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
Critical
New This Week
In CISA KEV
Latest AI Security Threats
Showing 20 of 509 results — High severity, Active exploitationGradio: CSV formula injection via flagging enables RCE
CVE-2022-24770 MLflow: insecure temp file handling causes DoS
CVE-2022-0736 TensorFlow MLIR-TFRT: DoS via scalar shape segfault
CVE-2022-23593 TensorFlow: heap OOB read in type inference engine
CVE-2022-23592 TensorFlow: SavedModel stack overflow via recursive GraphDef
CVE-2022-23591 TensorFlow: DoS via malicious SavedModel GraphDef
CVE-2022-23590 TensorFlow: heap OOB read/write enables network RCE
CVE-2022-23574 TensorFlow: uninitialized memory in AssignOp
CVE-2022-23573 TensorFlow: heap OOB write in Grappler, RCE risk
CVE-2022-23566 TFLite: OOB read/write in sparse tensor → RCE
CVE-2022-23560 TFLite: integer overflow in embedding lookup → heap OOB RW
CVE-2022-23559 TFLite: integer overflow in model loading, RCE risk
CVE-2022-23558 TensorFlow: heap overflow in sparse ops, RCE risk
CVE-2022-21740 TensorFlow: OOB read leaks heap memory, enables DoS
CVE-2022-21730 TensorFlow: heap OOB read in ReverseSequence op
CVE-2022-21728 TensorFlow: Dequantize integer overflow, RCE risk
CVE-2022-21727 TensorFlow: heap OOB read in Dequantize op allows RCE
CVE-2022-21726 pytorch-lightning: deserialization RCE via malicious checkpoint
CVE-2021-4118 Gradio: path traversal exposes host filesystem to users
CVE-2021-43831 Sockeye: unsafe YAML load RCE via model config file
CVE-2021-43811 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?
Get ATLAS technique mappings, compliance reports (ISO 42001, EU AI Act), breaking alerts, and full CISO analysis with a Pro subscription.
Start 14-Day Free Trial