Organisations are deploying AI at pace - but security, governance, and compliance are not keeping up. CyberSec Consulting's AI Security practice helps businesses govern, assess, secure, and harden their AI systems before they become a liability.
Built on 20 years of enterprise security and identity management expertise, our AI security services cover the full lifecycle - from governance frameworks and adversarial testing to data protection, model security, and workforce enablement. Whether you are adopting AI for the first time or scaling AI across the enterprise, CyberSec provides the security foundation that makes it safe to move fast.
AI systems introduce risks that traditional cybersecurity frameworks were not designed to handle. Large language models can leak sensitive data through their responses. Autonomous AI agents can exceed their intended scope. AI-generated code can introduce vulnerabilities at scale. And without governance, every employee using public LLM models is a compliance event waiting to happen.
The regulatory timeline is accelerating. The EU AI Act's high-risk obligations become enforceable in August 2026. ISO/IEC 42001 has established the international standard for AI management systems. The NIST AI Risk Management Framework provides the operational methodology. Regulators across the UK, UAE, and GCC are issuing AI-specific guidance. Organisations that wait will be playing catch-up against both the threat landscape and the compliance calendar
CyberSec's approach starts from what we know best, identity, access, and governance, and extends it into the AI specific risks that enterprise security teams are now expected to manage
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GOVERN
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SECURE
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PROTECT
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ENABLE
Most organisations fall into one of two starting positions. Both lead to the same destination – a secure, governed AI environment – but the journey starts in different places.
Begin with our AI Security Assessment. In two to four weeks, we inventory your AI tools, classify your data, test for the most common vulnerabilities, and produce a roadmap that tells you exactly what to fix first. The assessment fee is credited against any implementation engagement, so you are never paying twice.
Begin with our AI Governance Framework service. We build the policies, risk registers, and oversight structures your regulator expects — aligned to ISO 42001, NIST AI RMF, and the EU AI Act. If you are facing an SRA review, a CQC inspection, or an internal audit, this is where to start.
AI systems introduce risks that traditional cybersecurity frameworks were not designed to handle. Large language models can leak sensitive data through their responses. Autonomous AI agents can exceed their intended scope. AI-generated code can introduce vulnerabilities at scale. And without governance, every employee using public LLM models is a compliance event waiting to happen.
Contact UsCyberSec Consulting provides end-to-end AI security services across six domains: AI governance and compliance advisory, AI security assessment and red teaming, AI application security, data security for AI systems, AI model and MLOps security, and AI security training and enablement. Our services are aligned to ISO 42001, NIST AI RMF, the OWASP LLM Top 10, and the EU AI Act.
An AI security assessment is a structured evaluation of your organisation's AI systems, covering governance gaps, data security risks, application vulnerabilities, and regulatory compliance. CyberSec's assessment produces a scored risk register, a regulatory alignment matrix, and a prioritised remediation roadmap. It typically takes two to four weeks and the fee is credited against implementation.
ISO/IEC 42001:2023 is the international standard for Artificial Intelligence Management Systems (AIMS). It provides a framework for the ethical, secure, and responsible implementation of AI within organisations. CyberSec Consulting offers ISO 42001 implementation support, gap analysis, and pre-audit readiness to help organisations achieve certification or demonstrate governance maturity.
I red teaming is adversarial testing specifically designed for AI systems. Unlike traditional penetration testing, it covers AIspecific attack vectors such as prompt injection, jailbreaking, data leakage through LLM responses, model extraction, and agentic AI exploitation. CyberSec's red teaming is aligned to the OWASP LLM Top 10 and covers both LLM and agentic AI attack surfaces..
Agentic AI security addresses the risks introduced by autonomous AI agents that can take actions, use tools, and make decisions without direct human oversight. CyberSec assesses agent behaviour boundaries, tool access policies, MCP server security, inter-agent authentication, and cascading failure risks an emerging attack surface that most security consultancies do not yet address.
AI systems create a significant non-human identity challenge. AI agents, API keys, MCP server credentials, and service accounts all require the same governance principles as human identities authentication, least-privilege access, lifecycle management, and audit trails. CyberSec brings 20 years of enterprise identity and access management expertise to this problem, providing AI-specific NHI governance that most AI security providers lack.
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