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 3023 resultssnorkel: RCE via insecure model checkpoint loading
CVE-2026-31222 pytorch-lightning: RCE via insecure checkpoint deserialization
CVE-2026-31221 optimate: RCE via unsafe torch.load() deserialization
CVE-2026-31219 optimate: unsafe torch.load() enables RCE via model file
CVE-2026-31218 torch-checkpoint: unsafe pickle deserialization RCE
CVE-2026-31214 MLflow: path traversal allows unauthenticated file read
CVE-2026-2614 local-deep-research: HTML injection enables SSRF via WeasyPrint
CVE-2026-43979 Flowise: SSRF in agent tools bypasses security wrapper
CVE-2026-43995 MLflow: SSRF in webhook URL enables cloud credential theft
CVE-2026-2393 Crabbox: path traversal enables arbitrary file wipe
CVE-2026-45224 Crabbox: coordinator auth bypass via forged admin claim
CVE-2026-45223 flash-attention: RCE via unsafe checkpoint deserialization
CVE-2026-31253 CosyVoice: RCE via unsafe torch.load() deserialization
CVE-2026-31252 CosyVoice: RCE via unsafe torch.load() deserialization
CVE-2026-31251 CosyVoice: RCE via unsafe torch.load() in model averaging
CVE-2026-31250 CosyVoice: insecure deserialization RCE via .pt files
CVE-2026-31249 BentoML: Dockerfile injection enables build-time RCE
CVE-2026-44346 BentoML: unsanitized base_image allows Dockerfile RCE
CVE-2026-44345 open-webui: IDOR exposes cross-user AI memory data
CVE-2026-44570 open-webui: auth bypass allows message tampering
CVE-2026-44571 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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