Privacy by Design | Security Research | AI-Assisted Analysis | Post-Quantum Ready

Darkelf Labs is the home of the Darkelf ecosystem---an open collection of privacy-focused browsers, OSINT tools, AI-assisted utilities, and security research projects designed for cybersecurity professionals, researchers, developers, and privacy-conscious users.

🌐 Website: Darkelf Browser 🧠 Documentation & Guides: Darkelf-Docs

Darkelf Labs is not a single application---it is a unified ecosystem of software focused on:

• Privacy-first browsing
• Security research
• Digital forensics
• Open Source Intelligence (OSINT)
• AI-assisted investigation
• Experimental post-quantum technologies

Each project is developed independently while sharing common security and privacy principles.

Enterprise-focused browser designed for security professionals and specialized research environments.

Cross-platform hardened browser focused on privacy, security, and anonymous research.

Current Release: v7.0.3 (macOS & PyPI)

Linux and Windows editions are planned.

Native macOS edition built specifically for Apple's WebKit ecosystem.

Secure command-line utilities including Tor helpers, secure deletion tools, networking utilities, and security automation.

Local AI-assisted OSINT toolkit featuring:

• Local Ollama integration
• Intelligence analysis
• Investigation workflows
• Case management
• Indicator extraction
• Report generation

Lightweight OSINT utilities for quick investigations and analysis.

Experimental research environment for testing new ideas, prototypes, and advanced command-line tooling.

Legacy utilities, historical projects, and compatibility tools.

The central documentation repository containing:

• Architecture
• Documentation
• Security design
• Development guides
• Project roadmap

Local browser monitoring system that:

• Detects suspicious behavior
• Monitors tracking attempts
• Detects automation indicators
• Operates entirely on-device

Designed around integrity verification using technologies such as:

• SHA3-512 request fingerprinting
• Session integrity validation
• TLS trust consistency monitoring (TOFU)

Local AI integration using Ollama for:

• Offline analysis
• OSINT assistance
• Investigation summaries
• Privacy-preserving workflows

• Privacy by Design
• Ephemeral Execution
• Local Processing
• Isolation by Default
• Minimal Attack Surface
• Transparency

Privacy should be enforced by architecture---not by relying solely on user configuration.

• Memory-oriented browsing sessions
• Tracker reduction
• Telemetry reduction
• Fingerprinting detection
• Anonymous research support

• Tracking detection
• Suspicious activity monitoring
• Local threat assessment
• Session monitoring

• SHA3-512 integrity verification
• TLS consistency monitoring
• Session validation
• Optional post-quantum research components

• Session lockdown during significant anomalies
• Controlled recovery mechanisms
• Passive monitoring without modifying user traffic

• Python
• PySide6
• PyObjC
• QtWebEngine
• WebKit
• HTML / CSS
• Ollama
• Tor
• Post-Quantum Cryptography (research)

• 🔴 Darkelf RedSec --- Enterprise security browser (Private / Under Revision)
• 🌑 Darkelf Shadow --- Hardened privacy browser
• 🍫 Darkelf Cocoa --- Native macOS browser

• 🧰 Darkelf CLI Tools
• 🤖 Darkelf OSINT AI
• 🧪 Darkelf CLI Research Suite
• 🔎 Darkelf OSINT Toolkit Lite
• 🕹️ Darkelf Retro CLI Hub

• 🌐 Darkelf Browser Website
• 🧠 Documentation & Developer Guides

Darkelf Labs software is intended for:

• Cybersecurity research
• Digital forensics
• OSINT investigations
• Educational use
• Software development
• Academic research

Some projects include privacy-enhancing or security-testing capabilities that may attract the attention of security software. Users are responsible for ensuring their use complies with applicable laws, regulations, and organizational policies.

Unless otherwise stated:

• Documentation --- LGPL-3.0-or-later
• Browser Projects --- LGPL-3.0-or-later
• CLI Tools --- LGPL-3.0-or-later

Individual repositories may contain additional licensing information for third-party dependencies.

Darkelf Labs brings together a growing ecosystem of open-source software focused on:

• Privacy-first browsing
• AI-assisted security research
• Open Source Intelligence
• Local threat detection
• Security experimentation
• Post-quantum research
• Open development

Built for researchers, developers, educators, and security professionals who value privacy, transparency, and practical security engineering.