CVE-2022-23557: Division by zero in TFLite
First published: Fri Feb 04 2022(Updated: )
### Impact An attacker can craft a TFLite model that would trigger a division by zero in [`BiasAndClamp` implementation](https://github.com/tensorflow/tensorflow/blob/5100e359aef5c8021f2e71c7b986420b85ce7b3d/tensorflow/lite/kernels/internal/common.h#L75): ```cc inline void BiasAndClamp(float clamp_min, float clamp_max, int bias_size, const float* bias_data, int array_size, float* array_data) { // ... TFLITE_DCHECK_EQ((array_size % bias_size), 0); // ... } ``` There is no check that the `bias_size` is non zero. ### Patches We have patched the issue in GitHub commit [8c6f391a2282684a25cbfec7687bd5d35261a209](https://github.com/tensorflow/tensorflow/commit/8c6f391a2282684a25cbfec7687bd5d35261a209). The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range. ### For more information Please consult [our security guide](https://github.com/tensorflow/tensorflow/blob/master/SECURITY.md) for more information regarding the security model and how to contact us with issues and questions. ### Attribution This vulnerability has been reported by Wang Xuan of Qihoo 360 AIVul Team.
Credit: security-advisories@github.com security-advisories@github.com
| Affected Software | Affected Version | How to fix |
|---|---|---|
| Google TensorFlow | <=2.5.2 | |
| Google TensorFlow | >=2.6.0<=2.6.2 | |
| Google TensorFlow | =2.7.0 | |
| pip/tensorflow-gpu | =2.7.0 | 2.7.1 |
| pip/tensorflow-gpu | >=2.6.0<2.6.3 | 2.6.3 |
| pip/tensorflow-gpu | <2.5.3 | 2.5.3 |
| pip/tensorflow-cpu | =2.7.0 | 2.7.1 |
| pip/tensorflow-cpu | >=2.6.0<2.6.3 | 2.6.3 |
| pip/tensorflow-cpu | <2.5.3 | 2.5.3 |
| pip/tensorflow | =2.7.0 | 2.7.1 |
| pip/tensorflow | >=2.6.0<2.6.3 | 2.6.3 |
| pip/tensorflow | <2.5.3 | 2.5.3 |
Never miss a vulnerability like this again
Sign up to SecAlerts for real-time vulnerability data matched to your software, aggregated from hundreds of sources.
Reference Links
- https://github.com/tensorflow/tensorflow/blob/5100e359aef5c8021f2e71c7b986420b85ce7b3d/tensorflow/lite/kernels/internal/common.h#L75
- https://github.com/tensorflow/tensorflow/commit/8c6f391a2282684a25cbfec7687bd5d35261a209
- https://github.com/tensorflow/tensorflow/security/advisories/GHSA-gf2j-f278-xh4v
- https://nvd.nist.gov/vuln/detail/CVE-2022-23557
- https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2022-66.yaml
- https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2022-121.yaml
- https://github.com/advisories/GHSA-gf2j-f278-xh4v (Advisory)
Frequently Asked Questions
What is the severity of CVE-2022-23557?
CVE-2022-23557 has a medium severity rating due to its potential to cause an application crash.
How do I fix CVE-2022-23557?
To fix CVE-2022-23557, upgrade TensorFlow to version 2.7.1 or higher.
Which versions of TensorFlow are affected by CVE-2022-23557?
CVE-2022-23557 affects TensorFlow versions prior to 2.5.3, between 2.6.0 and 2.6.3, and exactly 2.7.0.
What vulnerability does CVE-2022-23557 exploit?
CVE-2022-23557 exploits a division by zero issue in the BiasAndClamp implementation of TensorFlow Lite.
Is CVE-2022-23557 a remote code execution vulnerability?
CVE-2022-23557 does not enable remote code execution, but it can lead to application instability.
- collector/nvd-index
- agent/type
- agent/remedy
- collector/mitre-cve
- source/MITRE
- agent/weakness
- agent/title
- agent/severity
- agent/first-publish-date
- collector/github-advisory-latest
- source/GitHub
- alias/GHSA-gf2j-f278-xh4v
- alias/CVE-2022-23557
- agent/software-canonical-lookup
- agent/last-modified-date
- agent/author
- agent/references
- agent/description
- collector/nvd-cve
- source/NVD
- agent/event
- agent/softwarecombine
- collector/github-advisory
- agent/trending
- agent/tags
- agent/source
- vendor/google
- canonical/google tensorflow
- version/google tensorflow/2.5.2
- version/google tensorflow/2.6.0
- version/google tensorflow/2.6.2
- version/google tensorflow/2.7.0
- package-manager/pip