prompt-guard

Prompt injection detection identifies malicious attempts to hijack AI prompts and manipulate output. This Skill filters user inputs and third-party data to secure LLM applications against unauthorized prompt manipulation.

Multilingual jailbreak detection filters unauthorized model access attempts across 8 different languages. It safely processes user inputs to stop manipulation while maintaining multilingual support for global LLM applications.

HuggingFace jailbreak detection uses transformers and torch dependencies to score malicious inputs. You can run batch processing or evaluate individual strings to identify unauthorized LLM manipulation attempts.

Securing user inputs against prompt injection requires filtering third-party data before it reaches the LLM. Batch processing evaluates text inputs to detect and block unauthorized manipulation attempts across multiple languages.

Yes, torch and transformers are required dependencies for prompt injection detection. These frameworks provide the underlying model processing needed to evaluate user inputs and calculate jailbreak scores.

Input filtering stops unauthorized LLM manipulation by evaluating user submissions and third-party data for malicious prompts before processing. It detects injection attempts and jailbreaks to maintain AI application safety and integrity.