CVE-2022-35967 Vulnerability Details

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CVE-2022-35967 Metadata Quick Info

CVE Published: 16/09/2022 | CVE Updated: 03/08/2024 | CVE Year: 2022
Source: GitHub_M | Vendor: tensorflow | Product: tensorflow
Status : PUBLISHED

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CVE-2022-35967 Description

TensorFlow is an open source platform for machine learning. If `QuantizedAdd` is given `min_input` or `max_input` tensors of a nonzero rank, it results in a segfault that can be used to trigger a denial of service attack. We have patched the issue in GitHub commit 49b3824d83af706df0ad07e4e677d88659756d89. The fix will be included in TensorFlow 2.10.0. We will also cherrypick this commit on TensorFlow 2.9.1, TensorFlow 2.8.1, and TensorFlow 2.7.2, as these are also affected and still in supported range. There are no known workarounds for this issue.

Metrics

CVSS Version: 3.1 | Base Score: 5.9 MEDIUM
Vector: CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:N/I:N/A:H

l➤ Exploitability Metrics:
    Attack Vector (AV)* NETWORK
    Attack Complexity (AC)* HIGH
    Privileges Required (PR)* NONE
    User Interaction (UI)* NONE
    Scope (S)* UNCHANGED

l➤ Impact Metrics:
    Confidentiality Impact (C)* NONE
    Integrity Impact (I)* NONE
    Availability Impact (A)* HIGH

Weakness Enumeration (CWE)

CWE-ID: CWE-20
CWE Name: CWE-20: Improper Input Validation
Source: tensorflow

Common Attack Pattern Enumeration and Classification (CAPEC)

CAPEC-ID:
CAPEC Description:


Source: NVD (National Vulnerability Database).