AI & Emerging Technology Security
LLM Security Testing & Prompt Injection Assessment
Prompt injection is the SQL injection of the AI era. We provide specialist security testing for LLM applications — systematically identifying the vulnerabilities attackers will exploit before your system reaches production.
Every LLM Application Has an Attack Surface Most Teams Have Never Assessed
LLM applications introduce a fundamentally new class of security vulnerability. Unlike traditional software bugs, LLM security flaws are probabilistic, context-sensitive, and emerge from the interaction between model capabilities, system prompt design, and the untrusted content the model processes. No static code analysis tool can find them.
The most critical — and most commonly exploited — vulnerability is prompt injection. Whether injected directly through user input or indirectly through retrieved documents, poison emails, or malicious web content, successful injection can cause your LLM to leak confidential data, bypass guardrails, or take harmful actions on behalf of an attacker.
Prompt Injection
Direct and indirect injection across user inputs and RAG-sourced content
Jailbreaking
Systematic testing of safety guardrails against current bypass techniques
Data Leakage
System prompt extraction, training data memorisation, PII disclosure
Agent Security
Tool use security, excessive agency, and authorisation controls for LLM agents
5-Phase LLM Security Testing Process
A structured, OWASP LLM Top 10 aligned methodology that systematically surfaces the vulnerabilities most likely to be exploited in your specific LLM deployment.
LLM Deployment Architecture Review
We map your complete LLM deployment stack — base model, fine-tuning approach, system prompt design, RAG pipeline, tool integrations, output filters, and downstream application logic — before any active testing begins.
Threat Modelling & Attack Surface Definition
We build a comprehensive threat model for your specific LLM application — mapping the complete set of injection points, trust boundaries, data flows, and potential misuse paths that shape the testing scope.
Prompt Injection & Jailbreak Testing
Systematic testing for direct prompt injection (bypassing system prompts via user input), indirect prompt injection (malicious instructions embedded in retrieved content), and jailbreak techniques that override safety guardrails across multiple attack categories.
Data Leakage & Model Behaviour Testing
We probe for sensitive data disclosure through carefully crafted queries — testing for system prompt extraction, training data memorisation, PII leakage, and excessive information disclosure across different input contexts and conversation histories.
Findings Report & Hardening Guidance
A detailed report mapping every finding to the OWASP LLM Top 10 with exploitability ratings, business impact assessment, and specific hardening recommendations covering input validation, output filtering, system prompt hardening, and architectural controls.
Comprehensive LLM Security Testing Services
From prompt injection to agent security — specialist testing coverage across the OWASP LLM Top 10 vulnerability taxonomy.
Prompt Injection Testing
Systematic testing for direct and indirect prompt injection vulnerabilities — evaluating whether attackers can override system prompts, manipulate LLM behaviour, or use retrieved content to inject malicious instructions.
Jailbreak & Guardrail Bypass Assessment
Evaluating the robustness of your LLM's safety controls — testing for jailbreak techniques that bypass content filters, role-playing exploits, many-shot jailbreaks, and competing objectives attacks.
System Prompt & Confidentiality Testing
Assessing the security of your system prompt — testing whether attackers can extract confidential instructions, business logic, or sensitive parameters embedded in the system context.
RAG Pipeline Security Testing
Security assessment of Retrieval-Augmented Generation pipelines — evaluating the injection risks introduced by external data sources, document stores, and web retrieval capabilities connecting to your LLM.
LLM Agent & Tool Use Security
Assessing the security of LLM agents with tool access — evaluating excessive agency risks, authorisation controls on tool invocations, and the attack surface introduced by giving LLMs the ability to execute code or call external APIs.
Output Validation & Downstream Risk
Evaluating the security controls on LLM outputs — testing for insecure output handling, XSS via LLM-generated HTML, code injection through generated code, and other downstream exploitation paths.
LLM Security is Not a Checkbox — It's a Specialist Discipline.
Our LLM security team understands language model architecture, RAG pipeline design, and the adversarial techniques being actively weaponised by threat actors targeting AI applications.
OWASP LLM Certified
Our testing methodology comprehensively addresses all 10 vulnerability categories in the OWASP Top 10 for LLMs — the definitive security standard for LLM applications.
Model-Agnostic
We test LLM applications regardless of the underlying model — GPT-4, Claude, Gemini, Llama, Mistral, or proprietary fine-tuned models — with techniques tailored to each model family.
RAG Specialists
Deep specialist expertise in Retrieval-Augmented Generation security — one of the most complex and underassessed attack surfaces in production LLM applications.
Regulation Ready
Our assessments generate documentation supporting EU AI Act high-risk AI system requirements and emerging LLM security governance frameworks.
Frameworks & Standards Our Testing Addresses
Frequently Asked Questions
Everything you need to know about LLM security testing
Test Your LLM Before Attackers Do
Prompt injection doesn't announce itself. Let our specialists systematically assess your LLM application's security posture — and provide the hardening guidance your engineering team needs to fix what we find.
Get in Touch
Ready to secure your future? Reach out to us for a consultation.