Vulnerability-Lookup

GHSA-X567-49G5-P4CF

Vulnerability from github – Published: 2026-10-28 21:14 – Updated: 2026-10-28 21:14

Summary

vLLM: Responses API bypasses trust_request_chat_template for chat_template_kwargs

Details

Summary

vLLM's /v1/responses endpoint accepts request-level chat_template_kwargs, but does not apply the --trust-request-chat-template gate that protects Chat Completions, render, tokenize, and pooling paths.

When the server is run with the documented default trust_request_chat_template=False and no explicit --chat-template, a Responses request can pass:

{"chat_template_kwargs": {"chat_template": "<attacker Jinja template>"}}

That key is preserved by ChatParams.get_apply_chat_template_kwargs() and then bound as the chat_template parameter to the shared HF renderer. Prior vLLM advisories establish that request-controlled Jinja chat templates can cause CPU/memory exhaustion. This report covers the current-head Responses sibling path missed by the earlier fixes.

Technical Details

The shared OpenAI frontend has a validation helper that rejects request-supplied chat templates unless the trust flag is enabled. It explicitly checks both top-level chat_template and chat_template_kwargs["chat_template"].

Responses is a separate serving path:

vllm/entrypoints/openai/responses/protocol.py exposes chat_template_kwargs.
ResponsesRequest.build_chat_params() merges request kwargs.
OpenAIServingResponses._effective_chat_template_kwargs() uses those kwargs.
ChatParams.get_apply_chat_template_kwargs() preserves a request chat_template key when the server chat template is None.
vllm/renderers/hf.py unpacks the result into safe_apply_chat_template.

There is no equivalent trust gate in vllm/entrypoints/openai/responses/serving.py.

Impact

An authenticated caller who can submit /v1/responses requests can supply a request-controlled Jinja chat template despite the trust flag being disabled. The expected fixed behavior is the same as Chat Completions: reject chat_template_kwargs["chat_template"] unless the server was started with --trust-request-chat-template.

Suggested Fix

Add trust_request_chat_template to OpenAIServingResponses.
Pass args.trust_request_chat_template when constructing the Responses serving object.
Reject request.chat_template_kwargs["chat_template"] before rendering when trust is false.
Keep ordinary kwargs such as enable_thinking working.
Add regression tests for default-deny and opt-in-allow behavior on /v1/responses.

Affected Package/Versions

Source sweep found the affected shape in:

v0.16.0
v0.18.0
v0.20.0
v0.21.0
v0.22.0
v0.22.1
v0.23.0
current checkout 470229c37efaf69c86e8bc97482b0b1ff7551c65
current origin/main b3f0a0a0df76dda92ec4b2c9335f77e84adad911

Suggested affected range:

>= 0.16.0, <= 0.23.0

Appendix: Duplicate Research

This is related to, but distinct from:

GHSA-6fvq-23cw-5628 / CVE-2025-61620
GHSA-69j4-grxj-j64p / CVE-2025-62426

Those advisories establish the security impact of request-controlled Jinja templates and chat_template_kwargs, but they cover older Chat Completions/tokenize implementations. This report covers a current /v1/responses sibling path that still lacks the trust gate.

Local prior submissions this report..029 do not cover this root cause.

This advisory was fixed in MR50300.

Severity

6.5 (Medium)


