CVE-2021-29549: TensorFlow is an end-to-end open source platform for machine learning. An attacker can cause a runtime division by zero
Summary
TensorFlow, a machine learning platform, has a vulnerability where an attacker can cause a division by zero error (attempting to divide by zero, which crashes a program) in a specific operation called `tf.raw_ops.QuantizedBatchNormWithGlobalNormalization`. The bug happens because the code performs a modulo operation (finding the remainder after division) without checking if the divisor is zero first, and an attacker can craft input shapes to make this divisor equal zero.
Solution / Mitigation
The fix will be included in TensorFlow 2.5.0. The fix will also be backported (applied to older versions still being supported) to TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3, and TensorFlow 2.1.4.
Vulnerability Details
2.5(low)
EPSS: 0.0%
Classification
Affected Vendors
Related Issues
CVE-2022-29200: TensorFlow is an open source platform for machine learning. Prior to versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4, the implem
CVE-2021-29541: TensorFlow is an end-to-end open source platform for machine learning. An attacker can trigger a dereference of a null p
Original source: https://nvd.nist.gov/vuln/detail/CVE-2021-29549
First tracked: February 15, 2026 at 08:38 PM
Classified by LLM (prompt v3) · confidence: 95%