Scaling Security in AI: Addressing Access Control Challenges with AgentCore Gateway
The Need for Secure Access Management in AI Platforms
As enterprises rapidly adopt AI agents to automate workflows and enhance productivity, they face a critical scaling challenge: managing secure access to thousands of tools across their organization. Modern AI deployments no longer involve a handful of agents calling a few APIs—instead, enterprises are building unified AI platforms where hundreds of agents, consumer AI applications, and automated workflows need to access thousands of Model Context Protocol (MCP) tools spanning different teams, organizations, and business units.
Addressing Security and Governance Challenges
This increase in scale creates a fundamental security and governance problem: How do you make sure each calling principal—whether it’s an AI agent, user, or application—only accesses the tools they’re authorized to use?
Introducing Gateway Interceptors for Enhanced Security
To address these challenges, we are launching a new feature: gateway interceptors for Amazon Bedrock AgentCore Gateway. This powerful capability provides fine-grained security, dynamic access control, and flexible schema management.
Fine-Grained Access Control for Tool Access
Enterprise customers are deploying thousands of MCP tools served through a unified AgentCore Gateway. The challenge is securing MCP tool access based on the calling principal’s access permissions and contextually responding to ListTools, InvokeTool, and Search calls.
Schema Translation and Data Protection
Customers face complex challenges in managing the contract between AI agents and downstream APIs while maintaining security and flexibility. Organizations must dynamically map MCP request schemas to downstream API schemas, enabling critical data protection capabilities.
Tenant Isolation for Multi-Tenant SaaS
Organizations offering agents or tools as a service face complex multi-tenancy requirements, necessitating proper tenant isolation and access controls based on user ID and tenant ID.
Dynamic Tool Filtering
Customers need real-time, context-aware tool filtering that adapts to changing permissions and user contexts. Unified MCP servers can filter tools in two stages based on agent permissions and workspace context.
Managing Identity Context with Custom Header Propagation
AI agents are fundamentally different from traditional microservices, necessitating secure workflows that respect user identity while mitigating security vulnerabilities.
Impersonation vs. Act-on-Behalf Approaches
Businesses face a fundamental security decision in how identity context propagates through multi-hop workflows, opting between impersonation or act-on-behalf models to manage security risks effectively.
AgentCore Gateway: Secure MCP Integration for AI Agents
AgentCore Gateway links existing APIs and AWS Lambda functions into agent-compatible tools, offering seamless integration and security management across enterprise systems.
Use Cases with Gateway Interceptors
Gateway interceptors enable an array of flexible security and access control patterns, from fine-grained access for tool invocation to dynamic tools filtering and managing identity propagation.
Observability and Monitoring
Comprehensive observability provided by AgentCore Observability is critical for monitoring, debugging, and auditing AI agent workflows, ensuring security and compliance.
Conclusion
AgentCore Gateway with gateway interceptors addresses the fundamental security and access control challenges faced by organizations deploying agentic AI systems at scale, providing a flexible foundation for implementing enterprise-grade security controls.
Navigating the Security Landscape of AI Agents: Introducing Gateway Interceptors
As enterprises increasingly turn to AI agents to streamline workflows and boost productivity, they face an escalating challenge: how to effectively manage secure access to a vast array of tools across their organizations. This isn’t just about a handful of agents calling basic APIs anymore; organizations are now creating consolidated AI platforms where hundreds of agents and automated workflows interact with thousands of Model Context Protocol (MCP) tools across various teams and business units.
This monumental shift brings with it critical questions regarding security and governance. How can organizations ensure that every executing principal—be it an AI agent, user, or application—only accesses the tools for which they are authorized? How do we adapt access dynamically based on user identity, agent context, and the specific channel through which access is requested? Furthermore, how can we safeguard sensitive data that traverses complex workflows while maintaining performance and efficiency?
To tackle these formidable challenges, we are excited to announce our latest feature: gateway interceptors for Amazon Bedrock AgentCore Gateway. This robust capability offers fine-grained security, dynamic access control, and flexible schema management, all designed to enhance the security posture of AI deployments.
