Vulnerability in Google Tensorflow
CVE-2021-29546
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.
EPSS: 0.002 (10.3th percentile) — read the EPSS interpretation.
CVSS v3 metric
CVSS v3 base score 2.5 (Low). Vector: CVSS:3.1/AV:L/AC:H/PR:L/UI:N/S:U/C:N/I:N/A:L.
Affected products
- Google Tensorflow
- Tensorflow — versions < 2.1.4, >= 2.2.0, < 2.2.3, >= 2.3.0, < 2.3.3
Weakness classification (CWE)
References
- security-advisories@github.com (x_refsource_CONFIRM, Exploit, Patch, Third Party Advisory)
- security-advisories@github.com (Patch, Third Party Advisory, x_refsource_MISC)
Frequently asked questions
- What is CVE-2021-29546?
- CVE-2021-29546 is a low-severity vulnerability in Google Tensorflow, classified under Divide By Zero. CVSS score: 2.5/10. Published 2021-05-14.
- How severe is CVE-2021-29546?
- Low severity. CVSS v3 base score is 2.5 out of 10.