TensorFlow up to 2.3.0 ResolveAxis Negative Value memory corruption

Summaryinfo

A vulnerability was found in TensorFlow up to 1.15.3/2.0.2/2.1.1/2.2.0/2.3.0 and classified as critical. This issue affects the function ResolveAxis. The manipulation as part of Negative Value results in memory corruption. This vulnerability is reported as CVE-2020-15207. The attack can be launched remotely. No exploit exists. It is suggested to upgrade the affected component.

Detailsinfo

A vulnerability, which was classified as critical, was found in TensorFlow up to 1.15.3/2.0.2/2.1.1/2.2.0/2.3.0 (Artificial Intelligence Software). Affected is the function ResolveAxis. The manipulation as part of a Negative Value leads to a memory corruption vulnerability. CWE is classifying the issue as CWE-119. The product performs operations on a memory buffer, but it can read from or write to a memory location that is outside of the intended boundary of the buffer. This is going to have an impact on confidentiality, integrity, and availability. CVE summarizes:

In tensorflow-lite before versions 1.15.4, 2.0.3, 2.1.2, 2.2.1 and 2.3.1, to mimic Python's indexing with negative values, TFLite uses `ResolveAxis` to convert negative values to positive indices. However, the only check that the converted index is now valid is only present in debug builds. If the `DCHECK` does not trigger, then code execution moves ahead with a negative index. This, in turn, results in accessing data out of bounds which results in segfaults and/or data corruption. The issue is patched in commit 2d88f470dea2671b430884260f3626b1fe99830a, and is released in TensorFlow versions 1.15.4, 2.0.3, 2.1.2, 2.2.1, or 2.3.1.

The weakness was disclosed 09/25/2020 (GitHub Repository). The advisory is shared for download at github.com. This vulnerability is traded as CVE-2020-15207 since 06/25/2020. It is possible to launch the attack remotely. The exploitation doesn't require any form of authentication. There are known technical details, but no exploit is available.

Upgrading to version 1.15.4, 2.0.3, 2.1.2, 2.2.1 or 2.3.1 eliminates this vulnerability. Applying the patch 2d88f470dea2671b430884260f3626b1fe99830a is able to eliminate this problem. The best possible mitigation is suggested to be upgrading to the latest version.

The entries VDB-162016, VDB-162015, VDB-162014 and VDB-162013 are pretty similar. Once again VulDB remains the best source for vulnerability data.

Productinfo

Type

• Artificial Intelligence Software

Name

• TensorFlow

Version

• 1.15.0
• 1.15.1
• 1.15.2
• 1.15.3
• 2.0
• 2.0.0
• 2.0.1
• 2.0.2
• 2.1
• 2.1.0
• 2.1.1
• 2.2
• 2.2.0
• 2.3.0

License

• free

Website

• Product: https://github.com/tensorflow/tensorflow/

CPE 2.3info

• 🔍
• 🔍
• 🔍

CPE 2.2info

• 🔍
• 🔍
• 🔍

CVSSv4info

CVSSv3info

CVSSv2info

Exploitinginfo

Threat Intelligenceinfo

Countermeasuresinfo

Timelineinfo

Sourcesinfo

Entryinfo

Once again VulDB remains the best source for vulnerability data.

Discussion