Offensive security

AI/ML Security Testing

Adversarial testing of models and LLM pipelines for prompt injection, poisoning, and data leakage.

OWASP
LLM Top 10 aligned
Adversarial
Model-level red teaming

Security testing

In plain terms Testing

What this is

Adversarial testing of models and LLM pipelines for prompt injection, poisoning, and data leakage.

Why it can hurt you

An LLM feature that concatenates user input into a system prompt is one crafted message away from leaking your instructions or your data.

Security testing

Why it matters to you Testing

The problem

An LLM feature that concatenates user input into a system prompt is one crafted message away from leaking your instructions or your data.

Ahead of a fast-moving threat class

Test against attack patterns that postdate most security training.

Deployment confidence

Ship AI features without the system prompt ending up on Twitter.

Security testing

How we do it Testing

Prompt injection testing

Direct and indirect injection attempts across every model-facing input.

Data leakage testing

Attempts to extract training data, system prompts, or other users’ context.

Pipeline & plugin review

RAG sources, tool integrations, and agent permissions tested for abuse paths.

Security testing

What we typically find Testing

Prompt injection

User-controlled input able to override system instructions.

Training/context data leakage

Model coaxed into revealing sensitive training or session data.

Insecure plugin/tool access

Agent tools invokable beyond their intended scope.

No scanner dump. A fixed problem.

Every finding is reproduced by hand and comes with a working proof of concept.

Security testing

What lands on your desk Testing

Adversarial test report

Attack transcripts and findings mapped to OWASP LLM Top 10.

Mitigation guidance

Guardrail and prompt-architecture recommendations.

Security testing

What you get out of it Testing

Ahead of a fast-moving threat class

Test against attack patterns that postdate most security training.

Deployment confidence

Ship AI features without the system prompt ending up on Twitter.

Security testing

Step by step Testing

1. Prompt injection testing

Direct and indirect injection attempts across every model-facing input.

2. Data leakage testing

Attempts to extract training data, system prompts, or other users’ context.

3. Pipeline & plugin review

RAG sources, tool integrations, and agent permissions tested for abuse paths.

Find out what we would find.

A scoping call is thirty minutes, costs nothing, and ends with a fixed price and a date. If we are not the right people for the job, we will tell you that too.