LIVE FEED
FIRST LOOK Microsoft MDASH Brings AI-Powered Windows Vulnerability Discovery // FIRST LOOK FableCut Ships AI-Drivable Browser Video Editor via MCP and REST // FIRST LOOK AI Agents Emerge as a New Identity Class Orgs Must Secure // HIGH CVE-2026-12958: GhostApproval Symlink Attack on Coding Agents // HIGH Prompt Injection Attacks Claude Code and Codex Execution // HIGH DPAPI Abuse in Claude Code and Cursor Triggers EDR // FIRST LOOK Y Combinator Ships Agentic Code Generation at 37K Lines Daily // HIGH Google Gemini Abused for Phishing-as-a-Service // CRITICAL Writer AI Session Token Leak Enables Account Takeover // MEDIUM Anthropic Mythos LLM Scans Federal Software for Vulnerabilities //
CLAUDE

Claude

17 reports
All LLM Security Agentic AI Industry News Research Supply Chain Prompt Injection First Look: Security Regulatory Jailbreaks Adversarial ML Data Poisoning Model Theft AI Security Tools Security Operations
botctl Process Manager Enables Prompt Injection Attacks

botctl Process Manager Enables Prompt Injection Attacks

ATLAS OWASP HIGH Significant risk · Prioritise patching ▲ 7.2 HN AI Security

botctl is an open-source process manager that enables persistent, autonomous AI agents (currently Claude-backed) to run continuously as background daemons with tool access, file system write permissions, and internet connectivity. While marketed as a productivity tool, the architecture introduces substantial attack surface through unattended agentic execution, a skills marketplace with third-party prompt injection, and a locally-exposed web dashboard. The combination of persistent autonomy, extensible skill modules from arbitrary GitHub repositories, and session memory creates compounding risk vectors relevant to agentic AI security.

Claude Source Code Leak Reveals AI Supply Chain Risk

Claude Source Code Leak Reveals AI Supply Chain Risk

ATLAS OWASP HIGH Significant risk · Prioritise patching ▲ 8.2 Dark Reading

A reported source code leak affecting Claude, Anthropic's large language model, underscores systemic weaknesses in AI software supply chains and the absence of robust oversight mechanisms at critical development and distribution layers. The incident highlights how proprietary model code, training pipelines, and system prompts can become high-value targets for adversarial actors seeking to enable model theft, backdoor insertion, or competitive intelligence gathering. This event serves as a broader warning about treating AI development infrastructure with the same rigor applied to other critical systems.

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