AWS bedrock-agentcore documentation change
Summary
Multiple terminology updates changing 'Amazon Bedrock AgentCore Policy' to 'Policy in AgentCore' and associated phrasing changes
Security assessment
Consistent branding/naming convention changes throughout document. Core security concepts (policy enforcement, Cedar language usage, safety checks) remain unchanged. No new security features or vulnerability fixes introduced
Diff
diff --git a/bedrock-agentcore/latest/devguide/policy.md b/bedrock-agentcore/latest/devguide/policy.md index 833419fba..5bdfb5645 100644 --- a//bedrock-agentcore/latest/devguide/policy.md +++ b//bedrock-agentcore/latest/devguide/policy.md @@ -7 +7 @@ Key benefitsKey features -# Amazon Bedrock AgentCore Policy: Control Agent-to-Tool Interactions +# Policy in Amazon Bedrock AgentCore: Control Agent-to-Tool Interactions @@ -9 +9 @@ Key benefitsKey features -Amazon Bedrock AgentCore Policy enables developers to define and enforce security controls for AI agent interactions with tools by creating a protective boundary around agent operations. AI agents can dynamically adapt to solve complex problems - from processing customer inquiries to automating workflows across multiple tools and systems. However, this flexibility introduces new security challenges, as agents may inadvertently misinterpret business rules, or act outside their intended authority. +Policy in Amazon Bedrock AgentCore enables developers to define and enforce security controls for AI agent interactions with tools by creating a protective boundary around agent operations. AI agents can dynamically adapt to solve complex problems - from processing customer inquiries to automating workflows across multiple tools and systems. However, this flexibility introduces new security challenges, as agents may inadvertently misinterpret business rules, or act outside their intended authority. @@ -11 +11 @@ Amazon Bedrock AgentCore Policy enables developers to define and enforce securit -With Amazon Bedrock AgentCore Policy, developers can create policy engines, create and store deterministic policies in them and associate policy engines with gateways. AgentCore Policy intercepts all agent traffic through Amazon Bedrock AgentCore Gateways and evaluates each request against defined policies in the policy engine before allowing tool access. +With Policy in AgentCore, developers can create policy engines, create and store deterministic policies in them and associate policy engines with gateways. Policy in AgentCore intercepts all agent traffic through Amazon Bedrock AgentCore Gateways and evaluates each request against defined policies in the policy engine before allowing tool access. @@ -13 +13 @@ With Amazon Bedrock AgentCore Policy, developers can create policy engines, crea -Policies are constructed using [Cedar language](https://www.cedarpolicy.com/en), an open source language for writing and enforcing authorization policies. This allows developers to precisely specify what agents can access and what actions they can perform. Amazon Bedrock AgentCore Policy provides the capability to author policies using natural language by allowing developers to describe rules in plain English instead of writing formal policy code in Cedar. Natural language-based policy authoring interprets what the user intends, generates candidate policies, validates them against the tool schema, and uses automated reasoning to check safety conditions such as identifying policies that are overly permissive, overly restrictive, or contain conditions that can never be satisfied - ensuring customers catch these issues before enforcing policies. +Policies are constructed using [Cedar language](https://www.cedarpolicy.com/en), an open source language for writing and enforcing authorization policies. This allows developers to precisely specify what agents can access and what actions they can perform. Policy in AgentCore also provides the capability to author policies using natural language by allowing developers to describe rules in plain English instead of writing formal policy code in Cedar. Natural language-based policy authoring interprets what the user intends, generates candidate policies, validates them against the tool schema, and uses automated reasoning to check safety conditions such as identifying policies that are overly permissive, overly restrictive, or contain conditions that can never be satisfied - ensuring customers catch these issues before enforcing policies. @@ -15 +15 @@ Policies are constructed using [Cedar language](https://www.cedarpolicy.com/en), -AgentCore Policy supports fine-grained permissions based on user identity and tool input parameters, making it possible to safely deploy autonomous agents at enterprise scale. By moving security controls outside of agent code, developers can focus on building innovative agent capabilities while maintaining strong security guarantees - eliminating the need for custom security implementation and reducing the risk of policy bypass through agent manipulation. +Policy in AgentCore supports fine-grained permissions based on user identity and tool input parameters, making it possible to safely deploy autonomous agents at enterprise scale. By moving security controls outside of agent code, developers can focus on building innovative agent capabilities while maintaining strong security guarantees - eliminating the need for custom security implementation and reducing the risk of policy bypass through agent manipulation. @@ -19 +19 @@ AgentCore Policy supports fine-grained permissions based on user identity and to -AgentCore Policy provides three key benefits that enable secure, scalable deployment of AI agents in enterprise environments: +Policy in AgentCore provides three key benefits that enable secure, scalable deployment of AI agents in enterprise environments: @@ -38 +38 @@ Write policies using natural language prompts or directly in Cedar (AWS's open-s -AgentCore Policy offers comprehensive capabilities for policy-based governance of agent interactions. AgentCore Policy provides the following key features: +Policy in AgentCore offers comprehensive capabilities for policy-based governance of agent interactions, including the following key features: @@ -63 +63 @@ AgentCore MCP Server: Vibe coding with your coding assistant -Getting started with AgentCore Policy +Getting started with Policy in AgentCore