CVE-2021-29551: Tensorflow OOB Read Vulnerability

Q: What is CVE-2021-29551?

CVE-2021-29551 is a security vulnerability in Tensorflow involving OOB read in `MatrixTriangularSolve` under CWE-125: Out-of-bounds Read.

Q: Which Tensorflow versions are affected?

Affected versions include releases prior to 2.1.4, 2.2.3, 2.3.3, 2.4.2 across affected packages: tensorflow, tensorflow-cpu, tensorflow-gpu.

Q: What version fixes CVE-2021-29551?

Upgrading to 2.1.4, 2.2.3, 2.3.3, 2.4.2 (or the latest patched release for your respective branch) resolves the vulnerability.

Q: Is tensorflow affected?

Yes, tensorflow is affected in releases prior to 2.1.4, 2.2.3, 2.3.3, 2.4.2. Upgrade your dependency to 2.1.4, 2.2.3, 2.3.3, 2.4.2 or later.

Q: Is tensorflow-cpu affected?

Yes, tensorflow-cpu is affected in releases prior to 2.1.4, 2.2.3, 2.3.3, 2.4.2. Upgrade your dependency to 2.1.4, 2.2.3, 2.3.3, 2.4.2 or later.

Q: What is the CVSS score of CVE-2021-29551?

CVE-2021-29551 has a CVSS v3.1 base score of 2.5 (LOW) with vector string CVSS:3.1/AV:L/AC:H/PR:L/UI:N/S:U/C:N/I:N/A:L.

Q: What CWE is associated with CVE-2021-29551?

CVE-2021-29551 is classified under CWE-125: Out-of-bounds Read (The product reads data past the end, or before the beginning, of the intended buffer.).

Q: How can I check PyPI dependencies for CVE-2021-29551?

Run the dependency tree command: 'pip show tensorflow'. This command lists direct and transitive dependencies in your build configuration so you can verify if a vulnerable version is resolved.

LOW

Advisory Identifier: GHSA-vqw6-72r7-fgw7

CVSS 2.5

CWE-125

Published 2021-05-21

Advisory Summary

CVE-2021-29551 is a LOW (CVSS 2.5) oob read vulnerability (CWE-125: Out-of-bounds Read) affecting Tensorflow libraries in the PyPI ecosystem. The issue involves oob read in `matrixtriangularsolve`. Remediation is available by upgrading affected packages to version 2.1.4, 2.2.3, 2.3.3, 2.4.2.

CVE-2021-29551 at a Glance

CVE Identifier CVE-2021-29551

GHSA Identifier GHSA-vqw6-72r7-fgw7

Severity LOW

CVSS v3.1 Base Score 2.5

CWE Classification CWE-125: Out-of-bounds Read

Affected Product Tensorflow

Package Ecosystem PyPI

Published Date 2021-05-21

Last Updated 2024-10-31

Security Impact

CVSS: 2.5

The security impact metrics below are parsed directly from the CVSS v3.1 vector string (CVSS:3.1/AV:L/AC:H/PR:L/UI:N/S:U/C:N/I:N/A:L).

Attack Vector Local (AV:L)

Attack Complexity High (AC:H)

Privileges Required Low (PR:L)

User Interaction None (UI:N)

Scope Unchanged (S:U)

Confidentiality None (C:N)

Integrity None (I:N)

Availability Low (A:L)

How to Fix CVE-2021-29551

To remediate this vulnerability, upgrade all affected Tensorflow dependencies to a patched release. Both direct and transitive dependencies should be checked, as frameworks or security libraries may pull in vulnerable versions transitively.

tensorflow fixed: 2.1.4

pip install tensorflow>=2.1.4

tensorflow fixed: 2.2.3

pip install tensorflow>=2.2.3

tensorflow fixed: 2.3.3

pip install tensorflow>=2.3.3

tensorflow fixed: 2.4.2

pip install tensorflow>=2.4.2

tensorflow-cpu fixed: 2.1.4

pip install tensorflow-cpu>=2.1.4

tensorflow-cpu fixed: 2.2.3

pip install tensorflow-cpu>=2.2.3

tensorflow-cpu fixed: 2.3.3

pip install tensorflow-cpu>=2.3.3

tensorflow-cpu fixed: 2.4.2

pip install tensorflow-cpu>=2.4.2

tensorflow-gpu fixed: 2.1.4

pip install tensorflow-gpu>=2.1.4

tensorflow-gpu fixed: 2.2.3

pip install tensorflow-gpu>=2.2.3

tensorflow-gpu fixed: 2.3.3

pip install tensorflow-gpu>=2.3.3

tensorflow-gpu fixed: 2.4.2

pip install tensorflow-gpu>=2.4.2

Verify Direct and Transitive Dependencies

Run the following command in your project directory to verify that all resolved dependencies use the patched release:

pip show tensorflow

How to Check if You Are Affected

To determine whether your Python environment is affected by CVE-2021-29551, inspect your installed packages using pip:

pip show tensorflow

Analyze the terminal output to locate any version of Tensorflow in your dependency tree. If any resolved version matches the vulnerable ranges listed in the table below (for example, versions earlier than 2.1.4), your application is affected.

