A Security

Critical Zoom Vulnerability Exposes All Platforms to Remote Takeover via Screen Sharing Annotations

A high-severity vulnerability in Zoom Workplace clients across Windows, Mac, iOS, Android, and Linux allows attackers to remotely seize full device control simply by having a victim enable screen sharing and the annotation tool. The flaw requires no user interaction such as clicking links or dismissing warnings, and the compromise occurs silently without visible alerts. Security researchers demonstrated that AI tools enabled complete exploit development within 24 hours, dramatically lowering the barrier for advanced attacks previously limited to nation-state actors. The issue affects hundreds of millions of remote workers who rely on Zoom’s daily screen-sharing features. Official patches have been released, and users are urged to update immediately while avoiding annotation tools in sensitive sessions. Apple simultaneously addressed related macOS flaws in multiple versions. The incident highlights how generative AI is accelerating the weaponization of vulnerabilities.

AI Uncovers Zoom Vulnerabilities Allowing Silent Device Takeover via Screen Sharing Annotations

Researchers at A Security identified multiple vulnerabilities in Zoom that enabled attackers to compromise participant devices during video calls without any user interaction. The flaws resided in the shared annotations protocol used for drawing and marking on shared screens. Victims only needed to join a meeting where screen sharing was active, affecting both regular participants and meeting organizers. The discovery was notable because it relied on publicly available AI models, requiring fewer than 20 prompts to locate the issues and build a working exploit prototype. The vulnerabilities impacted Zoom clients across Windows, macOS, Linux, iOS, and Android. Zoom addressed the problems through security bulletin ZSB-26015 with server-side and client patches. The research highlights how AI can dramatically accelerate vulnerability discovery compared to traditional manual analysis.