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HIGH AI Agents Compress Exploit Discovery to Minutes After Rumour // CRITICAL Claude Misuse Spans Cybercrime, Hacking, and Bioweapons // CRITICAL OpenAI Rogue AI Agents Attack RubyGems via RCE and API Key Theft // CRITICAL CVE-2026-81578: AI Agents Exploit PaperCut in 395-Org Campaign // HIGH PuzzleMask Bypasses LLM Policy Guards Using Plain Prose // HIGH AI Agents Lie, Cheat and Coordinate: Bengio on Misalignment // CRITICAL OpenAI Agent Swarm Attacked RubyGems Supply Chain in May // HIGH Meta Faces Lawsuit Over Biometric Data Harvesting for AI Training // CRITICAL Claude Weaponised by State Hackers for Automated Data Theft // LOW Hugging Face security.txt Redirects AI Agents Away From Live Systems //
LLM-GATEWAY

Llm-Gateway

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LiteLLM PyPI Poisoning Exposes 2,500+ Orgs via CI Secrets

LiteLLM PyPI Poisoning Exposes 2,500+ Orgs via CI Secrets

ATLAS OWASP CRITICAL Active exploitation · Immediate action required ▲ 9.1 The Hacker News

Two malicious LiteLLM releases (versions 1.82.7 and 1.82.8) were uploaded to PyPI on March 24 and remained live for approximately 40 minutes, carrying credential-stealing code that harvested cloud keys, SSH keys, Kubernetes tokens, and database passwords. CloudSEK's analysis of roughly 434,000 captured files maps potential exposure to more than 2,500 organisations, including NVIDIA, Cisco, and Siemens, though the dataset reflects files taken rather than confirmed misuse. The FBI has separately warned that affiliated actors are likely to weaponise exfiltrated credentials long after the initial compromise, making immediate secret rotation critical regardless of confirmed exploitation.

CVE-2026-42208: LiteLLM SQL Injection Stealing AI Credentials

CVE-2026-42208: LiteLLM SQL Injection Stealing AI Credentials

ATLAS OWASP CRITICAL Active exploitation · Immediate action required ▲ 9.2 BleepingComputer

A critical unauthenticated SQL injection vulnerability (CVE-2026-42208) in LiteLLM, a widely-used LLM proxy and SDK middleware, is being actively exploited to extract API keys, provider credentials, and configuration secrets from the proxy database. Exploitation began within 36 hours of public disclosure, with attackers demonstrating precise targeting of sensitive tables containing OpenAI, Anthropic, and Bedrock credentials. The stolen credentials could enable downstream attacks against AI infrastructure at scale, given LiteLLM's broad adoption across LLM application ecosystems.

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