Description
vLLM is an inference and serving engine for large language models. Prior to 0.26.0, the /v1/completions/derender and /v1/chat/completions/derender endpoints accept caller-supplied GenerateResponse objects whose generate_responses, choices, token_ids, prompt_logprobs, logprobs.content, top_logprobs, and routed_experts structures are processed by OnlineDerenderer and tokenizer.decode before max_model_len, max_tokens, max_num_seqs, or response-size limits are enforced, allowing an authenticated API client to consume excessive CPU and memory and produce oversized responses. This issue is fixed in version 0.26.0.
Published: 2026-08-17
Score: 4.3 Medium
EPSS: n/a
KEV: No
Impact: n/a
Action: n/a
AI Analysis

Impact

The vulnerability allows an authenticated API client to send GenerateResponse objects that are decoded without enforcing maximum response size or token limits. This permits the client to cause the server to consume excessive CPU and memory, resulting in large or unlimited responses, which can lead to denial of service or resource exhaustion.

Affected Systems

The issue affects the vllm-project vllm inference engine before version 0.26.0. All releases prior to 0.26.0 are vulnerable; later releases contain the fix.

Risk and Exploitability

The CVSS score of 4.3 denotes a moderate severity. The EPSS score is not available and the vulnerability is not listed in the CISA KEV catalog, suggesting a lower immediate exploitation risk. However, because the flaw is triggered only by an authenticated user sending a specially crafted request to the derender endpoints, the attack requires valid credentials. The lack of output size checks means an attacker can drain server resources and potentially disrupt service availability within a single authenticated session.

Generated by OpenCVE AI on August 17, 2026 at 21:37 UTC.

Remediation

No vendor fix or workaround currently provided.

OpenCVE Recommended Actions

  • Upgrade the vllm engine to version 0.26.0 or later.
  • Disable or restrict the /v1/completions/derender and /v1/chat/completions/derender endpoints for unauthenticated or non‑critical traffic.
  • Monitor CPU and memory usage of the inference service and enforce overall limits at the infrastructure level.

Generated by OpenCVE AI on August 17, 2026 at 21:37 UTC.

Tracking

Sign in to view the affected projects.

Advisories

No advisories yet.

History

Mon, 17 Aug 2026 22:00:00 +0000

Type Values Removed Values Added
First Time appeared Vllm-project
Vllm-project vllm
Vendors & Products Vllm-project
Vllm-project vllm

Mon, 17 Aug 2026 20:15:00 +0000

Type Values Removed Values Added
Description vLLM is an inference and serving engine for large language models. Prior to 0.26.0, the /v1/completions/derender and /v1/chat/completions/derender endpoints accept caller-supplied GenerateResponse objects whose generate_responses, choices, token_ids, prompt_logprobs, logprobs.content, top_logprobs, and routed_experts structures are processed by OnlineDerenderer and tokenizer.decode before max_model_len, max_tokens, max_num_seqs, or response-size limits are enforced, allowing an authenticated API client to consume excessive CPU and memory and produce oversized responses. This issue is fixed in version 0.26.0.
Title vLLM: Derender endpoints decode caller-supplied GenerateResponse token IDs without output bounds
Weaknesses CWE-400
CWE-770
References
Metrics cvssV3_1

{'score': 4.3, 'vector': 'CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:L'}


Subscriptions

Vllm-project Vllm
cve-icon MITRE

Status: PUBLISHED

Assigner: GitHub_M

Published:

Updated: 2026-08-17T20:13:06.289Z

Reserved: 2026-08-06T19:56:23.725Z

Link: CVE-2026-71486

cve-icon Vulnrichment

No data.

cve-icon NVD

Status : Received

Published: 2026-08-17T20:16:45.927

Modified: 2026-08-17T20:16:45.927

Link: CVE-2026-71486

cve-icon Redhat

No data.

cve-icon OpenCVE Enrichment

Updated: 2026-08-17T21:45:03Z

Weaknesses
  • CWE-400

    Uncontrolled Resource Consumption

  • CWE-770

    Allocation of Resources Without Limits or Throttling