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MEDIUM severity

CVE-2022-36001 — tensorflow

MEDIUMFix: tensorflow/tensorflow@da0d65c

CVE-2022-36001 is a medium-severity (CVSS 5.9) Reachable Assertion vulnerability in tensorflow. A fix is available for tensorflow — see the affected versions and patch details below.

`CHECK` fail in `DrawBoundingBoxes` in TensorFlow

Also known asBIT-tensorflow-2022-36001GHSA-jqm7-m5q7-3hm5PYSEC-2026-1014PYSEC-2026-3209PYSEC-2026-3346
Published
Updated
Affected
9 pkgs
Patched
9 / 9
Exploits
None indexed
Exploitation data as of Nov 11, 2026 · OSV.dev, NVD, FIRST.org (EPSS)

Exploitation Status

No confirmed exploitation observed yet

  • CISA’s own triage has not observed active exploitation or public proof-of-concept code for this CVE as of its last assessment.

Exploitation and automatability from CISA’s SSVC triage for CVE-2022-36001.

EPSS Exploitation Probability

via FIRST.org ↗
0.5%probability of exploitation in next 30 days
Lower Risk+0.01%
Lower risk than most CVEs42th percentile — riskier than 42% of all scored CVEsHighest risk
0.00%0.33%0.66%0.99%0.1%0.5%May 26Sep 26Nov 26

Probability of exploitation in the next 30 days, from FIRST.org EPSS.

How urgent is this, really

Where this sits among everything scored

Real-World Exposure

9 pkgs affected
🐍tensorflow🐍tensorflow🐍tensorflow🐍tensorflow-cpu🐍tensorflow-cpu🐍tensorflow-cpu🐍tensorflow-gpu🐍tensorflow-gpu+1 more

Real-time download stats are indexed for npm and PyPI packages. This vulnerability affects PyPI packages — download data is not available via public APIs for these ecosystems.

Description

Impact

When DrawBoundingBoxes receives an input boxes that is not of dtype float, it gives a CHECK fail that can trigger a denial of service attack.

import tensorflow as tf
import numpy as np
arg_0=tf.constant(value=np.random.random(size=(1, 3, 2, 3)), shape=(1, 3, 2, 3), dtype=tf.half)
arg_1=tf.constant(value=np.random.random(size=(1, 2, 4)), shape=(1, 2, 4), dtype=tf.float32)
arg_2=''
tf.raw_ops.DrawBoundingBoxes(images=arg_0, boxes=arg_1, name=arg_2)

Patches

We have patched the issue in GitHub commit da0d65cdc1270038e72157ba35bf74b85d9bda11.

The fix will be included in TensorFlow 2.10.0. We will also cherrypick this commit on TensorFlow 2.9.1, TensorFlow 2.8.1, and TensorFlow 2.7.2, as these are also affected and still in supported range.

For more information

Please consult our security guide for more information regarding the security model and how to contact us with issues and questions.

Attribution

This vulnerability has been reported by 刘力源, Information System & Security and Countermeasures Experiments Center, Beijing Institute of Technology.

Affected Packages

9 total 9 fixed
EcosystemPackageVulnerable rangeFix
🐍PyPItensorflowall versions2.7.2pip install --upgrade 'tensorflow==2.7.2'
🐍PyPItensorflow≥ 2.8.0&&< 2.8.12.8.1pip install --upgrade 'tensorflow==2.8.1'
🐍PyPItensorflow≥ 2.9.0&&< 2.9.12.9.1pip install --upgrade 'tensorflow==2.9.1'
🐍PyPItensorflow-cpuall versions2.7.2pip install --upgrade 'tensorflow-cpu==2.7.2'
🐍PyPItensorflow-cpu≥ 2.8.0&&< 2.8.12.8.1pip install --upgrade 'tensorflow-cpu==2.8.1'
🐍PyPItensorflow-cpu≥ 2.9.0&&< 2.9.12.9.1pip install --upgrade 'tensorflow-cpu==2.9.1'

Affected Products

1 product · 7 configurations
Application
tensorflowgoogle
≥ 2.9.0 && < 2.9.1
1 version
2.10

Detection & mitigation playbook

Open-source dependency
  1. Detect

    Scan your dependency tree (package-lock.json, pnpm-lock.yaml, requirements.txt, go.sum, etc.) for tensorflow, including transitive dependencies — a direct dependency you never call can still pull in a vulnerable version.

  2. Fix

    Update tensorflow to 2.7.2 or later, then make sure no transitive (indirect) dependency still pins the vulnerable range — O3 confirms CVE-2022-36001 is resolved across your whole dependency graph.

  3. Workarounds

    Cap what an attacker can consume: apply request size, rate and timeout limits in front of the affected component, and run it with memory and CPU limits so exhaustion degrades one worker rather than the whole service.

Frequently Asked Questions

### Impact When `DrawBoundingBoxes` receives an input `boxes` that is not of dtype `float`, it gives a `CHECK` fail that can trigger a denial of service attack. ```python import tensorflow as tf import numpy as np arg_0=tf.constant(value=np.random.random(size=(1, 3, 2, 3)), shape=(1, 3, 2, 3), dtype=tf.half) arg_1=tf.constant(value=np.random.random(size=(1, 2, 4)), shape=(1, 2, 4), dtype=tf.float32) arg_2='' tf.raw_ops.DrawBoundingBoxes(images=arg_0, boxes=arg_1, name=arg_2) ``` ### Patches We have patched the issue in GitHub commit [da0d65cdc1270038e72157ba35bf74b85d9bda11](https://github.co
O3 Security · Impact-Aware SCA

Is CVE-2022-36001 in your dependencies?

Find it across PyPI, including transitive dependencies.

CVE-2022-36001: tensorflow DoS — Fixed in 2.7.2