CVE-2023-25661 Vulnerability Details

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CVE-2023-25661 Metadata Quick Info

CVE Published: 27/03/2023 | CVE Updated: 02/08/2024 | CVE Year: 2023
Source: GitHub_M | Vendor: tensorflow | Product: tensorflow
Status : PUBLISHED

CVE-2023-25661 Description

TensorFlow is an Open Source Machine Learning Framework. In versions prior to 2.11.1 a malicious invalid input crashes a tensorflow model (Check Failed) and can be used to trigger a denial of service attack. A proof of concept can be constructed with the `Convolution3DTranspose` function. This Convolution3DTranspose layer is a very common API in modern neural networks. The ML models containing such vulnerable components could be deployed in ML applications or as cloud services. This failure could be potentially used to trigger a denial of service attack on ML cloud services. An attacker must have privilege to provide input to a `Convolution3DTranspose` call. This issue has been patched and users are advised to upgrade to version 2.11.1. There are no known workarounds for this vulnerability.

Metrics

CVSS Version: 3.1 | Base Score: 6.5 MEDIUM
Vector: CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H

l➤ Exploitability Metrics:
    Attack Vector (AV)* NETWORK
    Attack Complexity (AC)* LOW
    Privileges Required (PR)* LOW
    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).