AI Threat Alert

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.

Sources
Each CVE is enriched with
  • CVSS severity
  • EPSS exploit probability
  • Exploitation confidence
  • AI-component classification
  • Compliance mappings
2,415

AI/ML CVEs Tracked

350

Critical

295

New This Week

18

In CISA KEV

Sort: Date CVSS EPSS KEV first Most exploited
Filter: All Critical High Medium KEV only Active exploitation Has patch No patch

Latest AI Security Threats

Showing 20 of 1583 results — no patch
Severity CVE ID Summary CVSS EPSS Package Date
CRIT GHSA-wx9m-wx4f-4cmg mistralai 2.4.6: supply chain dropper executes on import 9.6 — mistralai May 18 CRIT E CVE-2026-45829 ChromaDB: pre-auth RCE via trust_remote_code injection 10.0 10.3% chromadb May 18 HIGH E CVE-2026-8756 Bert-VITS2: path traversal exposes ML training filesystem 7.3 0.5% — May 17 HIGH E CVE-2026-44246 nnU-Net: prompt injection hijacks CI/CD triage agent 7.2 0.2% claude-code May 12 CRIT CVE-2026-31233 guardrails-ai: RCE via malicious Hub package manifest 9.8 0.6% guardrails-ai May 12 CRIT CVE-2026-31239 mamba: RCE via unsafe torch.load() on model load 9.8 0.4% mamba-ssm May 12 CRIT CVE-2026-31238 Ludwig: RCE via unsafe pickle deserialization in model serve 9.8 0.5% ludwig May 12 HIGH CVE-2026-31232 CosyVoice: RCE via unsafe torch.load() model deserialization 8.8 0.5% — May 12 CRIT CVE-2026-31229 ART: torch.load() RCE via insecure deserialization 9.8 0.6% — May 12 HIGH CVE-2026-31224 snorkel: RCE via unsafe model deserialization 8.8 0.4% snorkel May 12 HIGH CVE-2026-31222 snorkel: RCE via insecure model checkpoint loading 8.8 0.4% snorkel May 12 HIGH CVE-2026-31221 pytorch-lightning: RCE via insecure checkpoint deserialization 7.8 0.4% pytorch-lightning May 12 UNKN CVE-2026-31219 optimate: RCE via unsafe torch.load() deserialization — 0.6% — May 12 UNKN CVE-2026-31218 optimate: unsafe torch.load() enables RCE via model file — 0.6% — May 12 CRIT CVE-2026-31214 torch-checkpoint: unsafe pickle deserialization RCE 9.8 0.5% — May 12 CRIT E CVE-2026-43995 Flowise: SSRF in agent tools bypasses security wrapper 9.8 0.4% flowise May 11 HIGH CVE-2026-31253 flash-attention: RCE via unsafe checkpoint deserialization 7.3 0.2% flash_attn May 11 UNKN CVE-2026-31252 CosyVoice: RCE via unsafe torch.load() deserialization — 0.1% — May 11 UNKN CVE-2026-31251 CosyVoice: RCE via unsafe torch.load() deserialization — 0.2% — May 11 UNKN CVE-2026-31250 CosyVoice: RCE via unsafe torch.load() in model averaging — 0.2% — May 11

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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