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MEDIUM severity

CVE-2021-37672 — tensorflow

MEDIUMFix: tensorflow/tensorflow@a4e1386

CVE-2021-37672 is a medium-severity (CVSS 5.5) Out-of-bounds Read vulnerability in tensorflow. A fix is available for tensorflow — see the affected versions and patch details below.

Heap OOB in `SdcaOptimizerV2`

Also known asBIT-tensorflow-2021-37672GHSA-5hj3-vjjf-f5m7PYSEC-2021-294PYSEC-2021-585PYSEC-2021-783
Published
Updated
Affected
9 pkgs
Patched
9 / 9
Exploits
None indexed
Exploitation data as of Oct 8, 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 CVEs6th percentile — riskier than 6% of all scored CVEsHighest risk
0.00%0.22%0.45%0.67%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-2021-37672 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 read from outside of bounds of heap allocated data by sending specially crafted illegal arguments to tf.raw_ops.SdcaOptimizerV2:

import tensorflow as tf
  
tf.raw_ops.SdcaOptimizerV2(
  sparse_example_indices=[[1]],
  sparse_feature_indices=[[1]],
  sparse_feature_values=[[1.0,2.0]],
  dense_features=[[1.0]],
  example_weights=[1.0],
  example_labels=[],
  sparse_indices=[1],
  sparse_weights=[1.0],
  dense_weights=[[1.0]],
  example_state_data=[[100.0,100.0,100.0,100.0]],
  loss_type='logistic_loss',
  l1=100.0,
  l2=100.0,
  num_loss_partitions=1,
  num_inner_iterations=1,
  adaptive=True)       

The implementation does not check that the length of example_labels is the same as the number of examples.

Patches

We have patched the issue in GitHub commit a4e138660270e7599793fa438cd7b2fc2ce215a6.

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-2021-37672 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 An attacker can read from outside of bounds of heap allocated data by sending specially crafted illegal arguments to `tf.raw_ops.SdcaOptimizerV2`: ```python import tensorflow as tf tf.raw_ops.SdcaOptimizerV2( sparse_example_indices=[[1]], sparse_feature_indices=[[1]], sparse_feature_values=[[1.0,2.0]], dense_features=[[1.0]], example_weights=[1.0], example_labels=[], sparse_indices=[1], sparse_weights=[1.0], dense_weights=[[1.0]], example_state_data=[[100.0,100.0,100.0,100.0]], loss_type='logistic_loss', l1=100.0, l2=100.0, num_loss_partitions=1, nu
O3 Security · Impact-Aware SCA

Is CVE-2021-37672 in your dependencies?

Find it across PyPI, including transitive dependencies.

CVE-2021-37672: tensorflow — Fixed in 2.3.4