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AI security threats move fast and get buried under hype and noise. Built by an Information Systems Security researcher to help security teams and developers stay ahead of vulnerabilities, privacy incidents, safety research, and policy developments.
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Amazon Q Developer Executes Malicious Code From Cloned Repos: Amazon Q for VS Code had a high-severity vulnerability (CVE-2026-12957, CVSS 8.5) that allowed attackers to run arbitrary commands and steal AWS credentials by embedding malicious MCP server configurations (local processes that extend AI assistant capabilities) in a repository. The flaw occurred because Amazon Q automatically loaded and executed these configurations without verifying workspace trust or requesting user permission, giving attackers full access to the developer's environment variables and cloud credentials.
US Government Restricts GPT-5.6 and Mythos Releases: The Trump administration requested that OpenAI limit its GPT-5.6 rollout to government-vetted partners before a wider launch, marking the first time a US AI firm has been told to restrict model access pre-release. Anthropic's Mythos models were pulled from service for two weeks under similar restrictions before being released to approximately 100 approved companies and federal agencies, signaling a new era of government oversight for advanced AI deployments.
Attackers Exploit OpenAI's Organization Invites to Impersonate Companies: Cybersecurity firms are being targeted by fraudulent OpenAI organization invitations that appear to come from legitimate companies, using OpenAI's real email infrastructure with attached payment methods to trick employees into sharing source code and internal documents. The invitations are difficult to detect despite OpenAI's domain mismatch warnings, as they leverage the platform's authentic communication channels.
Malware Designed to Evade LLM-Based Security Tools: Security researchers identified malware such as macOS.Gaslight (linked to North Korean threat actors) that specifically subverts AI-powered security analysis tools by causing LLM-assisted detection systems (security products that use large language models to analyze threats) to halt analysis or refuse to operate. This represents an emerging adversarial technique where malware authors are actively engineering code to bypass AI-based defenses.