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Safeguard your generative AI workloads from prompt injections
- Generative AI applications introduce new security challenges, including prompt injections and excessive agency. Developing a comprehensive threat model can help to identify potential vulnerabilities related to prompt injection, such as unauthorized data access.
- AWS provides generative AI security strategies that can be used to create appropriate threat models to safeguard AI systems. This blog post provides an overview of prompt injection risks in generative AI and outlines defense mechanisms that can be implemented.
- Prompt injections involve manipulating prompts to influence LLM outputs, with the intent to introduce biases or harmful outcomes. There are two main types of prompt injections: direct and indirect.
- Defending against prompt injection involves a multi-layered approach, including content moderation, secure prompt engineering, access control, and ongoing monitoring and testing. AWS provides tools, such as Guardrails, user and content moderation, and input validation.
- Prompt engineering, the practice of carefully crafting the instructions and context provided to an LLM, plays a crucial role in maintaining control over the model’s behavior and mitigating risks. Developers can use prompt templates as an effective technique to mitigate prompt injection risks.
- Access control and establishing trust boundaries are essential components of a comprehensive security strategy for generative AI applications. Monitoring and logging are crucial for detecting and responding to potential prompt injection attempts.
- You can use AWS CloudTrail to monitor for potential prompt injection attempts and AWS CloudWatch to set up dashboards and alarms, providing real-time visibility into the application’s behavior and performance.
- To protect generative AI applications from prompt injections, a defense-in-depth strategy that combines technical controls, system design, and ongoing vigilance can be adopted by organizations.
- By adopting a proactive, layered security approach, organizations can confidently realize the potential of generative AI while maintaining user trust and protecting sensitive information.
- AWS Identity and Access Management (IAM), Amazon Cognito, AWS WAF, and Amazon Bedrock are some of the AWS services that can be used to develop a comprehensive security strategy for generative AI applications.
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