CVE intelligence and bounded remediation

CVE-2025-30202 — vLLM is a high-throughput and memory-efficient inference and serving engine for LLMs

High CVSS 7.5

vLLM is a high-throughput and memory-efficient inference and serving engine for LLMs. Versions starting from 0.5.2 and prior to 0.8.5 are vulnerable to denial of service and data exposure via ZeroMQ on multi-node vLLM deployment. In a multi-node vLLM deployment, vLLM uses ZeroMQ for some multi-node communication purposes. The primary vLLM host opens an XPUB ZeroMQ socket and binds it to ALL interfaces. While the socket is always opened for a multi-node deployment, it is only used when doing tensor parallelism across multiple hosts. Any client with network access to this host can connect to this XPUB socket unless its port is blocked by a firewall. Once connected, these arbitrary clients will receive all of the same data broadcasted to all of the secondary vLLM hosts. This data is internal vLLM state information that is not useful to an attacker. By potentially connecting to this socket many times and not reading data published to them, an attacker can also cause a denial of service by slowing down or potentially blocking the publisher. This issue has been patched in version 0.8.5.

Severity
High
CVSS
7.5 (3.1)
Published
2025-04-30
CISA KEV
Not currently listed
Ecosystem
software/application
Weaknesses
CWE-770

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

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