CVE-2026-43979
MediumCVSS 5.0Summary
W wersjach przed 1.6.0, funkcja PDFService._markdown_to_html() w Local Deep Research nieprawidłowo interpoluje wartości kontrolowane przez użytkownika, co pozwala na wstrzykiwanie niebezpiecznych tagów HTML. Umożliwia to atakującemu, który jest uwierzytelniony, na wykonanie ataku SSRF poprzez odpowiednio skonstruowane zapytanie badawcze.
Risk Assessment
Organizacja może być narażona na ataki SSRF, które mogą prowadzić do nieautoryzowanego dostępu do wewnętrznych zasobów sieciowych. Wykorzystanie tej podatności może skutkować poważnymi konsekwencjami dla bezpieczeństwa danych.
Recommendation
Zaleca się aktualizację do wersji 1.6.0 lub nowszej, aby usunąć tę podatność. Dodatkowo, warto przeprowadzić audyt zabezpieczeń aplikacji w celu zidentyfikowania i naprawienia innych potencjalnych luk.
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Original NVD description (English source)
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.
Vulnerability data from NVD (NIST) · CISA KEV · EPSS

