CVE-2026-43979

{
  "id": "CVE-2026-43979",
  "sourceIdentifier": "[email protected]",
  "published": "2026-05-28T19:16:38.067",
  "lastModified": "2026-10-26T13:10:00.140",
  "vulnStatus": "Deferred",
  "cveTags": [],
  "descriptions": [
    {
      "lang": "en",
      "value": "Local Deep Research is an AI-powered research assistant for deep, iterative research. Prior to 1.6.0, PDFService._markdown_to_html() constructs an HTML document by interpolating user-controlled values — specifically title (sourced from research.title or research.query) and metadata key-value pairs — directly into an f-string without any HTML escaping. An authenticated attacker can craft a research query containing HTML special characters to inject arbitrary HTML tags into the document processed by WeasyPrint during PDF export. This injection can be chained to trigger a Server-Side Request Forgery (SSRF), bypassing the application's existing SSRF defenses in ssrf_validator.py. This vulnerability is fixed in 1.6.0."
    },
    {
      "lang": "es",
      "value": "Local Deep Research es un asistente de investigación impulsado por IA para investigación profunda e iterativa. Antes de la versión 1.6.0, PDFService._markdown_to_html() construye un documento HTML interpolando valores controlados por el usuario - específicamente el título (obtenido de research.title o research.query) y pares clave-valor de metadatos - directamente en una f-string sin ningún escape HTML. Un atacante autenticado puede elaborar una consulta de investigación que contenga caracteres especiales HTML para inyectar etiquetas HTML arbitrarias en el documento procesado por WeasyPrint durante la exportación a PDF. Esta inyección puede encadenarse para desencadenar una Falsificación de Petición del Lado del Servidor (SSRF), eludiendo las defensas SSRF existentes de la aplicación en ssrf_validator.py. Esta vulnerabilidad está corregida en la versión 1.6.0."
    }
  ],
  "affected": [
    {
      "source": "[email protected]",
      "affectedData": [
        {
          "vendor": "LearningCircuit",
          "product": "local-deep-research",
          "versions": [
            {
              "version": "< 1.6.0",
              "status": "affected"
            }
          ]
        }
      ]
    }
  ],
  "metrics": {
    "cvssMetricV31": [
      {
        "source": "[email protected]",
        "type": "Secondary",
        "cvssData": {
          "version": "3.1",
          "vectorString": "CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:C/C:L/I:N/A:N",
          "baseScore": 5.0,
          "baseSeverity": "MEDIUM",
          "attackVector": "NETWORK",
          "attackComplexity": "LOW",
          "privilegesRequired": "LOW",
          "userInteraction": "NONE",
          "scope": "CHANGED",
          "confidentialityImpact": "LOW",
          "integrityImpact": "NONE",
          "availabilityImpact": "NONE"
        },
        "exploitabilityScore": 3.1,
        "impactScore": 1.4
      }
    ],
    "ssvcV203": [
      {
        "source": "134c704f-9b21-4f2e-91b3-4a467353bcc0",
        "ssvcData": {
          "timestamp": "2026-05-28T19:33:32.262907Z",
          "id": "CVE-2026-43979",
          "options": [
            {
              "exploitation": "poc"
            },
            {
              "automatable": "no"
            },
            {
              "technicalImpact": "partial"
            }
          ],
          "role": "CISA Coordinator",
          "version": "2.0.3"
        }
      }
    ]
  },
  "weaknesses": [
    {
      "source": "[email protected]",
      "type": "Secondary",
      "description": [
        {
          "lang": "en",
          "value": "CWE-79"
        },
        {
          "lang": "en",
          "value": "CWE-918"
        }
      ]
    }
  ],
  "references": [
    {
      "url": "https://github.com/LearningCircuit/local-deep-research/pull/3082",
      "source": "[email protected]"
    },
    {
      "url": "https://github.com/LearningCircuit/local-deep-research/pull/3613",
      "source": "[email protected]"
    },
    {
      "url": "https://github.com/LearningCircuit/local-deep-research/security/advisories/GHSA-fj2m-qvh9-jq4q",
      "source": "[email protected]"
    },
    {
      "url": "https://github.com/LearningCircuit/local-deep-research/security/advisories/GHSA-fj2m-qvh9-jq4q",
      "source": "134c704f-9b21-4f2e-91b3-4a467353bcc0"
    }
  ]
}