Assertion failure based denial of service in Tensorflow (CVE-2022-21737)

Why this deserves its current priority

CVSS is 6.5. The current sources do not mark it as known exploited. Treat this as a source-backed prioritization signal, not a statement about your environment.

Analysis status

Analysis pending evidence review

Factual feed record only; HOL analysis is not approved for indexing. Read the methodology.

Affected scope and exposure questions

The current feed maps tensorflow (pypi), tensorflow (pypi), tensorflow (pypi), tensorflow-cpu (pypi) and additional mapped packages. Check affected ranges and fixed versions before updating.

Mapped affected packages and fixed versions
Package	Affected range	Fixed version
tensorflowpypi	>=0 <2.5.3	2.5.3
tensorflowpypi	>=2.6.0 <2.6.3	2.6.3
tensorflowpypi	>=2.7.0 <2.7.1	2.7.1
tensorflow-cpupypi	>=0 <2.5.3	2.5.3
tensorflow-cpupypi	>=2.6.0 <2.6.3	2.6.3
tensorflow-cpupypi	>=2.7.0 <2.7.1	2.7.1
tensorflow-gpupypi	>=0 <2.5.3	2.5.3
tensorflow-gpupypi	>=2.6.0 <2.6.3	2.6.3
tensorflow-gpupypi	>=2.7.0 <2.7.1	2.7.1

Recommended response

Check inventory. Check lockfiles and deployed manifests for tensorflow, tensorflow, tensorflow.
Review the reported fix. Update tensorflow to 2.5.3; tensorflow to 2.6.3; tensorflow to 2.7.1; tensorflow-cpu to 2.5.3; tensorflow-cpu to 2.6.3; tensorflow-cpu to 2.7.1; tensorflow-gpu to 2.5.3; tensorflow-gpu to 2.6.3; tensorflow-gpu to 2.7.1 if you use the affected versions. Test the change in a non-production environment first.

Evidence timeline and material changes

Published upstream
Feb 9, 2022
Evidence: source:osv:source_dates:source-dates:record
Source modified
Sep 10, 2026
Evidence: source:osv:source_dates:source-dates:record
First seen by HOL
Sep 10, 2026

Sources and claim methodology

Upstream source description

### Impact The [implementation of `*Bincount` operations](https://github.com/tensorflow/tensorflow/blob/5100e359aef5c8021f2e71c7b986420b85ce7b3d/tensorflow/core/kernels/bincount_op.cc) allows malicious users to cause denial of service by passing in arguments which would trigger a `CHECK`-fail: ```python import tensorflow as tf tf.raw_ops.DenseBincount( input=[[0], [1], [2]], size=[1], weights=[3,2,1], binary_output=False) ``` There are several conditions that the input arguments must satisfy. Some are not caught during shape inference and others are not caught during kernel implementation. This results in `CHECK` failures later when the output tensors get allocated. ### Patches We have patched the issue in GitHub commit [7019ce4f68925fd01cdafde26f8d8c938f47e6f9](https://github.com/tensorflow/tensorflow/commit/7019ce4f68925fd01cdafde26f8d8c938f47e6f9). The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range. ### For more information Please consult [our security guide](https://github.com/tensorflow/tensorflow/blob/master/SECURITY.md) for more information regarding the security model and how to contact us with issues and questions. ### Attribution This vulnerability has been reported by Faysal Hossain Shezan from University of Virginia.

Quoted source text, attributed separately from HOL analysis.