Our AI & technology
Three proprietary machine-learning engines. Purpose-built offensive security models. A platform developed by PenetraTech to connect testing, evidence and the decisions that follow.
Developed by PenetraTech
Our proprietary ML engines work with larger AI models where they add value. Together, they support the practical work of an assessment: discovering the attack surface, generating tests, analysing responses and capturing evidence.
What the AI does
Each stage has a practical purpose: understand the target, test its behaviour and give your team findings they can investigate.
Identify hosts, services and application entry points within the assessment scope. Build the target context that guides testing across your applications, APIs and networks.
Use the target's structure, access and observed behaviour to generate tests relevant to the environment. Execution stays within the scope and conditions set for the assessment.
Analyse test responses and observed behaviour for potential issues. Bring the supporting observations together so your team can investigate the finding and assess its significance.
Keep findings connected to the requests, responses and technical detail behind them. Turn assessment results into reports your team can review, edit and share.
Intelligence you can use
APE connects offensive security knowledge with your assessment context. Explore what a finding means, why it matters and what to investigate or address next.
“Where is the authorisation check failing, and what should our developers change?”
Human-led by design
People define the scope, approve sensitive actions and retain the final security judgment. Run the assessment with your own team, or work with our specialists through managed pentesting.
Explore our approachLet’s move forward
Explore the platform, the assessment workflow and the technology behind it in a focused demonstration.
