6.3
CVE-2020-15197
- EPSS 0.22%
- Published 25.09.2020 19:15:14
- Last modified 21.11.2024 05:05:03
- Source security-advisories@github.com
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In Tensorflow before version 2.3.1, the `SparseCountSparseOutput` implementation does not validate that the input arguments form a valid sparse tensor. In particular, there is no validation that the `indices` tensor has rank 2. This tensor must be a matrix because code assumes its elements are accessed as elements of a matrix. However, malicious users can pass in tensors of different rank, resulting in a `CHECK` assertion failure and a crash. This can be used to cause denial of service in serving installations, if users are allowed to control the components of the input sparse tensor. The issue is patched in commit 3cbb917b4714766030b28eba9fb41bb97ce9ee02 and is released in TensorFlow version 2.3.1.
Data is provided by the National Vulnerability Database (NVD)
Google ≫ Tensorflow Version2.3.0 SwEdition-
Zu dieser CVE wurde keine CISA KEV oder CERT.AT-Warnung gefunden.
| Type | Source | Score | Percentile |
|---|---|---|---|
| EPSS | FIRST.org | 0.22% | 0.416 |
| Source | Base Score | Exploit Score | Impact Score | Vector string |
|---|---|---|---|---|
| nvd@nist.gov | 6.3 | 1.8 | 4 |
CVSS:3.1/AV:N/AC:H/PR:L/UI:N/S:C/C:N/I:N/A:H
|
| nvd@nist.gov | 3.5 | 6.8 | 2.9 |
AV:N/AC:M/Au:S/C:N/I:N/A:P
|
| security-advisories@github.com | 6.3 | 1.8 | 4 |
CVSS:3.1/AV:N/AC:H/PR:L/UI:N/S:C/C:N/I:N/A:H
|
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-617 Reachable Assertion
The product contains an assert() or similar statement that can be triggered by an attacker, which leads to an application exit or other behavior that is more severe than necessary.