CVE-2026-54236

{"id": "CVE-2026-54236", "cveTags": [], "metrics": {"ssvcV203": [{"source": "134c704f-9b21-4f2e-91b3-4a467353bcc0", "ssvcData": {"id": "CVE-2026-54236", "role": "CISA Coordinator", "options": [{"exploitation": "poc"}, {"automatable": "yes"}, {"technicalImpact": "partial"}], "version": "2.0.3", "timestamp": "2026-06-23T12:32:56.752434Z"}}], "cvssMetricV31": [{"type": "Secondary", "source": "security-advisories@github.com", "cvssData": {"scope": "UNCHANGED", "version": "3.1", "baseScore": 5.3, "attackVector": "NETWORK", "baseSeverity": "MEDIUM", "vectorString": "CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:L/I:N/A:N", "integrityImpact": "NONE", "userInteraction": "NONE", "attackComplexity": "LOW", "availabilityImpact": "NONE", "privilegesRequired": "NONE", "confidentialityImpact": "LOW"}, "impactScore": 1.4, "exploitabilityScore": 3.9}]}, "affected": [{"source": "security-advisories@github.com", "affectedData": [{"vendor": "vllm-project", "product": "vllm", "versions": [{"status": "affected", "version": "< 0.23.1rc0"}]}]}], "published": "2026-06-22T23:16:31.290", "references": [{"url": "https://github.com/vllm-project/vllm/commit/94923629729381d7f7c9efde72071a2441f7fd82", "tags": ["Patch"], "source": "security-advisories@github.com"}, {"url": "https://github.com/vllm-project/vllm/pull/45119", "tags": ["Issue Tracking"], "source": "security-advisories@github.com"}, {"url": "https://github.com/vllm-project/vllm/security/advisories/GHSA-hgg8-fqqc-vfmw", "tags": ["Exploit", "Third Party Advisory"], "source": "security-advisories@github.com"}, {"url": "https://github.com/vllm-project/vllm/security/advisories/GHSA-hgg8-fqqc-vfmw", "tags": ["Exploit", "Third Party Advisory"], "source": "134c704f-9b21-4f2e-91b3-4a467353bcc0"}], "vulnStatus": "Analyzed", "weaknesses": [{"type": "Secondary", "source": "security-advisories@github.com", "description": [{"lang": "en", "value": "CWE-532"}]}], "descriptions": [{"lang": "en", "value": "vLLM is an inference and serving engine for large language models (LLMs). Prior to 0.23.1rc0, the fix for CVE-2026-22778, which introduced a sanitize_message helper that strips object-repr memory addresses from error messages before they reach the client, is incomplete: several response paths echo str(exc) directly to clients without calling sanitize_message. The unsanitized sites include the Anthropic API router in vllm/entrypoints/anthropic/api_router.py (the POST /v1/messages and POST /v1/messages/count_tokens handlers), the Server-Sent Events streaming converter in vllm/entrypoints/anthropic/serving.py, and the realtime speech-to-text WebSocket in vllm/entrypoints/speech_to_text/realtime/connection.py. These paths catch the exception inside the route coroutine and construct the JSONResponse themselves, bypassing the sanitizing global FastAPI exception handler, and WebSocket frames do not traverse that handler chain at all. Using the same primitive as the parent issue, an unauthenticated attacker can send malformed image bytes through the Anthropic Messages API image content parts so that PIL.Image.open raises an UnidentifiedImageError whose message contains the BytesIO object repr, leaking the heap memory address verbatim in the error.message field of the response body. This vulnerability is fixed in 0.23.1rc0."}, {"lang": "es", "value": "vLLM es un motor de inferencia y servicio para modelos de lenguaje grandes (LLMs). Antes de 0.23.1rc0, la correcci\u00f3n para CVE-2026-22778, que introdujo un gestor auxiliar sanitize_message que elimina las direcciones de memoria de representaci\u00f3n de objetos de los mensajes de error antes de que lleguen al cliente, est\u00e1 incompleta: varias rutas de respuesta devuelven str(exc) directamente a los clientes sin llamar a sanitize_message. Los sitios no saneados incluyen el router de la API de Anthropic en vllm/entrypoints/anthropic/api_router.py (los gestores POST /v1/messages y POST /v1/messages/count_tokens), el conversor de streaming de Server-Sent Events en vllm/entrypoints/anthropic/serving.py, y el WebSocket de voz a texto en tiempo real en vllm/entrypoints/speech_to_text/realtime/connection.py. Estas rutas capturan la excepci\u00f3n dentro de la corrutina de la ruta y construyen la JSONResponse por s\u00ed mismas, omitiendo el gestor de excepciones global de FastAPI que realiza el saneamiento, y los frames de WebSocket no atraviesan esa cadena de gestores en absoluto. Usando la misma primitiva que el problema padre, un atacante no autenticado puede enviar bytes de imagen malformados a trav\u00e9s de las partes de contenido de imagen de la API de Mensajes de Anthropic de modo que PIL.Image.open genere un UnidentifiedImageError cuyo mensaje contiene la representaci\u00f3n del objeto BytesIO, filtrando la direcci\u00f3n de memoria del heap textualmente en el campo error.message del cuerpo de la respuesta. Esta vulnerabilidad est\u00e1 corregida en 0.23.1rc0."}], "lastModified": "2026-10-25T23:10:00.167", "configurations": [{"nodes": [{"negate": false, "cpeMatch": [{"criteria": "cpe:2.3:a:vllm:vllm:*:*:*:*:*:*:*:*", "vulnerable": true, "matchCriteriaId": "BF7F1CE7-1A95-41E3-95A5-732906527D08", "versionEndExcluding": "0.23.1"}], "operator": "OR"}]}], "sourceIdentifier": "security-advisories@github.com"}