5.5
CVE-2022-29202
- EPSS 0.05%
- Veröffentlicht 20.05.2022 23:15:44
- Zuletzt bearbeitet 21.11.2024 06:58:42
- Quelle security-advisories@github.com
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TensorFlow is an open source platform for machine learning. Prior to versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4, the implementation of `tf.ragged.constant` does not fully validate the input arguments. This results in a denial of service by consuming all available memory. Versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4 contain a patch for this issue.
Daten sind bereitgestellt durch National Vulnerability Database (NVD)
Google ≫ Tensorflow Version < 2.6.4
Google ≫ Tensorflow Version >= 2.7.0 < 2.7.2
Google ≫ Tensorflow Version2.7.0 Updaterc0
Google ≫ Tensorflow Version2.7.0 Updaterc1
Google ≫ Tensorflow Version2.8.0 Update-
Google ≫ Tensorflow Version2.8.0 Updaterc0
Google ≫ Tensorflow Version2.8.0 Updaterc1
Google ≫ Tensorflow Version2.9.0 Updaterc0
Google ≫ Tensorflow Version2.9.0 Updaterc1
Zu dieser CVE wurde keine CISA KEV oder CERT.AT-Warnung gefunden.
| Typ | Quelle | Score | Percentile |
|---|---|---|---|
| EPSS | FIRST.org | 0.05% | 0.156 |
| Quelle | Base Score | Exploit Score | Impact Score | Vector String |
|---|---|---|---|---|
| nvd@nist.gov | 5.5 | 1.8 | 3.6 |
CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H
|
| nvd@nist.gov | 2.1 | 3.9 | 2.9 |
AV:L/AC:L/Au:N/C:N/I:N/A:P
|
| security-advisories@github.com | 5.5 | 1.8 | 3.6 |
CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H
|
CWE-1284 Improper Validation of Specified Quantity in Input
The product receives input that is expected to specify a quantity (such as size or length), but it does not validate or incorrectly validates that the quantity has the required properties.
CWE-20 Improper Input Validation
The product receives input or data, but it does not validate or incorrectly validates that the input has the properties that are required to process the data safely and correctly.
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.