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 1581 results — no patchmistralai 2.4.6: supply chain dropper executes on import
GHSA-wx9m-wx4f-4cmg ChromaDB: pre-auth RCE via trust_remote_code injection
CVE-2026-45829 Bert-VITS2: path traversal exposes ML training filesystem
CVE-2026-8756 nnU-Net: prompt injection hijacks CI/CD triage agent
CVE-2026-44246 guardrails-ai: RCE via malicious Hub package manifest
CVE-2026-31233 mamba: RCE via unsafe torch.load() on model load
CVE-2026-31239 Ludwig: RCE via unsafe pickle deserialization in model serve
CVE-2026-31238 CosyVoice: RCE via unsafe torch.load() model deserialization
CVE-2026-31232 ART: torch.load() RCE via insecure deserialization
CVE-2026-31229 snorkel: RCE via unsafe model deserialization
CVE-2026-31224 snorkel: 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 Flowise: SSRF in agent tools bypasses security wrapper
CVE-2026-43995 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 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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