VDB-302050 · Submit #524212 · CVE-2025-3001

PyTorch 2.6.0 torch.lstm_cell memory corruption

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.
4.8	$0-$5k	0.00

Summaryinfo

A vulnerability classified as critical was found in PyTorch 2.6.0. Affected by this issue is the function torch.lstm_cell. Executing a manipulation can lead to memory corruption. This vulnerability is registered as CVE-2025-3001. The attack needs to be launched locally. Furthermore, an exploit is available.

Detailsinfo

A vulnerability classified as critical was found in PyTorch 2.6.0. This vulnerability affects the function torch.lstm_cell. The manipulation with an unknown input leads to a memory corruption vulnerability. The CWE definition for the vulnerability is CWE-119. The product performs operations on a memory buffer, but it can read from or write to a memory location that is outside of the intended boundary of the buffer. As an impact it is known to affect confidentiality, integrity, and availability.

The advisory is available at github.com. This vulnerability was named CVE-2025-3001. The exploitation appears to be easy. Local access is required to approach this attack. Technical details and also a public exploit are known.

It is possible to download the exploit 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.

If you want to get best quality of vulnerability data, you may have to visit VulDB.

Productinfo

Name

PyTorch

Version

2.6.0

Website

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

CPE 2.3info

CPE 2.2info

CVSSv4info

VulDB Vector: 🔍
VulDB Reliability: 🔍

CVSSv3info

VulDB Meta Base Score: 5.3
VulDB Meta Temp Score: 4.8

VulDB Base Score: 5.3
VulDB Temp Score: 4.8
VulDB Vector: 🔍
VulDB Reliability: 🔍

CVSSv2info

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

Exploitinginfo

Class: Memory corruption
CWE: CWE-119
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
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Threat Intelligenceinfo

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

Countermeasuresinfo

Recommended: no mitigation known
Status: 🔍

0-Day Time: 🔍

Timelineinfo

03/30/2025 🔍
03/30/2025 +0 days 🔍
03/30/2025 +0 days 🔍

Sourcesinfo

Product: github.com

Advisory: 149626
Status: Not defined

CVE: CVE-2025-3001 (🔍)
GCVE (CVE): GCVE-0-2025-3001
GCVE (VulDB): GCVE-100-302050
scip Labs: https://www.scip.ch/en/?labs.20161013

Entryinfo

Created: 03/30/2025 19:47
Changes: 03/30/2025 19:47 (54)
Complete: 🔍
Submitter: Default436352
Cache ID: 216::103

Submitinfo

Accepted

Submit #524212: pytorch pytorch (in torch.lstm_cell) torch 2.6.0 Segmentation Fault (by Default436352)