CyberSecBulletin
CVE-2022-36013NVD status: Modified

tensorflow: NULL Pointer Dereference

Published Updated By the CyberSecBulletin desk

CVE-2022-36013 is a high-severity NULL pointer dereference vulnerability in tensorflow, with a CVSS 3.1 base score of 7.5 out of 10. It can be exploited remotely over the network by an unauthenticated attacker, without any action from a user. Affected tensorflow versions: < 2.7.2; >= 2.8.0, < 2.8.1; >= 2.9.0, < 2.9.1. The record does not name a fixed version, so check the vendor advisory. There is no confirmed exploitation so far. EPSS estimates a 0.72% chance of exploitation within 30 days, higher than 54% of scored CVEs.

Next patch cycle

High severity with no evidence of exploitation so far.

What to do

  1. Check which version of tensorflow you run against the affected versions below, and install the vendor's latest release.
  2. Read the advisory on github.com for workarounds and exact fixed builds.
  3. Until you can update, restrict network access to the affected service so it is not reachable from untrusted networks.

Affected products and versions

VendorProductAffected versionsFixed in
TensorFlowtensorflow< 2.7.2; >= 2.8.0, < 2.8.1; >= 2.9.0, < 2.9.1Not stated

Version data comes from the organisation that assigned the CVE. Confirm against the vendor advisory before deciding you are unaffected.

How the severity score breaks down

Attack vector
NetworkCan be exploited remotely over a network, including the internet.
Attack complexity
LowNo special conditions are needed; the attack works reliably.
Privileges required
NoneNo account or login is needed.
User interaction
NoneNo action by a victim is required.
Scope
UnchangedImpact stays within the vulnerable component.
Confidentiality
NoneNo data is disclosed.
Integrity
NoneNothing can be modified.
Availability
HighThe component can be taken down completely.

Vector: CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H. Scored by NVD.

Scoring systemScoreSeverityScored by
CVSS 3.15.9MediumCNA (github.com)
CVSS 3.17.5HighNVD

Official description

TensorFlow is an open source platform for machine learning. When `mlir::tfg::GraphDefImporter::ConvertNodeDef` tries to convert NodeDefs without an op name, it crashes. We have patched the issue in GitHub commit a0f0b9a21c9270930457095092f558fbad4c03e5. The fix will be included in TensorFlow 2.10.0. We will also cherrypick this commit on TensorFlow 2.9.1, TensorFlow 2.8.1, and TensorFlow 2.7.2, as these are also affected and still in supported range. There are no known workarounds for this issue.

Source: the CVE record as published by its numbering authority, via NVD and CVE.org.

The underlying weakness: NULL Pointer Dereference

The product dereferences a pointer that it expects to be valid but is NULL.

How developers prevent this class of flaw

  • For any pointers that could have been modified or provided from a function that can return NULL, check the pointer for NULL before use. When working with a multithreaded or otherwise asynchronous environment, ensure that proper locking APIs are used to lock before the check, and unlock when it has finished.
  • Select a programming language that is not susceptible to these issues.
  • Check the results of all functions that return a value and verify that the value is non-null before acting upon it.

More NULL Pointer Dereference vulnerabilities (CWE-476)

Timeline

  1. CVE record published.
  2. CISA published its SSVC assessment (exploitation: none, automatable: no, technical impact: partial).
  3. Record last changed materially (score, affected products, status or references).

References

Other vulnerabilities in tensorflow

All tensorflow vulnerabilities

Recent NULL Pointer Dereference vulnerabilities

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