CVE-2020-15212

Out of bounds access in tensorflow-lite

Published Sep 25, 2020 CVSS 3.1 · 8.1 High EPSS < 1% KEV · Not listed
Description
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.

Remediation

No solution or workaround provided in the CVE record

Tracking

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Advisories

Source ID Title
EUVD EUVD EUVD-2020-0208 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.
Github GHSA Github GHSA GHSA-hx2x-85gr-wrpq Out of bounds access in tensorflow-lite
History

No history.

Weaknesses

Sources

Status
PUBLISHED
Assigner
GitHub_M
Published
Updated
Aug 4, 2024, 1:08 PM
Reserved
Jun 25, 2020, 12:00 AM
Status
Modified
Published
Sep 25, 2020, 7:15 PM
Modified
Jun 17, 2026, 2:56 AM