AI Agent Pentesting
We probe agentic LLM systems the way real adversaries would — prompt injection, tool abuse, goal hijacking, data exfiltration, and unsafe autonomy, mapped to the OWASP LLM Top 10.
Manual, research-driven testing across AI, applications, cloud, and blockchain. Every engagement delivers evidence, real impact, reproducible steps, and fixes that can be acted on immediately.
We probe agentic LLM systems the way real adversaries would — prompt injection, tool abuse, goal hijacking, data exfiltration, and unsafe autonomy, mapped to the OWASP LLM Top 10.
We dissect Model Context Protocol servers and tools: broken auth, over-broad scopes, and injection through tool definitions and untrusted context.
Manual review and live exploitation of on-chain logic — reentrancy, broken access control, oracle manipulation, and economic attacks across EVM and Solana programs.
A full, OWASP-aligned offensive against authentication, access control, injection, business logic, and session handling — performed by hand, not just scanners.
iOS and Android assessments aligned to OWASP MASVS — storage, transport, binary protections, and the API trust boundaries behind them.
REST, GraphQL, and WebSocket testing against the OWASP API Top 10 — BOLA, mass assignment, and broken function-level authorization included.
Desktop and native application assessments: local storage, IPC, binary tampering, and the server-side trust boundaries attackers attempt to bypass.
Anti-cheat bypass, client tampering, economy abuse, and backend exploitation for live game platforms.
IAM and privilege-escalation hunting, misconfig and exposed-asset discovery, and storage and key hardening across AWS and GCP environments.
External perimeter testing, internal lateral movement and segmentation analysis, Active Directory attack paths, and the patch and config gaps that let it all happen.
Full kill-chain adversary emulation from initial access through lateral movement, with detection and response put to the test against MITRE ATT&CK.
Human-led, AI-accelerated. Senior testers drive the strategy while automation widens the coverage — the same disciplined six steps on every engagement.
Lock down targets, rules of engagement, and objectives.
Map the attack surface and enumerate every asset.
Manually verify and chain weaknesses into real impact.
Rate impact and likelihood, then rank by risk.
Deliver clear findings with reproducible proof of concept.
Re-attack the fixes and confirm they actually hold.
Most engagements run about 2–4 weeks, scope to verified fix — the exact window is confirmed during scoping.
A concise, business-level read on overall risk posture, key themes, and priorities — written for leadership and stakeholders.
Every finding in full: evidence, impact, severity, and reproducible steps — written for the teams who actually fix it.
CVSS-based severity that makes the fix order obvious.
Concrete, actionable fixes — never generic advice.
We re-attack to prove the issues are really gone.
A walkthrough with the teams who own the fix.
Aligned to the standards auditors and customers actually ask about.
Web application risks
API-specific risks
Mobile app security
AI / LLM application risks
Penetration testing standard
Adversary tactics & techniques
Technical assessment guide
Severity scoring
Real environments, not checklists. If it ships, it's in scope.