Our Security Methodology

Our methodology is threat-informed, engineering-driven, and designed to reduce real-world risk, not simply produce a list of findings. We combine deep offensive expertise with practical security engineering to help teams build and operate more resilient applications and AI systems.

1. Discovery & Context Alignment

We begin by understanding your architecture, business objectives, technology stack, development practices, and risk tolerance. This ensures our work is aligned with what actually matters to your organization.

2. Architecture & Threat Modeling

We analyze system design, trust boundaries, data flows, and critical business logic (including AI/LLM components). This allows us to identify realistic attacker goals and high-impact risk areas before any hands-on work begins.

3. Deep Security Assessment

Our assessments prioritize manual, threat intelligence-led testing over automated scanning. We focus on complex authorization issues, business logic flaws, multi-step attack chains, and emerging AI-specific risks such as prompt injection, jailbreaks, data leakage, and model abuse.

4. Exploit Validation & Risk Prioritization

Findings are validated through controlled exploitation to confirm real impact. We deliberately filter out low-signal or theoretical issues so your team can focus engineering effort on vulnerabilities that truly matter.

5. Practical Remediation & Secure Design Guidance

We provide clear, actionable recommendations tailored to your stack and workflows. Beyond fixes, we advise on secure design patterns, stronger controls, and, where relevant, effective AI guardrails and LLMOps improvements.

6. Collaboration & Knowledge Transfer

We work directly with your engineers and architects to explain root causes, discuss trade-offs, and strengthen both the application and the development process itself.

7. Continuous Hardening & Improvement

Security is an ongoing capability. We support lasting risk reduction through retesting, secure development guidance, LLMOps integration recommendations, and continuous feedback loops that help your team ship more resilient software over time.