CVE-2021-29580
CVE.org · Published
- Record status
- Published
- Identifier year (not publication year)
- 2021
- Source publication
- Source updated
- Imported by cveboard
- Source snapshot
- cve_2026-10-24_midnight_baseline ·
CNA source text (English)
Undefined behavior and `CHECK`-fail in `FractionalMaxPoolGrad`
TensorFlow is an end-to-end open source platform for machine learning. The implementation of `tf.raw_ops.FractionalMaxPoolGrad` triggers an undefined behavior if one of the input tensors is empty. The code is also vulnerable to a denial of service attack as a `CHECK` condition becomes false and aborts the process. The implementation(https://github.com/tensorflow/tensorflow/blob/169054888d50ce488dfde9ca55d91d6325efbd5b/tensorflow/core/kernels/fractional_max_pool_op.cc#L215) fails to validate that input and output tensors are not empty and are of the same rank. Each of these unchecked assumptions is responsible for the above issues. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range.
Scoped product and version facts
Fix information unknown; no fixed version is derived here. Missing information does not prove that no fix exists.
Exploitation unknown; this catalogue does not assess exploitation.
tensorflow
- Vendor
- tensorflow
- Product
- tensorflow
- Platforms
- Unknown
- Default status
Unknown
| Version (version) | Status (status) | Version scheme (versionType) | Exclusive end (lessThan) | Inclusive end (lessThanOrEqual) | Status changes (at → status) |
|---|---|---|---|---|---|
| < 2.1.4 | affected | Unavailable | Unavailable | Unavailable | None listed |
| >= 2.2.0, < 2.2.3 | affected | Unavailable | Unavailable | Unavailable | None listed |
| >= 2.3.0, < 2.3.3 | affected | Unavailable | Unavailable | Unavailable | None listed |
| >= 2.4.0, < 2.4.2 | affected | Unavailable | Unavailable | Unavailable | None listed |