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 535 results — Medium severity, no patchTensorFlow: DoS via SparseDenseCwiseMul OOB
CVE-2021-29567 TensorFlow: null ptr dereference crashes sparse ops
CVE-2021-29565 TensorFlow: null ptr deref DoS in EditDistance op
CVE-2021-29564 TensorFlow: DoS via RFFT empty matrix assertion crash
CVE-2021-29563 TensorFlow: assertion failure DoS in IRFFT op
CVE-2021-29562 TensorFlow: DoS via malformed LoadAndRemapMatrix input
CVE-2021-29561 TensorFlow: FPE in SparseMatMul causes process DoS
CVE-2021-29557 TensorFlow: DoS via divide-by-zero in Reverse op
CVE-2021-29556 TensorFlow: FusedBatchNorm divide-by-zero crashes ML jobs
CVE-2021-29555 TensorFlow: DoS via empty num_segments tensor assertion
CVE-2021-29552 TensorFlow: OOB read DoS in MatrixTriangularSolve kernel
CVE-2021-29551 TensorFlow: FractionalAvgPool DoS via divide-by-zero
CVE-2021-29550 TensorFlow: divide-by-zero DoS in quantized batch norm op
CVE-2021-29549 TensorFlow: DoS via division by zero in QuantizedBatchNorm
CVE-2021-29548 TensorFlow: OOB read DoS via empty tensor in QuantizedBatchNorm
CVE-2021-29547 TensorFlow: heap OOB write in sparse tensor DoS
CVE-2021-29545 TensorFlow: DoS via missing tensor rank validation
CVE-2021-29544 TensorFlow: DoS via assertion fail in CTCGreedyDecoder
CVE-2021-29543 TensorFlow: StringNGrams heap overflow crashes ML process
CVE-2021-29542 TensorFlow: null ptr deref DoS in StringNGrams op
CVE-2021-29541 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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