Data & knowledge security
Classification, access, minimization, source permissions, retrieval boundaries, retention, leakage prevention, and handling of sensitive content.
AI Security
Protect AI data, architecture, integrations, access, and usage.
DTXI helps organizations assess and strengthen the security of GenAI tools, LLM and RAG solutions, AI-enabled workflows, third-party platforms, and the sensitive data they process.
Security Scope
AI security extends beyond the model.
The relevant attack surface includes users, prompts, identities, data sources, retrieval, orchestration, tools, APIs, applications, logging, vendors, and operational processes.
Identity & access
User, service, tool, and administrative access; least privilege; segregation; authentication; authorization; and privileged actions.
Architecture & integrations
Trust boundaries, model endpoints, RAG components, plugins, APIs, tools, connectors, isolation, secrets, and failure modes.
Monitoring & operations
Logging, prompt and output monitoring, abuse detection, incidents, model or vendor changes, content concerns, and response procedures.
Risk Scenarios
Assess how misuse, error, or compromise can affect the business.
Risk evaluation considers both intentional attack and operational failure within the specific use case.
Sensitive-data disclosure
Prompts, outputs, retrieval, logs, or integrations expose information beyond the intended user or approved purpose.
Prompt and instruction manipulation
Malicious or untrusted content changes system behaviour, bypasses intended controls, or triggers unsafe actions.
Excessive tool authority
An AI-enabled workflow can access, modify, send, approve, or execute more than the user or process should allow.
Insecure retrieval
RAG sources are incomplete, untrusted, mis-permissioned, or manipulated, producing unauthorized or misleading responses.
Vendor and model dependency
Changes in provider terms, model behaviour, hosting, data use, availability, or security affect the use case.
Insufficient oversight
Teams cannot trace decisions, investigate incidents, review outputs, or identify material changes in risk.
Assessment Method
Review the use case, not only the technology.
DTXI combines business context, data-flow review, architecture analysis, control assessment, targeted testing, and operational-readiness review.
Use-case context
Purpose, users, decisions, actions, impact, data, vendors, ownership, and approved boundaries.
Architecture & data flow
Components, trust boundaries, identities, integrations, retrieval, tools, storage, logging, and administrative paths.
Control review & testing
Access, data protection, configuration, prompt and content handling, monitoring, vendor controls, and targeted abuse scenarios.
Risk treatment
Prioritized findings, design changes, operating controls, monitoring, acceptance conditions, and validation plan.
Typical Deliverables
Outputs for design, implementation, governance, and assurance.
The package is selected according to whether the engagement concerns adoption of a third-party tool, an internal solution, or a production workflow.
AI security architecture review
Data flows, trust boundaries, components, risks, control gaps, design recommendations, and security requirements.
Secure GenAI adoption guidance
Approved-use conditions, data restrictions, access requirements, vendor considerations, monitoring, and operational safeguards.
AI threat and risk register
Scenario-based risks, affected assets and processes, likelihood, impact, controls, treatment, ownership, and residual risk.
Control validation package
Assessment evidence, findings, remediation guidance, acceptance criteria, retest results, and monitoring recommendations.
Related Services
Security and governance reinforce one another.
AI Security focuses on protection and assurance. Related services address governance decisions and solution implementation.
AI Governance & Risk
Define policy, accountability, risk-tiering, approval, monitoring, and the conditions under which AI use is permitted.
Explore AI GovernanceAI Solutions & Business Automation
Design and implement RAG, copilots, and workflows with security requirements incorporated into delivery.
Explore Automation