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 839 results — Medium severityTensorFlow: DoS via TensorSummaryV2 input validation failure
CVE-2022-29193 TensorFlow: DoS via malformed DeleteSessionTensor input
CVE-2022-29194 TensorFlow: DoS via QuantizeAndDequantize input validation
CVE-2022-29192 TensorFlow: DoS via GetSessionTensor input validation
CVE-2022-29191 TensorFlow XLA: null pointer dereference causes DoS
CVE-2022-23595 TensorFlow MLIR: heap OOB via malicious SavedModel file
CVE-2022-23594 TensorFlow Grappler: DoS via malicious SavedModel
CVE-2022-23589 TensorFlow: DoS via crafted SavedModel crashes Grappler
CVE-2022-23588 TensorFlow: SavedModel DoS crashes Python interpreter
CVE-2022-23586 TensorFlow: memory leak in PNG decode causes DoS
CVE-2022-23585 TensorFlow: use-after-free in PNG decode causes DoS
CVE-2022-23584 TensorFlow: SavedModel type confusion triggers DoS crash
CVE-2022-23583 TensorFlow: SavedModel CHECK-fail causes DoS
CVE-2022-23582 TensorFlow: DoS via Grappler optimizer CHECK failure
CVE-2022-23581 TensorFlow: uncontrolled allocation DoS in shape inference
CVE-2022-23580 TensorFlow: DoS via Grappler optimizer CHECK failure
CVE-2022-23579 TensorFlow: memory leak via invalid graph node
CVE-2022-23578 TensorFlow: null pointer deref crashes model loader
CVE-2022-23577 TensorFlow: integer overflow in cost estimator causes DoS
CVE-2022-23576 TensorFlow: integer overflow in cost estimator → DoS
CVE-2022-23575 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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