AI Research · Security

Prompt Hacking:
Know Your Enemy

Prompt injection, jailbreaking, and adversarial attacks are the next frontier of cybersecurity. Our research practice investigates real-world AI vulnerabilities so your organisation can build defences that actually work.

78%
of AI systems vulnerable
to prompt injection

The AI Security Threat Landscape

As AI becomes embedded in critical systems, the attack surface grows. Understanding the vulnerabilities is the first step to building resilient AI.

01
Injection
01

Prompt Injection

Malicious instructions embedded in user input that override or hijack an AI system's original purpose. A growing threat for AI-powered customer service, internal tools, and autonomous agents.

02
Jailbreak
02

Jailbreaking & Guardrail Bypass

Techniques that manipulate large language models into ignoring their safety constraints. Our red-team research catalogues current methods and tests your AI systems' resilience against them.

03
Exfiltration
03

Data Exfiltration via AI

AI interfaces that have access to sensitive data can be manipulated into leaking it. We test for these attack vectors across RAG systems, AI agents, and enterprise copilot deployments.

Our AI Red-Teaming Approach

We apply the structured discipline of traditional penetration testing to AI systems, probing for vulnerabilities with the same rigour as a skilled threat actor, but with the ethics and accountability of a trusted consultant.

Our research is vendor-neutral and academically grounded, drawing on the latest published work in adversarial machine learning, while remaining deeply practical and relevant to the AI tools your organisation actually uses.

Request a red-team assessment
Systematic prompt injection testing across your AI surfaces
Jailbreak resilience evaluation for LLM-powered products
RAG system data leakage & retrieval manipulation testing
AI agent autonomy boundary testing
System prompt extraction & reverse engineering assessment
Vulnerability reporting & remediation guidance
AI security policy & governance recommendations

Active Research Areas

Our current research in adversarial AI security and responsible disclosure.

Research 01

Multi-Modal Prompt Injection

Investigating attack vectors that exploit image, audio, and document inputs in multi-modal AI systems. The next generation of injection attacks.

Research 02

Agentic AI Security

How autonomous AI agents can be manipulated into taking harmful real-world actions, and how to prevent it through robust boundary controls.

Research 03

Enterprise Copilot Vulnerabilities

Security testing of Microsoft 365 Copilot, SharePoint AI, and connected enterprise AI deployments. Finding the gaps before attackers do.

Research 04

Prompt Leakage in SaaS Products

Responsible disclosure research into system prompt exposure across AI-powered SaaS applications. Protecting your intellectual property.

Research 05

AI Governance & Policy for Security Teams

Translating AI red-team findings into actionable governance policies, CAIQ responses, and board-level risk reporting.

Prompt Hacking & AI Security FAQ

Prompt hacking (also called prompt injection) is when attackers manipulate AI system prompts to bypass safety controls, extract confidential data, or make the system behave in unintended ways. It's the #1 vulnerability in deployed AI systems today.

If you're deploying AI-powered chatbots, assistants, or automated workflows, they're exposed to prompt injection attacks. Without testing, attackers can extract your system prompts, bypass content filters, or manipulate outputs, causing reputational and financial damage.

We simulate real-world attacks against your AI systems: prompt injection, jailbreaking, data exfiltration, output manipulation, and social engineering. You get a detailed report of vulnerabilities found, risk ratings, and specific remediation steps.

No AI system is 100% immune, but the risk can be dramatically reduced. We implement multi-layered defences including input sanitisation, output filtering, prompt hardening, and architectural controls that make attacks significantly harder and less impactful.

We recommend quarterly AI security assessments, plus testing after any significant model update, prompt change, or new feature deployment. AI threats evolve rapidly. The attacks of 6 months ago are already obsolete.

Don't wait for a breach to find your AI vulnerabilities.

Every organisation deploying AI has attack surfaces they haven't mapped yet. Let us find them first, with structured, accountable, expert red-teaming.

Commission a red-team assessment