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MEDIUM severity

CVE-2021-29551 — tensorflow

MEDIUMFix: tensorflow/tensorflow@480641e

CVE-2021-29551 is a medium-severity (CVSS 5.5) Out-of-bounds Read 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.

OOB read in `MatrixTriangularSolve`

Also known asBIT-tensorflow-2021-29551GHSA-vqw6-72r7-fgw7PYSEC-2021-188PYSEC-2021-479PYSEC-2021-677
Published
Updated
Affected
12 pkgs
Patched
12 / 12
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 CVEs11th percentile — riskier than 11% of all scored CVEsHighest risk
0.00%0.24%0.48%0.72%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-2021-29551 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

12 pkgs affected
🐍tensorflow🐍tensorflow🐍tensorflow🐍tensorflow🐍tensorflow-cpu🐍tensorflow-cpu🐍tensorflow-cpu🐍tensorflow-cpu+4 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 MatrixTriangularSolve fails to terminate kernel execution if one validation condition fails:

void ValidateInputTensors(OpKernelContext* ctx, const Tensor& in0,
                            const Tensor& in1) override {
  OP_REQUIRES(
      ctx, in0.dims() >= 2,
      errors::InvalidArgument("In[0] ndims must be >= 2: ", in0.dims()));

  OP_REQUIRES(
      ctx, in1.dims() >= 2,
      errors::InvalidArgument("In[0] ndims must be >= 2: ", in1.dims()));
}
  
void Compute(OpKernelContext* ctx) override {
  const Tensor& in0 = ctx->input(0);
  const Tensor& in1 = ctx->input(1);

  ValidateInputTensors(ctx, in0, in1);

  MatMulBCast bcast(in0.shape().dim_sizes(), in1.shape().dim_sizes());
  ...
}

Since OP_REQUIRES only sets ctx->status() to a non-OK value and calls return, this allows malicious attackers to trigger an out of bounds read:

import tensorflow as tf
import numpy as np

matrix_array = np.array([])
matrix_tensor = tf.convert_to_tensor(np.reshape(matrix_array,(1,0)),dtype=tf.float32)
rhs_array = np.array([])
rhs_tensor = tf.convert_to_tensor(np.reshape(rhs_array,(0,1)),dtype=tf.float32)

tf.raw_ops.MatrixTriangularSolve(matrix=matrix_tensor,rhs=rhs_tensor,lower=False,adjoint=False)

As the two input tensors are empty, the OP_REQUIRES in ValidateInputTensors should fire and interrupt execution. However, given the implementation of OP_REQUIRES, after the in0.dims() >= 2 fails, execution moves to the initialization of the bcast object. This initialization is done with invalid data and results in heap OOB read.

Patches

We have patched the issue in GitHub commit 480641e3599775a8895254ffbc0fc45621334f68.

The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, 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 Ye Zhang and Yakun Zhang of Baidu X-Team.

Affected Packages

12 total 12 fixed
EcosystemPackageVulnerable rangeFix
🐍PyPItensorflowall versions2.1.4pip install --upgrade 'tensorflow==2.1.4'
🐍PyPItensorflow≥ 2.2.0&&< 2.2.32.2.3pip install --upgrade 'tensorflow==2.2.3'
🐍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-cpuall versions2.1.4pip install --upgrade 'tensorflow-cpu==2.1.4'
🐍PyPItensorflow-cpu≥ 2.2.0&&< 2.2.32.2.3pip install --upgrade 'tensorflow-cpu==2.2.3'

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 2.1.4 or later, then make sure no transitive (indirect) dependency still pins the vulnerable range — O3 confirms CVE-2021-29551 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 The implementation of [`MatrixTriangularSolve`](https://github.com/tensorflow/tensorflow/blob/8cae746d8449c7dda5298327353d68613f16e798/tensorflow/core/kernels/linalg/matrix_triangular_solve_op_impl.h#L160-L240) fails to terminate kernel execution if one validation condition fails: ```cc void ValidateInputTensors(OpKernelContext* ctx, const Tensor& in0, const Tensor& in1) override { OP_REQUIRES( ctx, in0.dims() >= 2, errors::InvalidArgument("In[0] ndims must be >= 2: ", in0.dims())); OP_REQUIRES( ctx, in1.dims() >= 2, errors::
O3 Security · Impact-Aware SCA

Is CVE-2021-29551 in your dependencies?

Find it across PyPI, including transitive dependencies.

CVE-2021-29551: tensorflow — Fixed in 2.1.4