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OWASP Principles for Securing Large Language Models
- The OWASP community includes security professionals, developers, and researchers who collaborate to create freely available resources.
- The scope of OWASP has expanded to encompass advanced systems like Large Language Models (LLMs).
- OWASP’s adaptive methodology provides a structured framework for identifying and mitigating risks in LLM deployments.
- The article explores the top security risks associated with the usage of LLMs, offering practical insights into mitigation strategies.
- The article discusses several top security risks, including prompt injection vulnerabilities, sensitive information disclosure, supply chain vulnerabilities, and data and model poisoning.
- Other risks discussed include improper output handling, excessive agency, system prompt leakage, vectors, embeddings and misinformation propagation, and unbounded consumption.
- The article offers mitigation strategies for each of the security risks.
- Implementing input validation mechanisms to filter and sanitize inputs before they reach the model can address prompt injection vulnerabilities.
- Encrypting sensitive data, minimizing data, integrating privacy-preserving techniques, and implementing access controls can mitigate sensitive information disclosure.
- Conducting regular dependency audits, employing software composition analysis (SCA) tools, and implementing runtime protections for the supply chain can mitigate supply chain vulnerabilities.
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