AI Agent Security
Security reviews of AI agents that call tools, browse, read documents and take actions — where prompt injection becomes real-world impact.
What I deliver
- Agent threat modeling: tools, data sources, permissions
- Indirect prompt injection through documents, web pages and tool output
- Excessive agency and unsafe tool chaining
- Human-in-the-loop and approval design review
- Mapped to OWASP Top 10 for Agentic Applications and MITRE ATLAS
Step by step
- 01
Map the agent's tools, data and permissions
- 02
Threat-model who can influence its inputs
- 03
Attack with indirect prompt injection and tool abuse
- 04
Review approvals and least privilege
- 05
Re-test in CI after every change
Selected engagements
From my work at BERRY9 IT Services, as a freelancer, at CRIS InfoTech and Hacktr Technologies, and my own tools and research.
AI attack & pentest agent (self-built) — recon, scanning and exploit validation with human approval before any exploitation
MCP server and agentic AI reviews — tool poisoning, excessive permissions and insecure data flows
Top bugs I hunt — and the steps
The recurring weaknesses I see in this domain, with the repeatable workflow I run from discovery to fix.
- STEP 1Plant instructions in content the agent will read (email, PDF, web page)
- STEP 2Watch whether the agent follows them and calls tools
- STEP 3Prove impact: data sent out, records changed
- STEP 4Fix: separate trusted instructions from untrusted data, approval for sensitive tools