Yesterday a build shipped that flips the usual AI security workflow upside down.
The standard move: deploy your agent, wait for something to break in production, then patch it. Shark (shark.fencio.dev) reverses that. You break your agent on purpose first, get a full map of where it fails, and fix it before it ships.
The twist is what happens after the assessment. Devs get specific remediation steps tied to each vulnerability. Enterprise teams get something more interesting: those vulnerabilities get converted into deterministic rules enforced at runtime. Not suggestions. Hard rules baked into the agent’s behavior in production.
How to run your first red team:
- 🔗 Go to shark.fencio.dev
- 🎯 Run the assessment against your agent
- 📋 Review the vulnerability map (where it breaks vs. where it holds)
- 🔧 Follow the remediation steps for each failure point
- For enterprise teams: convert findings into deterministic production rules
Pro tip: Run this before every major feature update, not just at launch. Agent behavior shifts when you add tools or expand context windows. What held at v1 might crack at v2.
If you’re building agents that touch anything real (money, data, users), knowing your failure points before attackers do isn’t optional. Go break your agent on purpose and see what you find. 🚀
red teaming assessment for ai agents
by u/OneSafe8149 in PromptEngineering