🔍 Darkelf Research Suite
Privacy-Focused CLI Research & OSINT Toolkit
Darkelf Research Suite is a modern command-line research environment designed for investigators, security professionals, students, and OSINT practitioners. It combines web research, domain intelligence, Tor integration, Internet Archive access, AI-assisted analysis, and browser utilities into a single cross-platform terminal application.
Features
- 🌐 DuckDuckGo Lite web search
- 🧅 Optional Tor network integration
- 🔒 Isolated Tor data directory
- 🤖 Optional Ollama AI research assistant
- 📚 Internet Archive search
- 🌍 WHOIS domain lookup
- 🌐 DNS record inspection
- 🔁 Reverse DNS lookup
- 📄 Save webpages as PDF
- 📑 HTML page snapshots
- 📂 Multi-tab terminal browser
- 🔖 Persistent bookmarks
- 📜 Search history
- 🛡️ HTTP header inspection
- 🧹 Cache, history, and session cleanup
- 🖥️ Cross-platform support (Windows, macOS, Linux)
Installation
Install from PyPI
pip install darkelf-research-suite
Launch:
darkelf-research
or
python -m darkelf_research_suite
Optional Components
Certain features require optional software.
Tor
Tor is only required for Onion browsing and anonymous routing.
Install Tor:
- macOS (Homebrew)
brew install tor
- Ubuntu
sudo apt install tor
- Windows
Install the official Tor Expert Bundle or Tor Browser.
If Tor is unavailable, Darkelf Research Suite continues operating normally with Onion features disabled.
Ollama AI
AI-assisted research requires Ollama.
Install from:
Example:
ollama pull mistral
If Ollama is not installed, all other functionality remains available.
Main Menu
Darkelf Research Suite includes:
- Web OSINT Search
- AI Research Assistant
- Internet Archive Research
- Multi-tab Browser
- Search History
- HTTP Header Inspector
- WHOIS Lookup
- DNS Lookup
- Reverse DNS
- Onion Browser
- Bookmarks
- User-Agent Switching
- PDF Export
- Tor Identity Rotation
- Tor Management
- Cache & History Wipe
Privacy
Darkelf Research Suite is designed with privacy in mind.
- No telemetry
- No analytics
- No cloud account required
- Tor support is optional
- AI is optional
- Local bookmark storage
- Local search history
- User-controlled data
Supported Platforms
- macOS
- Linux
- Windows
Python 3.11+
Dependencies
Core dependencies include:
- requests
- beautifulsoup4
- rich
- stem
- dnspython
- python-whois
- tldextract
- weasyprint
- pdfkit
- pyperclip
Optional:
- Tor
- Ollama
Security Notice
Darkelf Research Suite is intended for:
- Open Source Intelligence (OSINT)
- Security research
- Digital investigations
- Educational purposes
- Defensive cybersecurity
Users are responsible for ensuring they have authorization before investigating systems, services, or data.
License
Licensed under the GNU Lesser General Public License v3.0 (LGPL-3.0-or-later).
See the LICENSE.md file for details.
Author
Dr. Kevin Moore
Creator and Lead Developer of the Darkelf Project
Disclaimer
Darkelf Research Suite is provided "as is" without warranty of any kind. The authors assume no liability for misuse, damages, or violations of applicable laws resulting from use of this software.
Metadata
Release files for darkelf-research 2.3.2
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| darkelf_research-2.3.2.tar.gz | 20.6 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| darkelf_research-2.3.2-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 41.7 kB
Release files / darkelf_research-2.3.2.tar.gz
| Download URL | darkelf_research-2.3.2.tar.gz |
|---|---|
| Size | 20.6 kB |
| Tags | Source |
|
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Yes |
| Uploaded via |
twine/6.1.0 CPython/3.13.14
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Signed by GitHub Actions, verified by PyPI on Jul 21, 2026.
Transparency logRelease files / darkelf_research-2.3.2-py3-none-any.whl
| Download URL | darkelf_research-2.3.2-py3-none-any.whl |
|---|---|
| Size | 21.1 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
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BLAKE2b-256 checksum How to use checksums |
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| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
twine/6.1.0 CPython/3.13.14
|
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
PyPI Publish Attestation
PyPI verified that this artifact, at this checksum, originated from the publisher listed below.
Signed by GitHub Actions, verified by PyPI on Jul 21, 2026.
Transparency log