CVEvulnerability
CVE-2021-29522
5.5 MEDIUM
Official page ↗
- Status
- Modified
- Published
- 2021-05-14
- Last modified
- 2026-06-17
- Assigner
- [email protected]
- CVSS 3.1 ([email protected])
- 2.5 LOW — CVSS:3.1/AV:L/AC:H/PR:L/UI:N/S:U/C:N/I:N/A:L
- CVSS 3.1 ([email protected])
- 5.5 MEDIUM — CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H
- CVSS 2.0 ([email protected])
- 2.1 LOW — AV:L/AC:L/Au:N/C:N/I:N/A:P
- Weaknesses
- CWE-369
Description
TensorFlow is an end-to-end open source platform for machine learning. The `tf.raw_ops.Conv3DBackprop*` operations fail to validate that the input tensors are not empty. In turn, this would result in a division by 0. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/a91bb59769f19146d5a0c20060244378e878f140/tensorflow/core/kernels/conv_grad_ops_3d.cc#L430-L450) does not check that the divisor used in computing the shard size is not zero. Thus, if attacker controls the input sizes, they can trigger a denial of service via a division by zero error. 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.
Affected configurations
• google tensorflow (< 2.1.4)
• google tensorflow (>= 2.2.0 < 2.2.3)
• google tensorflow (>= 2.3.0 < 2.3.3)
• google tensorflow (>= 2.4.0 < 2.4.2)
Related
Weakness · CWE (1)
- CWE-369 Divide By Zero weakness
References
- https://github.com/tensorflow/tensorflow/commit/311403edbc9816df80274bd1ea8b3c0c0f22c3fa Patch, Third Party Advisory
- https://github.com/tensorflow/tensorflow/security/advisories/GHSA-c968-pq7h-7fxv Exploit, Patch, Third Party Advisory
- https://github.com/tensorflow/tensorflow/commit/311403edbc9816df80274bd1ea8b3c0c0f22c3fa Patch, Third Party Advisory
- https://github.com/tensorflow/tensorflow/security/advisories/GHSA-c968-pq7h-7fxv Exploit, Patch, Third Party Advisory