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Penetration Testing

AI & LLM Penetration Testing

LLMs are being integrated into products, workflows, and customer-facing systems faster than anyone is testing them. A single prompt injection flaw can turn your AI feature into a data exfiltration tool.

About This Service

What is AI & LLM Penetration Testing?

Security assessment of AI-powered applications and large language model (LLM) integrations — testing for prompt injection, model manipulation, data leakage, and AI-specific attack vectors.

Most AI and LLM deployments are in production before anyone has assessed what an attacker could extract, manipulate, or exploit. Prompt injection, data leakage, and model manipulation are real, exploitable risks — and the attack surface is new enough that most security teams have limited experience assessing it.

At a Glance

Frameworks
OWASP LLM Top 10, NIST AI RMF
Typical Timeline
3–7 days depending on system complexity
Report
Executive summary + full technical findings
Retest
Complimentary, included in every engagement
NDA
Signed before any technical discussion
What You Gain

Outcomes that move your security forward

Prevent prompt injection attacks that could allow users to manipulate your AI into leaking sensitive data or taking unauthorised actions
Protect proprietary training data and confidential business information from model extraction attacks
Demonstrate AI security due diligence to enterprise customers and compliance auditors
Stay ahead of a rapidly evolving threat landscape — AI-specific attacks are increasing as LLM adoption grows
Identify insecure LLM integrations before they become a liability in your product or internal workflows
Build enterprise customer confidence in your AI-powered features with independent security validation
Deliverables

What You Receive

Executive Summary Report

AI/LLM risk overview for product, security, and leadership teams

Full Technical Report

All findings mapped to the OWASP LLM Top 10 with proof-of-concept prompts and reproduction steps

Prompt Injection Test Results

Documented adversarial prompt attempts and their outcomes

Integration Security Assessment

Review of API integration security, input validation, and output handling

Developer Remediation Guide

Practical mitigations including prompt hardening and architectural recommendations

Retest Report

Confirms mitigations are effective after your team applies fixes

Scope

What We Test

Prompt injection — direct and indirect injection attacks
Jailbreaking and safety filter bypass attempts
Data exfiltration via LLM outputs
Training data leakage and memorisation issues
Model inversion and extraction attacks
Insecure LLM API integration — authentication, rate limiting, input validation
Retrieval-Augmented Generation (RAG) pipeline security
Agentic AI tool-use and plugin security
Output handling and downstream injection risks
Adversarial inputs targeting AI-driven decision systems
Process

How We Run This Engagement

Every engagement follows a defined, transparent process — no surprises, no hidden scope changes, and no invoice for work you did not agree to.

01

Scoping

Understand the AI system architecture, LLM provider, integration points, and threat model.

02

Prompt Engineering & Injection Testing

Systematically attempt to manipulate LLM behaviour through adversarial prompts.

03

API & Integration Testing

Test the security of the surrounding application and API layer.

04

Data Leakage & Privacy Testing

Assess whether the model can be made to reveal training data or sensitive information.

05

Reporting

Findings mapped to OWASP LLM Top 10 with remediation guidance.

06

Retest

Verify mitigations are effective.

Why Us

Why Work With Vigilant Defenders

01

Manual Testing. Not Scanner Output.

Automated tools find known signatures. Our certified consultants find the chained attack paths, logic flaws, and context-specific vulnerabilities that no scanner will surface. Every finding we report is manually verified — zero false positives.

02

Reports Built for Action, Not Filing.

Every finding includes a proof-of-concept, a CVSS risk score, the affected system or endpoint, and step-by-step remediation guidance written for the team that has to fix it. Your developers and your board both get a report they can use.

03

Confidentiality From Day One.

We sign a formal NDA before any technical discussion begins. Your vulnerabilities, your architecture, and your engagement findings are treated with the same confidentiality as attorney-client communications. We have never disclosed client information.

04

We Stay Until It's Fixed.

Every engagement includes a complimentary retest once your team has addressed the findings. We verify that the vulnerabilities are genuinely closed — not surface-patched — and issue a formal retest certificate you can share with clients and auditors.

05

We Work at the Frontier of AI Security.

AI security testing is not just a renamed web app checklist. We have hands-on experience with LLM integrations, RAG pipelines, and agentic AI systems — and we follow the rapidly evolving OWASP LLM Top 10 and NIST AI Risk Management Framework to ensure your AI deployment is assessed against the latest known threats.

FAQ

Frequently asked questions

Everything you need to know about this engagement.

LLMs are being integrated into customer-facing products, internal tools, and automated workflows at speed — often without security review. Prompt injection alone can lead to data exfiltration, unauthorised actions, and reputational damage.

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Find Out How Your AI Integration Can Be Exploited

Get a free scoping consultation — no commitment required. We’ll scope the right AI & LLM penetration testing engagement for your environment and send a fixed-fee proposal within 24 hours.