Rebuff AI Description

Store the embeddings from previous attacks in a database of vectors to recognize and prevent them in the future. Use a dedicated LLM for analyzing incoming prompts to identify potential attacks. Add canary tokens in prompts to detect leakages. This allows the framework to store embedded embeddings of the incoming prompt into the vector database to prevent future attacks. Filter out malicious input before it reaches LLM.

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Company Details

Company:
Rebuff AI
Website:
www.rebuff.ai/
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Product Details

Platforms
SaaS
Type of Training
Documentation
Customer Support
Online

Rebuff AI Features and Options

Application Security Software

Analytics / Reporting
Open Source Component Monitoring
Source Code Analysis
Third-Party Tools Integration
Training Resources
Vulnerability Detection
Vulnerability Remediation

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