Vulnerability · Published May 28, 2026 · Assigned by GitHub_M

CVE-2026-43979Local Deep Research: HTML Injection via Unescaped User Input in PDF Export (`pdf_service.py:_markdown_to_html`)

Medium 5.0

In plain English

A medium-severity cross-site scripting in local-deep-research from LearningCircuit. Proof-of-concept exploit code is public. The chance it is exploited in the next 30 days is estimated at 0.3% (higher than 26% of all known vulnerabilities). Fixed versions are available - upgrade the affected package.

Severity (CVSS 3.1)5.0Medium
Exploit odds (30 days)0.3%top 73.6% of all CVEs
Exploited in the wildNo reportsCISA SSVC: poc
Attack toolingNoneno public tooling known

Official description

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.

Affected packages & fixed versions

EcosystemPackageFixed inAdvisory
PyPIlocal-deep-research1.6.0GHSA-fj2m-qvh9-jq4q
PyPIlocal-deep-research1.6.0PYSEC-2026-2610

Affected products (as reported)

VendorProductVersions
LearningCircuit local-deep-research < 1.6.0

Weakness: CWE-79, CWE-918 · Vector: CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:C/C:L/I:N/A:N

References