CVE-2021-37691: FPE in LSH in TFLite
(updated )
An attacker can craft a TFLite model that would trigger a division by zero error in LSH implementation.
int RunningSignBit(const TfLiteTensor* input, const TfLiteTensor* weight,
float seed) {
int input_item_bytes = input->bytes / SizeOfDimension(input, 0);
// ...
}
There is no check that the first dimension of the input is non zero.
References
- github.com/advisories/GHSA-27qf-jwm8-g7f3
- github.com/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2021-604.yaml
- github.com/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2021-802.yaml
- github.com/pypa/advisory-database/tree/main/vulns/tensorflow/PYSEC-2021-313.yaml
- github.com/tensorflow/tensorflow
- github.com/tensorflow/tensorflow/commit/0575b640091680cfb70f4dd93e70658de43b94f9
- github.com/tensorflow/tensorflow/security/advisories/GHSA-27qf-jwm8-g7f3
- nvd.nist.gov/vuln/detail/CVE-2021-37691
Detect and mitigate CVE-2021-37691 with GitLab Dependency Scanning
Secure your software supply chain by verifying that all open source dependencies used in your projects contain no disclosed vulnerabilities. Learn more about Dependency Scanning →