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AI-driven exploration

Explore attack paths with a controlled budget

AI exploration extends the diagnostic with adaptive hypotheses. You choose the cap before launch; the agent stops automatically when it is reached.

Security, with a methodDocumented scopeExplicit limitsPractical advice
01

A bounded exploration, not a magic promise

The agent uses the available observations to choose which hypotheses to pursue. A higher budget gives it more time to explore and verify, but does not guarantee finding every vulnerability or absolute resistance.

The amount measures the maximum effort allocated to this run. It should not be presented as a financial value of the company’s security.

02

Essential safeguards

Any offensive exploration must target an authorized system. The domain is verified, the scope is recorded and risky tests should be avoided on real data. A realistic staging environment lets you go further without exposing users.

  • Authorization and ownership of the target
  • Budget and limits defined before the run
  • Logging of who launched what and when
  • Sensitive report protected, with a limited retention period
03

AI and human expertise are complementary

An agent can repeat explorations and quickly correlate several signals. A human expert brings business judgment, adapts scenarios, settles an ambiguous impact and takes responsibility for a scoped engagement. For a critical stake, use the automated result as preparation, not as a silent substitute.

Frequently asked questions

Move forward with the right answers.

Scope, method and limits: what you need to know to make your choice.

What happens when the budget is reached?

The exploration stops automatically. The report reflects what was run within that limit and does not claim to cover leads that were not explored.

Does a high budget guarantee there are no flaws?

No. It allows a deeper exploration, but no analysis can guarantee the absence of vulnerabilities.

Should production be used?

A representative staging environment is recommended for active testing. A production target requires stricter scoping and a prior risk assessment.

Go further

Keep exploring.

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Put it into practice

A first step toward a safer application.

Choose your GitHub repositories and get a clear first diagnosis. Your code is accessed read-only.

Choose an analysis depth

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