In TensorFlow Lite before versions 2.2.1 and 2.3.1, models using segment sum can trigger writes outside of bounds of heap allocated buffers by inserting negative elements in the segment ids tensor. Users having access to `segment_ids_data` can alter `output_index` and then write to outside of `output_data` buffer. This might result in a segmentation fault but it can also be used to further corrupt the memory and can be chained with other vulnerabilities to create more advanced exploits. The issue is patched in commit 204945b19e44b57906c9344c0d00120eeeae178a and is released in TensorFlow versions 2.2.1, or 2.3.1. A potential workaround would be to add a custom `Verifier` to the model loading code to ensure that the segment ids are all positive, although this only handles the case when the segment ids are stored statically in the model. A similar validation could be done if the segment ids are generated at runtime between inference steps. If the segment ids are generated as outputs of a tensor during inference steps, then there are no possible workaround and users are advised to upgrade to patched code.
History

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cve-icon MITRE

Status: PUBLISHED

Assigner: GitHub_M

Published: 2020-09-25T18:50:34

Updated: 2024-08-04T13:08:22.919Z

Reserved: 2020-06-25T00:00:00

Link: CVE-2020-15212

cve-icon Vulnrichment

No data.

cve-icon NVD

Status : Modified

Published: 2020-09-25T19:15:16.510

Modified: 2024-11-21T05:05:06.047

Link: CVE-2020-15212

cve-icon Redhat

No data.