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MEDIUM severity

CVE-2021-29611 — tensorflow

MEDIUMFix: tensorflow/tensorflow@1d04d7d

CVE-2021-29611 is a medium-severity (CVSS 5.5) CWE-665 vulnerability in tensorflow. 1 public exploit reference exists, so weaponization risk is real. A fix is available for tensorflow — see the affected versions and patch details below.

Incomplete validation in `SparseReshape`

Also known asBIT-tensorflow-2021-29611GHSA-9rpc-5v9q-5r7fPYSEC-2021-248PYSEC-2021-539PYSEC-2021-737
Published
Updated
Affected
6 pkgs
Patched
6 / 6
Exploits
1 known
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 CVEs9th percentile — riskier than 9% of all scored CVEsHighest risk
0.00%0.23%0.47%0.70%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-2021-29611 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

6 pkgs affected
🐍tensorflow🐍tensorflow🐍tensorflow-cpu🐍tensorflow-cpu🐍tensorflow-gpu🐍tensorflow-gpu

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

Incomplete validation in SparseReshape results in a denial of service based on a CHECK-failure.

import tensorflow as tf

input_indices = tf.constant(41, shape=[1, 1], dtype=tf.int64)
input_shape = tf.zeros([11], dtype=tf.int64)
new_shape = tf.zeros([1], dtype=tf.int64)

tf.raw_ops.SparseReshape(input_indices=input_indices,
    input_shape=input_shape,
    new_shape=new_shape)

The implementation has no validation that the input arguments specify a valid sparse tensor.

Patches

We have patched the issue in GitHub commit 1d04d7d93f4ed3854abf75d6b712d72c3f70d6b6.

The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2 and TensorFlow 2.3.3, as these are the only affected versions.

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 Ying Wang and Yakun Zhang of Baidu X-Team.

Affected Packages

6 total 6 fixed
EcosystemPackageVulnerable rangeFix
🐍PyPItensorflow≥ 2.3.0&&< 2.3.32.3.3pip install --upgrade 'tensorflow==2.3.3'
🐍PyPItensorflow≥ 2.4.0&&< 2.4.22.4.2pip install --upgrade 'tensorflow==2.4.2'
🐍PyPItensorflow-cpu≥ 2.3.0&&< 2.3.32.3.3pip install --upgrade 'tensorflow-cpu==2.3.3'
🐍PyPItensorflow-cpu≥ 2.4.0&&< 2.4.22.4.2pip install --upgrade 'tensorflow-cpu==2.4.2'
🐍PyPItensorflow-gpu≥ 2.3.0&&< 2.3.32.3.3pip install --upgrade 'tensorflow-gpu==2.3.3'
🐍PyPItensorflow-gpu≥ 2.4.0&&< 2.4.22.4.2pip install --upgrade 'tensorflow-gpu==2.4.2'

Affected Products

1 product · 4 configurations
Application
tensorflowgoogle
≥ 2.4.0 && < 2.4.2
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 2.3.3 or later, then make sure no transitive (indirect) dependency still pins the vulnerable range — O3 confirms CVE-2021-29611 is resolved across your whole dependency graph.

  3. Workarounds

    Cap what an attacker can consume: apply request size, rate and timeout limits in front of the affected component, and run it with memory and CPU limits so exhaustion degrades one worker rather than the whole service.

Frequently Asked Questions

### Impact Incomplete validation in `SparseReshape` results in a denial of service based on a `CHECK`-failure. ```python import tensorflow as tf input_indices = tf.constant(41, shape=[1, 1], dtype=tf.int64) input_shape = tf.zeros([11], dtype=tf.int64) new_shape = tf.zeros([1], dtype=tf.int64) tf.raw_ops.SparseReshape(input_indices=input_indices, input_shape=input_shape, new_shape=new_shape) ``` The [implementation](https://github.com/tensorflow/tensorflow/blob/e87b51ce05c3eb172065a6ea5f48415854223285/tensorflow/core/kernels/sparse_reshape_op.cc#L40) has no validation that the
O3 Security · Impact-Aware SCA

Is CVE-2021-29611 in your dependencies?

Find it across PyPI, including transitive dependencies.

CVE-2021-29611: tensorflow DoS — Fixed in 2.3.3