𝗕𝘂𝗶𝗹𝗱𝗶𝗻𝗴 𝗔𝗴𝗲𝗻𝘁𝗚𝘂𝗮𝗿𝗱𝗶𝗮𝗻: 𝗔 𝗟𝗼𝗰𝗮𝗹 𝗙𝗶𝗿𝘀𝘁 𝗔𝗜 𝗦𝗲𝗰𝘂𝗿𝗶𝘁𝘆 𝗦𝗰𝗮𝗻𝗻𝗲𝗿

𝗕𝘂𝗶𝗹𝗱𝗶𝗻𝗴 𝗔𝗴𝗲𝗻𝘁𝗚𝘂𝗮𝗿𝗱𝗶𝗮𝗻: 𝗔 𝗟𝗼𝗰𝗮𝗹-𝗙𝗶𝗿𝘀𝘁 𝗔𝗜 𝗦𝗲𝗰𝘂𝗿𝗶𝘁𝘆 𝗦𝗰𝗮𝗻𝗻𝗲𝗿

AI agents now use tools. They access your email, files, and databases. This makes them useful. It also makes them risky.

How do you know if an AI agent is safe before you deploy it?

I built AgentGuardian. It is a web app to scan AI workflows for security risks.

It scans for:

• Prompt injection
• Tool misuse
• Data leaks
• Too much autonomy
• Lack of human oversight

How it works:

• You enter the agent name and purpose.
• You list the tools and data types it uses.
• A Python engine calculates a risk score from 0 to 100.
• A local LLM via Ollama explains the results.

Why a local approach?

• No external API keys are needed.
• Your sensitive data stays on your machine.
• It is private.

You get:

• A clear risk level from Low to Critical.
• A list of detected risks.
• Recommended safety controls.
• A downloadable security report.

AI agents need security reviews. AgentGuardian makes this process simple and clear.

Source: https://dev.to/codewithbg/building-agentguardian-a-local-first-security-scanner-for-agentic-ai-workflows-2gcn GitHub: https://github.com/zosob/AgentGuardian.git Optional learning community: https://t.me/GyaanSetuAi