GitHub repository documents 16 prompt injection techniques and defense strategies for public AI chats
A developer built a custom AI chat on their website as an experiment and encountered multiple security challenges when real users attempted to break it. The experience prompted the creation of a comprehensive security guide available on GitHub.
Security challenges encountered
Users attempted various attacks including:
- Prompt injection
- Roleplay attacks
- Multilingual tricks
- Base64 encoded payloads
Defense strategies implemented
The developer documented a defense-in-depth approach covering:
- Input sanitization
- Rate limiting
- Zero-trust system prompt design
- Output controls
- Cost caps
GitHub repository contents
The repository includes:
- A breakdown of 16 prompt injection techniques
- A Claude code skill that automatically tests all 16 techniques against your chatbot
- Full defense implementation details
The developer notes that users tried things they "never would have thought to test" and that the guide is intended to be useful for anyone implementing similar public AI chat systems.
📖 Read the full source: r/ClaudeAI
👀 See Also
Threat data from 91K AI agent interactions: Tool abuse up 6.4%, new multimodal attacks
Analysis of 91,284 AI agent interactions from February 2026 shows tool/command abuse increased 6.4% to 14.5%, with tool chain escalation as the dominant pattern. RAG poisoning shifted to metadata attacks (12.0%), and multimodal injection via images/PDFs emerged at 2.3%.
KnightClaw: Local Security Extension for OpenClaw Agents
KnightClaw is a drop-in extension that intercepts messages before they reach OpenClaw agents, providing an 8-layer hybrid detection system and egress redaction. It runs entirely local with zero telemetry and is MIT licensed.
AI Vulnerability Discovery Outpacing Patch Deployment Times
A security expert argues that AI tools like Mythos will find vulnerabilities faster than fixes can be deployed, citing Log4j data showing average remediation times of 17 days and a decade-long elimination timeline.
AgentSeal Security Scan Finds AI Agent Risks in Blender MCP Server
AgentSeal scanned the Blender MCP server (17k stars) and identified several security issues relevant to AI agents, including arbitrary Python execution, potential file exfiltration chains, and prompt injection patterns in tool descriptions.