AI-assisted pentesting: more coverage in less time
AI does not replace the pentester: it makes them more effective. We combine AI tooling with the judgment of our experts to deliver faster audits, with broader coverage and lower cost.
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How does AI improve traditional pentesting?
Traditional tools generate noise: thousands of findings in which false positives and low-relevance alerts vastly outnumber the genuinely exploitable vulnerabilities. AI lets us prioritize automatically, generate adaptive payloads, analyze large volumes of source code in minutes and correlate findings to identify attack chains. The result: more real vulnerabilities in less time.
How we apply AI to pentesting
- Automated source-code analysis with LLMs for vulnerability detection
- Generation of adaptive payloads for injection and business-logic testing
- Intelligent prioritization of findings by real impact (not theoretical CVSS)
- Automatic correlation of vulnerabilities to identify attack chains
- Accelerated reconnaissance: enumeration, subdomains, exposed services
- Dependency and CVE analysis in real time during the test
- Intelligent fuzzing of APIs and web applications
- Report generation with automated business context
Hybrid AI + human methodology
- AI-assisted reconnaissance: We automate reconnaissance and enumeration with AI to cover the entire attack surface in less time.
- Analysis and prioritization: AI models classify and prioritize attack vectors. Our experts validate them and add business context.
- Human-led exploitation: Exploiting complex vulnerabilities, business logic and chaining attacks together requires human judgment. This is where the expert makes the difference.
- Post-exploitation and escalation: AI-guided lateral movement and privilege escalation, validated manually.
- Intelligent reporting: A report generated with AI assistance and reviewed by experts: prioritized by real impact with business context.
Deliverables
- Executive report prioritized by business impact
- Technical report with a PoC for each real finding
- Coverage analysis: percentage of the attack surface assessed
- Efficiency comparison vs. traditional pentesting
- Retest included
Use cases
- Complex web applications that require exhaustive coverage within a limited timeframe
- Pre-launch security reviews with tight deadlines
- Source-code audits of large repositories
- Companies seeking the best coverage/cost ratio in their assessments
- Bug bounty programs that need a systematic starting point
Frequently asked questions
Is AI-powered pentesting as rigorous as manual testing?
It is more rigorous in coverage (AI does not tire and never skips steps) and less so in pure creativity. That is why we combine both: AI guarantees systematic coverage while the human expert brings creativity, context and advanced exploitation.
Which AI tools do you use?
We combine proprietary tooling with recognized industry solutions, tailored to each type of assessment. We do not rely on a single vendor or on generic AI tools that have not been validated for security work.
Is it cheaper than traditional pentesting?
Generally yes, because automation reduces the hours spent on manual reconnaissance. But the main value is not the cost: it is the broader coverage achieved in the same amount of time.
How do you avoid the false positives AI produces?
No finding reaches the report without manual validation. AI widens reconnaissance coverage and groups evidence, but confirming that something is exploitable is done by a pentester reproducing the attack. A report full of false positives makes the development team stop reading it, and that costs more than not automating at all.
Is our data sent to third-party models?
Not without prior written agreement. Scope, tooling and data handling are agreed before the engagement starts. When an exercise requires processing sensitive client information, where it is processed and under what conditions is agreed in advance and written into the contract alongside the NDA.
Which part of the work is still human?
The part that decides. AI speeds up reconnaissance, data correlation and initial prioritization; the pentester defines scope, designs the attack chains, exploits business logic and judges real impact on your operations. Broken business logic remains the finding no tool discovers on its own, because it requires understanding what the company actually does.
Related resources
- AI-powered pentesting: how the methodology changes
- Penetration testing services for businesses: web, APIs, network, cloud and mobile
Ready to protect your business?
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