Security built in,
not bolted on.
We embed security into every layer of your product — from architecture decisions to deployment. Penetration testing, threat modeling, secure code review, and compliance readiness across OWASP, SOC 2, ISO 27001, and more.
Core capabilities
Penetration testing
PentestManual and automated pentests against your web app, API, and infrastructure. We find what automated scanners miss — business logic flaws, access control gaps, and complex chains.
Secure architecture design
ArchitectureSecurity baked into your system design — zero-trust principles, least privilege, secrets management, and defense-in-depth from day one.
Compliance readiness
ComplianceWe map your application against SOC 2, ISO 27001, GDPR, HIPAA, and PCI DSS — and build the evidence required for certification.
Incident response preparation
IR PrepWe help you build detection, alerting, and response playbooks before an incident happens — so you're never caught flat-footed.
What you get
- Full penetration test report with severity ratings
- Exact remediation guidance per finding
- Secure architecture review document
- Threat model for your application
- Compliance gap analysis (SOC 2 / ISO 27001 / GDPR)
- Security hardening checklist
- Developer security training session
- Executive-ready security summary
How we work
We define the attack surface — which systems, APIs, and flows are in scope for testing.
We build a threat model specific to your application before starting active testing.
Manual pentest with real attacker techniques — not just scanner output. We chain vulnerabilities to demonstrate real impact.
Detailed report, fix guidance, and a retest after remediation to confirm findings are resolved.
Tools & technologies
Who this is for
Pre-launch security audit
StartupsShip with confidence. We run a full security assessment before your product goes public.
SOC 2 / ISO preparation
SaaSWe prepare your technical controls, evidence collection, and gap remediation for certification.
AI system security
AI ProductsSecurity assessments for LLM-powered products — prompt injection, data leakage, and model abuse vectors.