                  
                    CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H

Show details on source website

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{
  "affected": [
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "vllm"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "0.16.0"
            },
            {
              "fixed": "0.32.0"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ]
    }
  ],
  "aliases": [
    "CVE-2026-115918"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-400",
      "CWE-770"
    ],
    "github_reviewed": true,
    "github_reviewed_at": "2026-10-28T21:14:59Z",
    "nvd_published_at": "2026-10-26T18:17:39Z",
    "severity": "MODERATE"
  },
  "details": "## Summary\n\nvLLM\u0027s `/v1/responses` endpoint accepts request-level `chat_template_kwargs`, but does not apply the `--trust-request-chat-template` gate that protects Chat Completions, render, tokenize, and pooling paths.\n\nWhen the server is run with the documented default `trust_request_chat_template=False` and no explicit `--chat-template`, a Responses request can pass:\n\n```json\n{\"chat_template_kwargs\": {\"chat_template\": \"\u003cattacker Jinja template\u003e\"}}\n```\n\nThat key is preserved by `ChatParams.get_apply_chat_template_kwargs()` and then bound as the `chat_template` parameter to the shared HF renderer. Prior vLLM advisories establish that request-controlled Jinja chat templates can cause CPU/memory exhaustion. This report covers the current-head Responses sibling path missed by the earlier fixes.\n\n## Technical Details\n\nThe shared OpenAI frontend has a validation helper that rejects request-supplied chat templates unless the trust flag is enabled. It explicitly checks both top-level `chat_template` and `chat_template_kwargs[\"chat_template\"]`.\n\nResponses is a separate serving path:\n\n- `vllm/entrypoints/openai/responses/protocol.py` exposes `chat_template_kwargs`.\n- `ResponsesRequest.build_chat_params()` merges request kwargs.\n- `OpenAIServingResponses._effective_chat_template_kwargs()` uses those kwargs.\n- `ChatParams.get_apply_chat_template_kwargs()` preserves a request `chat_template` key when the server chat template is `None`.\n- `vllm/renderers/hf.py` unpacks the result into `safe_apply_chat_template`.\n\nThere is no equivalent trust gate in `vllm/entrypoints/openai/responses/serving.py`.\n\n## Impact\n\nAn authenticated caller who can submit `/v1/responses` requests can supply a request-controlled Jinja chat template despite the trust flag being disabled. The expected fixed behavior is the same as Chat Completions: reject `chat_template_kwargs[\"chat_template\"]` unless the server was started with `--trust-request-chat-template`.\n\n## Suggested Fix\n\n- Add `trust_request_chat_template` to `OpenAIServingResponses`.\n- Pass `args.trust_request_chat_template` when constructing the Responses serving object.\n- Reject `request.chat_template_kwargs[\"chat_template\"]` before rendering when trust is false.\n- Keep ordinary kwargs such as `enable_thinking` working.\n- Add regression tests for default-deny and opt-in-allow behavior on `/v1/responses`.\n\n## Affected Package/Versions\n\nSource sweep found the affected shape in:\n\n- `v0.16.0`\n- `v0.18.0`\n- `v0.20.0`\n- `v0.21.0`\n- `v0.22.0`\n- `v0.22.1`\n- `v0.23.0`\n- current checkout `470229c37efaf69c86e8bc97482b0b1ff7551c65`\n- current `origin/main` `b3f0a0a0df76dda92ec4b2c9335f77e84adad911`\n\nSuggested affected range:\n\n```text\n\u003e= 0.16.0, \u003c= 0.23.0\n```\n\n## Appendix: Duplicate Research\n\nThis is related to, but distinct from:\n\n- `GHSA-6fvq-23cw-5628` / `CVE-2025-61620`\n- `GHSA-69j4-grxj-j64p` / `CVE-2025-62426`\n\nThose advisories establish the security impact of request-controlled Jinja templates and `chat_template_kwargs`, but they cover older Chat Completions/tokenize implementations. This report covers a current `/v1/responses` sibling path that still lacks the trust gate.\n\nLocal prior submissions this report..029 do not cover this root cause.\n\nThis advisory was fixed in [MR50300](https://github.com/vllm-project/vllm/pull/50300).",
  "id": "GHSA-x567-49g5-p4cf",
  "modified": "2026-10-28T21:14:59Z",
  "published": "2026-10-28T21:14:59Z",
  "references": [
    {
      "type": "WEB",
      "url": "https://github.com/vllm-project/vllm/security/advisories/GHSA-x567-49g5-p4cf"
    },
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2026-115918"
    },
    {
      "type": "WEB",
      "url": "https://github.com/vllm-project/vllm/pull/50300"
    },
    {
      "type": "WEB",
      "url": "https://github.com/vllm-project/vllm/commit/cff08b461e086523cee8bba5bd3c66d302625134"
    },
    {
      "type": "PACKAGE",
      "url": "https://github.com/vllm-project/vllm"
    },
    {
      "type": "WEB",
      "url": "https://github.com/vllm-project/vllm/releases/tag/v0.32.0"
    }
  ],
  "schema_version": "1.4.0",
  "severity": [
    {
      "score": "CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H",
      "type": "CVSS_V3"
    }
  ],
  "summary": "vLLM: Responses API bypasses trust_request_chat_template for chat_template_kwargs"
}

CVE-2026-115918 (GCVE-0-2026-115918)

Vulnerability from cvelistv5 – Published: 2026-10-26 17:21 – Updated: 2026-10-26 17:21

Title

vLLM: Responses API bypasses trust_request_chat_template for chat_template_kwargs

Summary

vLLM is an inference and serving engine for large language models. From 0.16.0 until 0.32.0, the /v1/responses endpoint allows an authenticated caller to place an attacker-controlled template in chat_template_kwargs[chat_template] when no server template is configured. ChatParams.get_apply_chat_template_kwargs() preserves that value without enforcing trust_request_chat_template, so the request can bypass the intended trust policy and cause CPU or memory exhaustion through Jinja rendering. This issue is fixed in version 0.32.0.

