CVE intelligence and bounded remediation

CVE-2025-48943 — vLLM is an inference and serving engine for large language models (LLMs)

Medium CVSS 6.5

vLLM is an inference and serving engine for large language models (LLMs). Version 0.8.0 up to but excluding 0.9.0 have a Denial of Service (ReDoS) that causes the vLLM server to crash if an invalid regex was provided while using structured output. This vulnerability is similar to GHSA-6qc9-v4r8-22xg/CVE-2025-48942, but for regex instead of a JSON schema. Version 0.9.0 fixes the issue.

Severity
Medium
CVSS
6.5 (3.1)
Published
2025-05-30
CISA KEV
Not currently listed
Ecosystem
software/application
Weaknesses
CWE-248

Affected products

  • vllm / vllm

Matched remediation archetype

Resource exhaustion and denial of service

This catalog composition supplies bounded fallback guidance. Explicitly reviewed curated workflows load with the complete record below.

Check exposure

  • Identify attacker-influenced work factors including input size, nesting, compression, fan-out, regex cost, allocation, recursion, retries, and connection lifetime.
  • Map per-request and shared CPU, memory, disk, descriptor, thread, queue, and downstream-service limits.
  • Determine whether authentication, tenancy, quotas, and rate controls apply before expensive processing begins.

Remediate safely

  • Bound input size, nesting, expansion, work, concurrency, queue depth, retries, and execution time before resource-intensive processing.
  • Release resources on every success, error, cancellation, and timeout path and use backpressure instead of unbounded buffering.
  • Update affected components and add small deterministic tests that assert resource ceilings rather than exhausting a host.

Authoritative sources

Complete CVE record and remediation plan

The detailed catalog view below loads this exact record, its source evidence, and the full seven-phase agentic change plan.