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HIGH severity

CVE-2021-37659 — tensorflow

HIGHFix: tensorflow/tensorflow@93f428f

CVE-2021-37659 is a high-severity (CVSS 7.8) Out-of-bounds Read vulnerability in tensorflow. A fix is available for tensorflow — see the affected versions and patch details below.

Reference binding to nullptr and heap OOB in binary cwise ops

Also known asBIT-tensorflow-2021-37659GHSA-q3g3-h9r4-prrcPYSEC-2021-281PYSEC-2021-572PYSEC-2021-770
Published
Updated
Affected
9 pkgs
Patched
9 / 9
Exploits
None indexed
Exploitation data as of Oct 10, 2026 · OSV.dev, NVD, FIRST.org (EPSS)

EPSS Exploitation Probability

via FIRST.org ↗
0.2%probability of exploitation in next 30 days
Lower Risk0.00%
Lower risk than most CVEs7th percentile — riskier than 7% of all scored CVEsHighest risk
0.00%0.23%0.45%0.68%0.0%0.2%Apr 26Aug 26Oct 26

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

How urgent is this, really

CVE-2021-37659 by exploitation likelihood (EPSS) against impact (CVSS). Outside the shaded patch-first corner.

Where this sits among everything scored

Of 385,738 CVEs with a current EPSS score, this one falls in the < 10% band (highlighted). Counts from FIRST.org, log-scaled.

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

An attacker can cause undefined behavior via binding a reference to null pointer in all binary cwise operations that don't require broadcasting (e.g., gradients of binary cwise operations):

import tensorflow as tf

tf.raw_ops.SqrtGrad(y=[4, 16],dy=[])

The implementation assumes that the two inputs have exactly the same number of elements but does not check that. Hence, when the eigen functor executes it triggers heap OOB reads and undefined behavior due to binding to nullptr.

Patches

We have patched the issue in GitHub commit 93f428fd1768df147171ed674fee1fc5ab8309ec.

The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, TensorFlow 2.4.3, and TensorFlow 2.3.4, 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 members of the Aivul Team from Qihoo 360.

Affected Packages

9 total 9 fixed
EcosystemPackageVulnerable rangeFix
🐍PyPItensorflowall versions2.3.4pip install --upgrade 'tensorflow==2.3.4'
🐍PyPItensorflow≥ 2.4.0&&< 2.4.32.4.3pip install --upgrade 'tensorflow==2.4.3'
🐍PyPItensorflow≥ 2.5.0&&< 2.5.12.5.1pip install --upgrade 'tensorflow==2.5.1'
🐍PyPItensorflow-cpuall versions2.3.4pip install --upgrade 'tensorflow-cpu==2.3.4'
🐍PyPItensorflow-cpu≥ 2.4.0&&< 2.4.32.4.3pip install --upgrade 'tensorflow-cpu==2.4.3'
🐍PyPItensorflow-cpu≥ 2.5.0&&< 2.5.12.5.1pip install --upgrade 'tensorflow-cpu==2.5.1'

Affected Products

1 product · 6 configurations
Application
tensorflowgoogle
≥ 2.4.0 && < 2.4.3
2 versions
2.5.02.6.0

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 2.3.4 or later, then make sure no transitive (indirect) dependency still pins the vulnerable range — O3 confirms CVE-2021-37659 is resolved across your whole dependency graph.

  3. Workarounds

    Constrain what reaches the vulnerable code: limit the size and shape of untrusted input, isolate the affected component in a sandboxed or least-privileged process, and enable the platform's memory-safety mitigations (ASLR, stack protector, hardened allocator) so an out-of-bounds access is more likely to fail closed than to be exploitable.

Frequently Asked Questions

### Impact An attacker can cause undefined behavior via binding a reference to null pointer in all binary cwise operations that don't require broadcasting (e.g., gradients of binary cwise operations): ```python import tensorflow as tf tf.raw_ops.SqrtGrad(y=[4, 16],dy=[]) ``` The [implementation](https://github.com/tensorflow/tensorflow/blob/84d053187cb80d975ef2b9684d4b61981bca0c41/tensorflow/core/kernels/cwise_ops_common.h#L264) assumes that the two inputs have exactly the same number of elements but does not check that. Hence, when the eigen functor executes it triggers heap OOB reads an
O3 Security · Impact-Aware SCA

Is CVE-2021-37659 in your dependencies?

Find it across PyPI, including transitive dependencies.

CVE-2021-37659: tensorflow — Fixed in 2.3.4