In Tensorflow before versions 1.15.4, 2.0.3, 2.1.2, 2.2.1 and 2.3.1, 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. Fixed were added in commits 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. The issue is patched in commit adf095206f25471e864a8e63a0f1caef53a0e3a6, and is released in TensorFlow versions 1.15.4, 2.0.3, 2.1.2, 2.2.1, or 2.3.1.
beschreibt (1)
Zugehörige CVEs.
| ID | Schweregrad | ausnutzbar | ||
|---|---|---|---|---|
| CVE-2020-15206US | high7.5 | — | ||
In Tensorflow before versions 1.15.4, 2.0.3, 2.1.2, 2.2.1 and 2.3.1, changing the TensorFlow's `SavedModel` protocol buffer and altering the name of required keys results in segfau… | ||||
Referenzen
Externe Belege — Patches, Meldungen, Analysen.
- http://lists.opensuse.org/opensuse-security-announce/2020-10/msg00065.htmlWEB
- https://github.com/tensorflow/tensorflow/commit/adf095206f25471e864a8e63a0f1caef53a0e3a6FIX
- https://github.com/tensorflow/tensorflow/releases/tag/v2.3.1WEB
- https://github.com/tensorflow/tensorflow/security/advisories/GHSA-w5gh-2wr2-pm6gADVISORY
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