Vendor evidence

Zenity claims continuous discovery, inventory, ownership, configuration, permission, dependency, behavior, policy, posture, graph, incident, and audit governance across software as a service (SaaS)-managed, home-grown, and device-based AI agents.

Zenity platform materials reviewed did not provide a public customer-facing product claim for automated adversarial testing, repeatable attack suites, model or agent red teaming, or release-gate evaluation.

Zenity claims pre-session evaluation of Claude configurations, Model Context Protocol (MCP) servers, skills, plugins, and agent extensions plus dependency and attack-path mapping across agents, tools, knowledge, automations, triggers, and actions.

Zenity claims real-time inline protection and policy enforcement over agent execution, application programming interface (API) calls, tools, prompts, memory, sensitive data, credentials, commands, and multi-step behavior across software as a service (SaaS), cloud, and endpoints.

Zenity claims ownership, identity relationship, permission, tool-access, and execution-path mapping with policy enforcement against over-privileged agents, unauthorized application programming interface (API) calls, restricted-data access, and privilege escalation.

Zenity claims lifecycle visibility, posture evaluation, and runtime enforcement for Claude Code and device-based coding agents across code changes, commits, pull requests, configurations, Model Context Protocol (MCP) servers, skills, plugins, commands, credentials, files, tools, and memory.

Token Security claims lifecycle governance for AI agents with continuous discovery, ownership, intent, access, policy, compliance validation, audit trails, behavioral monitoring, and automated remediation from creation through retirement.

Token Security product materials reviewed did not provide a public product claim for automated adversarial testing, repeatable attack suites, model or agent red teaming, or release-gate evaluation.

Token Security product materials reviewed did not establish model artifact scanning, provenance, signing, dependency or Model Context Protocol (MCP) component analysis, tamper detection, or model-registry release controls.

Token Security claims behavioral monitoring, suspicious-activity alerting, runtime constraints, intent-based permission enforcement, dynamic risk response, and automated remediation for AI agents and their identities.

Token Security claims discovery and lifecycle control for agent identities, owners, intent, credentials, tokens, roles, permissions, access paths, behavioral baselines, access reviews, least-privilege enforcement, remediation, and deprovisioning.

Token Security claims discovery and governance of coding agents, custom GPTs, Model Context Protocol (MCP) servers, cloud and software as a service (SaaS) access, credentials, permissions, owners, intent, activity, and least-privilege boundaries.

Iterate.ai claims centralized policy, observability, compliance controls, audit trails, data classification, retention, cost governance, and usage visibility across employees, applications, business agents, coding agents, models, and providers.

Iterate.ai AgentWatch and AgentOne materials reviewed did not provide a public product claim for automated adversarial testing, repeatable attack suites, model or agent red teaming, or release-gate evaluation.

Iterate.ai claims repository indexing and code analysis for Model Context Protocol (MCP)-connected workflows with optional Semgrep and Trivy security scanning, dependency management, and Model Context Protocol (MCP) server installation and configuration controls.

AgentWatch claims a centralized OpenAI-compatible gateway with multi-provider routing, data loss prevention (DLP), prompt screening, guardrails, blocking, authentication, role-based access, encrypted secrets, audit logs, budgets, caching, failover, and real-time policy enforcement.

AgentWatch claims JWT authentication, role-based access control, organization and team hierarchies, encrypted application programming interface (API)-key management, user and device attribution, correlated request logs, and policy status across business and coding agents.

Iterate.ai claims a private coding-agent environment with code privacy, security review, activity audit, human approval for file changes, Git checkpoints, diff review, repository indexing, Semgrep and Trivy scanning, dependency management, and Model Context Protocol (MCP) server controls.

WitnessAI claims AI-interaction visibility and attribution, intent-based policies that consider risk, cost, and purpose, model routing based on cost, and audit trails supporting financial accountability.

Tenable AI Exposure and AI-SPM materials reviewed did not provide a public product claim for AI usage-cost attribution, token or spend metrics, budgets, chargeback, or cost-aware model routing.