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CVE-2025-32381


XGrammar is an open-source library for efficient, flexible, and portable structured generation. Prior to 0.1.18, Xgrammar includes a cache for compiled grammars to increase performance with repeated use of the same grammar. This cache is held in memory. Since the cache is unbounded, a system making use of xgrammar can be abused to fill up a host's memory and case a denial of service. For example, sending many small requests to an LLM inference server with unique JSON schemas would eventually cause this denial of service to occur. This vulnerability is fixed in 0.1.18.


Security Impact Summary

This vulnerability carries a MEDIUM severity rating with a CVSS v3.1 score of 6.5, indicating it can be exploited remotely over the network with relatively low complexity without requiring user interaction requiring only low-level privileges . The vulnerability impacts and availability (service disruption) for affected systems. Impacting 1 product from mlc-ai organizations running these solutions should prioritize assessment and patching.

Historical Context

Reported in 2025, this vulnerability emerged during an era marked by increased sophistication in supply chain attacks, cloud infrastructure vulnerabilities, and software-as-a-service (SaaS) security challenges. Security practices during this period emphasized zero-trust architectures, container security, and API protection.


Published

2025-04-09T16:15:26.210

Last Modified

2025-09-17T18:14:55.287

Status

Analyzed

Source

[email protected]

Severity

CVSSv3.1: 6.5 (MEDIUM)

Weaknesses
  • Type: Secondary
    CWE-770

Affected Vendors & Products
Type Vendor Product Version/Range Vulnerable?
Application mlc-ai xgrammar < 0.1.18 Yes

References

How SecUtils Interprets This CVE

SecUtils normalizes and enriches National Vulnerability Database (NVD) records by standardizing vendor and product identifiers, aggregating vulnerability metadata from both NVD and MITRE sources, and providing structured context for security teams. For mlc-ai's affected products, we extract Common Platform Enumeration (CPE) data, Common Weakness Enumeration (CWE) classifications, CVSS severity metrics, and reference data to enable rapid vulnerability prioritization and asset correlation. This record contains no exploit code, proof-of-concept instructions, or attack methodologies—only defensive intelligence necessary for patch management, risk assessment, and security operations.