Note: The pip show tensorflow command checks currently installed packages in your active Python environment.

Technical Details

Vulnerability Mechanism & Technical Analysis

This vulnerability is classified under CWE-125: Out-of-bounds Read, where the product reads data past the end, or before the beginning, of the intended buffer. In Tensorflow, software state validation or input boundaries are circumvented during processing. Review the official source advisory statement below for specific affected components, classes, and reproduction details.

Source Advisory Statement

### 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::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: ```python 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](https://github.com/tensorflow/tensorflow/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](https://github.com/tensorflow/tensorflow/blob/master/SECURITY.md) 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.

CVE-2021-29551 Affected Tensorflow Versions

12 component(s)

Fixed Versions:

2.1.42.2.32.3.32.4.2

Product / Package	Ecosystem	Affected Versions	Fixed Version
tensorflow pypi/tensorflow	PyPI	< 2.1.4	2.1.4
tensorflow pypi/tensorflow	PyPI	≥ 2.2.0 < 2.2.3	2.2.3
tensorflow pypi/tensorflow	PyPI	≥ 2.3.0 < 2.3.3	2.3.3
tensorflow pypi/tensorflow	PyPI	≥ 2.4.0 < 2.4.2	2.4.2
tensorflow-cpu pypi/tensorflow-cpu	PyPI	< 2.1.4	2.1.4
tensorflow-cpu pypi/tensorflow-cpu	PyPI	≥ 2.2.0 < 2.2.3	2.2.3
tensorflow-cpu pypi/tensorflow-cpu	PyPI	≥ 2.3.0 < 2.3.3	2.3.3
tensorflow-cpu pypi/tensorflow-cpu	PyPI	≥ 2.4.0 < 2.4.2	2.4.2
tensorflow-gpu pypi/tensorflow-gpu	PyPI	< 2.1.4	2.1.4
tensorflow-gpu pypi/tensorflow-gpu	PyPI	≥ 2.2.0 < 2.2.3	2.2.3
tensorflow-gpu pypi/tensorflow-gpu	PyPI	≥ 2.3.0 < 2.3.3	2.3.3
tensorflow-gpu pypi/tensorflow-gpu	PyPI	≥ 2.4.0 < 2.4.2	2.4.2

References

GitHub Advisory / Wiki ADVISORY

https://github.com/tensorflow/tensorflow/security/advisories/GHSA-vqw6-72r7-fgw7

NVD — CVE-2021-29551 NVD

https://nvd.nist.gov/vuln/detail/CVE-2021-29551

Security Fix Commit FIX COMMIT

https://github.com/tensorflow/tensorflow/commit/480641e3599775a8895254ffbc0fc45621334f68

Tensorflow Source Repository REPOSITORY

https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2021-479.yaml

Tensorflow Source Repository REPOSITORY

https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2021-677.yaml

Tensorflow Source Repository REPOSITORY

https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow/PYSEC-2021-188.yaml

Tensorflow Source Repository REPOSITORY

https://github.com/tensorflow/tensorflow

Frequently Asked Questions

What is CVE-2021-29551?

CVE-2021-29551 is a security vulnerability in Tensorflow involving OOB read in `MatrixTriangularSolve` under CWE-125: Out-of-bounds Read.

Which Tensorflow versions are affected?

Affected versions include releases prior to 2.1.4, 2.2.3, 2.3.3, 2.4.2 across affected packages: tensorflow, tensorflow-cpu, tensorflow-gpu.

What version fixes CVE-2021-29551?

Upgrading to 2.1.4, 2.2.3, 2.3.3, 2.4.2 (or the latest patched release for your respective branch) resolves the vulnerability.

Is tensorflow affected?

Yes, tensorflow is affected in releases prior to 2.1.4, 2.2.3, 2.3.3, 2.4.2. Upgrade your dependency to 2.1.4, 2.2.3, 2.3.3, 2.4.2 or later.

