Service
AI & LLM Security Testing — Before Your AI Becomes Your Attack Surface
Expert-driven penetration testing for AI applications, LLM integrations, and generative AI systems. Prompt injection, data leakage, model API abuse, and the full OWASP Top 10 for LLMs.
Overview
AI and LLM-powered applications are the fastest-growing attack surface in enterprise software. From prompt injection and jailbreaking to training data extraction and model API abuse, these systems introduce an entirely new class of vulnerabilities that traditional scanners cannot detect. Our AI/LLM VAPT service combines deep expertise in both offensive security and AI systems to test your LLM integrations the way a sophisticated adversary would — probing business logic, data boundaries, and trust assumptions that are unique to AI-powered applications.
What We Test
How We Work
Our 16-step methodology.
Phase 1 — Context & Reconnaissance
Phase 2 — Structural Probing & Filtering
Phase 3 — Human-Led Deep-Dive
Phase 4 — Exploitation, Validation & Governance
Questions
Frequently asked.
What types of AI systems do you test?+
We test LLM-powered applications (chatbots, copilots, AI agents), RAG systems, AI APIs, embedded AI features in SaaS products, and custom model deployments. Both cloud-hosted (OpenAI, Anthropic, Google) and self-hosted models.
How is this different from regular API security testing?+
Traditional API testing focuses on authentication, authorization, and input validation. AI/LLM testing adds an entirely new layer: prompt-level attacks, context window manipulation, guardrail bypass, training data extraction, and abuse of tool-use capabilities that conventional scanners cannot evaluate.
Do you follow the OWASP Top 10 for LLMs?+
Yes. We test against the full OWASP Top 10 for Large Language Model Applications and go beyond it with proprietary test cases for business-logic abuse, multi-turn manipulation, and indirect prompt injection via untrusted data sources.
Can you test without access to the model weights?+
Yes. Most engagements are black-box or grey-box, testing the application layer and API endpoints without requiring access to model internals. We can also perform white-box testing if model access is available.
What deliverables do we receive?+
An executive summary, CVSS-scored findings with reproduction steps, remediation guidance specific to AI/LLM architectures, compliance mapping, and a full verification round after your team remediates.