CSA AI Controls Matrix for Wallarm AI Control Platform
See how Wallarm AI Control Platform's public claims connect to security requirements and CSA AI Controls Matrix references.
What this page shows
Requirements connected to Wallarm AI Control Platform's public claims
Only requirements with strong or limited public support appear. The framework references identify what to investigate; they do not establish implementation, conformance, certification, or product effectiveness.
Versionv1.1 (June 22, 2026)Current source
Related requirements11security questions in this research
Security requirements with public support9strong or limited public support
References61identifiers, clauses, safeguards, or categories
How to use this map
Framework connections help structure your evaluation
Each connection shows how a security requirement relates to this framework. Public vendor claims are shown separately, and deployed effectiveness still requires confirmation or testing.
Closely aligned
10
Contributes
1
Requirement connections
From Wallarm AI Control Platform's public claims to questions to verify
Each row starts with a security requirement that has public support, then shows the connected framework references and the next question to verify.
Closely alignedSpecific reference
AI usage inventory
Maintain an inventory of AI tools, services, models, agents, software as a service (SaaS) AI capabilities, data flows, and provider relationships.
Framework references
DSP-03 · IAM-03 · STA-08 · UEM-04
Lifecycle
Govern · Identify · Monitor
Security requirements with public support
1 requirement with public support
Limited public supportApproved AI usage monitoring
Monitor approved AI workspaces, tenants, gateways, and model platforms such as ChatGPT Enterprise, Claude Enterprise, Gemini, Microsoft Copilot, Vertex AI, Elvex, or internal AI gateways.
Public claims reviewed
1
Next question to verify
Approved AI workspace activity appears with user, workspace or tenant, model or provider, and timestamp.
Limited public supportApproved AI usage monitoring
Monitor approved AI workspaces, tenants, gateways, and model platforms such as ChatGPT Enterprise, Claude Enterprise, Gemini, Microsoft Copilot, Vertex AI, Elvex, or internal AI gateways.
Public claims reviewed
1
Next question to verify
Approved AI workspace activity appears with user, workspace or tenant, model or provider, and timestamp.
Enforce policy against unapproved AI tools or unsafe AI interactions through blocking, coaching, allowlists, or runtime controls.
Framework references
AIS-11 · GRC-09 · TVM-13 · UEM-02
Lifecycle
Protect · Deploy · Operate
Security requirements with public support
1 requirement with public support
Strong public supportGenerative AI application security
Protect enterprise-built large language model (LLM) applications, retrieval-augmented generation (RAG) systems, prompts, application programming interfaces (APIs), model calls, tools, and production runtime behavior.
Public claims reviewed
1
Next question to verify
A test large language model (LLM) application event records prompt, application programming interface (API), model, retrieval, or tool interaction context.
Protect enterprise-built large language model (LLM) applications, retrieval-augmented generation (RAG) systems, prompts, application programming interfaces (APIs), model calls, tools, and production runtime behavior.
Public claims reviewed
1
Next question to verify
A test large language model (LLM) application event records prompt, application programming interface (API), model, retrieval, or tool interaction context.
Monitor approved AI workspaces, tenants, gateways, and model platforms such as ChatGPT Enterprise, Claude Enterprise, Gemini, Microsoft Copilot, Vertex AI, Elvex, or internal AI gateways.
Public claims reviewed
1
Next question to verify
Approved AI workspace activity appears with user, workspace or tenant, model or provider, and timestamp.
Secure large language model (LLM) applications, retrieval-augmented generation (RAG) systems, prompts, tool calls, application programming interfaces (APIs), model interactions, and runtime behavior.
Strong public supportGenerative AI application security
Protect enterprise-built large language model (LLM) applications, retrieval-augmented generation (RAG) systems, prompts, application programming interfaces (APIs), model calls, tools, and production runtime behavior.
Public claims reviewed
1
Next question to verify
A test large language model (LLM) application event records prompt, application programming interface (API), model, retrieval, or tool interaction context.
Detect, classify, redact, or block sensitive data in prompts, responses, files, retrieval, memory, and AI-connected workflows.
Public claims reviewed
1
Next question to verify
Sensitive prompt, response, or file test data is detected and classified during an AI interaction.
