Integer overflow in TFLite memory allocation
Impact
The TFLite code for allocating TFLiteIntArrays is vulnerable to an integer overflow issue:
int TfLiteIntArrayGetSizeInBytes(int size) {
static TfLiteIntArray dummy;
return sizeof(dummy) + sizeof(dummy.data[0]) * size;
}An attacker can craft a model such that the size multiplier is so large that the return value overflows the int datatype and becomes negative. In turn, this results in invalid value being given to malloc:
TfLiteIntArray* TfLiteIntArrayCreate(int size) {
TfLiteIntArray* ret = (TfLiteIntArray*)malloc(TfLiteIntArrayGetSizeInBytes(size));
ret->size = size;
return ret;
}In this case, ret->size would dereference an invalid pointer.
Patches
We have patched the issue in GitHub commit 7c8cc4ec69cd348e44ad6a2699057ca88faad3e5.
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 members of the Aivul Team from Qihoo 360.
Affected software
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| Platform | Package | Vulnerable versions | Fixed in |
|---|---|---|---|
| Python (PyPI) | tensorflow | < 2.1.4, >= 2.2.0, < 2.2.3, >= 2.3.0, < 2.3.3, >= 2.4.0, < 2.4.2 | 2.1.4, 2.2.3, 2.3.3, 2.4.2 |
| Python (PyPI) | tensorflow-cpu | < 2.1.4, >= 2.2.0, < 2.2.3, >= 2.3.0, < 2.3.3, >= 2.4.0, < 2.4.2 | 2.1.4, 2.2.3, 2.3.3, 2.4.2 |
| Python (PyPI) | tensorflow-gpu | < 2.1.4, >= 2.2.0, < 2.2.3, >= 2.3.0, < 2.3.3, >= 2.4.0, < 2.4.2 | 2.1.4, 2.2.3, 2.3.3, 2.4.2 |
References
- https://github.com/tensorflow/tensorflow/security/advisories/GHSA-jf7h-7m85-w2v2
- https://github.com/tensorflow/tensorflow/commit/7c8cc4ec69cd348e44ad6a2699057ca88faad3e5
- https://nvd.nist.gov/vuln/detail/CVE-2021-29605
- https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2021-533.yaml
- https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2021-731.yaml
- https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow/PYSEC-2021-242.yaml
- https://github.com/tensorflow/tensorflow
- https://github.com/tensorflow/tensorflow/blob/4ceffae632721e52bf3501b736e4fe9d1221cdfa/tensorflow/lite/c/common.c#L24-L27
- CVSS vector
CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:H/A:H- Weakness (CWE)
CWE-190- Platform
- Python (PyPI)
- Package
tensorflow, tensorflow-cpu, tensorflow-gpu- Disclosed
- 14.05.2021
- Updated
- 11.10.2026 15:17
Sources and licenses
OSV / GitHub Advisory Database - PYSEC-2021-242 - PyPA Advisory Database; CC BY 4.0
OSV / GitHub Advisory Database - PYSEC-2021-533 - PyPA Advisory Database; CC BY 4.0
OSV / GitHub Advisory Database - PYSEC-2021-731 - PyPA Advisory Database; CC BY 4.0
OSV / GitHub Advisory Database - GHSA-jf7h-7m85-w2v2 - 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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