VDB-299060 · Submit #506563 · CVE-2025-2149

PyTorch 2.6.0+cu124 Quantized Sigmoid nnq_Sigmoid scale/zero_point initialization

CVSS Meta Temp Score CVSS is a standardized scoring system to determine possibilities of attacks. The Temp Score considers temporal factors like disclosure, exploit and countermeasures. The unique Meta Score calculates the average score of different sources to provide a normalized scoring system.	Current Exploit Price (≈) Our analysts are monitoring exploit markets and are in contact with vulnerability brokers. The range indicates the observed or calculated exploit price to be seen on exploit markets. A good indicator to understand the monetary effort required for and the popularity of an attack.	CTI Interest Score Our Cyber Threat Intelligence team is monitoring different web sites, mailing lists, exploit markets and social media networks. The CTI Interest Score identifies the interest of attackers and the security community for this specific vulnerability in real-time. A high score indicates an elevated risk to be targeted for this vulnerability.
2.4	$0-$5k	0.00

Summaryinfo

A vulnerability was found in PyTorch 2.6.0+cu124. It has been declared as problematic. This vulnerability affects the function nnq_Sigmoid of the component Quantized Sigmoid Module. Such manipulation of the argument scale/zero_point leads to initialization. This vulnerability is referenced as CVE-2025-2149. The attack can only be performed from a local environment. Furthermore, an exploit is available.

Detailsinfo

A vulnerability was found in PyTorch 2.6.0+cu124. It has been rated as problematic. Affected by this issue is the function nnq_Sigmoid of the component Quantized Sigmoid Module. The manipulation of the argument scale/zero_point with an unknown input leads to a initialization vulnerability. Using CWE to declare the problem leads to CWE-665. The product does not initialize or incorrectly initializes a resource, which might leave the resource in an unexpected state when it is accessed or used. Impacted is integrity.

The advisory is shared for download at github.com. This vulnerability is handled as CVE-2025-2149. The exploitation is known to be difficult. The attack needs to be approached locally. Technical details as well as a public exploit are known.

The exploit is available at github.com. It is declared as proof-of-concept.

There is no information about possible countermeasures known. It may be suggested to replace the affected object with an alternative product.

Once again VulDB remains the best source for vulnerability data.

Productinfo

Name

PyTorch

Version

2.6.0+cu124

Website

Product: https://github.com/pytorch/pytorch/

CPE 2.3info

CPE 2.2info

CVSSv4info

VulDB Vector: 🔍
VulDB Reliability: 🔍

CNA CVSS-B Score: 🔍
CNA CVSS-BT Score: 🔍
CNA Vector: 🔍

CVSSv3info

VulDB Meta Base Score: 2.5
VulDB Meta Temp Score: 2.4

VulDB Base Score: 2.5
VulDB Temp Score: 2.3
VulDB Vector: 🔍
VulDB Reliability: 🔍

CNA Base Score: 2.5
CNA Vector: 🔍

CVSSv2info

AV	AC	Au	C	I	A
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💳	💳	💳	💳	💳	💳
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Vector	Complexity	Authentication	Confidentiality	Integrity	Availability
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VulDB Base Score: 🔍
VulDB Temp Score: 🔍
VulDB Reliability: 🔍

Exploitinginfo

Class: Initialization
CWE: CWE-665
CAPEC: 🔍
ATT&CK: 🔍

Physical: Partially
Local: Yes
Remote: No

Availability: 🔍
Access: Public
Status: Proof-of-Concept
Download: 🔍

EPSS Score: 🔍
EPSS Percentile: 🔍

Price Prediction: 🔍
Current Price Estimation: 🔍

0-Day	Unlock	Unlock	Unlock	Unlock
Today	Unlock	Unlock	Unlock	Unlock

Threat Intelligenceinfo

Interest: 🔍
Active Actors: 🔍
Active APT Groups: 🔍

Countermeasuresinfo

Recommended: no mitigation known
Status: 🔍

0-Day Time: 🔍

Timelineinfo

03/10/2025 🔍
03/10/2025 +0 days 🔍
06/23/2025 +105 days 🔍

Sourcesinfo

Product: github.com

Advisory: 147818
Status: Not defined

CVE: CVE-2025-2149 (🔍)
GCVE (CVE): GCVE-0-2025-2149
GCVE (VulDB): GCVE-100-299060
scip Labs: https://www.scip.ch/en/?labs.20161013

Entryinfo

Created: 03/10/2025 07:19
Updated: 06/23/2025 21:41
Changes: 03/10/2025 07:19 (56), 03/10/2025 14:28 (30), 06/23/2025 21:41 (1)
Complete: 🔍
Submitter: Default436352
Cache ID: 216::103

Submitinfo

Accepted

Submit #506563: pytorch 2.6.0+cu124 Inconsistency Between Implementation and Documented Design (by Default436352)