CyberSecBulletin
CVE-2022-23558NVD status: Modified

tensorflow: Integer Overflow or Wraparound

Published Updated By the CyberSecBulletin desk

CVE-2022-23558 is a high-severity integer overflow or wraparound vulnerability in tensorflow, with a CVSS 3.1 base score of 8.8 out of 10. It can be exploited remotely over the network by an attacker with a low-privileged account, without any action from a user. Affected tensorflow versions: >= 2.7.0, < 2.7.1; >= 2.6.0, < 2.6.3; < 2.5.3. The record does not name a fixed version, so check the vendor advisory. There is no confirmed exploitation so far. EPSS estimates a 0.82% chance of exploitation within 30 days, higher than 58% 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.

Affected products and versions

VendorProductAffected versionsFixed in
TensorFlowtensorflow>= 2.7.0, < 2.7.1; >= 2.6.0, < 2.6.3; < 2.5.3Not 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
LowA basic user account is enough.
User interaction
NoneNo action by a victim is required.
Scope
UnchangedImpact stays within the vulnerable component.
Confidentiality
HighAll data handled by the component can be read.
Integrity
HighData or code can be modified at will.
Availability
HighThe component can be taken down completely.

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

Scoring systemScoreSeverityScored by
CVSS 3.17.6HighCNA (github.com)
CVSS 3.18.8HighNVD
CVSS 2.06.5MediumNVD

Official description

Tensorflow is an Open Source Machine Learning Framework. An attacker can craft a TFLite model that would cause an integer overflow in `TfLiteIntArrayCreate`. The `TfLiteIntArrayGetSizeInBytes` returns an `int` instead of a `size_t. An attacker can control model inputs such that `computed_size` overflows the size of `int` datatype. 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.

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

The underlying weakness: Integer Overflow or Wraparound

The product performs a calculation that can produce an integer overflow or wraparound when the logic assumes that the resulting value will always be larger than the original value. This occurs when an integer value is incremented to a value that is too large to store in the associated representation. When this occurs, the value may become a very small or negative number.

How developers prevent this class of flaw

  • Ensure that all protocols are strictly defined, such that all out-of-bounds behavior can be identified simply, and require strict conformance to the protocol.
  • Use a language that does not allow this weakness to occur or provides constructs that make this weakness easier to avoid. If possible, choose a language or compiler that performs automatic bounds checking.
  • Use a vetted library or framework that does not allow this weakness to occur or provides constructs that make this weakness easier to avoid. Use libraries or frameworks that make it easier to handle numbers without unexpected consequences. Examples include safe integer handling packages such as SafeInt (C++) or IntegerLib (C or C++).

More Integer Overflow or Wraparound vulnerabilities (CWE-190)

Timeline

  1. CVE record published.
  2. CISA published its SSVC assessment (exploitation: poc, 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 Integer Overflow or Wraparound vulnerabilities

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