GitHub Advisory — vLLM model-load RCE risk via auto_map (CVE-2026-22807)
A GitHub Advisory (CVE-2026-22807) says vLLM could execute attacker-controlled code during model resolution via Hugging Face auto_map, even when trust_remote_code is false.
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High-signal AI/security/automation notes.
Filter: All AI Vulnerabilities & CVEs (183)Tools & Comparisons (2)AI Security Research (171)Agent & Supply Chain Security (595)
GitHub/NVD: vm2 sandbox escape (CVE-2026-22709) enables host code execution
A new vm2 sandbox escape (CVE-2026-22709) allows untrusted JavaScript to break out via Promise callback sanitization bypass. Upgrade guidance + what to audit.
Best AI automation tools for non-technical teams (Zapier vs Make vs n8n)
A practical comparison of Zapier, Make, and n8n for AI workflows: pricing, flexibility, reliability, and when to pick each.
AI Email Triage Workflow (labels, summaries, suggested replies)
A practical workflow to triage email: classify, summarize, propose a reply, and route the message automatically.
AI-related CVEs: a practical tracker and triage workflow
A practical way to track AI-adjacent CVEs (RAG stacks, vector DBs, inference servers, agent tooling), prioritize risk, and patch fast.
AI security news digest: what to watch this week
A short digest focused on AI-adjacent security risk: where CVEs show up in modern AI stacks and what to do about it.
Zapier + ChatGPT: 5 real workflows (step-by-step)
Five practical Zapier+LLM automations you can set up quickly, with setup steps and testing checklist.
CISA/NSA/FBI — Deploying AI systems securely (joint guidance)
A security-first reading of the joint guidance on deploying AI systems securely: what it recommends, why it matters, and quick actions teams can take.
Google — SAIF (Secure AI Framework): a practitioner’s map
Google’s Secure AI Framework (SAIF) frames AI security as a set of risks + controls. Here’s how to use it as a practical checklist.
OWASP — Top 10 for LLM Apps: what to fix first
A practical prioritization of the OWASP Top 10 for LLM Applications: where teams should start, and the most common implementation traps.
NIST — AI Risk Management Framework (RMF) for security teams
A practical, security-first translation of the NIST AI RMF: what it is, how to operationalize it, and what to do next.