Innovation is moving faster than security. The AI models powering your business are the new high-value targets for sophisticated adversaries.
As organisations move beyond simple pilot projects to Agentic AI, autonomous systems that can reason, use tools, and interact with core data, the attack surface has fundamentally shifted. Traditional security tools cannot detect a "jailbreak" or an "indirect prompt injection" that bypasses your entire technical stack to manipulate a model's logic.
At Mongoose, we provide the UK’s most rigorous AI and LLM security assessments. Our technical specialists identify the hidden flaws in your AI architecture before they become a gateway for data exfiltration or unauthorised system control.
AI Vulnerability Testing
Automated tools focus on "known-knowns"; common software signatures and unpatched services. They are incapable of:
Direct & Indirect Prompt Injection:
Probing for vulnerabilities where a model can be tricked into ignoring its safety guardrails through carefully crafted input or through malicious data retrieved from untrusted external sources.
Excessive Agency & Tool Abuse:
Identifying where autonomous AI agents have been granted excessive permissions to execute actions (such as database modifications or financial transactions) without sufficient human-in-the-loop validation.
Sensitive Data Leakage & RAG/Context Poisoning:
Testing for "Model Inversion" and data extraction to ensure the AI does not inadvertently reveal PII, trade secrets, or internal system prompts used during training or fine-tuning. Manipulating the external data sources your AI uses (Retrieval-Augmented Generation) to warp the model's reasoning and force malicious or compromised outcomes.
Our AI assessments are built on a "Secured-by-Design" philosophy, aligning with the OWASP Top 10 for LLM Applications and the NIST AI Risk Management Framework.
Adversarial LLM Red Teaming
We act as the adversary to "jailbreak" your models. Using a combination of manual probing and automated adversarial prompt generation, we test resistance to bypass techniques, role-play attacks, and system prompt extraction.
AI Agent & Workflow Audit
If your AI has "hands" (the ability to call APIs or execute code) we test the containment and governance. We evaluate the sandboxing of AI-generated code, the scoping of API permissions, and the effectiveness of automated approval workflows.
Infrastructure & Supply Chain Review
AI does not live in a vacuum. We audit the entire LLMOps pipeline, from the security of third-party model providers and vector databases to the integrity of the data used for model fine-tuning.
Regulatory & Compliance Mapping
We ensure your AI deployment meets the rigorous standards of the EU AI Act, the UK Data (Use and Access) Act 2025, and sector-specific guidance from the FCA and ICO.
We provide the technical depth required by IT teams and the strategic clarity needed by stakeholders.
Deep Adversarial Expertise:
Our team focuses on the logic-based vulnerabilities unique to machine learning, moving beyond traditional application security to address the core of the AI threat.
Actionable Remediation:
Our reports provide technical blueprints for building AI Firewalls, robust System Guardrails, and Output Detection Logic.
Future-Proof Security:
As the AI landscape evolves, our methodology is updated in real-time to combat the latest jailbreaking and evasion techniques identified by the global research community.
What is the difference between an AI audit and a standard AppSec test?
Does Mongoose test for AI bias and fairness?
Can you test "Black Box" models like GPT-4o or Claude 3.5?
When should we commission an AI security assessment?
Ready to see the gaps others are missing?
Don't wait for a real adversary to find the pathway. Contact our team today to discuss a tailored manual assessment for your organisation.
