Tensorflow: Out-of-bounds Read
CVE-2022-21726 is a high-severity out-of-bounds read vulnerability in Tensorflow from Google, 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: 2.5.2 and earlier; 2.6.0 through 2.6.2; 2.7.0. The record does not name a fixed version, so check the vendor advisory. There is no confirmed exploitation so far. EPSS estimates a 0.83% chance of exploitation within 30 days, higher than 58% 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 | 2.5.2 and earlier; 2.6.0 through 2.6.2; 2.7.0 | Not stated |
Version data comes from NVD's product matching. 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 | 8.1 | 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. The implementation of `Dequantize` does not fully validate the value of `axis` and can result in heap OOB accesses. The `axis` argument can be `-1` (the default value for the optional argument) or any other positive value at most the number of dimensions of the input. Unfortunately, the upper bound is not checked and this results in reading past the end of the array containing the dimensions of the input tensor. 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: 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: partial).
- Record last changed materially (score, affected products, status or references).
References
Advisories
- github.com/tensorflow/tensorflow/security/advisories/GHSA-23hm-7w47-xw72Third Party Advisory
Patches and release notes
- github.com/tensorflow/tensorflow/commit/23968a8bf65b009120c43b5ebcceaf52dbc9e943Third Party Advisory
Technical write-ups (may include proof of concept)
- github.com/tensorflow/tensorflow/blob/5100e359aef5c8021f2e71c7b986420b85ce7b3d/tensorflow/core/kernels/dequan…Exploit, Third Party Advisory
Other vulnerabilities in Tensorflow
- 7.5 High severity
- 8.8 High severity
- 8.1 High severity
- 8.1 High severity
- 8.8 High severity
Recent Out-of-bounds Read vulnerabilities
- 7.8 High severity
- 9.1 Critical severity
- 9.1 Critical severity
- 9.1 Critical severity
- 7.1 High severity
- 7.5 High severity
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