Null pointer dereference in TFLite MLIR optimizations
Impact
An attacker can craft a TFLite model that would trigger a null pointer dereference, which would result in a crash and denial of service:
This is caused by the MLIR optimization of L2NormalizeReduceAxis operator. The implementation unconditionally dereferences a pointer to an iterator to a vector without checking that the vector has elements:
bool L2NormalizeReduceAxis(Value sq_op, DenseElementsAttr axis) {
if (sq_op.getType().cast<ShapedType>().getRank() - 1 ==
*axis.getValues<int>().begin() ||
*axis.getValues<int>().begin() == -1) {
// ...
}
// ...
}
Patches
We have patched the issue in GitHub commit d6b57f461b39fd1aa8c1b870f1b974aac3554955.
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.
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 Yakun Zhang of Baidu Security.
Affected software
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| Platform | Package | Vulnerable versions | Fixed in |
|---|---|---|---|
| Python (PyPI) | tensorflow | < 2.3.4, >= 2.4.0, < 2.4.3, >= 2.5.0, < 2.5.1 | 2.3.4, 2.4.3, 2.5.1 |
| Python (PyPI) | tensorflow-cpu | < 2.3.4, >= 2.4.0, < 2.4.3, >= 2.5.0, < 2.5.1 | 2.3.4, 2.4.3, 2.5.1 |
| Python (PyPI) | tensorflow-gpu | < 2.3.4, >= 2.4.0, < 2.4.3, >= 2.5.0, < 2.5.1 | 2.3.4, 2.4.3, 2.5.1 |
References
- https://github.com/tensorflow/tensorflow/commit/d6b57f461b39fd1aa8c1b870f1b974aac3554955
- https://github.com/tensorflow/tensorflow/security/advisories/GHSA-wf5p-c75w-w3wh
- https://nvd.nist.gov/vuln/detail/CVE-2021-37689
- https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2021-602.yaml
- https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2021-800.yaml
- https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow/PYSEC-2021-311.yaml
- https://github.com/tensorflow/tensorflow
- https://github.com/tensorflow/tensorflow/blob/149562d49faa709ea80df1d99fc41d005b81082a/tensorflow/compiler/mlir/lite/transforms/optimize.cc#L67-L70
- CVSS vector
CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H- Weakness (CWE)
CWE-476- Platform
- Python (PyPI)
- Package
tensorflow, tensorflow-cpu, tensorflow-gpu- Disclosed
- 12.08.2021
- Updated
- 11.10.2026 15:17
Sources and licenses
OSV / GitHub Advisory Database - PYSEC-2021-311 - PyPA Advisory Database; CC BY 4.0
OSV / GitHub Advisory Database - PYSEC-2021-602 - PyPA Advisory Database; CC BY 4.0
OSV / GitHub Advisory Database - PYSEC-2021-800 - PyPA Advisory Database; CC BY 4.0
OSV / GitHub Advisory Database - GHSA-wf5p-c75w-w3wh - CC BY 4.0
Vulnerability history: tensorflow-gpu
All published vulnerabilities of this package (Python (PyPI)), newest first. Shows whether this is a one-off slip or a package that needs watching.
- Total entries
- 427
- First → latest
- 04.2019 07.2024
- Without a fix
- 0
- Exploited in attacks
- 0
Severity breakdown
- Critical 6
- High 109
- Medium 207
- Low 105
Disclosures per year
- 2019: 7
- 2020: 35
- 2021: 200
- 2022: 166
- 2023: 18
- 2024: 1
- 2025: 0
- 2026: 0
-
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