LLM Firewall Context-Aware Policy Enforcement
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Solution Overview
Problem
Large Language Models (LLMs) face security risks due to methods discovered to bypass restrictions and 'jailbreak' access to restricted content, posing a threat to both clients and LLMs, with existing security measures being inadequate or non-existent in many cases.
Innovation Solution
A universal LLM firewall/gateway system intercepts and monitors communications between clients and LLMs, applying policies based on context to prevent unauthorized access, detect malicious intent, and maintain reputations of clients and LLMs, thereby protecting against insecure code and jailbreaking attempts.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If LLMs are deployed without security restrictions, then accessibility and ease of operation are improved, but security risks and harmful content increase
Solution Approach 1:
The patent introduces a firewall system as an intermediary component positioned between users and LLMs. This firewall intercepts, monitors, and filters communications to block harmful content and jailbreaking attempts while allowing legitimate access, thus resolving the contradiction between accessibility and security.
Solution Approach 2:
The system proactively detects and prevents jailbreaking attempts and harmful content before they can affect the LLM or user. By monitoring conversation context and applying policies in advance, the firewall counteracts potential security threats before they manifest as harmful effects.
2Reliability
If security restrictions are implemented to prevent jailbreaking, then security is improved, but accessibility and ease of operation deteriorate
Solution Approach 1:
The firewall applies different levels of monitoring and filtering based on the specific characteristics of each communication. It analyzes conversation context to determine when strict security policies apply and when more permissive access is appropriate, thereby maintaining security while preserving ease of operation for legitimate uses.
Solution Approach 2:
The system dynamically adjusts its security policies based on real-time conversation context and detected patterns. The firewall can tighten or loosen restrictions depending on the situation, allowing flexible security management that adapts to user behavior and conversation content.
3Reliability
If existing security measures are used, then some protection is provided, but they are inadequate against sophisticated attacks and bypass methods
Solution Approach 1:
The firewall continuously monitors conversation context and uses this feedback to detect bypass attempts and jailbreaking patterns. By analyzing the flow of communication and comparing it against known attack patterns, the system can identify and block sophisticated bypass methods that evade static security rules.
Solution Approach 2:
The patent creates a universal firewall system that can protect against multiple types of threats including jailbreaking, harmful content generation, and bypass attempts. The single system performs multiple security functions through context-aware policy application, making it more effective than specialized individual measures.
Data Source
AI summary
Presented herein is a universal Large Language Model (LLM) firewall/gateway that operates at the LLM level to protect clients and LLMs from a new threat landscape. The LLM firewall/gateway may generate alerts warning users about insecure codes that LLMs propose, as well as detecting and preventing LLMs from jailbreaking through sessions/conversations. A method is provided comprising: intercepting communications associated with a conversation between a client and a Large Language Model (LLM) service, the communications including a request message from the client to the LLM service and a response message from the LLM service to the client; deriving a context for the conversation based on the communications between the client and the LLM service; and applying one or more policies to the communications between the client and the LLM service based on the context.