AI Security

AI technologies introduce new categories of risk including data exposure, model misuse, supply chain dependencies, and unintended automation. Organisations often lack visibility into how AI tools are being used and what controls are required to manage risk effectively.

Parabellum conducts a comprehensive AI readiness and risk assessment to evaluate your organisation’s AI usage, governance maturity, and security posture. We identify sanctioned and unsanctioned tools, assess data handling practices, and evaluate controls across identity, infrastructure, and operational workflows.

Our assessment aligns with recognised frameworks including the NIST AI Risk Management Framework, ISO 42001, and existing enterprise security standards. We deliver actionable recommendations to support secure and responsible AI adoption.

AI technologies create new attack surfaces that traditional security testing does not fully address. Attackers may manipulate prompts, exploit integrations, or extract sensitive data through AI workflows.

Parabellum conducts AI threat modelling and adversary simulation to stress test deployments using real world attack techniques. Our offensive security team evaluates AI workflows, integrations, and automation capabilities to identify exploitable weaknesses.

This engagement validates controls and provides prioritised remediation guidance to strengthen AI security.

Artificial intelligence environments change rapidly. New features, integrations, and tools introduce new risks over time. Without governance and continuous oversight, organisations risk insecure adoption and compliance challenges.

Parabellum provides governance framework development and ongoing assurance services to support long term AI adoption. We define policies, establish monitoring controls, and provide periodic reassessment to maintain secure AI environments.

Our governance frameworks align with enterprise risk management and compliance requirements.

Organisations often struggle to balance innovation with security when adopting AI technologies. This structured engagement provides a clear roadmap for secure adoption, from initial readiness assessment through deployment, validation, and ongoing governance.

Each phase builds on the previous, ensuring organisations can safely enable AI while maintaining visibility, control, and compliance.

Phase One

AI Readiness & Risk Assessment

The first phase establishes visibility into AI usage and evaluates organisational readiness. We identify how AI tools are currently being used, assess governance maturity, and evaluate risk exposure across data handling, integrations, and workflows.

This phase aligns findings with recognised frameworks such as the NIST AI Risk Management Framework and enterprise security standards.

Phase One Focus Areas

• AI usage discovery and shadow AI identification
• Governance and policy maturity assessment
• Data protection and privacy risks
• Third party model and supply chain exposure
• Regulatory and compliance alignment
• Risk prioritisation and remediation roadmap

Phase Two‍

Secure Deployment Architecture & Policy Advisory

Phase two focuses on designing secure deployment architectures for AI technologies. We define how AI tools should be implemented within your organisation, ensuring alignment with identity, infrastructure, and governance controls.

This phase ensures AI deployments are secure by design and aligned with enterprise security requirements.

Phase Two Focus Areas

• Identity and access control integration
• Role based access and governance design
• Network isolation and secure infrastructure
• Data protection and retention controls
• Policy driven deployment configuration
• Integration governance and MCP server controls
• Secure deployment documentation

Phase Three

AI Threat Modelling & Adversary Simulation

Once deployments are designed or implemented, phase three validates security controls through adversary simulation. Our offensive security team simulates real world attackers targeting AI workflows and integrations.

This phase identifies exploitable weaknesses and validates security controls before large scale adoption.

Phase Three Focus Areas

• Prompt injection testing
• Data exfiltration simulation
• Tool abuse and integration testing
• Model manipulation testing
• Privilege escalation scenarios
• Attack path mapping and remediation guidance

Phase Four

Governance Framework & Ongoing Assurance

The final phase establishes governance structures and ongoing assurance to maintain secure AI adoption over time. AI technologies evolve rapidly, and governance must adapt accordingly.

We implement governance frameworks, monitoring controls, and periodic reassessment to ensure long term security and compliance.

Phase Four Focus Areas

• AI acceptable use policy development
• AI asset inventory and AIBOM creation
• Monitoring and audit integration
• Incident response planning for AI risks
• Periodic reassessment and governance reviews
• Continuous assurance and oversight

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Secure deployment of AI technologies requires careful consideration across identity, network architecture, data protection, and operational governance. Without structured deployment planning, organisations risk insecure adoption and unintended exposure.

Parabellum provides architecture and policy advisory services to support secure AI deployments. Our engagement begins with an offensive security led architecture review to identify risks prior to deployment. We then design secure deployment models aligned with your infrastructure and operational requirements.

We advise on identity integration, network isolation, data protection controls, and policy driven governance to ensure AI tools are deployed safely and responsibly.