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
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Latest AI Security Threats
Showing 20 of 1245 results — has patchpicklescan: PyTorch gadget bypasses pickle RCE detection
GHSA-vr7h-p6mm-wpmh picklescan: detection bypass via PyTorch proxy RCE
GHSA-h3qp-7fh3-f8h4 picklescan: RCE bypass via torch.utils.collect_env
GHSA-f745-w6jp-hpxx picklescan: scanner bypass enables RCE via PyTorch function
GHSA-f4x7-rfwp-v3xw picklescan: detection bypass enables PyTorch model RCE
GHSA-86cj-95qr-2p4f picklescan: PyTorch bypass allows undetected RCE
GHSA-4r9r-ch6f-vxmx vLLM: RCE via eval() in Qwen3 Coder tool parser
CVE-2025-9141 picklescan: detection bypass allows malicious pickle exec
GHSA-9gvj-pp9x-gcfr skops: joblib fallback enables RCE via model load
CVE-2025-54886 ExecuTorch: integer overflow RCE on model load
CVE-2025-30404 ExecuTorch: OOB read in model loader enables RCE
CVE-2025-54950 ExecuTorch: heap buffer overflow RCE in model loading
CVE-2025-54951 ExecuTorch: integer overflow in model load → RCE
CVE-2025-30405 ExecuTorch: heap buffer overflow RCE via model loading
CVE-2025-54949 skops: RCE via MethodNode unsafe deserialization
CVE-2025-54413 skops: OperatorFuncNode type confusion → RCE
CVE-2025-54412 ExecuTorch: heap overflow in method load, RCE risk
CVE-2025-30402 llama-index: DocugamiReader MD5 hash collision drops chunks
CVE-2025-6211 llama_index: path traversal allows arbitrary file read
CVE-2025-6209 llama-index: JSONReader DoS via recursive JSON parsing
CVE-2025-5472 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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