CVE-2021-37657
Description
TensorFlow is an end-to-end open source platform for machine learning. In affected versions an attacker can cause undefined behavior via binding a reference to null pointer in all operations of type `tf.raw_ops.MatrixDiagV*`. The [implementation](https://github.com/tensorflow/tensorflow/blob/84d053187cb80d975ef2b9684d4b61981bca0c41/tensorflow/core/kernels/linalg/matrix_diag_op.cc) has incomplete validation that the value of `k` is a valid tensor. We have check that this value is either a scalar or a vector, but there is no check for the number of elements. If this is an empty tensor, then code that accesses the first element of the tensor is wrong. We have patched the issue in GitHub commit f2a673bd34f0d64b8e40a551ac78989d16daad09. 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.
Predictions
Heuristic predictions, AS-IS, for prioritization only.
Mitigations
No mitigations published for this CVE yet.
The vendor-content worker queues fetches as references arrive (check back in a few minutes). Or — if you've already worked around this in production — publish your fix to the community-verified tier.
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OS impact
Arch Fixed 1 release
| Version | Status | Fixed in |
|---|---|---|
| — | Fixed | 2.5.1-1 |
Debian Fixed 2 releases
| Version | Status | Fixed in |
|---|---|---|
| sid | Fixed | 0 |
| forky | Fixed | 0 |
Package impact
| Ecosystem | Package | Vulnerable | Fixed |
|---|---|---|---|
| PyPI | tensorflow-cpu | >=2.5.0,<2.5.1 | 2.5.1 |
| PyPI | tensorflow-gpu | <2.3.4 | 2.3.4 |
| PyPI | tensorflow-gpu | >=2.4.0,<2.4.3 | 2.4.3 |
| PyPI | tensorflow-gpu | >=2.5.0,<2.5.1 | 2.5.1 |
| PyPI | tensorflow | >=2.5.0,<2.5.1 | 2.5.1 |
| PyPI | tensorflow-cpu | <2.3.4 | 2.3.4 |
| PyPI | tensorflow-cpu | >=2.4.0,<2.4.3 | 2.4.3 |
| PyPI | tensorflow | >=2.4.0,<2.4.3 | 2.4.3 |
| PyPI | tensorflow | <2.3.4 | 2.3.4 |
| PyPI | tensorflow-cpu | <f2a673bd34f0d64b8e40a551ac78989d16daad09||>=2.4.0,<2.4.3 | f2a673bd34f0d64b8e40a551ac78989d16daad09 |
| PyPI | tensorflow | <f2a673bd34f0d64b8e40a551ac78989d16daad09||>=2.4.0,<2.4.3 | f2a673bd34f0d64b8e40a551ac78989d16daad09 |
| PyPI | tensorflow-gpu | <f2a673bd34f0d64b8e40a551ac78989d16daad09||>=2.4.0,<2.4.3 | f2a673bd34f0d64b8e40a551ac78989d16daad09 |
References
- https://github.com/tensorflow/tensorflow/security/advisories/GHSA-5xwc-mrhx-5g3m
- https://nvd.nist.gov/vuln/detail/CVE-2021-37657
- https://github.com/tensorflow/tensorflow/commit/f2a673bd34f0d64b8e40a551ac78989d16daad09
- https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2021-570.yaml
- https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2021-768.yaml
- https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow/PYSEC-2021-279.yaml
- https://github.com/tensorflow/tensorflow
- https://security-tracker.debian.org/tracker/CVE-2021-37657
Community-verified mitigations for this CVE will appear above when contributors publish them.
Verify integrity in audit chain (admin only). AS-IS.