prompt-guard

You can defend your AI agent against multi-language prompt injection by applying pattern matching that detects malicious instructions across 10 languages, including Korean, Japanese, and Chinese. This approach blocks over 550 known attack patterns including jailbreaks and secret exfiltration attempts.

To prevent data loss in AI responses, implement output data loss prevention (DLP) and sanitization. This mechanism scans AI-generated responses for leaked credentials and automatically redacts sensitive information before it reaches the end user.

Prompt injection defense handles token optimization by utilizing tiered pattern loading and message caching. This approach minimizes token consumption and improves processing performance for AI agents handling large volumes of user messages.

Yes, you can secure an AI agent in group chats by integrating prompt guard. It safely analyzes user messages to prevent unauthorized access, blocks social engineering attacks, and stops unintended actions caused by malicious text inputs.

Prompt injection defense works against advanced obfuscation techniques by utilizing robust pattern matching. It identifies and blocks disguised malicious instructions, preventing attackers from hijacking agent behavior through manipulated text.

Yes, you need to install pyyaml and langdetect to enable AI safety defense features. These dependencies provide the necessary configuration parsing and multi-language detection capabilities required to identify threats across different languages.