Source URL: https://embracethered.com/blog/posts/2025/aws-kiro-aribtrary-command-execution-with-indirect-prompt-injection/
Source: Embrace The Red
Title: AWS Kiro: Arbitrary Code Execution via Indirect Prompt Injection
Feedly Summary: On the day AWS Kiro was released, I couldn’t resist putting it through some of my Month of AI Bugs security tests for coding agents.
AWS Kiro was vulnerable to arbitrary command execution via indirect prompt injection. This means that a remote attacker, who controls data that Kiro processes, could hijack it to run arbitrary operating system commands or write and run custom code.
In particular two attack paths that enabled this with AWS Kiro were identified:
AI Summary and Description: Yes
Summary: The text highlights a significant security vulnerability in AWS Kiro, specifically an arbitrary command execution vulnerability via indirect prompt injection. For professionals in AI and cloud security, this underscores the critical need for robust testing frameworks in AI systems to mitigate potential exploits.
Detailed Description:
The provided text discusses a security assessment of AWS Kiro, an AI coding agent, revealing a critical vulnerability that allows malicious actors to execute unauthorized commands remotely. This finding is particularly relevant for security professionals in cloud computing and AI domains, emphasizing the importance of proactive security measures.
Key Points:
– **Product Tested**: AWS Kiro, an AI coding agent
– **Vulnerability Identified**: Arbitrary command execution through indirect prompt injection
– **Attack Vector**: A remote attacker with control over the data processed by Kiro can exploit this vulnerability to run unauthorized OS commands or execute custom code
– **Specific Attack Paths**: The analysis points to two specific methods by which the vulnerability could be exploited
Practical Implications:
– **Security Testing**: The issue highlights the necessity for continuous security testing and auditing of AI systems, especially those deployed in production environments.
– **Defense in Depth**: Implementing layers of security controls can help mitigate such risks—emphasizing the significance of adopting a Zero Trust framework in AI and cloud domains.
– **Awareness and Response**: Security professionals should stay informed about such vulnerabilities to ensure that corrective measures are taken promptly to secure systems against potential exploits.
This analysis reinforces the critical nature of vigilance in security practices, especially as cloud-based AI solutions become more prevalent and integral to infrastructure.