Automated Penetration Testing
Continuously validate your defenses with automated, exploit-driven testing that proves which vulnerabilities are actually exploitable - at machine scale.
Do you need automated penetration testing?
A quick self-check. If several of these sound like you, it is worth a short conversation.
You likely need this if
- Your environment changes faster than annual testing can keep up with
- You want continuous validation of exposure between manual engagements
- You have a large or fast-moving estate of apps, APIs and infrastructure
- You need frequent, repeatable evidence of your security posture
Not sure where you land? A short scoping call will tell you plainly, including if you do not need this yet.
Book a scoping callExcellence through automation
Automated penetration testing lets you continuously evaluate and strengthen your security posture. It combines always-on scanning with systematic exploit validation, simulating a human attacker's reasoning at machine scale - so you prove impact, not just list findings.
It runs without requiring a manual red team for every cycle, making continuous, evidence-led validation practical for financial services, critical infrastructure, and AI development.
Go beyond scanner findings - validate which vulnerabilities can actually be exploited in your environment.
Simulate lateral movement, credential harvesting, and exfiltration to reveal complete attack paths.
Validate defenses on every change, catching regressions between traditional annual tests.
Generate standardized, mapped reports that satisfy DORA, NIS2, PCI-DSS, and EU AI Act expectations.
The threat landscape we test for
Automation closes the gaps that point-in-time, scanner-only programs leave open.
Scanners flag thousands of issues but cannot prove which are truly exploitable. We validate exploitability so you fix what matters.
Real breaches chain steps together. We simulate access, credential harvesting, lateral movement, and exfiltration to expose full paths.
Point-in-time tests miss what ships next week. Continuous automated testing catches regressions as they appear.
DORA, NIS2, PCI-DSS, and the EU AI Act expect proof that controls work - not just a list of findings.
Automated testing in practice
Scope & Scan Alignment
Define targets, environments, and rules of engagement, then align continuous scanning across your estate.
Attack Surface Baseline
Map endpoints, services, identities, and trust boundaries to establish a baseline for validation.
Exploit Build & Validation
Automatically craft and safely run exploits to prove which findings are genuinely exploitable.
Attack-Chain Simulation
Chain validated weaknesses - access, credential harvesting, lateral movement - to demonstrate real impact.
Reporting & Remediation
Generate standardized, mapped reports with prioritized fixes, and retest on every cycle.
Every validated finding comes with reproduction steps, remediation guidance, and standardized compliance documentation - refreshed on each cycle, not once a year.
Learn what's best for your company
Testing types
We tailor the access model and knowledge level to your risk profile and objectives.
Remote or onsite access
- Remote: testing performed over the internet, simulating an external attacker - the most common, cost-effective model.
- Onsite: testing from within your network, simulating an insider or post-breach attacker.
Zero, partial, or full knowledge
- Zero (black box): no prior information, simulating an external attacker with no inside knowledge.
- Partial (gray box): some access and documentation, balancing realism and coverage.
- Full (white box): full docs, source, and credentials for the deepest coverage.
Use cases
Continuous cloud validation
Always-on testing of cloud and hybrid estates so misconfigurations are caught as they appear.
CI/CD resilience
API-driven scans inside your pipeline assess pull requests, container images, and deploy scripts before release.
Ransomware path validation
Simulate access-to-exfiltration chains to prove segmentation and backup integrity hold up.
Scale & coverage
Validate large, fast-changing environments at machine scale without waiting on manual red-team capacity.
Reporting structure and metrics
Management Report
An executive overview of business risk, compliance alignment, and a prioritized remediation roadmap for board review.
Technical Report
Validated findings with exploit evidence, affected assets, attack-chain detail, severity, and prioritized fixes.
Validated (exploitable) vs total findings, attack chains proven, mean time-to-remediation, regression rate between cycles, and retest pass rate.
Not sure if automated penetration testing fits your need?
Tell us your environment and goals and we will scope a continuous validation program with the right depth, cadence, and compliance mapping.
Acceleration and automation in the era of AI
Fintech & Banking
The Problem: Financial systems face account takeover, transaction manipulation, and strict DORA resilience-testing obligations across fast-changing estates.
The Outcome: Continuous validation proves segmentation, access control, and resilience controls work - producing the evidence DORA and acquirers expect.
AI & ML Development
The Problem: AI services and their pipelines ship constantly, expanding the attack surface faster than manual testing can keep up.
The Outcome: Pipeline-integrated, adversarial validation provides robustness evidence for the EU AI Act and catches regressions on every release.
Regulatory & compliance deep dive (EU focus)
Continuous, exploit-driven testing produces the independent, mapped evidence that EU regulations increasingly expect - tying each obligation to demonstrable proof that controls work.
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DORA (Art. 24-30, 25(3)): Continuous validation of ICT risk controls, with audit-ready evidence for Threat-Led Penetration Testing and proof of the 'effectiveness of security controls' rather than mere vulnerability existence.
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NIS2 Directive: Regular, repeatable penetration testing of critical systems to evidence the appropriate and proportionate technical measures essential and important entities must demonstrate.
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GDPR (Art. 32): Validates the appropriate technical measures protecting personal data - encryption enforcement, access control, and breach detection - on every test cycle.
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EU AI Act (Annex III): Provides the robustness and adversarial-resilience evidence expected for high-risk AI systems and general-purpose models.
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PCI-DSS (Req. 11.3): Satisfies the penetration testing and vulnerability management obligations for cardholder-data environments.