CVE-2021-29546
An attacker can trigger an integer division by zero undefined behavior in `tf.raw_ops.QuantizedBiasAdd`.
Does this matter?
High impact if exploited, but EPSS currently rates exploitation as unlikely (0.20%). Schedule it in the normal patch cycle and watch for a rise in EPSS or a public exploit.
Description
TensorFlow is an end-to-end open source platform for machine learning. An attacker can trigger an integer division by zero undefined behavior in `tf.raw_ops.QuantizedBiasAdd`. This is because the implementation of the Eigen kernel(https://github.com/tensorflow/tensorflow/blob/61bca8bd5ba8a68b2d97435ddfafcdf2b85672cd/tensorflow/core/kernels/quantization_utils.h#L812-L849) does a division by the number of elements of the smaller input (based on shape) without checking that this is not zero. 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.
- CVSS 3.1
- 7.8 HIGHCVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H
- EPSS
- 0.20% probability · 10th percentile
- CISA KEV
- Not listed
- Weakness
- CWE-369
- Affected
- google/tensorflow
- Source
- security-advisories@github.com
References
- https://github.com/tensorflow/tensorflow/commit/67784700869470d65d5f2ef20aeb5e97c31673cbPatch, Third Party Advisory
- https://github.com/tensorflow/tensorflow/security/advisories/GHSA-m34j-p8rj-wjxqExploit, Patch, Third Party Advisory
- https://github.com/tensorflow/tensorflow/commit/67784700869470d65d5f2ef20aeb5e97c31673cbPatch, Third Party Advisory
- https://github.com/tensorflow/tensorflow/security/advisories/GHSA-m34j-p8rj-wjxqExploit, Patch, Third Party Advisory
Source: NVD record, EPSS from FIRST.org, KEV from CISA. Refreshed daily.