AI Security Threat Feed
Latest CVEs affecting AI/ML systems — LLM frameworks, ML libraries, AI agents, vector databases, and inference servers. Vulnerabilities are tracked from NVD, GitHub Advisory, CISA KEV, MITRE ATLAS, and enriched with CVSS, EPSS, exploitation confidence, AI-component classification, and compliance mappings to ISO 42001, EU AI Act, NIST AI RMF, and OWASP LLM Top 10. Updated continuously as new CVEs are published.
- CVSS severity
- EPSS exploit probability
- Exploitation confidence
- AI-component classification
- Compliance mappings
AI/ML CVEs Tracked
Critical
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Latest AI Security Threats
Showing 20 of 820 results — Active exploitation, no patchvLLM: unauthenticated OOM DoS via video frame parsing
CVE-2026-5497 Boxlite: OCI symlink traversal enables host RCE
CVE-2026-46703 draw.io: stored XSS executes JS via crafted diagram file
CVE-2026-46642 Flowise: mass-assignment allows cross-workspace takeover
CVE-2026-46480 Flowise: mass assignment cross-workspace takeover
CVE-2026-46479 Flowise: mass-assignment enables workspace takeover
CVE-2026-46475 Flowise: sandbox escape enables authenticated RCE
CVE-2026-46442 Flowise: mass assignment breaks multi-tenant isolation
CVE-2026-46441 Flowise: plaintext auth brute-force, no rate limit
CVE-2026-46440 OpenAI Atlas: XSS enables browser history exfiltration
CVE-2026-11326 Milvus: weak hash allows RBAC grantee impersonation
CVE-2026-10814 LMCache: weak hash enables KV cache integrity bypass
CVE-2026-10813 Streamlit: weak hash enables cache integrity bypass
CVE-2026-10804 MLflow: weak dataset hash allows integrity bypass
CVE-2026-10803 ms-swift: weak hash enables image cache poisoning
CVE-2026-10801 Gradio: weak hash exposes audio cache to local users
CVE-2026-10783 jupyter-server: CORS bypass enables arbitrary code execution
CVE-2026-6657 transformers: trust_remote_code bypass enables RCE via model load
CVE-2026-5241 MLflow: AI Gateway leaks cloud credentials via env injection
CVE-2026-4035 jupyter-server: path traversal exposes sibling dir files
CVE-2026-5422 Frequently asked questions
What is an AI security threat feed?
An AI security threat feed is a continuously updated stream of vulnerabilities (CVEs) affecting AI and machine-learning systems — LLM frameworks, ML libraries, AI agents, vector databases, and inference servers — filtered out of the broader CVE firehose and enriched for relevance.
Which sources are the AI CVEs tracked from?
CVEs are tracked from NVD, GitHub Advisory, CISA KEV, and MITRE ATLAS, then enriched with CVSS, EPSS, exploitation confidence, AI-component classification, and compliance mappings.
What AI systems do these vulnerabilities affect?
Coverage spans LLM frameworks, ML libraries, AI agents, vector databases, and inference servers — the components most security teams now run in production.
How often is the AI threat feed updated?
The feed updates continuously as new CVEs are published and enriched, so the most recent AI/ML vulnerabilities appear at the top.
Is the AI security feed free?
Yes — the public feed is free to browse. A Pro subscription adds breaking alerts, MITRE ATLAS mappings, compliance reports (ISO 42001, EU AI Act), and full CISO analysis.
Need deeper analysis?
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