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Not in CISA KEV
HIGH severity

GHSA-cgfm-62j4-v4rf

HIGHFix: tensorflow/tensorflow@87158f4

GHSA-cgfm-62j4-v4rf is a high-severity (CVSS 7.3) Out-of-bounds Read vulnerability in tensorflow. O3 Security confirms whether GHSA-cgfm-62j4-v4rf is actually reachable in your code before you act, and blocks exploitation at runtime until you patch.

Heap out of bounds access in sparse reduction operations

Also known asBIT-tensorflow-2021-37635CVE-2021-37635PYSEC-2021-257PYSEC-2021-548PYSEC-2021-746
Published
Aug 25, 2021
Updated
Jul 8, 2026
Affected
9 pkgs
Patched
9 / 9
Exploits
None indexed
Exploitation data as of Aug 23, 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

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

GHSA-cgfm-62j4-v4rf 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 0 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 sparse reduction operations in TensorFlow can trigger accesses outside of bounds of heap allocated data:

import tensorflow as tf

x = tf.SparseTensor(
      indices=[[773, 773, 773], [773, 773, 773]],
      values=[1, 1],
      dense_shape=[337, 337, 337])
tf.sparse.reduce_sum(x, 1)

The implementation fails to validate that each reduction group does not overflow and that each corresponding index does not point to outside the bounds of the input tensor.

Patches

We have patched the issue in GitHub commit 87158f43f05f2720a374f3e6d22a7aaa3a33f750.

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 versions2.3.4
🐍PyPItensorflow2.4.0&&< 2.4.32.4.3
🐍PyPItensorflow2.5.0&&< 2.5.12.5.1
🐍PyPItensorflow-cpuall versions2.3.4
🐍PyPItensorflow-cpu2.4.0&&< 2.4.32.4.3
🐍PyPItensorflow-cpu2.5.0&&< 2.5.12.5.1

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. O3's reachability analysis confirms whether the vulnerable code path is actually invoked in your application, so you act on real exposure instead of every transitive match.

  2. Fix

    Update tensorflow to 2.3.4 or later, then make sure no transitive (indirect) dependency still pins the vulnerable range — O3 confirms GHSA-cgfm-62j4-v4rf 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 pinpoints whether GHSA-cgfm-62j4-v4rf is reachable in your code and exactly where to fix it, then blocks exploitation in production at runtime until the patched version is deployed.

Tailored to GHSA-cgfm-62j4-v4rf. 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 sparse reduction operations in TensorFlow can trigger accesses outside of bounds of heap allocated data: ```python import tensorflow as tf x = tf.SparseTensor( indices=[[773, 773, 773], [773, 773, 773]], values=[1, 1], dense_shape=[337, 337, 337]) tf.sparse.reduce_sum(x, 1) ``` The [implementation](https://github.com/tensorflow/tensorflow/blob/a1bc56203f21a5a4995311825ffaba7a670d7747/tensorflow/core/kernels/sparse_reduce_op.cc#L217-L228) fails to validate that each reduction group does not overflow and that each corresponding index does not
O3 Security · Impact-Aware SCA

Is GHSA-cgfm-62j4-v4rf in your dependencies?

O3 detects GHSA-cgfm-62j4-v4rf across PyPI dependencies and uses function-level reachability to confirm whether the vulnerable code path is actually reachable — not just present. No false positives.

GHSA-cgfm-62j4-v4rf: Heap out of bounds… | O3 Security