p PatchFirst

PatchFirst · Aktuelle Sicherheitslücken

Sicherheitslücken in local-deep-research

In den letzten 30 Tagen veröffentlichte Sicherheitslücken für local-deep-research: 0. Davon im KEV-Katalog: 0.

Sicherheitslücken filtern
Filter zurücksetzen

Sicherheitslücken: 3

  1. CVE-2026-43979

    Mittel · CVSS 5EPSS 0,33%Korrektur verfügbar

    Local Deep Research: HTML Injection via Unescaped User Input in PDF Export (`pdf_service.py:_markdown_to_html`)

    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 S

    • Auf 1.6.0 aktualisieren
    Veröffentlicht Aktualisiert
  2. CVE-2026-46526

    Mittel · CVSS 5EPSS 0,3%Korrektur verfügbar

    Local Deep Research: SSRF bypass in `safe_get`

    Local Deep Research is an AI-powered research assistant for deep, iterative research. Prior to 1.6.10, the URL checking logic in local-deep-research has a logical flaw that could be bypassed by attackers, leading to SSRF attacks. The current project uses validate_url to validate the input URL. The main logic is to perform security checks on the host portion of the URL extracted by urlparse to prevent SSRF attacks. However, there are indeed differences in parsing between urlparse and the library that actually sends the request. For example, in safe_get, validate_url is first used to perform an SSRF check, and then requests.get is used to send

    • Auf 1.6.10 aktualisieren
    Veröffentlicht Aktualisiert
  3. CVE-2025-67743

    Mittel · CVSS 6.3EPSS 0,32%Korrektur verfügbar

    Local Deep Research is Vulnerable to Server-Side Request Forgery (SSRF) in Download Service

    Local Deep Research is an AI-powered research assistant for deep, iterative research. In versions from 1.3.0 to before 1.3.9, the download service (download_service.py) makes HTTP requests using raw requests.get() without utilizing the application's SSRF protection (safe_requests.py). This can allow attackers to access internal services and attempt to reach cloud provider metadata endpoints (AWS/GCP/Azure), as well as perform internal network reconnaissance, by submitting malicious URLs through the API, depending on the deployment and surrounding controls. This issue has been patched in version 1.3.9.

    • Auf 1.3.9 aktualisieren
    Veröffentlicht Aktualisiert

Prüfen Sie Ihren Server

Gleichen Sie Ihren installierten Stack und seine Versionen mit den aktuellen Sicherheitsmeldungen ab.

Prüfen Sie Ihren Server →