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 818 results — Active exploitation, no patchTensorFlow: 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: div-by-zero in QuantizedBiasAdd, C/I/A high
CVE-2021-29546 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 TensorFlow: heap buffer overflow in Conv2D gradient op
CVE-2021-29540 TensorFlow: type confusion in ImmutableConst causes DoS
CVE-2021-29539 TensorFlow: div-by-zero DoS in Conv2DBackpropFilter
CVE-2021-29538 TensorFlow: heap overflow in QuantizedResizeBilinear op
CVE-2021-29537 TensorFlow: heap overflow in QuantizedReshape op
CVE-2021-29536 TensorFlow: heap overflow in QuantizedMul op
CVE-2021-29535 TensorFlow: DoS via CHECK-fail in SparseConcat op
CVE-2021-29534 TensorFlow: DoS via empty image in DrawBoundingBoxes
CVE-2021-29533 TensorFlow: heap OOB read via RaggedCross op
CVE-2021-29532 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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