AI工作流 是 AI Skill Hub 本期精选Agent工作流之一。综合评分 7.5 分,整体质量较高。我们推荐使用将其纳入你的 AI 工具库,帮助提升工作效率。
AI工作流 是一套完整的 AI Agent 自动化工作流方案。通过可视化的节点编排,将复杂的多步骤任务拆解为清晰的自动化流程,实现全程无人值守的智能处理。支持与数百种外部服务和 API 无缝集成,适合构建数据处理管线、业务自动化和 AI 辅助决策系统。
AI工作流 是一套完整的 AI Agent 自动化工作流方案。通过可视化的节点编排,将复杂的多步骤任务拆解为清晰的自动化流程,实现全程无人值守的智能处理。支持与数百种外部服务和 API 无缝集成,适合构建数据处理管线、业务自动化和 AI 辅助决策系统。
# 方式一:pip 安装(推荐)
pip install crucible
# 方式二:虚拟环境安装(推荐生产环境)
python -m venv .venv
source .venv/bin/activate # Windows: .venv\Scripts\activate
pip install crucible
# 方式三:从源码安装(获取最新功能)
git clone https://github.com/crucible-security/crucible
cd crucible
pip install -e .
# 验证安装
python -c "import crucible; print('安装成功')"
# 命令行使用
crucible --help
# 基本用法
crucible input_file -o output_file
# Python 代码中调用
import crucible
# 示例
result = crucible.process("input")
print(result)
# crucible 配置文件示例(config.yml) app: name: "crucible" debug: false log_level: "INFO" # 运行时指定配置文件 crucible --config config.yml # 或通过环境变量配置 export CRUCIBLE_API_KEY="your-key" export CRUCIBLE_OUTPUT_DIR="./output"
<p align="center"> <pre align="center"> ██████╗██████╗ ██╗ ██╗ ██████╗██╗██████╗ ██╗ ███████╗ ██╔════╝██╔══██╗██║ ██║██╔════╝██║██╔══██╗██║ ██╔════╝ ██║ ██████╔╝██║ ██║██║ ██║██████╔╝██║ █████╗ ██║ ██╔══██╗██║ ██║██║ ██║██╔══██╗██║ ██╔══╝ ╚██████╗██║ ██║╚██████╔╝╚██████╗██║██████╔╝███████╗███████╗ ╚═════╝╚═╝ ╚═╝ ╚═════╝ ╚═════╝╚═╝╚═════╝ ╚══════╝╚══════╝ </pre> <em>pytest for AI agents -- test, score, and harden before production</em> </p>
pip install crucible-security
🆕 New to AI security? Read our Beginner's Getting Started Guide.
crucible init --target https://my-agent.com/api/chat
crucible scan --target https://my-agent.com/api/chat
crucible report crucible-report.json
One command. 90 attacks. Beautiful report.
We provide several example scripts in the examples/ directory to help you get started:
| Script | Framework | Description |
|---|---|---|
test_openai_agent.py | OpenAI Chat Completions | Scan a raw OpenAI /chat/completions endpoint |
test_langchain_agent.py | LangChain (LangServe) | Scan a LangChain ReAct agent with OWASP LLM Top 10 mapping |
test_openai_assistant.py | OpenAI Assistants API | Scan an Assistants API wrapper endpoint |
All examples use respx to mock HTTP calls so they pass CI without a live server.
Running the LangChain Example:
python examples/test_langchain_agent.py
Running the OpenAI Assistant Example:
python examples/test_openai_assistant.py
crucible init --target URL --provider openai --key sk-xxx
```bash
| Module | Attacks | Status | OWASP Coverage |
|---|---|---|---|
| Prompt Injection | 50 | ✅ Live | LLM01, LLM07 |
| Goal Hijacking | 20 | ✅ Live | Agentic #1 |
| Jailbreaks | 20 | ✅ Live | LLM01, LLM06 |
| Enterprise Graph | 10 | ✅ Live | Agentic #2, #4 |
| Memory Poisoning | 8 | ✅ Live | Agentic #5 |
| Infrastructure Escalation | 5 | ✅ Live | LLM06, SSRF |
| Advanced Orchestration | 4 | ✅ Live | Agentic #3 |
| MCP Security | 5 | ✅ Live | Agentic #3 |
| **MCP Server Scan** | **10** | **✅ Live (v0.4)** | **MCP-001 – MCP-005** |
| Behavioral Drift | multi-turn | ✅ Live (v0.3) | Agentic #1, #2 |
| Multi-turn Attacks | strategies | ✅ Live (v0.3) | LLM01, Agentic #1 |
| Deep Research Engine | autonomous | ✅ Live (v0.4) | AI Research |
| Multi-Agent Contagion | orchestration | ✅ Live (v0.4) | Agentic #2, #3 |
Add to your CI/CD in 3 lines:
```yaml
- uses: actions/checkout@v4 - run: pip install crucible-security - run: crucible scan --target ${{ secrets.AGENT_URL }} --fail-on CRITICAL ```
Does Crucible send my agent data to your servers? No. Crucible is a local CLI. Payloads go directly from your machine to your agent. Nothing passes through Crucible infrastructure. Zero data retention. Fully air-gappable.
Which agent frameworks does Crucible support? Any agent that accepts HTTP requests — LangChain, AutoGen, CrewAI, OpenAI Assistants, Bedrock, custom FastAPI agents.
How long does a full scan take? Under 60 seconds for 90 attacks using async parallel execution.
Can I add custom attack vectors? Yes. See CONTRIBUTING.md for how to submit new attack modules via PR.
Is this safe to run against production? Run against staging environments, not production. Crucible sends adversarial payloads that may cause unexpected behavior.
What does Grade F mean? Your agent complied with most attacks. It is vulnerable to prompt injection, jailbreaks, or goal hijacking. Review Critical findings first.
Why is the module called goal_hijacking if goal hijacking is an impact, not an attack? Crucible modules are named by the security impact they surface, not the attack vector. The underlying attack vector for most modules is prompt injection delivered in specialised forms. This naming convention helps security engineers quickly identify which risks each module addresses (e.g., searching for "goal hijacking" finds the right module immediately). See docs/owasp_mapping.md for the full attack vector → impact mapping.
Questions not answered here? Join our Discord or email crucible.sec@gmail.com
高质量的AI工作流项目
AI Skill Hub 为第三方内容聚合平台,本页面信息基于公开数据整理,不对工具功能和质量作任何法律背书。
建议在沙箱或测试环境中充分验证后,再部署至生产环境,并做好必要的安全评估。
✅ Apache 2.0 — 宽松开源协议,可商用,需保留版权声明和 NOTICE 文件,含专利授权条款。
经综合评估,AI工作流 在Agent工作流赛道中表现稳健,质量良好。如果你已有明确的使用需求,可以直接上手体验;如果还在评估阶段,建议对比同类工具后再做决策。
| 原始名称 | crucible |
| 原始描述 | 开源AI工作流:pytest for AI agents - Autonomous red-teaming, behavioral monitoring & security 。⭐41 · Python |
| Topics | ai-agentsai-securityllmowaspprompt-injection |
| GitHub | https://github.com/crucible-security/crucible |
| License | Apache-2.0 |
| 语言 | Python |
收录时间:2026-05-28 · 更新时间:2026-05-30 · License:Apache-2.0 · AI Skill Hub 不对第三方内容的准确性作法律背书。
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