Incorrect validation of `SaveV2` inputs
Impact
The code for tf.raw_ops.SaveV2 does not properly validate the inputs and an attacker can trigger a null pointer dereference:
import tensorflow as tf
tf.raw_ops.SaveV2(
prefix=['tensorflow'],
tensor_name=['v'],
shape_and_slices=[],
tensors=[1,2,3])
The implementation uses ValidateInputs to check that the input arguments are valid. This validation would have caught the illegal state represented by the reproducer above.
However, the validation uses OP_REQUIRES which translates to setting the Status object of the current OpKernelContext to an error status, followed by an empty return statement which just terminates the execution of the function it is present in. However, this does not mean that the kernel execution is finalized: instead, execution continues from the next line in Compute that follows the call to ValidateInputs. This is equivalent to lacking the validation.
Patches
We have patched the issue in GitHub commit 9728c60e136912a12d99ca56e106b7cce7af5986.
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 members of the Aivul Team from Qihoo 360.
Betroffene Software
Klicken Sie auf eine Technologie, um alle zugehörigen Schwachstellen anzuzeigen.
| Plattform | Paket | Anfällige Versionen | Behoben 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 |
Verweise
- https://github.com/tensorflow/tensorflow/commit/9728c60e136912a12d99ca56e106b7cce7af5986
- https://github.com/tensorflow/tensorflow/security/advisories/GHSA-wp77-4gmm-7cq8
- https://nvd.nist.gov/vuln/detail/CVE-2021-37648
- https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2021-561.yaml
- https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2021-759.yaml
- https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow/PYSEC-2021-270.yaml
- https://github.com/tensorflow/tensorflow
- CVSS-Vektor
CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H- Schwäche (CWE)
CWE-476- Plattform
- Python (PyPI)
- Paket
tensorflow, tensorflow-cpu, tensorflow-gpu- Veröffentlicht
- 12.08.2021
- Aktualisiert
- 11.10.2026 13:19
Quellen und Lizenzen
OSV / GitHub Advisory Database - PYSEC-2021-270 - PyPA Advisory Database; CC BY 4.0
OSV / GitHub Advisory Database - PYSEC-2021-561 - PyPA Advisory Database; CC BY 4.0
OSV / GitHub Advisory Database - PYSEC-2021-759 - PyPA Advisory Database; CC BY 4.0
OSV / GitHub Advisory Database - GHSA-wp77-4gmm-7cq8 - CC BY 4.0
Schwachstellenhistorie: tensorflow-cpu
Alle veröffentlichten Schwachstellen dieses Pakets (Python (PyPI)), neueste zuerst. Zeigt, ob es ein einmaliger Ausrutscher ist oder ein Paket, das man im Auge behalten muss.
- Einträge insgesamt
- 430
- Erste → letzte
- 04.2019 07.2024
- Ohne Fix
- 0
- In Angriffen ausgenutzt
- 0
Verteilung nach Schweregrad
- Kritisch 6
- Hoch 111
- Mittel 208
- Niedrig 105
Veröffentlichungen pro Jahr
- 2019: 7
- 2020: 35
- 2021: 200
- 2022: 166
- 2023: 21
- 2024: 1
- 2025: 0
- 2026: 0
-
Incorrect validation of `SaveV2` inputs dieser Eintrag
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