CVE-2026-54236

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{"affected": [{"affectedData": [{"product": "vllm", "vendor": "vllm-project", "versions": [{"status": "affected", "version": "< 0.23.1rc0"}]}], "source": "security-advisories@github.com"}], "configurations": [{"nodes": [{"cpeMatch": [{"criteria": "cpe:2.3:a:vllm:vllm:*:*:*:*:*:*:*:*", "matchCriteriaId": "BF7F1CE7-1A95-41E3-95A5-732906527D08", "versionEndExcluding": "0.23.1", "vulnerable": true}], "negate": false, "operator": "OR"}]}], "cveTags": [], "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."}], "id": "CVE-2026-54236", "lastModified": "2026-10-25T23:10:00.167", "metrics": {"cvssMetricV31": [{"cvssData": {"attackComplexity": "LOW", "attackVector": "NETWORK", "availabilityImpact": "NONE", "baseScore": 5.3, "baseSeverity": "MEDIUM", "confidentialityImpact": "LOW", "integrityImpact": "NONE", "privilegesRequired": "NONE", "scope": "UNCHANGED", "userInteraction": "NONE", "vectorString": "CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:L/I:N/A:N", "version": "3.1"}, "exploitabilityScore": 3.9, "impactScore": 1.4, "source": "security-advisories@github.com", "type": "Secondary"}], "ssvcV203": [{"source": "134c704f-9b21-4f2e-91b3-4a467353bcc0", "ssvcData": {"id": "CVE-2026-54236", "options": [{"exploitation": "poc"}, {"automatable": "yes"}, {"technicalImpact": "partial"}], "role": "CISA Coordinator", "timestamp": "2026-06-23T12:32:56.752434Z", "version": "2.0.3"}}]}, "published": "2026-06-22T23:16:31.290", "references": [{"source": "security-advisories@github.com", "tags": ["Patch"], "url": "https://github.com/vllm-project/vllm/commit/94923629729381d7f7c9efde72071a2441f7fd82"}, {"source": "security-advisories@github.com", "tags": ["Issue Tracking"], "url": "https://github.com/vllm-project/vllm/pull/45119"}, {"source": "security-advisories@github.com", "tags": ["Exploit", "Third Party Advisory"], "url": "https://github.com/vllm-project/vllm/security/advisories/GHSA-hgg8-fqqc-vfmw"}, {"source": "134c704f-9b21-4f2e-91b3-4a467353bcc0", "tags": ["Exploit", "Third Party Advisory"], "url": "https://github.com/vllm-project/vllm/security/advisories/GHSA-hgg8-fqqc-vfmw"}], "sourceIdentifier": "security-advisories@github.com", "vulnStatus": "Analyzed", "weaknesses": [{"description": [{"lang": "en", "value": "CWE-532"}], "source": "security-advisories@github.com", "type": "Secondary"}]}

