely execute untrusted JavaScript code in an isolated environment, preventing that code from accessing the underlying host system. It is commonly used in platforms that need to run user-supplied or third-party scripts without exposing the server to risk. The discovery of these flaws fundamentally undermines that security guarantee. What the Vulnerabilities Allow All twelve flaws share a common and critical outcome: they enable sandbox escape, meaning an attacker can break out of the isolated environment and execute arbitrary code directly on the host machine. Several of the vulnerabilities...

A high-severity vulnerability was disclosed in the AI-powered development environment Cursor, exposing developers to arbitrary code execution through malicious Git repositories. The flaw, tracked as CVE-2026-26268 with a severity score of 8.1, demonstrates how modern AI-assisted development tools can introduce new attack surfaces when combined with traditional software mechanisms such as version control systems. The vulnerability allows attackers to execute code on a developer’s machine simply by convincing them to clone a specially crafted repository. This significantly lowers the barrier for exploitation, as cloning repositories is a routine and trusted operation in software development workflows. Once the repository is cloned, hidden malicious logic embedded within Git configurations can be triggered automatically without requiring additional user interaction. At the core of the issue is the interaction between Cursor’s AI agent and Git’s built-in features, particularly Git hooks....