Categories
CVE-2026-43979 medium CVSS 5.0

Cross-Site Scripting (XSS) in local-deep-research (CVE-2026-43979)

Summary

Cross-site scripting in local-deep-research (CVE-2026-43979). Risk of unauthorized operations or information disclosure. Exploitable via POST /api/start_research. Mitigation: upgrade to 1.6.0 or later.

Original description

The description as published by the source.

Summary

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.


Details

Vulnerable code: src/local_deep_research/web/services/pdf_service.py, lines 171–176

# pdf_service.py:171-176
if title:
    html_parts.append(f"{title}")   # ← title is not escaped

if metadata:
    for key, value in metadata.items():
        html_parts.append(f'')  # ← key/value are not escaped

Data flow trace:

User input: research.query
        │
        ▼
research_routes.py:1321
  pdf_title = research.title or research.query
        │
        ▼
research_routes.py:1325-1326
  export_report_to_memory(report_content, format, title=pdf_title)
        │
        ▼
pdf_service.py:107
  PDFService.markdown_to_pdf(markdown_content, title=pdf_title)
        │
        ▼
pdf_service.py:137
  _markdown_to_html(markdown_content, title, metadata)
        │
        ▼
pdf_service.py:172
  f"{title}"   ← injection point, no escaping
        │…

Source: GitHub Security Advisories (Global) NVD GitHub Advisory

Auto-generated summary

Assembled by SecPulse from the source data (CVSS, CWE, affected versions) using templates — no AI involved. Check the original description and references below for exact details.

A vulnerability tracked as CVE-2026-43979 has been found in local-deep-research.
Attackers can target a specific entry point like POST /api/start_research over the network to misuse the product.
Risk of unauthorized operations or information disclosure. CVSS score: 5.0/10.
What to do: upgrade local-deep-research to 1.6.0 or later.
If unsure, ask your IT team or search "local-deep-research CVE-2026-43979" on the vendor's site.

CVE-2026-43979 (local-deep-research) — CWE-79 / CVSS v3 5.0
Attack vector: remote (network-reachable) / no user interaction
Attack surface: POST /api/start_research / POST /api/v1/research/ / POST /api/v1/research/aaaa-bbbb-cccc-dddd/export/pdf / GET /latest/meta-data/iam/security-credentials/
Patched: 1.6.0 — apply immediately
Plan: 1) Audit SBOM/dependencies, 2) Stage→prod upgrade, 3) Add WAF/proxy monitoring on affected endpoints, 4) Hunt IOCs in logs.
Refs: see the GHSA / vendor advisory / patched release linked on this page.

❓ What is the problem

Cross-site scripting (XSS) (CWE-79) exists in local-deep-research. Attackers reach the vulnerable code path via POST /api/start_research.

📍 Affected scope

Check the vendor advisory for the affected versions of local-deep-research. Attack surface: POST /api/start_research / POST /api/v1/research/ / POST /api/v1/research/aaaa-bbbb-cccc-dddd/export/pdf / GET /latest/meta-data/iam/security-credentials/.

🔥 Severity

Severity: Medium (CVSS 5.0/10). Risk of unauthorized operations or information disclosure.

🔧 How to fix

Update to 1.6.0.

🛡️ Workaround

Until the patch is applied: disable the affected feature, apply WAF rules, or restrict access via network ACLs.

🔍 Detection

Search webserver/proxy logs for unusual POST /api/start_research requests with malformed payloads or SQL meta-characters. Run grep -r 'local-deep-research' . against your dependency files (package-lock.json, requirements.txt, go.sum) to find affected services.

Response actions

Concrete steps and command examples for SOC/SRE teams to execute in order

  1. 1
    Identify exposure identify
    grep -r 'local-deep-research' . | grep -v node_modules

    リポジトリと本番環境の依存ファイル (package-lock.json / requirements.txt / go.sum / Gemfile.lock 等) で local-deep-research を grep し、稼働しているサービス・バージョンを把握する。

  2. 2
    Hunt for indicators of compromise detect
    grep 'POST /api/start_research' /var/log/nginx/access.log | grep -E '(unusual_payload|sqli_pattern)'

    アクセスログで POST /api/start_research への異常なリクエスト (不正な認証ヘッダ・SQLメタ文字)を過去 30〜90日分捜索。WAF/SIEM があれば該当パスのアラート発火履歴を確認。

  3. 3
    Apply patch patch
    Upgrade local-deep-research to 1.6.0

    ステージング環境で 1.6.0 に上げて回帰テスト → 本番反映。回帰テストはアプリの主要ハッピーパスと、Step 2 で見つけた異常検知の続報チェックを含めること。

  4. 4
    Post-deployment verification verify
    Replay attack against POST /api/start_research on staging to confirm patch closes the vector

    パッチ適用後、ステージングで PoC または同等の悪用パターンを再現して脆弱性が閉じたことを確認。本番では Step 2 と同じログクエリでアラート再発が無いか継続監視。

Affected packages

pip local-deep-research
[{"type":"ECOSYSTEM","events":[{"introduced":"0"},{"fixed":"1.6.0"}]}]
PyPI local-deep-research
[{"type":"ECOSYSTEM","events":[{"introduced":"0"},{"fixed":"1.6.0"}]}]

References

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