Threat-Driven Offensive Security Testing
Simulating real-world attacks is the best way to test your defenses against motivated adversaries.
Methodology
What We Test
We focus on concrete attack surfaces that matter to real attackers. External and internal application attack surfaces, including authentication bypass, authorization flaws, and injection vulnerabilities. Cloud identity and trust boundaries—IAM privilege escalation, cross-tenant access, and service account abuse. API abuse paths and business logic weaknesses that automated scanners miss. AI/LLM abuse scenarios including prompt injection, training data exposure, and model manipulation. IoT, firmware, and embedded system entry points through wireless protocols, hardware interfaces, and supply chain vectors. Lateral movement and privilege escalation paths across networks, containers, and cloud environments.
How We Test
Our methodology starts from attacker-accessible entry points, not theoretical vulnerabilities. We chain vulnerabilities instead of reporting isolated findings—a SQL injection becomes a path to credential theft, which enables lateral movement, which leads to domain compromise. We pivot across systems, identities, and trust boundaries, validating how attackers would actually navigate your environment. Every finding is validated for exploitability, not just theoretical risk. We escalate impact until meaningful control or data access is achieved, demonstrating real-world consequences.
Deliverables
You receive exploit chains and attack paths, not just vulnerability lists. Each finding includes clear impact assessment tied to attacker objectives—what an attacker can actually achieve, not just what a scanner detected. Reproduction steps engineering teams can follow, with proof-of-concept code or detailed walkthroughs. Prioritized remediation guidance based on real risk, not CVSS scores. Executive-level summary alongside deep technical detail, enabling both strategic decisions and tactical fixes.
Toolkit
- Cobalt Strike
- Sliver
- BloodHound
- Custom Malware