Is tensorflow-cpu affected?

Yes, tensorflow-cpu is affected in releases prior to 2.1.4, 2.2.3, 2.3.3, 2.4.2. Upgrade your dependency to 2.1.4, 2.2.3, 2.3.3, 2.4.2 or later.

What is the CVSS score of CVE-2021-29551?

CVE-2021-29551 has a CVSS v3.1 base score of 2.5 (LOW) with vector string CVSS:3.1/AV:L/AC:H/PR:L/UI:N/S:U/C:N/I:N/A:L.

What CWE is associated with CVE-2021-29551?

CVE-2021-29551 is classified under CWE-125: Out-of-bounds Read (The product reads data past the end, or before the beginning, of the intended buffer.).

How can I check PyPI dependencies for CVE-2021-29551?

Run the dependency tree command: 'pip show tensorflow'. This command lists direct and transitive dependencies in your build configuration so you can verify if a vulnerable version is resolved.

Machine-readable OSV JSON OSV v1.5 Schema

Normalized schema output

View Raw JSON

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  "id" : "GHSA-vqw6-72r7-fgw7",
  "modified" : "2024-10-31T20:49:39Z",
  "published" : "2021-05-21T14:23:44Z",
  "aliases" : [ "CVE-2021-29551" ],
  "summary" : "OOB read in `MatrixTriangularSolve`",
  "details" : "### Impact\nThe 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:\n\n```cc\nvoid ValidateInputTensors(OpKernelContext* ctx, const Tensor& in0,\n                            const Tensor& in1) override {\n  OP_REQUIRES(\n      ctx, in0.dims() >= 2,\n      errors::InvalidArgument(\"In[0] ndims must be >= 2: \", in0.dims()));\n\n  OP_REQUIRES(\n      ctx, in1.dims() >= 2,\n      errors::InvalidArgument(\"In[0] ndims must be >= 2: \", in1.dims()));\n}\n  \nvoid Compute(OpKernelContext* ctx) override {\n  const Tensor& in0 = ctx->input(0);\n  const Tensor& in1 = ctx->input(1);\n\n  ValidateInputTensors(ctx, in0, in1);\n\n  MatMulBCast bcast(in0.shape().dim_sizes(), in1.shape().dim_sizes());\n  ...\n}\n```\n  \nSince `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:\n\n```python\nimport tensorflow as tf\nimport numpy as np\n\nmatrix_array = np.array([])\nmatrix_tensor = tf.convert_to_tensor(np.reshape(matrix_array,(1,0)),dtype=tf.float32)\nrhs_array = np.array([])\nrhs_tensor = tf.convert_to_tensor(np.reshape(rhs_array,(0,1)),dtype=tf.float32)\n\ntf.raw_ops.MatrixTriangularSolve(matrix=matrix_tensor,rhs=rhs_tensor,lower=False,adjoint=False)\n```\n\nAs 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.\n\n### Patches\nWe have patched the issue in GitHub commit [480641e3599775a8895254ffbc0fc45621334f68](https://github.com/tensorflow/tensorflow/commit/480641e3599775a8895254ffbc0fc45621334f68).\n\nThe 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.\n\n### For more information\nPlease consult [our security guide](https://github.com/tensorflow/tensorflow/blob/master/SECURITY.md) for more information regarding the security model and how to contact us with issues and questions.\n\n### Attribution\nThis vulnerability has been reported by Ye Zhang and Yakun Zhang of Baidu X-Team.",
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  "database_specific" : {
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    "severity" : "LOW",
    "github_reviewed" : true,
    "github_reviewed_at" : "2021-05-18T21:14:11Z",
    "nvd_published_at" : "2021-05-14T20:15:00Z"
  }
}

CVSS V3

2.5 LOW

Attack Vector Local (AV:L)

Attack Complexity High (AC:H)

Privileges Required Low (PR:L)

User Interaction None (UI:N)

Scope Unchanged (S:U)

Confidentiality None (C:N)

Integrity None (I:N)

Availability Low (A:L)

Vector String

CVSS:3.1/AV:L/AC:H/PR:L/UI:N/S:U/C:N/I:N/A:L

Advisory Metadata

Source ID: GHSA-vqw6-72r7-fgw7
Schema Version: 1.4.0
Published: 2021-05-21 14:23
Last Modified: 2024-10-31 20:49
Database Record File: advisories/github-reviewed/2021/05/GHSA-vqw6-72r7-fgw7/GHSA-vqw6-72r7-fgw7.json