AI Security Risk Assessment
Identify AI use cases, sensitive workflows, exposed interfaces, security gaps and potential risks across your AI environment.
AI Security Solutions
Secure Your AI. Innovate With Confidence.
Adopt artificial intelligence with stronger security, privacy and governance. Petabyte helps organisations assess AI-related risks, protect sensitive data, secure AI-enabled applications and establish controls for responsible AI use.
AI risk assessment
Data protection
Governance & oversight
AI SECURITY CONTROL MODEL● ILLUSTRATIVE
AI ApplicationsModels, copilots and AI-enabled services
Data ProtectionSensitive information and access policies
Access ControlsIdentity, permissions and authorisation
Risk GovernancePolicies, oversight and accountability
Assess→Protect→Monitor→Improve
Conceptual illustration — not a live AI security monitoring system.
Security across the AI lifecycle
Generative AI
AI Applications
Enterprise Copilots
AI Data & Models
Our Capabilities
Build Security Into Every Stage of AI Adoption
AI introduces risks involving sensitive data, model behaviour, integrations, access permissions and third-party services. Establish controls that reflect your use cases, risk exposure and operational requirements.
AI Data Privacy & Protection
Review how sensitive information enters AI systems, moves through workflows and is shared with external platforms. Strengthen data handling and access policies.
Generative AI Security
Assess risks associated with generative AI usage, including prompt injection, unsafe outputs, information disclosure and inappropriate tool access.
AI Identity & Access Controls
Review permissions for users, service accounts, AI agents and connected tools to support least privilege and controlled access to resources.
AI Governance & Policy
Develop practical AI usage policies, accountability structures, risk classifications and approval workflows that support responsible adoption.
AI Application & API Security
Assess AI-enabled applications, APIs, integrations and tool connections for authentication weaknesses, excessive permissions and insecure data flows.
Model & Supply Chain Risk
Review relevant risks from third-party models, packages, datasets, model-serving components and external AI service dependencies.
AI Monitoring & Incident Readiness
Define appropriate logging, oversight, escalation and incident handling for suspicious AI interactions, unexpected outputs and potential data exposure.
AI Security Awareness
Help employees understand acceptable AI use, data-sharing restrictions, output verification and the risks of connecting unapproved tools.
Our Security Framework
Four Steps Toward Safer AI Adoption
Make AI security an ongoing discipline with clear ownership, risk-based controls and regular review as models, data and use cases evolve.
PHASE 01
Discover
Identify AI systems, users, data sources, integrations, models and business-critical use cases.
PHASE 02
Assess
Evaluate threats, sensitive-data exposure, permissions, model-related risks and governance gaps.
PHASE 03
Protect
Apply appropriate access controls, data safeguards, secure configurations and AI usage policies.
PHASE 04
Govern
Review control effectiveness, document accountability and improve safeguards as AI usage changes.
How We Work
A Practical Roadmap for AI Security
AI security should enable informed adoption, not simply restrict innovation. Our approach helps prioritise safeguards based on the systems you use and the risks you need to manage.
Understand Your AI Environment
Review AI use cases, platforms, data flows, integrations, stakeholders and existing security or governance requirements.
Prioritise Controls
Identify material risks and recommend proportionate safeguards for data, identities, applications, models and user workflows.
Implement & Review
Support agreed improvements, define ongoing oversight and reassess controls as AI capabilities and business needs evolve.
Connected Security Solutions
Connect AI Security With Your Wider Security Strategy
AI systems depend on data, identities, applications and infrastructure. Align AI-specific controls with the security foundations already protecting your organisation.
Frequently Asked Questions
AI Security FAQs
Understand common AI security risks and the controls that can help manage them.
AI security covers the practices and technical controls used to protect AI systems, their data, models, integrations and users against misuse, manipulation, unauthorised access and information exposure.
Risks can include prompt injection, sensitive-data disclosure, insecure tool connections, excessive permissions, unreliable outputs and vulnerabilities in connected applications or third-party components.
Establish approved-use policies, assess provider data-handling terms, limit access to sensitive information, apply appropriate data-loss controls and configure available retention and privacy settings. Requirements depend on the platform and use case.
Yes. Organisations should review data handling, identity and access permissions, connected applications, logging, retention settings and supplier security assurances for the AI services they use.
AI governance defines how an organisation approves, manages and reviews AI use. It can include policies, assigned responsibilities, risk assessments, acceptable-use rules, human oversight and monitoring processes.
No security approach can eliminate every risk. A risk-based programme combines layered technical controls, governance, testing, human oversight and continuous improvement to reduce exposure and improve resilience.
Adopt AI With Security Built In From Day One.
Talk to Petabyte about assessing AI risks, protecting sensitive information and establishing practical security governance for your organisation.