Vulnerability in Google Tensorflow

CVE-2021-29549

TensorFlow is an end-to-end open source platform for machine learning. An attacker can cause a runtime division by zero error and denial of service in `tf.raw_ops.QuantizedBatchNormWithGlobalNormalization`. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/6f26b3f3418201479c264f2a02000880d8df151c/tensorflow/core/kernels/quantized_add_op.cc#L289-L295) computes a modulo operation without validating that the divisor is not zero. Since `vector_num_elements` is determined based on input shapes(https://github.com/tensorflow/tensorflow/blob/6f26b3f3418201479c264f2a02000880d8df151c/tensorflow/core/kernels/quantized_add_op.cc#L522-L544), a user can trigger scenarios where this quantity is 0. 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 (8.9th 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

Weakness classification (CWE)

References

Frequently asked questions

What is CVE-2021-29549?
CVE-2021-29549 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-2021-29549?
Low severity. CVSS v3 base score is 2.5 out of 10.