AI & GenAI Penetration Testing

Expose vulnerabilities in your AI before attackers do.

We simulate real-world adversarial behavior against GenAI systems, exposing logic flaws, unsafe outputs, and misalignment — with replayable attacks and offensive tooling.

Designed for:

AI Assistants & Chatbots
LLM APIs & System Prompts
RAG Pipelines & Memory Chains
LangChain + Function-Calling Agents
LLM-as-a-Service Platforms
Any Business-Critical AI Endpoint

Deliverables

What We Deliver

Full-spectrum AI Pentest. Real-world exploits. Complete analysis.

Prompt Injection Stress Testing

Simulate multi-step prompt chains, DAN-style jailbreaks, obfuscation tactics.

Output Abuse Detection

Detect hallucinated, toxic, or system-breaking responses.

Policy Violation Triggers

Test role override, hidden prompt execution, and context breaking.

Threat Logging & Replay

Capture full attack chains with replayable payload logs.

Abuse & Hallucination Modeling

Test ethical, legal, and factual guardrails under pressure.

Multi-Model Compatibility

OpenAI, Anthropic, Cohere, Mistral, LLaMA, fine-tuned models & APIs.

Realized

What CQR’s Firewall Covers

Full Offensive Coverage for Your AI Stack

Attack Surface

What We Do

Prompt Injection

Hidden payloads, DAN logic, prompt smuggling

Output Exploits

Malicious generations, hallucinated instructions

Data Disclosure

Extracted pretraining data, leaked emails, credentials

Plugin & Function Abuse

API hijacks, unauthorized actions, chain-of-command bypass

Role Impersonation

User-to-admin prompt escalation, identity spoofing

Compliance Bypass

Prompt-induced violations of content and data policy

Process

How we Operate?

Full Offensive Coverage for Your AI Stack

Recon & Input Mapping

1

Payload Injection

2

Real-Time Response Moderation

3

Reporting & Replay

4

Industries

WHO NEEDS AI & GenAI pentest

Whether you build, integrate, or expose LLMs — unprotected systems are at risk.
 This service protects AI in regulated industries, customer-facing platforms, and developer tools.

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