Local Deep Research

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 the actual request. This vulnerability is fixed in 1.6.10.

Published: 2026-05-28T17:58:22.669Z
Updated: 2026-05-29T14:05:55.976Z

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.

Published: 2026-05-28T17:59:19.443Z
Updated: 2026-05-28T19:33:58.899Z

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.

Published: 2025-12-23T00:01:19.309Z
Updated: 2025-12-23T15:41:01.533Z

Local Deep Research is an AI-powered research assistant for deep, iterative research. Versions 0.2.0 through 0.6.7 stored confidential information, including API keys, in a local SQLite database without encryption. This behavior was not clearly documented outside of the database architecture page. Users were not given the ability to configure the database location, allowing anyone with access to the container or host filesystem to retrieve sensitive data in plaintext by accessing the .db file. This is fixed in version 1.0.0.

Published: 2025-09-03T00:47:24.262Z
Updated: 2025-09-03T15:44:45.651Z