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GHSA-gh6x-4whr-2qv4

HIGH

Null pointer dereference and heap OOB read in operations restoring tensors

Also known asBIT-tensorflow-2021-37639CVE-2021-37639PYSEC-2021-261PYSEC-2021-552PYSEC-2021-750
Published
Aug 25, 2021
Updated
Mar 13, 2026
Affected
9 pkgs
Patched
9 / 9
Exploits
None indexed

EPSS Exploitation Probability

via FIRST.org ↗
0.2%probability of exploitation in next 30 days
Lower Risk7th percentile+0.16%
0.00%0.22%0.45%0.67%0.0%0.2%Dec 25Apr 26Jun 26

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.

Blast Radius

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

When restoring tensors via raw APIs, if the tensor name is not provided, TensorFlow can be tricked into dereferencing a null pointer:

import tensorflow as tf

tf.raw_ops.Restore(
  file_pattern=['/tmp'],
  tensor_name=[], 
  default_value=21,
  dt=tf.int,
  preferred_shard=1)

The same undefined behavior can be triggered by tf.raw_ops.RestoreSlice:

import tensorflow as tf

tf.raw_ops.RestoreSlice(
  file_pattern=['/tmp'],
  tensor_name=[], 
  shape_and_slice='2',
  dt=inp.array([tf.int]),
  preferred_shard=1)

Alternatively, attackers can read memory outside the bounds of heap allocated data by providing some tensor names but not enough for a successful restoration:

import tensorflow as tf

tf.raw_ops.Restore(
  file_pattern=['/tmp'],
  tensor_name=['x'], 
  default_value=21,
  dt=tf.int,
  preferred_shard=42)

The implementation retrieves the tensor list corresponding to the tensor_name user controlled input and immediately retrieves the tensor at the restoration index (controlled via preferred_shard argument). This occurs without validating that the provided list has enough values.

If the list is empty this results in dereferencing a null pointer (undefined behavior). If, however, the list has some elements, if the restoration index is outside the bounds this results in heap OOB read.

Patches

We have patched the issue in GitHub commit 9e82dce6e6bd1f36a57e08fa85af213e2b2f2622.

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
🐍PyPItensorflow≥ 2.4.0&&< 2.4.32.4.3
🐍PyPItensorflow≥ 2.5.0&&< 2.5.12.5.1
🐍PyPItensorflow-cpuall versions2.3.4
🐍PyPItensorflow-cpu≥ 2.4.0&&< 2.4.32.4.3
🐍PyPItensorflow-cpu≥ 2.5.0&&< 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-gh6x-4whr-2qv4 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-gh6x-4whr-2qv4 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-gh6x-4whr-2qv4. Runtime protection reduces exposure until a permanent patch is applied and verified — it complements patching, it doesn't replace it.

Frequently Asked Questions

### Impact When restoring tensors via raw APIs, if the tensor name is not provided, TensorFlow can be tricked into dereferencing a null pointer: ```python import tensorflow as tf tf.raw_ops.Restore( file_pattern=['/tmp'], tensor_name=[], default_value=21, dt=tf.int, preferred_shard=1) ``` The same undefined behavior can be triggered by `tf.raw_ops.RestoreSlice`: ```python import tensorflow as tf tf.raw_ops.RestoreSlice( file_pattern=['/tmp'], tensor_name=[], shape_and_slice='2', dt=inp.array([tf.int]), preferred_shard=1) ``` Alternatively, attackers can read mem
O3 Security · Impact-Aware SCA

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