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 983 results — Medium severity, no patchTensorFlow: DoS via Grappler optimizer CHECK failure
CVE-2022-23579TensorFlow: memory leak via invalid graph node
CVE-2022-23578TensorFlow: null pointer deref crashes model loader
CVE-2022-23577TensorFlow: integer overflow in cost estimator causes DoS
CVE-2022-23576TensorFlow: integer overflow in cost estimator → DoS
CVE-2022-23575TensorFlow: DoS via shape inference assertion failure
CVE-2022-23572TensorFlow: protobuf assertion DoS via invalid tensor dtype
CVE-2022-23571TensorFlow: null-deref DoS via malformed protobuf tensor
CVE-2022-23570TensorFlow: DoS via malicious SavedModel AttrDef duplication
CVE-2022-23565TensorFlow: DoS via reachable assertion in protobuf decode
CVE-2022-23564TensorFlow: TOC/TOU race allows temp file hijacking
CVE-2022-23563TensorFlow TFLite: DoS via divide-by-zero in BiasAndClamp
CVE-2022-23557TensorFlow Lite: DoS via crafted depthwise conv model
CVE-2022-21741TensorFlow: QuantizedMaxPool null ptr deref causes DoS
CVE-2022-21739TensorFlow: integer overflow crashes process via sparse op
CVE-2022-21738TensorFlow: DoS via malformed Bincount arguments
CVE-2022-21737TensorFlow: DoS via reachable assertions in ML ops
CVE-2022-23569TensorFlow: DoS via FractionalMaxPool div-by-zero
CVE-2022-21735TensorFlow: DoS via MapStage non-scalar key crash
CVE-2022-21734TensorFlow: UnravelIndex integer overflow → DoS
CVE-2022-21729Frequently 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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