Use Case

Autonomous Penetration Testing

Adversary tradecraft on autopilot — recon, chaining, and exploitation, continuously.

The problem

Think in attack paths, not alert lists.

Real breaches chain small issues — an exposed debug page plus a weak reset flow plus a verbose error — into full compromise. Tools that report issues in isolation never show you the path an attacker actually walks.

In practice
  • Tradecraft playbooks: agents execute recon, enumeration, and exploitation sequences modeled on real adversary behavior.
  • Chaining and pivoting: low-severity findings are combined to reveal reachable impact — the report shows paths, not piles.
  • Supervised autonomy: every agent action runs in scope with guardrails, escalating to humans on high-impact moves.
How it runs
1 Recon see what attackers see 2 Chain & exploit combine weaknesses 3 Report paths impact, proven
Where it fits
Enterprise

Beyond the annual test

Adversary-grade pressure between formal engagements — no more quiet quarters.

Providers

Augmented red teams

Human testers aim where agents already mapped — leverage per expert multiplies.

Fintech

Targeted-attack readiness

High-value targets rehearsed against the exact tradecraft aimed at them.

See it on your own stack

Request a demo and watch Foctos AI agents test a live target in real time.

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