Security & Guardrails
Securing AI systems is not just a technical necessity it is a strategic imperative. As AI capabilities evolve, so too do the risks of misuse, system compromise, and unintended consequences. This page outlines how organisations can establish strong governance and security guardrails around AI, ensuring systems are protected, controlled, and aligned with intended outcomes. Grounded in UK Government guidance and best practice, the 6 Sided Dice approach provides practical, actionable steps to safeguard AI across its lifecycle, protecting your organisation, your users, and customers.
Security & Guardrails
Security is foundational to the responsible deployment of generative AI. Without the right protections in place, these systems can expose sensitive data, introduce vulnerabilities, or behave unpredictably. At 6 Sided Dice, we help organisations implement robust security controls and governance guardrails to ensure generative AI is used safely, lawfully and with full accountability. This section draws on established best practice, including the UK Government’s guidance, to give you clear, practical steps to protect your data, maintain compliance, and uphold trust every step of the way.
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The 6 Sided Dice Security & Guardrails Framework
A structured approach to building secure, responsible AI systems
As generative AI becomes more integrated into operations, the risks around data privacy, system misuse, and unintentional harm increase. The 6 Sided Dice Security & Guardrails Framework offers a practical, principle-based model to help organisations mitigate these risks while maintaining agility and innovation.
Rooted in UK Government guidance, this framework brings together technical safeguards, governance measures, and operational controls into a unified approach. It ensures that generative AI systems are secure by design, monitored in real time, and governed with transparency.
6 Sided Dice Security & Guardrails Framework
A practical guide to 7 key areas (underpinned by UK Government AI Framework):
1.
Access & Data Control
Limiting AI systems to the data they truly need, while tracking and managing user access to prevent unauthorised use.
2.
Data & Sovereignty & Hosting Transparency
Understanding where data is processed and stored, especially when working with third-party models or APIs.
3.
Technical Safeguards
Deploying filters, validation tools, and usage monitors to prevent malicious prompts, reduce harmful outputs, and maintain stability.
4.
Human Oversight
Ensuring qualified people are involved in validating AI outputs and making key decisions, particularly in sensitive or high-impact contexts.
5.
Lifecycle Integration
Embedding security and governance checks at every stage of the AI lifecycle, from design to deployment and beyond.
6.
Regulatory Alignment
Complying with existing laws and government frameworks, including GDPR, the Technology Code of Practice, and cloud security standards.
7.
Appropriateness & Proportionality
Using AI only where it adds value and avoiding its use in scenarios where accuracy, transparency, or risk exposure is critical.