STT-tensorflow/tensorflow/security/advisory/tfsa-2020-010.md
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PiperOrigin-RevId: 333195707
Change-Id: I1e2fed8ff207fbfce6eb8fb2b910d12bcab4100c
2020-09-22 17:56:00 -07:00

2.0 KiB

TFSA-2020-010: Incomplete validation in TensorFlow's SavedModel's constant nodes causes segfaults

CVE Number

CVE-2020-15206

Impact

Changing the TensorFlow's SavedModel protocol buffer and altering the name of required keys results in segfaults and data corruption while loading the model. This can cause a denial of service in products using tensorflow-serving or other inference-as-a-service installments.

We have added fixes to this in f760f88b4267d981e13f4b302c437ae800445968 and fcfef195637c6e365577829c4d67681695956e7d (both going into TensorFlow 2.2.0 and 2.3.0 but not yet backported to earlier versions). However, this was not enough, as #41097 reports a different failure mode.

Vulnerable Versions

TensorFlow 1.15.0, 1.15.1, 1.15.2, 1.15.3, 2.0.0, 2.0.1, 2.0.2, 2.1.0, 2.1.1, 2.2.0, 2.3.0.

Patches

We have patched the issue in adf095206f25471e864a8e63a0f1caef53a0e3a6 and will release patch releases for all versions between 1.15 and 2.3. Patch releases for versions between 1.15 and 2.1 will also contain cherry-picks of f760f88b4267d981e13f4b302c437ae800445968 and fcfef195637c6e365577829c4d67681695956e7d.

We recommend users to upgrade to TensorFlow 1.15.4, 2.0.3, 2.1.2, 2.2.1, or 2.3.1.

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 Shuaike Dong, from Alipay Tian Qian Security Lab && Lab for Applied Security Research, CUHK.