CVE-2026-18830 in Amazon Bedrock AgentCore harness
Summary
by MITRE • 08/04/2026
Insufficient input validation in Amazon Bedrock AgentCore harness might allow an authenticated remote user to execute configured tools bypassing model invocation and security controls via crafted content blocks in conversation messages. AWS has addressed this issue. No customer action is required.
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Analysis
by VulDB Data Team • 08/04/2026
This vulnerability represents a critical authorization bypass flaw within Amazon Bedrock's AgentCore component that could enable authenticated remote attackers to circumvent established security controls and execute arbitrary tools through carefully crafted input manipulation. The weakness stems from inadequate validation of content blocks within conversation messages, allowing malicious actors to inject tool execution commands that bypass the normal model invocation workflow. This vulnerability specifically affects the AgentCore harness which serves as the foundational component for processing conversational inputs and orchestrating tool executions within Bedrock's agent framework.
The technical implementation flaw resides in how the system validates and processes content blocks within conversation messages, creating a path where authenticated users can manipulate input parameters to trigger unauthorized tool execution sequences. This represents a classic case of insufficient input validation that aligns with CWE-20, which describes weaknesses related to inadequate validation of input data. The vulnerability operates at the boundary between user input processing and tool execution orchestration, allowing attackers to craft messages that contain malicious content blocks designed to exploit the validation gap in the AgentCore component.
The operational impact of this vulnerability extends beyond simple privilege escalation as it fundamentally undermines the security model of Bedrock's agent system by enabling unauthorized tool execution without proper authorization checks. An attacker could potentially leverage this weakness to access sensitive data, perform administrative actions, or execute commands through the configured tools available within the agent environment. This represents a significant risk to organizations using Bedrock agents for sensitive operations, particularly those involving data processing, system administration, or business-critical workflows where unauthorized tool execution could lead to data breaches or operational disruption.
The mitigation strategy implemented by AWS addresses the core validation issue within the AgentCore harness through enhanced input sanitization and stricter content block validation mechanisms. This fix ensures that all content blocks within conversation messages undergo comprehensive validation before any tool execution can occur, preventing the bypass of security controls that would normally prevent unauthorized access to system capabilities. Organizations using Amazon Bedrock should monitor for and apply the available patches as recommended by AWS, though the vulnerability disclosure indicates that no customer action is required since the fix has been implemented at the service level. This incident highlights the importance of robust input validation in AI agent systems where user-provided content can directly influence system behavior and security posture.
The vulnerability demonstrates the increasing complexity of securing modern AI platforms where traditional access control mechanisms must be augmented with input validation to prevent exploitation through crafted user interactions. This aligns with ATT&CK technique T1059 which covers command and scripting interpreter usage, particularly when systems fail to properly validate user inputs that could contain malicious payloads designed to execute unintended commands through legitimate tool interfaces. Organizations should consider implementing additional monitoring for unusual tool execution patterns within their Bedrock agent environments as a defensive measure against similar vulnerabilities in other AI platforms.