Prompt injection testing
Direct and indirect injection through documents, web content, emails and tool responses.
Governance & Trust
Attack it yourself, on a schedule, before someone else does.
The problem we solve
AI systems expand the attack surface in ways traditional testing misses: untrusted content becomes instructions, tools become capabilities, and retrieval becomes an exfiltration path. We test those paths deliberately and fix what we find.
Direct and indirect injection through documents, web content, emails and tool responses.
Attempts to pull cross-tenant, cross-permission or confidential content through retrieval and tool chains.
Tool misuse, privilege chaining, loop and spend attacks against agents with real capabilities.
Input isolation, output filtering, allow-listed tools, spend caps and permission-aware retrieval implemented, not just recommended.
Adversarial suites in CI plus scheduled re-testing as models and prompts change.
How the engagement runs
Threat modelling across data, tools, identities and trust boundaries.
Manual and automated adversarial testing with findings triaged as they land.
Mitigation implementation, retest and CI suite handover.
Common questions
Related practices
Model registry, risk classification, documentation and audit trails mapped to the EU AI Act, ISO 42001 and internal policy.
ViewPII handling, retention, minimisation and EU/North American residency designed in rather than retrofitted.
ViewThird-party review of models, vendors and controls — an objective read for boards and risk committees.
ViewA 45-minute briefing with the people who would run the work — scope, timeline and a straight answer on whether it is the right next step.