Zenity Security: Features, Architecture, Limitations & Akto Comparison

Zenity is an AI agent security and governance platform that helps enterprises discover, monitor, and control AI agents across their environments. Its platform spans SaaS-managed agents (like Microsoft 365 Copilot and Salesforce Agentforce), homegrown agents built on cloud platforms (AWS Bedrock, Azure AI Foundry, Google Vertex AI), and device-based agents running on endpoints (GitHub Copilot, Cursor, Claude Desktop).

This blog explores what Zenity is, its key features, platform architecture, advantages and limitations, and a side-by-side comparison with Akto to help security teams choose the right AI agent security solution.

What is Zenity?

Zenity is a security and governance platform purpose-built for AI agents. Founded in 2021 and headquartered in New York, the company originally focused on low-code/no-code application security before pivoting to AI agent security and governance as agentic adoption accelerated across enterprises.

The platform delivers three core capabilities under a unified architecture:

• Zenity Observe (AI Observability),

• Zenity Govern (AI Security Posture Management)

• Zenity Defend (AI Detection & Response)

Together, these modules give security teams visibility into agent ownership, configurations, permissions, dependencies, and runtime behavior across SaaS, cloud, and endpoint environments.

Zenity positions itself as an agent-centric security platform that examines the full execution path of AI agents, including tool calls, memory access, data usage, and control flow, to surface intent-driven risk rather than relying on isolated prompt analysis.

Zenity’s Approach to Securing AI Agents

Key Components of Zenity’s AI Agent Security Platform

Zenity structures its platform around three pillars: Observe, Govern, and Defend. Each maps to a distinct phase of the agent lifecycle.

Zenity Observe: AI Observability

Zenity Observe continuously discovers and inventories AI agents across SaaS platforms, cloud frameworks, and endpoint devices. It surfaces agent ownership, configurations, permissions, tool integrations, memory usage, and behavioral patterns. Shadow agent discovery identifies unauthorized agents across departments and business units, bringing them under governance.

The platform replaces periodic posture scans with event-driven ingestion, reflecting configuration, permission, and connector changes within minutes of occurrence.

Zenity Govern: AI Security Posture Management (AISPM)

AISPM evaluates how agents are configured before they run. Security teams review agent permissions, memory access, instructions, actions, MCP integrations, and tool access across the entire lifecycle.

Policy enforcement automates alignment with frameworks like OWASP LLM Top 10, MITRE ATLAS, and NIST AI RMF.

Zenity covers posture assessment for Microsoft Copilot Studio agents, Salesforce Agentforce, ChatGPT Enterprise GPTs, and homegrown agents on Azure AI Foundry, AWS Bedrock, and Google Vertex AI.

Zenity Defend: AI Detection and Response (AIDR)

AIDR monitors agent intent and execution paths at runtime. It maps decision paths, tool invocations, and execution flow to detect prompt injection (direct and indirect), memory poisoning, tool misuse, data exfiltration, and covert agent behavior.

The platform uses a stateful threat engine that analyzes full interaction chains across users, agents, and sessions rather than evaluating each prompt in isolation.

A Correlation Agent interprets behavior patterns and explains what the agent was attempting to do, connecting posture gaps, runtime anomalies, and identity relationships into unified security incidents.

Advantages

• Enterprise governance depth -Posture management, policy controls, and compliance alignment to OWASP LLM and MITRE ATLAS

• Intent analysis - correlation across the full agent execution path, not just prompt-level filtering

• Industry recognition - Gartner 2025 Cool Vendor in Agentic AI TRiSM; Representative Vendor in Gartner's Market Guide for AI TRiSM; Forrester AI Governance Solutions Landscape Q2 2025; CyberSecurity Breakthrough "Agentic AI Security Solution of the Year"

• Microsoft-first depth - Inline prevention across the Microsoft AI platform stack with M12 as a strategic backer

Disadvantages

• Narrow agent coverage - Zenity has purpose-built support for Microsoft, Salesforce, ServiceNow, and ChatGPT enterprise AI platforms. Today’s enterprises have their AI Agents built with Agent frameworks like Langchain, or inside data platforms like Datarbricks and Zenity doesnt support those.

• No offensive security / red teaming capability - Zenity does not offer proactive attack simulation, adversarial probe libraries, or automated red teaming workflows. The platform is designed for detection and prevention, not for proactively finding what can be broken before production

• Developer toolchain gaps - Coverage of endpoint developer agents (Cursor, Copilot) is surface-level monitoring; Zenity does not secure MCP tool execution or the actual API interactions that agents make at runtime

Challenges and Limitations of Zenity

Governance-First, Not Attack-First

Zenity's architecture is built around observability and governance - discovering what agents exist and governing what they should do. This is valuable for enterprise risk management, but it does not replace proactive security testing. If an agent's configuration is secure on paper but the underlying model or toolchain has exploitable weaknesses, Zenity will not surface those vulnerabilities. A red team or adversarial probe library is required to fill that gap, which Zenity does not provide.

SaaS-Centric Blind Spots

Zenity's strength is enterprise SaaS: Microsoft, Salesforce, ServiceNow. But the fastest-growing segment of agentic AI is in homegrown applications - developers building autonomous agents using open-source frameworks like LangChain, CrewAI, or AutoGen, connected to internal APIs and databases. These environments are outside Zenity's core coverage model.

Alert-to-Action Gap

While Zenity's Correlation Agent improves incident narratives over raw alerting, the platform still requires human interpretation to translate findings into developer-side remediation. There is no built-in workflow to push findings back into CI/CD pipelines, or to surface agent vulnerabilities in a format that developers can act on directly.

Akto’s Approach to MCP and AI Agent Security

Akto offers agentic AI security through two purpose-built products: Akto Atlas (secures how employees use AI tools, MCPs, and agents on endpoints) and Akto Argus (secures homegrown AI applications, agents, and MCP servers). Together, they cover the full agentic attack surface with an emphasis on deep discovery, adversarial testing, and runtime enforcement.

AI Agent and MCP Discovery

Akto automatically discovers all AI agents, MCP servers, and LLM-associated endpoints across infrastructure, including shadow resources that security teams have no visibility into. This creates a comprehensive inventory of the entire agentic attack surface, not limited to specific SaaS platforms.

Agentic Red Teaming

Akto simulates adversarial attacks designed specifically for agent and MCP risks: prompt injection, tool poisoning, context leakage, permission escalation, and emerging agentic threats. Running 1000+ probes across discovered agents and MCP servers, Akto’s red teaming identifies weaknesses before attackers do. This proactive testing capability is a fundamental differentiator for teams that need to validate their agent security posture under real attack conditions.

AI Guardrails

Akto enforces actionable AI guardrails and automated policy actions to prevent harmful agent behavior, implement least-privilege access, mask sensitive data, and maintain compliance across autonomous workflows.

MCP Server Security

Akto provides dedicated MCP security that goes beyond monitoring MCP usage. It tests MCP server configurations, validates tool definitions, identifies protocol-level vulnerabilities, and secures the tool-calling surface that agents depend on. For organizations deploying custom MCP infrastructure, this is essential coverage that governance-only platforms do not provide.

Why Enterprises prefer Akto over Zenity

Choosing between Akto and Zenity?

Talk to our team and we'll walk you through exactly what each platform covers - and where the gaps are.