Self-learning prompt injection detection engine — 25 input detectors (10 languages), 5 output scanners, PII redaction, red team self-testing, F1: 96.0% with 0% false positives. Docker, GitHub Action, pre-commit, FastAPI/Flask/Django/LangChain/CrewAI/Dify/n8n.
推荐理由
README 将它定位为「Self-learning prompt injection detection engine — 25 input detectors (10 languages), 5 output scanners, PII redaction, red team self-testing, F1: 96.0% with 0% false positives」,核心痛点是把 prompt 技巧、模板和工作流沉淀成可复用资产。它有一定社区验证,同时仍保留发现潜力,license 清晰,主要技术栈是 Python,适合作为「AI agent 工具链」的候选项目。
注意事项
项目还偏早期,需要重点验证核心路径是否稳定;README 摘要信息有限,发布前建议再人工扫一遍文档;展示前建议跑通 README quickstart,并确认部署成本、外部依赖和数据安全边界。