# Platform ## AI Agent Security & Governance Platform Autonomous AI agents introduce new behaviors across the enterprise beyond the design of traditional security controls. ![Hero](https://cdn.sanity.io/images/bqvkdjz2/production/1de50c0dd09408e17b35cb184c079091614c199c-1920x1080.gif) - [Get a Demo](/book-a-demo) --- ## Securing AI Requires a New Approach Agents don’t just generate responses, they execute. They maintain state, invoke tools, access data, and chain actions across systems. This shifts risk from what a model produces to how an agent is configured, what it is allowed to do, and how its actions propagate at runtime. ### Tool Innovation & Action Abuse Agents can be steered into unintended actions invoking powerful tools or chaining workflows that impact systems, even when individual prompts appear safe. ### Execution-Driven Data Exposure Sensitive data can be accessed, moved, or exposed through agent actions, memory, or tool calls without ever appearing in a prompt or response. ### Permission & Configuration Risk Over-privileged or misconfigured agents can modify systems or access restricted data, creating risk that model filters and output controls cannot stop. ## Full-Coverage Security at the Agent Layer Zenity is built for this reality. By securing AI at the agent layer, across buildtime configuration and runtime execution, Zenity provides full coverage for the risks introduced by agentic systems, not just partial protection at the model layer. ### Tab 1 **You can’t secure and govern what you can’t see** Discover and inventory AI agents across all platforms. Security teams gain clear visibility into agent ownership, configurations, permissions, dependencies, and runtime behavior - establishing a reliable source of truth for agent risk **Key Features:** - Automatic discovery across your environment - Real-time agent inventory with ownership and dependency mapping - Behavioral analysis and usage pattern tracking - Shadow AI detection and governance - Cross-environment correlation and risk assessment [Explore Zenity Observe](/platform/ai-observability) ### Tab 2 **Configuration vulnerabilities amplify at runtime** Apply secure-by-design guardrails to agents before they reach runtime. AISPM enables teams to review configurations, permissions, tool access, and memory use early, reducing exposure caused by over-privileged or misconfigured agents. **Key Features:** - Security-by-design policies for agent configurations - Least privilege access control and validation - OWASP LLM Top 10 and MITRE ATLAS alignment - DevSecOps integration and pre-deployment scanning - Compliance framework mapping and reporting [Explore Zenity Govern](/platform/ai-security-posture-management) ### Tab 3 **Malicious intent won’t trigger traditional alerts** Monitor step-level agent execution to detect risky or malicious behavior as it unfolds. AIDR correlates agent intent, permissions, and actions, enabling security teams to respond immediately including inline enforcement to stop unsafe actions before impact. **Key Features:** - Intent-based threat detection and behavioral analysis - Step-level monitoring with full execution context - Real-time anomaly detection and privilege escalation alerts - Automated response playbooks and containment - Threat intelligence integration and correlation [Explore Zenity Defend](/platform/ai-security-platform/aidr) ## Don't Just Detect, Understand What Happened Zenity Issues connects posture gaps, runtime anomalies, identity relationships, and graph-based insights to produce high-confidence security incidents that clearly show what happened, why, and what was impacted. By revealing intent, something traditional detections can’t capture, our Correlation Agent interprets agent behavior, flags manipulation attempts, and explains what the agent was actually doing, eliminating guesswork and speeding investigations. ## All Platforms. Everywhere. AI agents already span SaaS, cloud, custom stacks, and endpoints. Control gaps expand as fast as adoption. ### SaaS-managed Agents Secure AI Agents embedded in your productivity tools like Salesforce Agentforce or built with one like Copilot Studio - with full visibility and policy enforcement. - [SaaS-managed Agents](/use-cases/agent-type/saas-managed) ### Home-grown Agents Secure home-grown AI agents on platforms like AWS Bedrock and Google Vertex AI, covering everything from configuration to runtime risk. - [Home-grown Agents](/use-cases/agent-type/home-grown) ### Device-based Agents Gain control over local agents with lightweight monitoring, detection, and response. - [Device-based Agents](/use-cases/agent-type/device-based) ## Built