2 Repos
Security analysis specifically for code fragments produced by AI models prior to execution.
Distinct from Source Code Vulnerability Scanning: Specializes source code scanning for the specific context of AI-generated outputs to prevent runtime execution of malicious commands.
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PurpleLlama is a collection of security toolsets and frameworks designed to audit large language model vulnerabilities and implement runtime input-output guardrails. It provides a security evaluation framework and benchmark suite to quantify risks associated with prompt injections and the generation of malicious code. The project includes a content moderator and input-output filters that use a standardized taxonomy to identify and block harmful content, jailbreaking attempts, and insecure commands. It also features capabilities for sensitive document classification to prevent the unauthorized
Inspects generated code fragments for security vulnerabilities and malicious commands prior to execution.
PurpleLlama is a collection of security components and toolkits designed for large language models. It provides specialized systems including a code security scanner, a content moderation system, a prompt injection firewall, and a security assessment toolkit. The project enables the identification and blocking of jailbreaking attempts and malicious prompts during model inference. It includes capabilities for detecting violating content across multiple languages and modalities and scanning generated code for vulnerabilities to prevent the execution of insecure commands. The framework further
Performs security analysis on AI-generated code fragments to prevent the execution of malicious commands.