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MEDIUM severity

CVE-2022-29211 tensorflow

MEDIUMFix: tensorflow/tensorflow@e57fd69

CVE-2022-29211 is a medium-severity (CVSS 5.5) Improper Input Validation vulnerability in tensorflow. 2 public exploit references exist, so weaponization risk is real. A fix is available for tensorflow — see the affected versions and patch details below.

Segfault in TensorFlow if `tf.histogram_fixed_width` is called with NaN values

Also known asBIT-tensorflow-2022-29211GHSA-xrp2-fhq4-4q3wPYSEC-2026-1048PYSEC-2026-3260PYSEC-2026-3382
Published
May 20, 2022
Updated
Aug 12, 2026
Affected
9 pkgs
Patched
9 / 9
Exploits
2 known
Exploitation data as of Sep 21, 2026 · OSV.dev, NVD, FIRST.org (EPSS)

Exploitation Status

Proof-of-concept exploit code exists

  • CISA’s SSVC triage found public proof-of-concept exploit code for this CVE, though no confirmed active exploitation.

Exploitation and automatability from CISA’s SSVC triage for CVE-2022-29211.

EPSS Exploitation Probability

via FIRST.org ↗
0.3%probability of exploitation in next 30 days
Lower Risk0.00%
Lower risk than most CVEs25th percentile — riskier than 25% of all scored CVEsHighest risk

EPSS (Exploit Prediction Scoring System) is a daily probability model maintained by FIRST.org. It estimates the likelihood a CVE will be exploited in production environments within the next 30 days, derived from real-world threat intelligence signals.

How urgent is this, really

CVE-2022-29211 plotted by exploitation likelihood (EPSS) against impact (CVSS). The shaded corner — EPSS 50%+ and CVSS 7.0+ — is where this CVE doesn't sit, though severity or exploitability alone can still warrant action.

Where this sits among everything scored

Of 377,636 CVEs with a current EPSS score, this one falls in the < 10% band (highlighted). Real counts from FIRST.org, not a sample — log-scaled since the landscape is heavily right-skewed.

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

The implementation of tf.histogram_fixed_width is vulnerable to a crash when the values array contain NaN elements:

import tensorflow as tf
import numpy as np

tf.histogram_fixed_width(values=np.nan, value_range=[1,2])

The implementation assumes that all floating point operations are defined and then converts a floating point result to an integer index:

index_to_bin.device(d) =
    ((values.cwiseMax(value_range(0)) - values.constant(value_range(0)))
         .template cast<double>() /
     step)
        .cwiseMin(nbins_minus_1)
        .template cast<int32>();

If values contains NaN then the result of the division is still NaN and the cast to int32 would result in a crash.

This only occurs on the CPU implementation.

Patches

We have patched the issue in GitHub commit e57fd691c7b0fd00ea3bfe43444f30c1969748b5.

The fix will be included in TensorFlow 2.9.0. We will also cherrypick this commit on TensorFlow 2.8.1, TensorFlow 2.7.2, and TensorFlow 2.6.4, 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 externally via a GitHub issue.

Affected Packages

9 total 9 fixed
EcosystemPackageVulnerable rangeFix
🐍PyPItensorflowall versions2.6.4pip install --upgrade 'tensorflow==2.6.4'
🐍PyPItensorflow2.7.0&&< 2.7.22.7.2pip install --upgrade 'tensorflow==2.7.2'
🐍PyPItensorflow2.8.0&&< 2.8.12.8.1pip install --upgrade 'tensorflow==2.8.1'
🐍PyPItensorflow-cpuall versions2.6.4pip install --upgrade 'tensorflow-cpu==2.6.4'
🐍PyPItensorflow-cpu2.7.0&&< 2.7.22.7.2pip install --upgrade 'tensorflow-cpu==2.7.2'
🐍PyPItensorflow-cpu2.8.0&&< 2.8.12.8.1pip install --upgrade 'tensorflow-cpu==2.8.1'
Exploits & PoCs
2

Research use only. For defensive security, authorized penetration testing, and academic research only. Never execute exploit code against systems without explicit written authorization.

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 2.6.4 or later, then make sure no transitive (indirect) dependency still pins the vulnerable range — O3 confirms CVE-2022-29211 is resolved across your whole dependency graph.

  3. Workarounds

    If you can't upgrade right away: gate or disable the affected feature, validate untrusted input at the boundary, and avoid passing attacker-controlled data into the vulnerable path. O3's runtime protection blocks exploitation in production as an interim safeguard until the upgrade lands.

  4. How O3 protects you

    O3 Security's impact-aware SCA analyses which vulnerable code paths your application actually calls, so a match like CVE-2022-29211 can be triaged on real exposure rather than presence alone.

Tailored to CVE-2022-29211. Runtime protection reduces exposure until a permanent patch is applied and verified — it complements patching, it doesn't replace it.

Frequently Asked Questions

### Impact The implementation of [`tf.histogram_fixed_width`](https://github.com/tensorflow/tensorflow/blob/f3b9bf4c3c0597563b289c0512e98d4ce81f886e/tensorflow/core/kernels/histogram_op.cc) is vulnerable to a crash when the values array contain `NaN` elements: ```python import tensorflow as tf import numpy as np tf.histogram_fixed_width(values=np.nan, value_range=[1,2]) ``` The [implementation](https://github.com/tensorflow/tensorflow/blob/f3b9bf4c3c0597563b289c0512e98d4ce81f886e/tensorflow/core/kernels/histogram_op.cc#L35-L74) assumes that all floating point operations are defined and then
O3 Security · Impact-Aware SCA

Is CVE-2022-29211 in your dependencies?

O3 Security finds CVE-2022-29211 across PyPI dependencies, including transitive ones, and its impact-aware SCA ranks findings by whether your code actually calls the vulnerable path.

CVE-2022-29211: tensorflow (Medium 5.5) | O3 Security