CVE-2025-67729

Published: Dic 26, 2025 Last Modified: Dic 31, 2025
ExploitDB:
Other exploit source:
Google Dorks:
HIGH 8,8
Attack Vector: network
Attack Complexity: low
Privileges Required: none
User Interaction: required
Scope: unchanged
Confidentiality: high
Integrity: high
Availability: high

Description

AI Translation Available

LMDeploy is a toolkit for compressing, deploying, and serving LLMs. Prior to version 0.11.1, an insecure deserialization vulnerability exists in lmdeploy where torch.load() is called without the weights_only=True parameter when loading model checkpoint files. This allows an attacker to execute arbitrary code on the victim's machine when they load a malicious .bin or .pt model file. This issue has been patched in version 0.11.1.

EPSS (Exploit Prediction Scoring System)

Trend Analysis

EPSS (Exploit Prediction Scoring System)

Prevede la probabilità di sfruttamento basata su intelligence sulle minacce e sulle caratteristiche della vulnerabilità.

EPSS Score
0,0011
Percentile
0,3th
Updated

EPSS Score Trend (Last 79 Days)

502

Deserialization of Untrusted Data

Draft
Common Consequences
Security Scopes Affected:
Integrity Availability Other
Potential Impacts:
Modify Application Data Unexpected State Dos: Resource Consumption (Cpu) Varies By Context
Applicable Platforms
Languages: Java, JavaScript, PHP, Python, Ruby
Technologies: AI/ML, ICS/OT, Not Technology-Specific
View CWE Details
Application

Lmdeploy by Internlm

Version Range Affected
To 0.11.1 (exclusive)
cpe:2.3:a:internlm:lmdeploy:*:*:*:*:*:*:*:*
Common Platform Enumeration - Standardized vulnerability identification
https://github.com/InternLM/lmdeploy/security/advisories/GHSA-9pf3-7rrr-x5jh
https://github.com/InternLM/lmdeploy/commit/eb04b4281c5784a5cff5ea639c8f96b33b3…
https://github.com/InternLM/lmdeploy/security/advisories/GHSA-9pf3-7rrr-x5jh