CVE-2021-29551: OOB read in `MatrixTriangularSolve`
First published: Fri May 14 2021(Updated: )
### 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.
Credit: security-advisories@github.com security-advisories@github.com
| Affected Software | Affected Version | How to fix |
|---|---|---|
| Google TensorFlow | <2.1.4 | |
| Google TensorFlow | >=2.2.0<2.2.3 | |
| Google TensorFlow | >=2.3.0<2.3.3 | |
| Google TensorFlow | >=2.4.0<2.4.2 | |
| pip/tensorflow-gpu | >=2.4.0<2.4.2 | 2.4.2 |
| pip/tensorflow-gpu | >=2.3.0<2.3.3 | 2.3.3 |
| pip/tensorflow-gpu | >=2.2.0<2.2.3 | 2.2.3 |
| pip/tensorflow-gpu | <2.1.4 | 2.1.4 |
| pip/tensorflow-cpu | >=2.4.0<2.4.2 | 2.4.2 |
| pip/tensorflow-cpu | >=2.3.0<2.3.3 | 2.3.3 |
| pip/tensorflow-cpu | >=2.2.0<2.2.3 | 2.2.3 |
| pip/tensorflow-cpu | <2.1.4 | 2.1.4 |
| pip/tensorflow | >=2.4.0<2.4.2 | 2.4.2 |
| pip/tensorflow | >=2.3.0<2.3.3 | 2.3.3 |
| pip/tensorflow | >=2.2.0<2.2.3 | 2.2.3 |
| pip/tensorflow | <2.1.4 | 2.1.4 |
Never miss a vulnerability like this again
Sign up to SecAlerts for real-time vulnerability data matched to your software, aggregated from hundreds of sources.
Reference Links
- https://github.com/tensorflow/tensorflow/commit/480641e3599775a8895254ffbc0fc45621334f68
- https://github.com/tensorflow/tensorflow/security/advisories/GHSA-vqw6-72r7-fgw7
- https://nvd.nist.gov/vuln/detail/CVE-2021-29551
- https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2021-479.yaml
- https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2021-677.yaml
- https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow/PYSEC-2021-188.yaml
- https://github.com/advisories/GHSA-vqw6-72r7-fgw7 (Advisory)
Frequently Asked Questions
What is the severity of CVE-2021-29551?
CVE-2021-29551 has a medium severity score according to the Common Vulnerability Scoring System.
How do I fix CVE-2021-29551?
To remediate CVE-2021-29551, upgrade to TensorFlow versions 2.1.4, 2.2.3, 2.3.3, or 2.4.2.
What software is affected by CVE-2021-29551?
CVE-2021-29551 affects TensorFlow versions prior to 2.1.4, between 2.2.0 and 2.2.3, between 2.3.0 and 2.3.3, and between 2.4.0 and 2.4.2.
What does CVE-2021-29551 involve?
CVE-2021-29551 involves a failure in the MatrixTriangularSolve implementation that does not terminate kernel execution under certain conditions.
Is CVE-2021-29551 likely to be exploited?
While the exploitability of CVE-2021-29551 is context-dependent, vulnerabilities that affect TensorFlow should be addressed promptly to prevent potential attacks.
- collector/nvd-index
- agent/type
- agent/remedy
- collector/mitre-cve
- source/MITRE
- agent/weakness
- agent/title
- agent/severity
- agent/first-publish-date
- collector/github-advisory-latest
- source/GitHub
- alias/GHSA-vqw6-72r7-fgw7
- alias/CVE-2021-29551
- agent/software-canonical-lookup
- agent/references
- agent/last-modified-date
- agent/softwarecombine
- agent/description
- agent/event
- collector/nvd-cve
- source/NVD
- agent/author
- collector/github-advisory
- agent/trending
- agent/tags
- agent/source
- vendor/google
- canonical/google tensorflow
- version/google tensorflow/2.2.0
- version/google tensorflow/2.3.0
- version/google tensorflow/2.4.0
- package-manager/pip