Learn CrewAI by building a real-world CTF challenge solver
I got tired of manually running steghide, binwalk, exiftool, and strings on every CTF challenge. After spending an hour on a challenge that turned out to be basic LSB steganography, I realized this workflow could be automated.
But instead of writing a bash script, I used this as an opportunity to learn CrewAI and multi-agent systems. This project is both a functional CTF solver and a complete learning resource for anyone wanting to understand how AI agents work together.
If you're new to CrewAI or multi-agent systems, this is a practical way to learn. If you're a CTF player, you'll get a tool that actually works.
A 5-agent system that automatically analyzes suspicious files and extracts hidden data:
Suspicious File → [AI Agent Team] → Solution + Flag
Agent Team:
- Reconnaissance Agent - File analysis and metadata extraction
- Steganography Expert - Runs steghide, binwalk, zsteg, etc.
- Pattern Hunter - Detects encodings, patterns, anomalies
- Decoder Agent - Base64, hex, ROT13, XOR decoding
- Orchestrator - Coordinates results and generates reports
Each agent specializes in one aspect of the challenge, then shares findings with the team. Sequential workflow ensures agents build on each other's discoveries.
8 lessons taking you from zero to a complete working system:
| Lesson | Topic | Time | Status |
|---|---|---|---|
| Lesson 1 | Multi-Agent Systems Concepts | 1-2h | Ready |
| Lesson 2 | Environment Setup | 1-2h | Ready |
| Lesson 3 | Your First Agent | 2-3h | Ready |
| Lesson 4 | Custom Tools | 2-3h | Ready |
| Lesson 5 | Multi-Agent Coordination | 3-4h | Ready |
| Lesson 6 | Steganography Tools Integration | 3-4h | Ready |
| Lesson 7 | Complete MVP Build | 4-6h | Ready |
| Lesson 8 | Testing & Deployment | 2-3h | Ready |
Total time: 2-3 weeks part-time, 1 week full-time
Start here: LEARNING_GUIDE.md
You need:
- Basic Python (functions, classes, imports)
- Command line basics
- Text editor or IDE
You don't need:
- ML/AI experience
- Advanced Python
- Prior CrewAI knowledge
- CTF expertise
If you can write a Python function, you're ready.
Why CrewAI?
I evaluated AutoGPT, LangGraph, and CrewAI. CrewAI won because:
- Clean API for defining agents and tasks
- Built-in context sharing between agents
- Good tool integration patterns
- Active development and community
LangGraph offers more control but has a steeper learning curve. AutoGPT felt too opinionated for this use case.
Why Claude over GPT-4?
After testing both extensively:
- Claude handles tool-calling more reliably (in my experience)
- Better at following complex instructions
- Cheaper for development/testing
GPT-4 is faster but I hit more tool-calling errors. Your results may vary - the code works with both.
Steganography Tools:
- steghide - Password-protected embedding
- binwalk - File carving and analysis
- exiftool - Metadata extraction
- zsteg - PNG/BMP LSB analysis
- strings - Basic text extraction
All wrapped as CrewAI tools with proper error handling.
StegoCrew/
├── README.md ← You are here
├── LEARNING_GUIDE.md ← Start here
├── requirements.txt ← Dependencies
│
├── docs/
│ ├── GLOSSARY.md ← Terms explained
│ └── lessons/
│ ├── LESSON_01.md ← Concepts
│ ├── LESSON_02.md ← Setup
│ └── ... ← More lessons
│
├── examples/
│ ├── 01_first_agent.py ← Hello World agent
│ ├── 02_first_tool.py ← Custom tools
│ ├── ...
│ └── 06_complete_stegocrew.py ← Full system
│
├── tests/
│ ├── test_challenges.py ← Challenge tests
│ └── benchmark.py ← Performance tests
│
└── src/ ← Production structure
├── agents/
├── tools/
├── tasks/
└── main.py
- Clone the repo
- Read LEARNING_GUIDE.md
- Start with Lesson 1
- Work through each lesson sequentially
- Run the examples
- Build the complete system
Each lesson has:
- Concepts explained
- Working code examples
- Practice exercises
- Troubleshooting tips
Multi-Agent Systems:
- How agents communicate and share context
- Task delegation and workflow design
- Tool integration patterns
- Error handling across agents
CrewAI Specifics:
- Agent configuration (role, goal, backstory)
- Tool wrapping and @tool decorator
- Task creation and context chains
- Sequential vs. hierarchical workflows
Practical Skills:
- Integrating system tools with AI agents
- Building modular, maintainable agent systems
- Testing and debugging multi-agent workflows
- Real-world CTF steganography techniques
What this solves well:
- Basic steganography (LSB, file embedding, metadata)
- Common CTF challenge formats
- Standard encoding schemes
- Password-protected steghide (with wordlist)
What it struggles with:
- Advanced cryptography (that's not the goal)
- Custom/exotic steganography methods
- Challenges requiring domain-specific knowledge
- Highly obfuscated data
Expected success rate on beginner-intermediate CTF stego challenges: 60-80%
Once you complete the project, you can:
Extend StegoCrew:
- Add audio steganography (LSB in WAV files)
- Implement password brute-forcing
- Add machine learning for anomaly detection
- Build a web interface
Build Other Systems:
- Research assistants
- Code review agents
- Content creation pipelines
- Data analysis teams
The patterns you learn here transfer to any multi-agent system.
Documentation:
- LEARNING_GUIDE.md - Course roadmap
- GLOSSARY.md - Term definitions
- Lesson files - Step-by-step guides
- Code examples - Reference implementations
Troubleshooting:
- Check the glossary first
- Review previous lessons
- Run provided examples to verify setup
- Lesson 2 has common setup issues covered
Found a bug? Have an improvement? Contributions welcome.
See CONTRIBUTING.md for guidelines.
Common contributions:
- New steganography tool integrations
- Additional test challenges
- Documentation improvements
- Bug fixes
Educational project licensed under MIT. See LICENSE.
Use this for:
- Learning CTF techniques
- Authorized CTF competitions
- Educational demonstrations
- Personal skill development
Don't use for unauthorized access to systems or malicious purposes.
- CrewAI team for the framework
- CTF community for technique documentation
- Steganography tool developers
Ready to start? → LEARNING_GUIDE.md
Last Updated: 2025-11-06