Review source claims →Strong public supportAI gateway, tool-connection, and runtime controls
Mediate model, agent, tool, application programming interface (API), connector, and Model Context Protocol (MCP) traffic through an enforcement point that applies identity-aware policy, content controls, routing, rate limits, and auditable allow or deny decisions.
Public claims reviewed
1
Next question to verify
A model, agent, tool, or Model Context Protocol (MCP) request passes through a named policy enforcement point.
Maintain accountable AI inventory, policy, risk assessments, approvals, exceptions, regulatory mappings, third-party oversight, and audit evidence across the AI lifecycle.
Framework references
GRC-09 · STA-08 · LOG-16
Lifecycle
Govern · Identify · Assess · Approve · Monitor
Security requirements with public support
1 requirement with public support
Limited public supportApproved AI usage monitoring
Monitor approved AI workspaces, tenants, gateways, and model platforms such as ChatGPT Enterprise, Claude Enterprise, Gemini, Microsoft Copilot, Vertex AI, Elvex, or internal AI gateways.
Public claims reviewed
1
Next question to verify
Approved AI workspace activity appears with user, workspace or tenant, model or provider, and timestamp.
AI assurance, red teaming, and supply-chain security
Test models, applications, retrieval-augmented generation (RAG) systems, agents, coding workflows, and AI artifacts before release and continuously thereafter, with reproducible findings and remediation gates.
Framework references
AIS-05 · AIS-08 · TVM-07 · TVM-13
Lifecycle
Develop · Test · Release · Monitor
Security requirements with public support
1 requirement with public support
Limited public supportAI model and supply-chain security
Discover, inventory, scan, validate, and monitor models, datasets, model artifacts, registries, dependencies, and AI development assets for tampering, unsafe serialization, provenance gaps, or malicious content.
Public claims reviewed
1
Next question to verify
A test model or AI artifact appears in inventory with origin, version, hash or provenance, and deployment context.
Secure trust, authorization, message flows, tool access, and communication between agents, tools, application programming interfaces (APIs), and external services.
Protect enterprise-built large language model (LLM) applications, retrieval-augmented generation (RAG) systems, prompts, application programming interfaces (APIs), model calls, tools, and production runtime behavior.
Public claims reviewed
1
Next question to verify
A test large language model (LLM) application event records prompt, application programming interface (API), model, retrieval, or tool interaction context.
Review source claims →Strong public supportAI gateway, tool-connection, and runtime controls
Mediate model, agent, tool, application programming interface (API), connector, and Model Context Protocol (MCP) traffic through an enforcement point that applies identity-aware policy, content controls, routing, rate limits, and auditable allow or deny decisions.
Public claims reviewed
1
Next question to verify
A model, agent, tool, or Model Context Protocol (MCP) request passes through a named policy enforcement point.
Limited public supportAI agent identity and permissions
Register AI agents as accountable identities, bind them to owners and delegating users, authorize task- and tool-level access, issue short-lived credentials, review access, and revoke or suspend agent authority.
Public claims reviewed
1
Next question to verify
A test agent is registered with a unique identity, accountable owner, purpose, and permitted resources.
Attribute AI usage and spend to accountable owners, workflows, agents, models, and business units while enforcing budget, rate-limit, and routing controls.
Framework references
BCR-02 · GRC-02 · I&S-02 · LOG-14
Lifecycle
Govern · Operate · Optimize
Security requirements with public support
3 requirements with public support
Limited public supportAI cost and usage controls
Visibility, attribution, budgeting, rate limiting, anomaly detection, and optimization for AI usage and spend across models, agents, workflows, and owners.
Public claims reviewed
1
Next question to verify
A controlled AI usage event is attributed to user, team, model, workflow, or owner with cost or token metrics.
Monitor approved AI workspaces, tenants, gateways, and model platforms such as ChatGPT Enterprise, Claude Enterprise, Gemini, Microsoft Copilot, Vertex AI, Elvex, or internal AI gateways.
Public claims reviewed
1
Next question to verify
Approved AI workspace activity appears with user, workspace or tenant, model or provider, and timestamp.
This page organizes research. Audit conclusions, certification assessments, control implementation statements, and vendor endorsements require separate evidence.