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MEDIUM severity

CVE-2022-41907 — tensorflow

MEDIUMFix: tensorflow/tensorflow@00c821a

CVE-2022-41907 is a medium-severity (CVSS 4.8) CWE-131 vulnerability in tensorflow. 1 public exploit or proof-of-concept reference is indexed, so weaponization risk is real. A fix is available for tensorflow — see the affected versions and patch details below.

Overflow in `ResizeNearestNeighborGrad` in Tensorflow

Also known asBIT-tensorflow-2022-41907GHSA-368v-7v32-52fxPYSEC-2026-3091PYSEC-2026-3268PYSEC-2026-945
Published
Updated
Affected
9 pkgs
Patched
9 / 9
Exploits
1 known
Exploitation data as of Nov 7, 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-2022-41907.

EPSS Exploitation Probability

via FIRST.org ↗
0.5%probability of exploitation in next 30 days
Lower Risk0.00%
Lower risk than most CVEs43th percentile — riskier than 43% 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-gpu🐍tensorflow-cpu🐍tensorflow-gpu🐍tensorflow-cpu+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 tf.raw_ops.ResizeNearestNeighborGrad is given a large size input, it overflows.

import tensorflow as tf

align_corners = True
half_pixel_centers = False
grads = tf.constant(1, shape=[1,8,16,3], dtype=tf.float16)
size = tf.constant([1879048192,1879048192], shape=[2], dtype=tf.int32)
tf.raw_ops.ResizeNearestNeighborGrad(grads=grads, size=size, align_corners=align_corners, half_pixel_centers=half_pixel_centers)

Patches

We have patched the issue in GitHub commit 00c821af032ba9e5f5fa3fe14690c8d28a657624.

The fix will be included in TensorFlow 2.11. We will also cherrypick this commit on TensorFlow 2.10.1, 2.9.3, and TensorFlow 2.8.4, 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 by Neophytos Christou from the Secure Systems Lab (SSL) at Brown University.

Affected Packages

9 total 9 fixed
EcosystemPackageVulnerable rangeFix
🐍PyPItensorflowall versions2.8.4pip install --upgrade 'tensorflow==2.8.4'
🐍PyPItensorflow≥ 2.9.0&&< 2.9.32.9.3pip install --upgrade 'tensorflow==2.9.3'
🐍PyPItensorflow≥ 2.10.0&&< 2.10.12.10.1pip install --upgrade 'tensorflow==2.10.1'
🐍PyPItensorflow-cpuall versions2.8.4pip install --upgrade 'tensorflow-cpu==2.8.4'
🐍PyPItensorflow-gpuall versions2.8.4pip install --upgrade 'tensorflow-gpu==2.8.4'
🐍PyPItensorflow-cpu≥ 2.9.0&&< 2.9.32.9.3pip install --upgrade 'tensorflow-cpu==2.9.3'

Affected Products

1 product · 3 configurations
Application
tensorflowgoogle
≥ 2.10.0 && < 2.10.1
range
Exploits & PoCs
1

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 2.8.4 or later, then make sure no transitive (indirect) dependency still pins the vulnerable range — O3 confirms CVE-2022-41907 is resolved across your whole dependency graph.

  3. Workarounds

    Stop feeding it untrusted input: reject or quarantine files and payloads from unverified sources until you can upgrade, restrict accepted formats to the ones you actually need, and run the parsing or decoding step in a least-privileged sandbox or short-lived worker so a crash or corrupted read cannot reach the rest of the process.

Frequently Asked Questions

### Impact When [`tf.raw_ops.ResizeNearestNeighborGrad`](https://github.com/tensorflow/tensorflow/blob/master/tensorflow/core/kernels/image/resize_nearest_neighbor_op.cc) is given a large `size` input, it overflows. ``` import tensorflow as tf align_corners = True half_pixel_centers = False grads = tf.constant(1, shape=[1,8,16,3], dtype=tf.float16) size = tf.constant([1879048192,1879048192], shape=[2], dtype=tf.int32) tf.raw_ops.ResizeNearestNeighborGrad(grads=grads, size=size, align_corners=align_corners, half_pixel_centers=half_pixel_centers) ``` ### Patches We have patched the issue in Gi
O3 Security · Impact-Aware SCA

Is CVE-2022-41907 in your dependencies?

Find it across PyPI, including transitive dependencies.

CVE-2022-41907: tensorflow — Fixed in 2.8.4