Prompt-injection testing
Probe direct and indirect instructions across multi-turn workflows.
AI system security
Test the system around the model.
Assess prompts, retrieval, tools, identities, and application logic together—because real AI attacks cross boundaries a model-only test cannot see.
The operating gap
AI risk lives across an interconnected system.
Prompt behavior matters, but so do retrieval permissions, tool authorization, sensitive context, application workflows, and the APIs behind them.
Capabilities
Built around the work your team owns.
One evidence trail from test to assurance.
Retrieval boundary testing
Assess document access, tenant isolation, poisoning, and sensitive context exposure.
Tool and agent abuse
Test whether actions can exceed the user, role, or workflow authorization boundary.
End-to-end attack paths
Connect AI behavior with application, API, identity, and cloud weaknesses.
Workflow
A clear path from scope to closure.
One approved objective. One record.
- 01
Model
Map prompts, retrieval sources, tools, identities, and trust boundaries.
- 02
Challenge
Run focused adversarial missions against approved scenarios.
- 03
Chain
Follow successful behaviors into downstream systems and actions.
- 04
Validate
Reproduce impact and package evidence for the owning team.
Evidence
Give every stakeholder the proof they need.
Technical depth for testers. Clear outcomes for leaders.
Governance and safety
Autonomy inside explicit boundaries.
Define where DeepScan can operate, how it validates, and who reviews the evidence.
- Approved scenarios
- Tool allowlists
- Data-handling boundaries
- Non-destructive validation
- Human review
- Complete trace history
Questions
How this solution fits your program.
Practical answers about scope, delivery, evidence, and ownership.
Is this only prompt-injection testing?
No. DeepScan treats prompts, retrieval, tools, application logic, APIs, and identity as one connected attack surface.
Can it test agentic workflows?
Yes. Testing can assess tool use, chained actions, excessive agency, and authorization boundaries within the approved scope.
How is sensitive data handled?
Teams define data and execution boundaries, while user-facing evidence passes through secret-redaction controls.
Start with proof
Put validated proof into your next security decision.
Start with an approved target.