{"data":{"id":"fc4428af-ec02-4375-9235-7f68ed3a20c3","title":"CVE-2021-29574: TensorFlow is an end-to-end open source platform for machine learning. The implementation of `tf.raw_ops.MaxPool3DGradGr","summary":"TensorFlow, an open-source machine learning platform, has a vulnerability in the `tf.raw_ops.MaxPool3DGradGrad` function where it doesn't check if input tensors (data structures that hold multi-dimensional arrays) are empty before accessing their contents. An attacker can provide empty tensors to cause a null pointer dereference (trying to access memory that doesn't exist), crashing the program or potentially executing malicious code.","solution":"The fix will be included in TensorFlow 2.5.0. The vulnerability will also be patched in earlier versions: TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3, and TensorFlow 2.1.4.","labels":["security"],"sourceUrl":"https://nvd.nist.gov/vuln/detail/CVE-2021-29574","publishedAt":"2021-05-15T00:15:14.017Z","cveId":"CVE-2021-29574","cweIds":["CWE-476"],"cvssScore":"2.5","cvssSeverity":"low","severity":"low","attackType":["denial_of_service"],"issueType":"vulnerability","affectedPackages":null,"affectedVendors":[],"affectedVendorsRaw":["TensorFlow"],"classifierModel":"claude-haiku-4-5-20251001","classifierPromptVersion":"v3","cvssVector":null,"attackVector":null,"attackComplexity":null,"privilegesRequired":null,"userInteraction":null,"exploitMaturity":"unknown","epssScore":0.00017,"patchAvailable":null,"disclosureDate":null,"capecIds":null,"crossRefCount":0,"attackSophistication":"trivial","impactType":["availability"],"aiComponentTargeted":"framework","llmSpecific":false,"classifierConfidence":0.95,"researchCategory":null,"atlasIds":null}}