{"resultsPerPage":1,"startIndex":0,"totalResults":1,"format":"NVD_CVE","version":"2.0","timestamp":"2026-04-21T00:39:33.309","vulnerabilities":[{"cve":{"id":"CVE-2026-32626","sourceIdentifier":"security-advisories@github.com","published":"2026-03-16T14:19:40.033","lastModified":"2026-03-16T20:34:47.637","vulnStatus":"Analyzed","cveTags":[],"descriptions":[{"lang":"en","value":"AnythingLLM is an application that turns pieces of content into context that any LLM can use as references during chatting. In 1.11.1 and earlier, AnythingLLM Desktop contains a Streaming Phase XSS vulnerability in the chat rendering pipeline that escalates to Remote Code Execution on the host OS due to insecure Electron configuration. This works with default settings and requires no user interaction beyond normal chat usage. The custom markdown-it image renderer in frontend/src/utils/chat/markdown.js interpolates token.content directly into the alt attribute without HTML entity escaping. The PromptReply component renders this output via dangerouslySetInnerHTML without DOMPurify sanitization — unlike HistoricalMessage which correctly applies DOMPurify.sanitize()."},{"lang":"es","value":"AnythingLLM es una aplicación que convierte fragmentos de contenido en contexto que cualquier LLM puede usar como referencias durante el chat. En la versión 1.11.1 y anteriores, AnythingLLM Desktop contiene una vulnerabilidad XSS de fase de streaming en la canalización de renderizado del chat que escala a ejecución remota de código en el sistema operativo anfitrión debido a una configuración insegura de Electron. Esto funciona con la configuración predeterminada y no requiere interacción del usuario más allá del uso normal del chat. El renderizador de imágenes personalizado de markdown-it en frontend/src/utils/chat/markdown.js interpola token.content directamente en el atributo alt sin escape de entidades HTML. El componente PromptReply renderiza esta salida a través de dangerouslySetInnerHTML sin la sanitización de DOMPurify, a diferencia de HistoricalMessage, que aplica correctamente DOMPurify.sanitize()."}],"metrics":{"cvssMetricV31":[{"source":"security-advisories@github.com","type":"Secondary","cvssData":{"version":"3.1","vectorString":"CVSS:3.1/AV:N/AC:L/PR:N/UI:R/S:C/C:H/I:H/A:H","baseScore":9.6,"baseSeverity":"CRITICAL","attackVector":"NETWORK","attackComplexity":"LOW","privilegesRequired":"NONE","userInteraction":"REQUIRED","scope":"CHANGED","confidentialityImpact":"HIGH","integrityImpact":"HIGH","availabilityImpact":"HIGH"},"exploitabilityScore":2.8,"impactScore":6.0}]},"weaknesses":[{"source":"security-advisories@github.com","type":"Primary","description":[{"lang":"en","value":"CWE-79"}]}],"configurations":[{"nodes":[{"operator":"OR","negate":false,"cpeMatch":[{"vulnerable":true,"criteria":"cpe:2.3:a:mintplexlabs:anythingllm:*:*:*:*:*:*:*:*","versionEndIncluding":"1.11.1","matchCriteriaId":"384FD8C3-E046-493C-9996-8E3042229081"}]}]}],"references":[{"url":"https://github.com/Mintplex-Labs/anything-llm/commit/9e2d144dc8be6fab29f560f5bcdaa9ef7dbb4214","source":"security-advisories@github.com","tags":["Patch"]},{"url":"https://github.com/Mintplex-Labs/anything-llm/security/advisories/GHSA-rrmw-2j6x-4mf2","source":"security-advisories@github.com","tags":["Exploit","Vendor Advisory"]}]}}]}