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AI pentest: agents that search, a tester who proves

AI agents explore your application or network more widely than a traditional assessment. A certified penetration tester reproduces every vulnerability before it enters the report. You get the coverage of automation with the reliability of a manual test.

Engagement log, HackHeart agents
  1. engagement start --target url1 --mode non-destructive
  2. recon214 endpoints, 4 roles, 2 APIs
  3. analysis11 attack hypotheses generated
  4. analysispossible IDOR on /api/invoices/{id}
  5. analysispossible SQL injection on /search
  6. adversarySQLi: HTTP 500, not exploitable
  7. adversaryIDOR holds: third-party invoice read
  8. humanIDOR reproduced, CVSS 6.5 confirmed
  9. report1 finding, 1 false positive dropped signed
Typical run, fictitious data. The target is pseudonymised (url1) before any model processing.
CPTS, CAPE and CRTA certified
Hack The Box and CyberWarFare Labs
More than 60 engagements
web, infrastructure, Purple Team
No destructive testing
restricted agents, locked scope
Pseudonymised data
no client IP, URL or identifier in clear, verifiable

By Sébastien De Coninck, founder of HackHeart. Updated .

In short

An AI pentest is a penetration test in which artificial intelligence agents automate part of the offensive work (reconnaissance, analysis, attack hypotheses, reporting) under the control of a human penetration tester who validates every finding, supervises risky actions and signs the report. At HackHeart, this hybrid approach covers more attack surface in less time without sacrificing the reliability of a manual assessment.

Why AI changes penetration testing

A traditional pentest is bounded by time. On a five-day engagement, a large share goes into repetitive work: enumeration, triaging tool output, reading HTTP responses, formatting the report. Large language models can now read source code, interpret server responses, suggest exploitation paths and document a finding. Used well, they free human time for what matters most: business logic flaws, creative attack chains and impact analysis.

Used without control, they also produce false positives, invented vulnerabilities and occasionally actions that harm production. That is why HackHeart does not sell a "fully automated pentest" but an augmented pentest: AI is the accelerator, the certified tester is the guarantor.

From 214 tested entry points to one proven vulnerability

The value of an AI pentest is not how many alerts it raises but what it rules out. Each stage filters the previous one, and only what a human has reproduced reaches the report.

  1. 214entry points exploredreconnaissance agents
  2. 11attack hypotheses testedanalysis agents
  3. 2findings sent for counter-reviewadversarial agent
  4. 1vulnerability reproduced and signedcertified tester
Typical web application engagement, illustrative figures. Volumes vary with scope.

What the AI actually does during an engagement

Broader reconnaissance

Mapping subdomains, endpoints, parameters and technologies, with automatic prioritisation of the most promising targets.

Continuous analysis

Reading responses, client-side JavaScript and error messages to catch clues a rushed human would miss.

Attack hypotheses

Specialised agents propose and test scenarios (access control, injection, logic) in a strictly non-destructive way.

Adversarial qualification

One agent tries to disprove every finding before it reaches the tester, removing most false positives.

Structured reporting

Evidence, reproduction steps, CVSS score and remediation drafted automatically, then reviewed by a human.

Human validation

Nothing ships until a CPTS, CAPE and CRTA certified tester has reproduced and confirmed it.

AI pentest vs vulnerability scanner vs manual pentest

CriterionVulnerability scannerManual pentestHybrid AI pentest (HackHeart)
Business logic flawsNot detectedYesYes (AI lead, human validation)
Multi-step attack chainsNoYes, time permittingYes, with more paths explored
False positives in reportManyFewFew (AI filter then human filter)
Surface coverageWide but shallowLimited by timeWide and deep
Executive-ready reportNoYesYes

Safeguards of a serious AI pentest

  • Written authorisation and a signed scope before any action. Scope is enforced technically, not merely "asked" of the AI.
  • No destructive testing: agents are restricted from denial of service, deletion or modification of production data.
  • Data pseudonymisation: client IPs, URLs and identifiers are replaced by tokens before any processing by a language model. No identifying data leaves our infrastructure in clear, and this is verifiable: the engagement logs showing what was transmitted can be shared with you.
  • Traceability: every agent action is logged and can be shared with the client.
  • Accountability: a named tester signs the report; HackHeart holds professional liability insurance specific to penetration testing.

Who is it for?

SaaS vendors shipping frequently, SMEs and mid-size companies that must prove their security level to customers or insurers, professional firms handling sensitive data, and organisations in scope of NIS2 or DORA that must regularly assess the effectiveness of their security measures. HackHeart works across Europe remotely and on site in southern France and Monaco.

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