tensorflow: Always-Incorrect Control Flow Implementation
CVE-2022-41884 is a high-severity always-incorrect control flow implementation 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: >= 2.10.0, < 2.10.1; >= 2.9.0, < 2.9.3; < 2.8.4. The record does not name a fixed version, so check the vendor advisory. There is no confirmed exploitation so far. EPSS estimates a 0.37% 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 | >= 2.10.0, < 2.10.1; >= 2.9.0, < 2.9.3; < 2.8.4 | 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 | 4.8 | Medium | CNA (github.com) |
| CVSS 3.1 | 7.5 | High | NVD |
Official description
TensorFlow is an open source platform for machine learning. If a numpy array is created with a shape such that one element is zero and the others sum to a large number, an error will be raised. We have patched the issue in GitHub commit 2b56169c16e375c521a3bc8ea658811cc0793784. The fix will be included in TensorFlow 2.11. We will also cherrypick this commit on TensorFlow 2.10.1, 2.9.3, and TensorFlow 2.8.4, 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: Always-Incorrect Control Flow Implementation
The code contains a control flow path that does not reflect the algorithm that the path is intended to implement, leading to incorrect behavior any time this path is navigated.
More Always-Incorrect Control Flow Implementation vulnerabilities (CWE-670)
Timeline
- CVE record published.
- CISA published its SSVC assessment (exploitation: poc, automatable: no, technical impact: partial).
- Record last changed materially (score, affected products, status or references).
References
Advisories
- github.com/tensorflow/tensorflow/security/advisories/GHSA-jq6x-99hj-q636Exploit, Third Party Advisory
Patches and release notes
- github.com/tensorflow/tensorflow/commit/2b56169c16e375c521a3bc8ea658811cc0793784Third Party Advisory
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 Always-Incorrect Control Flow Implementation vulnerabilities
- 7.5 High severity
- 7.5 High severity
- 7.5 High severity
- 7.5 High severity
- 7.5 High severity
- 7.5 High severity
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