AIMDS stands for AI Manipulation Defense System, a multi-layered security framework designed to protect AI models from adversarial inputs and policy violations using real-time analysis.

Do I need Rust to use this skill?

Yes, the core temporal analysis components are built in Rust for performance, while the database and orchestration layers utilize TypeScript and Node.js.

How does AgentDB contribute to AI security?

AgentDB provides high-speed vector search to match incoming inputs against a database of known attack patterns and malicious embeddings with extreme efficiency.

How does temporal analysis work in this skill?

It uses Midstream's Rust crates to detect anomalies in the timing and sequence of AI responses, identifying potential manipulation patterns as they stream in.

What is the role of lean-agentic in AIMDS?

It provides formal methods and symbolic reasoning to mathematically prove that an input or model response satisfies specific safety and organizational policies.

AIMDS: AI Manipulation Defense System

Name: AIMDS: AI Manipulation Defense System
Author: ruvnet

byruvnet

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보안 및 테스팅

Protects AI applications from adversarial attacks and manipulation using temporal analysis, vector intelligence, and formal verification.

소개

AIMDS (AI Manipulation Defense System) is a comprehensive security framework for AI-driven applications, leveraging the Midstream platform to analyze real-time interactions. By combining Rust-powered temporal pattern detection with AgentDB's high-speed vector search and lean-agentic's mathematical theorem proving, AIMDS provides a robust three-layer defense against jailbreaks, prompt injections, and data leaks, ensuring production-grade safety and policy compliance in complex agentic workflows.

주요 기능

Real-time stream analysis using Midstream's Rust-based architecture
Temporal behavioral pattern detection with nanosecond precision
53 GitHub stars
High-speed vector search and pattern matching via AgentDB
Distributed coordination using QUIC multi-stream synchronization
Mathematical formal verification of safety policies using lean-agentic

사용 사례

Verifying compliance with strict safety and data privacy policies using formal methods
Preventing prompt injection and jailbreak attempts in production LLM applications
Detecting complex manipulation loops and temporal anomalies in autonomous agent workflows

소개

주요 기능

Real-time stream analysis using Midstream's Rust-based architecture
Temporal behavioral pattern detection with nanosecond precision
53 GitHub stars
High-speed vector search and pattern matching via AgentDB
Distributed coordination using QUIC multi-stream synchronization
Mathematical formal verification of safety policies using lean-agentic

사용 사례

Verifying compliance with strict safety and data privacy policies using formal methods
Preventing prompt injection and jailbreak attempts in production LLM applications
Detecting complex manipulation loops and temporal anomalies in autonomous agent workflows