7.5
CVE-2022-23591
- EPSS 0.34%
- Published 04.02.2022 23:15:15
- Last modified 21.11.2024 06:48:52
- Source security-advisories@github.com
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Tensorflow is an Open Source Machine Learning Framework. The `GraphDef` format in TensorFlow does not allow self recursive functions. The runtime assumes that this invariant is satisfied. However, a `GraphDef` containing a fragment such as the following can be consumed when loading a `SavedModel`. This would result in a stack overflow during execution as resolving each `NodeDef` means resolving the function itself and its nodes. 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.
Data is provided by the National Vulnerability Database (NVD)
Google ≫ Tensorflow Version <= 2.5.2
Google ≫ Tensorflow Version >= 2.6.0 <= 2.6.2
Google ≫ Tensorflow Version2.7.0
Zu dieser CVE wurde keine CISA KEV oder CERT.AT-Warnung gefunden.
| Type | Source | Score | Percentile |
|---|---|---|---|
| EPSS | FIRST.org | 0.34% | 0.556 |
| Source | Base Score | Exploit Score | Impact Score | Vector string |
|---|---|---|---|---|
| nvd@nist.gov | 7.5 | 3.9 | 3.6 |
CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H
|
| nvd@nist.gov | 5 | 10 | 2.9 |
AV:N/AC:L/Au:N/C:N/I:N/A:P
|
| security-advisories@github.com | 7.5 | 3.9 | 3.6 |
CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H
|
CWE-400 Uncontrolled Resource Consumption
The product does not properly control the allocation and maintenance of a limited resource, thereby enabling an actor to influence the amount of resources consumed, eventually leading to the exhaustion of available resources.
CWE-674 Uncontrolled Recursion
The product does not properly control the amount of recursion that takes place, consuming excessive resources, such as allocated memory or the program stack.