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Control what the agent can do
AI agent hardening and control
Reduce unwanted actions and excessive permissions in an AI agent, and test what happens when something goes wrong.
From €12,500 excl. VAT · 3–5 weeks
Ask a question, no commitment
A good fit when
Teams with a concrete agent, an accessible repository and defined operational responsibilities.
The problem it solves
The agent works in ordinary tests, but malicious inputs, permissions, failures and recovery have not been checked adequately.
What you are actually buying
The findings, with any vulnerabilities ranked by risk, and the agreed fixes to address them.
Included activities
- Threat and action mapping
- Permission and tool review
- Adversarial tests
- Agreed plan/fixes
What we test
The classes that apply to your agent, within the agreed scope:
- Hidden instructions in emails, documents or pages the agent reads (direct and indirect prompt injection)
- Permissions and tools beyond what the task needs: unauthorised actions, access to other customers’ data or accounts
- Misuse of connected tools, including through MCP (the protocol that connects the agent to tools), and chains of actions that bypass controls
- Confidential data leaking into answers, logs or external systems
- High-impact actions, such as payments, refunds or data changes, without human confirmation
- Reconstructing failures: logs, traceability and recovery
Reference risk classes: OWASP Top 10 for agentic applications
What I need from you
- Repository and architecture
- Tools and credentials used
- Available logs or incidents
- Technical owner
How it works
- Review actions, access and permissions
- Test attempts to bypass controls
- Separate real risks from false alarms
- Verify fixes
How the work is verified
- Reproducible findings
- Controls linked to risk
- Regression tests for fixes
Who does the work
Fifteen years building software people rely on.
- 15+: years in software engineering
- Seed → IPO: product leadership through a public listing
- 3.2★ → 4.7★: App Store rating during the team's work at bunq
- SDA Bocconi: two sessions on applied and agentic AI
These results describe my experience. For your project, we define goals and measures around your company’s process.
Portfolio and roles · All services compared, with prices and next step
Scope limits
- One codebase or application
- Up to 3 tool/RAG boundaries
- Repository and test-environment access
- Not a certification or full infrastructure penetration test
What we do not promise
- Formal certification
- Full legal compliance review
- Security checks without a concrete attack scenario
Essential terms
Assessment and agreed fixes · Remote · one application or agent
50% at start · 30% on delivery of findings · 20% on retesting
Commercial tools, environments and travel excluded
One retest of agreed fixes within 30 days
Initial technical assessment within 2 business days
When the work is accepted
- Reproducible prioritised findings
- Fixes linked to risk
- Regression tests and declared residual risk
Terms
Related evidence
Limit what an AI agent can do, test its defences and reconstruct failures before trusting it with real data and operations.
B2B service. A request creates no commitment: price and scope become binding only in an accepted written proposal.