Severity

6.5 (Medium)


                        
                          CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H

CWE

CWE-400 - Uncontrolled Resource Consumption
CWE-770 - Allocation of Resources Without Limits or Throttling

Assigner

GitHub_M CNA under the mitre root

CNA scorecard C 72/100 over 7994 records in the last 180 days details

References

4 references

URL	Tags
https://github.com/vllm-project/vllm/security/adv…	x_refsource_CONFIRM
https://github.com/vllm-project/vllm/pull/50300	x_refsource_MISC
https://github.com/vllm-project/vllm/commit/cff08…	x_refsource_MISC
https://github.com/vllm-project/vllm/releases/tag…	x_refsource_MISC

Impacted products

1 product

Vendor	Product	Version
vllm-project	vllm	Affected: >= 0.16.0, < 0.32.0

Show details on NVD website

JSON

To clipboard

{
  "containers": {
    "cna": {
      "affected": [
        {
          "product": "vllm",
          "vendor": "vllm-project",
          "versions": [
            {
              "status": "affected",
              "version": "\u003e= 0.16.0, \u003c 0.32.0"
            }
          ]
        }
      ],
      "descriptions": [
        {
          "lang": "en",
          "value": "vLLM is an inference and serving engine for large language models. From 0.16.0 until 0.32.0, the /v1/responses endpoint allows an authenticated caller to place an attacker-controlled template in chat_template_kwargs[chat_template] when no server template is configured. ChatParams.get_apply_chat_template_kwargs() preserves that value without enforcing trust_request_chat_template, so the request can bypass the intended trust policy and cause CPU or memory exhaustion through Jinja rendering. This issue is fixed in version 0.32.0."
        }
      ],
      "metrics": [
        {
          "cvssV3_1": {
            "attackComplexity": "LOW",
            "attackVector": "NETWORK",
            "availabilityImpact": "HIGH",
            "baseScore": 6.5,
            "baseSeverity": "MEDIUM",
            "confidentialityImpact": "NONE",
            "integrityImpact": "NONE",
            "privilegesRequired": "LOW",
            "scope": "UNCHANGED",
            "userInteraction": "NONE",
            "vectorString": "CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H",
            "version": "3.1"
          }
        }
      ],
      "problemTypes": [
        {
          "descriptions": [
            {
              "cweId": "CWE-400",
              "description": "CWE-400: Uncontrolled Resource Consumption",
              "lang": "en",
              "type": "CWE"
            }
          ]
        },
        {
          "descriptions": [
            {
              "cweId": "CWE-770",
              "description": "CWE-770: Allocation of Resources Without Limits or Throttling",
              "lang": "en",
              "type": "CWE"
            }
          ]
        }
      ],
      "providerMetadata": {
        "dateUpdated": "2026-10-26T17:21:49.719Z",
        "orgId": "a0819718-46f1-4df5-94e2-005712e83aaa",
        "shortName": "GitHub_M"
      },
      "references": [
        {
          "name": "https://github.com/vllm-project/vllm/security/advisories/GHSA-x567-49g5-p4cf",
          "tags": [
            "x_refsource_CONFIRM"
          ],
          "url": "https://github.com/vllm-project/vllm/security/advisories/GHSA-x567-49g5-p4cf"
        },
        {
          "name": "https://github.com/vllm-project/vllm/pull/50300",
          "tags": [
            "x_refsource_MISC"
          ],
          "url": "https://github.com/vllm-project/vllm/pull/50300"
        },
        {
          "name": "https://github.com/vllm-project/vllm/commit/cff08b461e086523cee8bba5bd3c66d302625134",
          "tags": [
            "x_refsource_MISC"
          ],
          "url": "https://github.com/vllm-project/vllm/commit/cff08b461e086523cee8bba5bd3c66d302625134"
        },
        {
          "name": "https://github.com/vllm-project/vllm/releases/tag/v0.32.0",
          "tags": [
            "x_refsource_MISC"
          ],
          "url": "https://github.com/vllm-project/vllm/releases/tag/v0.32.0"
        }
      ],
      "source": {
        "advisory": "GHSA-x567-49g5-p4cf",
        "discovery": "UNKNOWN"
      },
      "title": "vLLM: Responses API bypasses trust_request_chat_template for chat_template_kwargs"
    }
  },
  "cveMetadata": {
    "assignerOrgId": "a0819718-46f1-4df5-94e2-005712e83aaa",
    "assignerShortName": "GitHub_M",
    "cveId": "CVE-2026-115918",
    "datePublished": "2026-10-26T17:21:49.719Z",
    "dateReserved": "2026-10-23T20:21:45.107Z",
    "dateUpdated": "2026-10-26T17:21:49.719Z",
    "state": "PUBLISHED"
  },
  "dataType": "CVE_RECORD",
  "dataVersion": "5.2"
}

