CVE-2022-23589mediumCWE-476

CVE-2022-23589: medium-severity vulnerability in tensorflow

Null pointer dereference in Grappler's `IsConstant` in Tensorflow

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13Vexday Risk Score

No sign of exploitation. No public exploitation artifact known so far.

ssvc Trackcvss 6.5epss 1.1%
In short

TensorFlow's optimization component (Grappler) crashes when processing specially crafted machine learning model files that have missing required nodes, causing the program to stop unexpectedly.

Technical detail

Null pointer dereference in Grappler's constant folding and IsIdentityConsumingSwitch functions occurs when a malicious or corrupted SavedModel lacks required nodes for binary operations. Attack vector requires local access to modify model files; impact is denial of service through application crash.

Summary generated and translated by AI from the official description.
Tensorflow is an Open Source Machine Learning Framework. Under certain scenarios, Grappler component of TensorFlow can trigger a null pointer dereference. There are 2 places where this can occur, for the same malicious alteration of a `SavedModel` file (fixing the first one would trigger the same dereference in the second place). First, during constant folding, the `GraphDef` might not have the required nodes for the binary operation. If a node is missing, the correposning `mul_*child` would be null, and the dereference in the subsequent line would be incorrect. We have a similar issue during `IsIdentityConsumingSwitch`. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.
CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H
Affected products
tensorflow · tensorflow
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