Fine-Grained Access Control for Tool Access
For enterprise customers, managing thousands of MCP tools via a unified AgentCore Gateway can be overwhelming. The need for security-conscious filtering is paramount, as permissions must adapt to various dynamic factors—user identity, execution context, and workspace access levels. This dynamic environment necessitates a filtering system where permission changes are immediate, ensuring that outdated permissions do not clutter tool availability.
User-Based Tool Filtering
Imagine an organization where users interact with multiple tools based on their roles and contexts. This requires an intelligent filtering system that assesses user authorizations before presenting a list of accessible tools. Using a sophisticated access management strategy, organizations can ensure that only the relevant tools are made available to each user, as illustrated in a user-based tool filtering diagram.
Schema Translation and Data Protection
One of the most significant challenges organizations face is managing the contract between AI agents and downstream APIs while ensuring security and flexibility. Organizations need to map MCP request schemas to downstream API schemas dynamically to protect sensitive data.
Data Leakage Prevention
Sensitive information, such as personally identifiable information (PII), must be managed with extreme caution. Organizations can achieve this by implementing schema translation capabilities that allow for sensitive data redaction, ensuring that unnecessary data is not sent downstream.
Decoupling from Downstream Implementations
Maintaining separation between MCP schemas and downstream implementations allows backend teams to modify API specifications without disrupting agent functionalities. This makes it possible to evolve APIs without requiring retraining of AI models, ensuring smoother transitions.
Tenant Isolation for Multi-Tenant SaaS
Organizations offering agents or tools as a service require strong multi-tenancy capabilities. Ensuring tenant isolation while passing and validating both tenant and user IDs is critical. The ability to enforce security controls while navigating complex multi-tenant architectures is essential to maintain data privacy and compliance.
Dynamic Tool Filtering
Real-time and context-aware filtering is crucial for organizations harnessing AI agents. With the new agent framework, organizations can filter tools effectively and dynamically—across two stages: agent permissions and workspace context—without employing caching that could lead to deprecated permission states.
Custom Header Propagation and Identity Context Management
AI agents operate fundamentally differently from traditional microservices. Because they execute workflows on behalf of users, managing identity context throughout these workflows is paramount. Failure to do so can expose organizations to security vulnerabilities like unauthorized access and privilege escalation.
Impersonation vs. Act-on-Behalf Approaches
Organizations must make a critical security choice in how identity context propagates through workflows. We recommend an act-on-behalf approach over impersonation. This means each service only receives the permissions necessary for its tasks, significantly reducing security risks and enhancing audit trails.
Protecting Against Unauthorized Actions
By employing scoped tokens tailored for specific downstream targets, organizations can effectively prevent scenarios where unauthorized service actions occur, thereby implementing the principle of least privilege and reducing security risks.
AgentCore Gateway: A Secure MCP Integration for AI Agents
The AgentCore Gateway unifies access across various tools, facilitating secure integration within enterprise systems. With gateway interceptors, organizations can implement fine-grained control measures during critical stages of data interaction, ensuring that tools can only be accessed by those who are authorized.
Key Features of Gateway Interceptors
- Request Interceptor: Handles incoming requests, validating user credentials and organizational policies.
- Response Interceptor: Modifies outgoing responses, ensuring compliance with security protocols and auditing regulations.
Use Cases with Gateway Interceptors
Implementing Fine-Grained Access Control
With gateway interceptors, organizations can restrict tool invocation based on user roles, ensuring that users can only request tools they have explicit access to.
Dynamic Tool Filtering
Leveraging semantic search capabilities alongside standard operations enables secure, context-sensitive tool discovery that aligns with user permissions, thereby preventing unauthorized exposure.
Conclusion
As businesses scale their AI agent frameworks, the integration of gateway interceptors within the AgentCore Gateway stands to revolutionize how enterprises manage security, compliance, and access control. By implementing flexible control measures, organizations can safeguard sensitive information, maintain compliance, and streamline operational workflows, ensuring a secure AI ecosystem that empowers productivity and innovation.
To explore the benefits of gateway interceptors further and learn about their implementation, consult our comprehensive documentation for fine-grained access control and schema management.
By addressing the security and governance challenges that arise as AI agents proliferate, organizations can harness the full strength of AI capabilities while maintaining a secure and compliant operational landscape.