tensorflow: Incorrect Comparison
CVE-2023-25673 is a high-severity incorrect comparison 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: < 2.11.1. The record does not name a fixed version, so check the vendor advisory. There is no confirmed exploitation so far. EPSS estimates a 0.39% chance of exploitation within 30 days, which is low compared with other CVEs.
High severity with no evidence of exploitation so far.
What to do
- Check which version of tensorflow you run against the affected versions below, and install the vendor's latest release.
- Read the advisory on github.com for workarounds and exact fixed builds.
- Until you can update, restrict network access to the affected service so it is not reachable from untrusted networks.
Affected products and versions
| Vendor | Product | Affected versions | Fixed in |
|---|---|---|---|
| TensorFlow | tensorflow | < 2.11.1 | Not 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 system | Score | Severity | Scored by |
|---|---|---|---|
| CVSS 3.1 | 7.5 | High | CNA (github.com) |
| CVSS 3.1 | 7.5 | High | NVD |
Official description
TensorFlow is an open source platform for machine learning. Versions prior to 2.12.0 and 2.11.1 have a Floating Point Exception in TensorListSplit with XLA. A fix is included in TensorFlow version 2.12.0 and version 2.11.1.
Source: the CVE record as published by its numbering authority, via NVD and CVE.org.
The underlying weakness: Incorrect Comparison
The product compares two entities in a security-relevant context, but the comparison is incorrect.
Timeline
- CVE record published.
- CISA published its SSVC assessment (exploitation: none, automatable: yes, technical impact: partial).
- Record last changed materially (score, affected products, status or references).
References
Patches and release notes
Other vulnerabilities in tensorflow
- 7.8 High severity
- 7.5 High severity
- 9.8 Critical severity
- 7.5 High severity
- 7.8 High severity
- 7.5 High severity
Recent Incorrect Comparison vulnerabilities
- 7.5 High severity
- 7.5 High severity
- 7.5 High severity
- 7.5 High severity
- 8.8 High severity
- 7.5 High severity
Unraid Authentication Bypass Exploited
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