EUVD-2021-0343 · Published May 21, 2021
Division by zero in TFLite's implementation of DepthwiseConv
Impact
The implementation of the DepthwiseConv TFLite operator is vulnerable to a division by zero error:
int num_input_channels = SizeOfDimension(input, 3);
TF_LITE_ENSURE_EQ(context, num_filter_channels % num_input_channels, 0);
An attacker can craft a model such that input's fourth dimension would be 0.
Patches
We have patched the issue in GitHub commit cbda3c6b2dbbd3fbdc482ff8c0170a78ec2e97d0.
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.
Technologies
Weaknesses
CVSS scores
- v3.12.5
CVSS:3.1/AV:L/AC:H/PR:L/UI:N/S:U/C:N/I:N/A:L
MITRE ATT&CK
InferredWhere this vulnerability fits in an attack
References
- https://github.com/tensorflow/tensorflow/security/advisories/GHSA-rf3h-xgv5-2q39
- https://github.com/tensorflow/tensorflow/commit/cbda3c6b2dbbd3fbdc482ff8c0170a78ec2e97d0
- https://nvd.nist.gov/vuln/detail/CVE-2021-29602
- https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2021-530.yaml
- https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2021-728.yaml
- https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow/PYSEC-2021-239.yaml
Potentially impacted assets
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