PYSEC-2026-4349

Vulnerability from pysec - Published: 2026-10-26 18:17 - Updated: 2026-10-29 10:34

Details

Severity

6.5 (Medium)


                  
                    CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H

Impacted products

Name	purl
vllm	pkg:pypi/vllm

Aliases

JSON

To clipboard

{
  "affected": [
    {
      "ecosystem_specific": {},
      "package": {
        "ecosystem": "PyPI",
        "name": "vllm",
        "purl": "pkg:pypi/vllm"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "0.16.0"
            },
            {
              "fixed": "0.32.0"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ],
      "versions": [
        "0.16.0",
        "0.17.0",
        "0.17.1",
        "0.18.0",
        "0.18.1",
        "0.19.0",
        "0.19.1",
        "0.20.0",
        "0.20.1",
        "0.20.2",
        "0.21.0",
        "0.22.0",
        "0.22.1",
        "0.23.0",
        "0.24.0",
        "0.25.0",
        "0.25.1",
        "0.26.0",
        "0.27.0",
        "0.27.1",
        "0.28.0",
        "0.29.0",
        "0.30.0",
        "0.31.0"
      ]
    }
  ],
  "aliases": [
    "CVE-2026-115918",
    "GHSA-x567-49g5-p4cf"
  ],
  "details": "vLLM is an inference and serving engine for large language models. From 0.16.0 until 0.32.0, the /v1/responses endpoint allows an authenticated caller to place an attacker-controlled template in chat_template_kwargs[chat_template] when no server template is configured. ChatParams.get_apply_chat_template_kwargs() preserves that value without enforcing trust_request_chat_template, so the request can bypass the intended trust policy and cause CPU or memory exhaustion through Jinja rendering. This issue is fixed in version 0.32.0.",
  "id": "PYSEC-2026-4349",
  "modified": "2026-10-29T10:34:17.613114Z",
  "published": "2026-10-26T18:17:39.440Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://github.com/vllm-project/vllm/releases/tag/v0.32.0"
    },
    {
      "type": "FIX",
      "url": "https://github.com/vllm-project/vllm/commit/cff08b461e086523cee8bba5bd3c66d302625134"
    },
    {
      "type": "FIX",
      "url": "https://github.com/vllm-project/vllm/pull/50300"
    },
    {
      "type": "FIX",
      "url": "https://github.com/vllm-project/vllm/security/advisories/GHSA-x567-49g5-p4cf"
    }
  ],
  "severity": [
    {
      "score": "CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H",
      "type": "CVSS_V3"
    }
  ]
}

Sightings

Author	Source	Type	Date	Other

Nomenclature

Seen: The vulnerability was mentioned, discussed, or observed by the user.
Confirmed: The vulnerability has been validated from an analyst's perspective.
Published Proof of Concept: A public proof of concept is available for this vulnerability.
Exploited: The vulnerability was observed as exploited by the user who reported the sighting.
Patched: The vulnerability was observed as successfully patched by the user who reported the sighting.
Not exploited: The vulnerability was not observed as exploited by the user who reported the sighting.
Not confirmed: The user expressed doubt about the validity of the vulnerability.
Not patched: The vulnerability was not observed as successfully patched by the user who reported the sighting.

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The MITRE ATT&CK techniques below are AI-generated suggestions, inferred from the description of the vulnerability by the CIRCL/vulnerability-attack-technique-classification-roberta-base model, served locally by ML-Gateway. They have not been verified by an analyst and are provided for guidance only.
The approach is described in our paper Mapping CVEs to MITRE ATT&CK Techniques: A Curated Gold-Set Classifier and the Limits of LLM-Assisted Label Expansion.
Browse all ATT&CK techniques and the vulnerabilities related to each.

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GHSA-X567-49G5-P4CF

Summary

Technical Details

Impact

Suggested Fix

Affected Package/Versions

Appendix: Duplicate Research

CVE-2026-115918 (GCVE-0-2026-115918)

PYSEC-2026-4349

Tags

Sightings

Nomenclature

Vulnerability timeline

Related by attack behaviour