to Tackle Ambiguity and Risk As AI agent adoption scales, security teams lose visibility into behavior, access, and risk propagation. Zenity restores context to understand, govern, and control agents across teams and environments. ### Comprehensive Visibility Know which agents exist, who owns them, what they can access, and how they behave across your environment. ### Preemptive Risk Prevention Enforce guardrails early to prevent risky configurations and over-permissioned agents from reaching runtime. ### Actionable Threat Signals Correlate configuration, permissions, and runtime behavior to surface intent-driven risk - not isolated alerts or noise. ### Contextual Incident Response Detect and respond with full context of agent execution paths, enabling faster identification and mitigation of sophisticated threats. ### Adopt with Confidence Apply consistent governance and enforcement across environments to support AI adoption without expanding the attack surface. ## Traditional Tools Were Not Built with Agents in Mind Most existing security tools, including model-focused controls and legacy platforms, were not designed to govern autonomous execution. While they remain critical for securing infrastructure, identities, and data, they lack visibility into how agents reason, chain actions, and operate across systems. Traditional tools fail because agents execute decisions, not just code paths or requests. ### AppSec & DLP Focus on inputs and outputs, not logic, memory, or actions agent take. ### EDR/XDR Detect system-level threats, but miss mulit-step agent behavior and decision-making context. ### CNAPP & CSPM Govern cloud infrastructure, not agents running inside applications or invoking external tools. ## Outcomes That Drive Secure AI Adoption ### Visibility & Governance **Left** ### Use Case Enable security teams to discover and inventory agents, so they can enforce policies and reduce unmanaged risk. **Right** ### Benefit Operate with confidence; know your AI agents are secure, governed, and under control. ### Strengthen AI governance By giving security teams continuous visibility into agents before they become a risk ### Accelerate safe AI agent adoption Across business units by giving security teams oversight and policy controls ### Replace manual discovery efforts With scalable visibility by securing AI adoption without slowing down innovation ### Risk Assessment & Management **Left** ### Use Case Give security teams a way to review AI agents for excessive permissions, sensitive data access, and shadow integrations before they cause damage **Right** ### Benefit Reduce the attack surface; prevent threats by design by ensuring proper configurations and addressing vulnerabilities in buildtime. ### Prevent costly misconfigurations That lead to breaches, compliance violations, or IP leakage ### Reduce security incident costs By proactively mitigating risks before agents or apps go live ### Embed security earlier For AI build cycles, enabling faster innovation with guardrails ### Threat Detection & Response **Left** ### Use Case Equip security teams to detect and respond to runtime threats like prompt injection and data leaks with real-time context **Right** ### Benefit Respond in real time; detect AI-specific risks like prompt injection, tool misuse, and unsafe data access missed by traditional tools. ### Minimize mean time to detect (MTTD) and respond (MTTR) With a platform purpose-built for AI-specific risks and threats ### Reduce breach impact By stopping sensitive data exposure or unauthorized tool usage in real time ### Extend existing security workflows To cover AI threats without needing to rip and replace tooling ## Research and Insights Shaping the Future of AI Agent Security Zenity Labs delivers original research, threat intelligence, and hands-on experimentation focused on the emerging risks of AI Agents. From real-world attack techniques to prompt injection patterns and policy best practices, our team explores what others haven’t so you can secure what’s next. - [Explore Zenity Labs](https://labs.zenity.io/) ## Ready to Secure Your AI Agents? Join leading enterprises who trust Zenity to secure their AI agent
deployments across SaaS, Cloud, and Endpoint environments. - [Get a Demo](/book-a-demo) --- ## Contact Explore how Zenity secures AI agents and enterprise copilots. For sales or questions, visit [zenity.io](https://www.zenity.io). --- **More content:** [Home](/.md) | [Blog](/blog.md) | [Resources](/resources.md) | [Labs](/labs.md) | [Academy](/academy.md) | [Use cases](/use-cases.md) | [Newsroom](/company-overview/newsroom.md)