See how Entro Security's public claims connect to security requirements and MITRE ATLAS references.
What this page shows
Requirements connected to Entro Security'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.
Version2026.06Current source
Related requirements11security questions in this research
Security requirements with public support9strong or limited public support
References64identifiers, 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.
Contributes
4
Closely aligned
7
Requirement connections
From Entro Security'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.
ContributesSpecific 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
AML.T0007 · AML.T0084
Lifecycle
Govern · Identify · Monitor
Security requirements with public support
1 requirement with public support
Threat discovery references clarify which AI artifacts and agent configurations defenders must know exist.
Limited public supportUnapproved AI use discovery
Discover and monitor workforce AI tools, accounts, prompts, domains, models, users, and usage outside approved controls.
Public claims reviewed
1
Next question to verify
An unmanaged AI app used by a test user appears in discovery inventory with user, app or domain, 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 supportControls for unapproved AI use
Block, coach, redirect, or contain non-approved AI use and policy-violating AI interactions.
Public claims reviewed
1
Next question to verify
A policy blocks, coaches, redirects, or contains a test interaction with an unapproved AI destination.
Review source claims →Limited 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
AML.M0024 · AML.T0084
Lifecycle
Govern · Identify · Assess · Approve · Monitor
Security requirements with public support
1 requirement with public support
Strong public supportAI governance, risk, and compliance
Inventory AI systems and owners, translate policy and regulatory obligations into governed workflows, assess risk, manage approvals and exceptions, and retain audit evidence across the AI lifecycle.
Public claims reviewed
1
Next question to verify
A test AI system is registered with owner, intended use, risk tier, lifecycle state, and applicable obligations.
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.
Limited public supportAI coding-agent and workstation security
Discover and govern AI coding agents, integrated development environment (IDE) assistants, command-line agents, skills, hooks, extensions, Model Context Protocol (MCP) tools, filesystem access, commands, network activity, secrets, and software-supply-chain actions on developer workstations and build environments.
Public claims reviewed
1
Next question to verify
A test coding agent and its skills, hooks, extensions, or Model Context Protocol (MCP) tools appear in an attributable inventory.
Authorize, log, and control agent-to-agent, agent-to-tool, Model Context Protocol (MCP), connector, and tool-chain handoffs.
Public claims reviewed
1
Next question to verify
An agent, tool, connector, or Model Context Protocol (MCP) handoff logs source identity, destination, and authorization decision.
Review source claims →Strong public supportNon-human identity and service-account security
Inventory, least privilege, credential hygiene, monitoring, and lifecycle management for non-human identities, workloads, service accounts, application programming interface (API) keys, and machine credentials.
Public claims reviewed
1
Next question to verify
A test service account, agent identity, or non-human identity appears in inventory with owner and privileges.
Secure trust, authorization, message flows, tool access, and communication between agents, tools, application programming interfaces (APIs), and external services.
Observe and govern agent plans, memory, tool calls, delegated tasks, autonomy, runtime decisions, and outcomes.
Public claims reviewed
1
Next question to verify
A test agent run captures plan, steps, tool calls, outcome, and timestamps.
Review source claims →Limited 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.
Strong public supportNon-human identity and service-account security
Inventory, least privilege, credential hygiene, monitoring, and lifecycle management for non-human identities, workloads, service accounts, application programming interface (API) keys, and machine credentials.
Public claims reviewed
1
Next question to verify
A test service account, agent identity, or non-human identity appears in inventory with owner and privileges.
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.
Strong public supportAction-taking agent monitoring
Observe and govern agent plans, memory, tool calls, delegated tasks, autonomy, runtime decisions, and outcomes.
Public claims reviewed
1
Next question to verify
A test agent run captures plan, steps, tool calls, outcome, and timestamps.
Review source claims →Strong public supportNon-human identity and service-account security
Inventory, least privilege, credential hygiene, monitoring, and lifecycle management for non-human identities, workloads, service accounts, application programming interface (API) keys, and machine credentials.
Public claims reviewed
1
Next question to verify
A test service account, agent identity, or non-human identity appears in inventory with owner and privileges.
This page organizes research. Audit conclusions, certification assessments, control implementation statements, and vendor endorsements require separate evidence.