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.

Focused capabilities connect exploration, validation, remediation, and assurance without splitting the evidence trail.

01

Prompt-injection testing

Probe direct and indirect instructions across multi-turn workflows.

02

Retrieval boundary testing

Assess document access, tenant isolation, poisoning, and sensitive context exposure.

03

Tool and agent abuse

Test whether actions can exceed the user, role, or workflow authorization boundary.

04

End-to-end attack paths

Connect AI behavior with application, API, identity, and cloud weaknesses.

Workflow

A clear path from scope to closure.

Every step stays connected to the same approved objective and evidence record.

  1. 01

    Model

    Map prompts, retrieval sources, tools, identities, and trust boundaries.

  2. 02

    Challenge

    Run focused adversarial missions against approved scenarios.

  3. 03

    Chain

    Follow successful behaviors into downstream systems and actions.

  4. 04

    Validate

    Reproduce impact and package evidence for the owning team.

Evidence

Give every stakeholder the proof they need.

Keep technical depth for practitioners while preserving an outcome-focused view for leaders and reviewers.

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 and keep the full path from test to closure.

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