tensorflow: Out-of-bounds Read
CVE-2022-23560 is a high-severity out-of-bounds read 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 0.84% chance of exploitation within 30 days, higher than 59% of scored 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.
Affected products and versions
| Vendor | Product | Affected versions | Fixed in |
|---|---|---|---|
| TensorFlow | tensorflow | >= 2.7.0, < 2.7.1; >= 2.6.0, < 2.6.3; < 2.5.3 | 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
- 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 system | Score | Severity | Scored by |
|---|---|---|---|
| CVSS 3.1 | 8.8 | High | CNA (github.com) |
| CVSS 3.1 | 8.8 | High | NVD |
| CVSS 2.0 | 6.5 | Medium | NVD |
Official description
Tensorflow is an Open Source Machine Learning Framework. An attacker can craft a TFLite model that would allow limited reads and writes outside of arrays in TFLite. This exploits missing validation in the conversion from sparse tensors to dense tensors. The fix is 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. Users are advised to upgrade as soon as possible.
Source: the CVE record as published by its numbering authority, via NVD and CVE.org.
The underlying weakness: Out-of-bounds Read
The product reads data past the end, or before the beginning, of the intended buffer.
How developers prevent this class of flaw
- Use a language that provides appropriate memory abstractions.
Timeline
- CVE record published.
- CISA published its SSVC assessment (exploitation: poc, automatable: no, technical impact: total).
- Record last changed materially (score, affected products, status or references).
References
Advisories
- github.com/tensorflow/tensorflow/security/advisories/GHSA-4hvf-hxvg-f67vThird Party Advisory
Patches and release notes
- github.com/tensorflow/tensorflow/commit/6364463d6f5b6254cac3d6aedf999b6a96225038Third Party Advisory
Technical write-ups (may include proof of concept)
- github.com/tensorflow/tensorflow/blob/ca6f96b62ad84207fbec580404eaa7dd7403a550/tensorflow/lite/kernels/intern…Exploit, Third 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 Out-of-bounds Read vulnerabilities
- 7.1 High severity
- 8.1 High severity
- 8.8 High severity
- 8.1 High severity
- 8.1 High severity
- 8.8 High severity
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