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 1577 results — no patch GHSA-m9mp-6x32-5rhg scio/PyTorch: torch.load weights_only bypass RCE — — — Oct 9 CRIT E CVE-2025-61913 Flowise: path traversal in file tools leads to RCE 9.9 11.9% flowise Oct 8 HIGH E CVE-2025-59425 vLLM: timing attack enables API key bypass 7.5 0.5% vllm Oct 7 HIGH E CVE-2025-61687 Flowise: unrestricted file upload enables persistent RCE 8.8 10.2% flowise Oct 6 HIGH CVE-2025-0616 Netsis Panel: unauthenticated SQLi enables data exfiltration 8.2 0.3% B2B - Netsis Panel Oct 3 HIGH E CVE-2025-55560 PyTorch: DoS via sparse/dense tensor Inductor compile 7.5 0.4% pytorch Sep 25 HIGH E CVE-2025-55559 TensorFlow: DoS via Conv2D valid padding crash 7.5 0.2% tensorflow Sep 25 HIGH E CVE-2025-55558 PyTorch: Inductor compiler buffer overflow causes DoS 7.5 0.4% pytorch Sep 25 HIGH E CVE-2025-55557 PyTorch: DoS via cummin+Inductor NameError in 2.7.0 7.5 0.4% pytorch Sep 25 MEDI E CVE-2025-55556 TensorFlow: non-deterministic compilation breaks Embedding 6.5 0.2% tensorflow Sep 25 MEDI E CVE-2025-55554 PyTorch: integer overflow in nan_to_num causes DoS 5.3 0.3% pytorch Sep 25 HIGH E CVE-2025-55553 PyTorch 2.7.0: DoS via proxy_tensor.py syntax error 7.5 0.4% pytorch Sep 25 HIGH E CVE-2025-55552 PyTorch: integer overflow in rot90+randn_like causes DoS 7.5 0.4% pytorch Sep 25 HIGH E CVE-2025-55551 PyTorch: DoS in linalg.lu via malformed slice op 7.5 0.4% pytorch Sep 25 MEDI CVE-2025-46153 PyTorch: Dropout inconsistency enables membership inference 5.3 0.4% pytorch Sep 25 MEDI CVE-2025-46152 PyTorch: OOB write causes incorrect bitwise shift results 5.3 0.4% pytorch Sep 25 MEDI CVE-2025-46150 PyTorch: torch.compile silent output inconsistency 5.3 0.4% pytorch Sep 25 MEDI CVE-2025-46149 PyTorch: reachable assertion in nn.Fold with inductor 5.3 0.3% pytorch Sep 25 MEDI CVE-2025-46148 PyTorch: PairwiseDistance silent miscalculation, integrity risk 5.3 0.4% pytorch Sep 25 HIGH CVE-2025-9900 A flaw was found in Libtiff. This vulnerability... 8.8 0.7% rhaiis/vllm-cuda-rhel9 Sep 23 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.
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