Local Deep Research: HTML Injection via Unescaped User Input in PDF Export (`pdf_service.py:_markdown_to_html`)
- Published
- Last modified
- Where the record stands: published, rejected by its publisher, or superseded by another id.What do these mean? →
- published
- Whether CISA lists it in its Known Exploited Vulnerabilities catalog: proof that attackers are using it.What do these mean? →
- Not listed in CISA KEV
- Fix
- Fixed in 1.6.0
- Whether working attack code is public (Exploit-DB, Metasploit, Nuclei or GitHub). Public code makes attacks easier.What do these mean? →
- None on Exploit-DB, Metasploit or GitHub
- Exploitation: poc
- Automatable: no
- Technical impact: partial
Summary
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.
Timeline
- CVE published
- CISA SSVC assessment
Exploitation: poc · Automatable: no · Technical impact: partial
- Record last updated
Affected versions
- LearningCircuit local-deep-research
fixed in 1.6.0
- local-deep-researchPyPI
fixed in 1.6.0