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 / Mitigation
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.
Vulnerability Details
2.5(low)
EPSS: 0.0%
Classification
Taxonomy References
Affected Vendors
Related Issues
CVE-2022-29200: TensorFlow is an open source platform for machine learning. Prior to versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4, the implem
CVE-2021-29541: TensorFlow is an end-to-end open source platform for machine learning. An attacker can trigger a dereference of a null p
Original source: https://nvd.nist.gov/vuln/detail/CVE-2021-29574
First tracked: February 15, 2026 at 08:39 PM
Classified by LLM (prompt v3) · confidence: 95%