The most complete platform for securing AI agents, MCP, and the full AI lifecycle
of enterprises are exploring AI applications
of enterprises unprepared for AI security challenges
of enterprises investing in AI security in 2025

MCP gives agents direct access to tools and resources without proper authorization or guardrails.

Prompt injections can trick agents into rogue actions, escalate privileges, and expose sensitive data.

Agents act at machine speed, allowing simple mistakes to cascade across systems.

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platform
Securing autonomous AI requires a comprehensive approach that spans the entire lifecycle—from discovery and hardening to runtime protection and governance.
PointGuard’s Agentic Security Platform delivers the industry’s most robust protection for agents, MCP infrastructure, models, and data. With integrated guardrails, the zero-trust MCP Security Gateway, DLPprotection, and deep visibility, organizations can safely scale agentic AI across the enterprise.

agentic ai
AI agents interact directly with enterprise tools, APIs, and data through the Model Context Protocol. The MCP Security Gateway provides a centralized control point that governs how agents access these resources. With zero-trust authorization, granular tool permissions, and secure secrets management, organizations can safely deploy autonomous agents while maintaining security, visibility, and policy enforcement across MCP integrations.
Enforce agent access through the MCP Security Gateway
Apply granular tool-level permissions for MCP tools and APIs
Protect credentials with Secrets Vault and identity controls
visibility
Visibility is the first step to securing agentic AI. Continuous discovery identifies every AI project, model, dataset, agent, MCP server, and endpoint across your enterprise, regardless of where they operate. By exposing shadow agents and unmanaged resources, security teams gain the clarity needed to manage risk, enforce governance, and scale agentic AI safely.
Inventory AI agents, models, datasets, and MCP resources
Detect risky or unapproved models, agents, and tools
Eliminate agentic blind spots with continuous discover
hardening
AI agents behave unpredictably, which makes continuous adversarial testing essential. Adaptive red teaming simulates real-world attacks against agents, models, MCP integrations, and tool workflows to uncover weaknesses before deployment. Security posture management then hardens agentic environments by identifying misconfigurations, blocking malicious components, and enforcing best practices across the AI stack.
Simulate attacks against AI agents, models, and MCP tools
Detect prompt injection, jailbreaks, and unsafe behaviors
Identify misconfigurations and harden AI environments
guardrails
Agentic AI delivers value through continuous interaction with enterprise systems, APIs, and data pipelines. Intelligent guardrails enforce security policies across agent prompts, responses, and tool interactions in real time. Built-in DLP protection inspects content for sensitive data, detecting malicious inputs, unsafe outputs, and policy violations before agents execute actions.
Inspect agent prompts, responses, and tool interactions
Enforce policies in real-time across agent actions and tool use
Prevent data leaks automatically blocking, masking, or redacting
integrity
Agentic systems rely on complex supply chains of MCP servers, tools, models, libraries, and third-party services. Every dependency introduces potential risk. The platform continuously monitors these ecosystems while the Trusted MCP Knowledge Base evaluates and rates thousands of MCP servers and tools, helping security teams identify risky components before agents interact with them.
Monitor agent dependencies, MCP servers, and integrations
Correlate risks across applications, models, & infrastructure
Evaluate MCP tools using the Trusted MCP Knowledge Base
Clients Words
AppSOC brings it all together in one intuitive dashboard – helping me prioritize vulnerabilities and ensure compliance.
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