Cybersecurity • GenAI Defense

AI & LLM PenTesting

Executive Overview

As enterprise applications integrate LLMs and AI pipelines, new attack vectors emerge. We test how secure your AI models really are against prompt injections, model extraction, training data poisoning, and unsafe tool execution.

The Challenge We Solve

Unsanitized AI agent inputs can result in prompt injection jailbreaks, private database exposure, and unintended autonomous actions.

Scope & Core Deliverables

Direct and indirect prompt injection & jailbreak simulation

Training data extraction and model poisoning analysis

Adversarial input and output manipulation testing

Agent tool-calling authorization and database access controls

Secure AI deployment, guardrail, and governance validation

Engagement & Delivery Methodology

Stage 01

LLM Architecture & Guardrail Inspection

Stage 02

Fuzzing & Adversarial Prompt Injection Testing

Stage 03

RAG Vector Database Leakage Analysis

Stage 04

Defensive System Prompt & Guardrail Engineering

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