{"bugzilla": {"description": "vllm: vLLM: Information Disclosure via Incomplete Error Message Sanitization", "id": "2491583", "url": "https://bugzilla.redhat.com/show_bug.cgi?id=2491583"}, "csaw": false, "cvss3": {"cvss3_base_score": "5.3", "cvss3_scoring_vector": "CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:L/I:N/A:N", "status": "draft"}, "cwe": "CWE-209", "details": ["A flaw was found in vLLM, an inference and serving engine for large language models (LLMs). An unauthenticated attacker can exploit this vulnerability by sending specially crafted malformed image bytes through the Anthropic Messages API. This action causes an error message to be generated that inadvertently includes sensitive heap memory addresses, leading to information disclosure. The issue stems from incomplete sanitization of error messages in several response paths, allowing these memory addresses to be exposed directly to clients."], "mitigation": {"lang": "en:us", "value": "Mitigation for this issue is either not available or the currently available options do not meet the Red Hat Product Security criteria comprising ease of use and deployment, applicability to widespread installation base, or stability."}, "name": "CVE-2026-54236", "package_state": [{"cpe": "cpe:/a:redhat:ai_inference_server:3", "fix_state": "Not affected", "package_name": "rhaiis/vllm-cpu-rhel9", "product_name": "Red Hat AI Inference Server"}, {"cpe": "cpe:/a:redhat:ai_inference_server:3", "fix_state": "Not affected", "package_name": "rhaiis/vllm-cuda-rhel9", "product_name": "Red Hat AI Inference Server"}, {"cpe": "cpe:/a:redhat:ai_inference_server:3", "fix_state": "Not affected", "package_name": "rhaiis/vllm-neuron-rhel9", "product_name": "Red Hat AI Inference Server"}, {"cpe": "cpe:/a:redhat:ai_inference_server:3", "fix_state": "Not affected", "package_name": "rhaiis/vllm-rocm-rhel9", "product_name": "Red Hat AI Inference Server"}, {"cpe": "cpe:/a:redhat:ai_inference_server:3", "fix_state": "Not affected", "package_name": "rhaiis/vllm-spyre-rhel9", "product_name": "Red Hat AI Inference Server"}, {"cpe": "cpe:/a:redhat:ai_inference_server:3", "fix_state": "Not affected", "package_name": "rhaiis/vllm-tpu-rhel9", "product_name": "Red Hat AI Inference Server"}, {"cpe": "cpe:/a:redhat:ai_inference_server:3", "fix_state": "Fix deferred", "package_name": "rhaii/vllm-cpu-rhel9", "product_name": "Red Hat AI Inference Server"}, {"cpe": "cpe:/a:redhat:ai_inference_server:3", "fix_state": "Fix deferred", "package_name": "rhaii/vllm-cuda-rhel9", "product_name": "Red Hat AI Inference Server"}, {"cpe": "cpe:/a:redhat:ai_inference_server:3", "fix_state": "Fix deferred", "package_name": "rhaii/vllm-gaudi-rhel9", "product_name": "Red Hat AI Inference Server"}, {"cpe": "cpe:/a:redhat:ai_inference_server:3", "fix_state": "Not affected", "package_name": "rhaii/vllm-neuron-rhel9", "product_name": "Red Hat AI Inference Server"}, {"cpe": "cpe:/a:redhat:ai_inference_server:3", "fix_state": "Fix deferred", "package_name": "rhaii/vllm-rocm-rhel9", "product_name": "Red Hat AI Inference Server"}, {"cpe": "cpe:/a:redhat:ai_inference_server:3", "fix_state": "Fix deferred", "package_name": "rhaii/vllm-spyre-rhel9", "product_name": "Red Hat AI Inference Server"}, {"cpe": "cpe:/a:redhat:ai_inference_server:3", "fix_state": "Not affected", "package_name": "rhaii/vllm-tpu-rhel9", "product_name": "Red Hat AI Inference Server"}, {"cpe": "cpe:/a:redhat:enterprise_linux_ai:3", "fix_state": "Fix deferred", "package_name": "rhelai3/bootc-aws-cuda-rhel9", "product_name": "Red Hat Enterprise Linux AI (RHEL AI) 3"}, {"cpe": "cpe:/a:redhat:enterprise_linux_ai:3", "fix_state": "Fix deferred", "package_name": "rhelai3/bootc-azure-cuda-rhel9", "product_name": "Red Hat Enterprise Linux AI (RHEL AI) 3"}, {"cpe": "cpe:/a:redhat:enterprise_linux_ai:3", "fix_state": "Fix deferred", "package_name": "rhelai3/bootc-azure-rocm-rhel9", "product_name": "Red Hat Enterprise Linux AI (RHEL AI) 3"}, {"cpe": "cpe:/a:redhat:enterprise_linux_ai:3", "fix_state": "Fix deferred", "package_name": "rhelai3/bootc-cuda-rhel9", "product_name": "Red Hat Enterprise Linux AI (RHEL AI) 3"}, {"cpe": "cpe:/a:redhat:enterprise_linux_ai:3", "fix_state": "Fix deferred", "package_name": "rhelai3/bootc-gaudi-rhel9", "product_name": "Red Hat Enterprise Linux AI (RHEL AI) 3"}, {"cpe": "cpe:/a:redhat:enterprise_linux_ai:3", "fix_state": "Fix deferred", "package_name": "rhelai3/bootc-gcp-cuda-rhel9", "product_name": "Red Hat Enterprise Linux AI (RHEL AI) 3"}, {"cpe": "cpe:/a:redhat:enterprise_linux_ai:3", "fix_state": "Fix deferred", "package_name": "rhelai3/bootc-rocm-rhel9", "product_name": "Red Hat Enterprise Linux AI (RHEL AI) 3"}, {"cpe": "cpe:/a:redhat:openshift_ai", "fix_state": "Not affected", "package_name": "rhoai/odh-kserve-agent-rhel9", "product_name": "Red Hat OpenShift AI (RHOAI)"}, {"cpe": "cpe:/a:redhat:openshift_ai", "fix_state": "Not affected", "package_name": "rhoai/odh-kserve-controller-rhel9", "product_name": "Red Hat OpenShift AI (RHOAI)"}, {"cpe": "cpe:/a:redhat:openshift_ai", "fix_state": "Not affected", "package_name": "rhoai/odh-kserve-router-rhel9", "product_name": "Red Hat OpenShift AI (RHOAI)"}, {"cpe": "cpe:/a:redhat:openshift_ai", "fix_state": "Not affected", "package_name": "rhoai/odh-kserve-storage-initializer-rhel9", "product_name": "Red Hat OpenShift AI (RHOAI)"}, {"cpe": "cpe:/a:redhat:openshift_ai", "fix_state": "Not affected", "package_name": "rhoai/odh-llm-d-kv-cache-rhel9", "product_name": "Red Hat OpenShift AI (RHOAI)"}, {"cpe": "cpe:/a:redhat:openshift_ai", "fix_state": "Fix deferred", "package_name": "rhoai/odh-vllm-gaudi-rhel9", "product_name": "Red Hat OpenShift AI (RHOAI)"}], "public_date": "2026-06-22T22:09:15Z", "references": ["https://www.cve.org/CVERecord?id=CVE-2026-54236\nhttps://nvd.nist.gov/vuln/detail/CVE-2026-54236\nhttps://github.com/vllm-project/vllm/commit/94923629729381d7f7c9efde72071a2441f7fd82\nhttps://github.com/vllm-project/vllm/pull/45119\nhttps://github.com/vllm-project/vllm/security/advisories/GHSA-hgg8-fqqc-vfmw"], "statement": "This Moderate impact information disclosure flaw in vLLM does not affect Red Hat products. The vulnerable code responsible for incomplete error message sanitization, which could leak heap memory addresses via specially crafted image bytes sent to the Anthropic Messages API, is not present in Red Hat's supported offerings.", "threat_severity": "Moderate"}

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