CVE-2022-23558: Integer overflow in TFLite array creation
First published: Fri Feb 04 2022(Updated: )
### Impact An attacker can craft a TFLite model that would cause an integer overflow [in `TfLiteIntArrayCreate`](https://github.com/tensorflow/tensorflow/blob/ca6f96b62ad84207fbec580404eaa7dd7403a550/tensorflow/lite/c/common.c#L53-L60): ```cc TfLiteIntArray* TfLiteIntArrayCreate(int size) { int alloc_size = TfLiteIntArrayGetSizeInBytes(size); // ... TfLiteIntArray* ret = (TfLiteIntArray*)malloc(alloc_size); // ... } ``` The [`TfLiteIntArrayGetSizeInBytes`](https://github.com/tensorflow/tensorflow/blob/ca6f96b62ad84207fbec580404eaa7dd7403a550/tensorflow/lite/c/common.c#L24-L33) returns an `int` instead of a `size_t`: ```cc int TfLiteIntArrayGetSizeInBytes(int size) { static TfLiteIntArray dummy; int computed_size = sizeof(dummy) + sizeof(dummy.data[0]) * size; #if defined(_MSC_VER) // Context for why this is needed is in http://b/189926408#comment21 computed_size -= sizeof(dummy.data[0]); #endif return computed_size; } ``` An attacker can control model inputs such that `computed_size` overflows the size of `int` datatype. ### Patches We have patched the issue in GitHub commit [a1e1511dde36b3f8aa27a6ec630838e7ea40e091](https://github.com/tensorflow/tensorflow/commit/a1e1511dde36b3f8aa27a6ec630838e7ea40e091). 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 |
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Reference Links
- https://github.com/tensorflow/tensorflow/blob/ca6f96b62ad84207fbec580404eaa7dd7403a550/tensorflow/lite/c/common.c#L24-L33
- https://github.com/tensorflow/tensorflow/blob/ca6f96b62ad84207fbec580404eaa7dd7403a550/tensorflow/lite/c/common.c#L53-L60
- https://github.com/tensorflow/tensorflow/commit/a1e1511dde36b3f8aa27a6ec630838e7ea40e091
- https://github.com/tensorflow/tensorflow/security/advisories/GHSA-9gwq-6cwj-47h3
- https://nvd.nist.gov/vuln/detail/CVE-2022-23558
- https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2022-67.yaml
- https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2022-122.yaml
- https://github.com/advisories/GHSA-9gwq-6cwj-47h3 (Advisory)
Frequently Asked Questions
What is the severity of CVE-2022-23558?
CVE-2022-23558 is classified as a medium severity vulnerability due to the potential for integer overflow.
How do I fix CVE-2022-23558?
To fix CVE-2022-23558, upgrade to TensorFlow versions 2.5.3, 2.6.3, or 2.7.1.
What versions of TensorFlow are affected by CVE-2022-23558?
CVE-2022-23558 affects TensorFlow versions up to 2.5.2, between 2.6.0 and 2.6.2, and exactly 2.7.0.
What is the nature of the vulnerability described in CVE-2022-23558?
CVE-2022-23558 involves an integer overflow that can be exploited through specially crafted TFLite models.
Are TensorFlow GPU and CPU packages also affected by CVE-2022-23558?
Yes, both TensorFlow GPU and CPU packages are affected by CVE-2022-23558 if running the vulnerable versions.
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