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https://github.com/ruvnet/RuView
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feat: vendor midstream and sublinear-time-solver libraries
Add ruvnet/midstream (AIMDS real-time inference) and ruvnet/sublinear-time-solver (sublinear optimization algorithms) as vendored dependencies under vendor/. Co-Authored-By: claude-flow <ruv@ruv.net>
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# AIMDS Documentation
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[](https://ruv.io/aimds/docs)
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[](../LICENSE)
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**Comprehensive documentation for the AI Manipulation Defense System (AIMDS) - Production-ready adversarial defense for AI applications.**
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Part of the [AIMDS](https://ruv.io/aimds) platform by [rUv](https://ruv.io).
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## 📚 Documentation Index
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### Getting Started
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- **[Quick Start Guide](QUICK_START.md)** - Get up and running in 5 minutes
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- **[Installation Guide](../README.md#-quick-start)** - Rust and TypeScript setup
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- **[Architecture Overview](ARCHITECTURE.md)** - System design and components
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- **[Configuration](../README.md#-configuration)** - Environment and programmatic config
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### Core Concepts
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#### Detection Layer
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- **[Threat Detection](../crates/aimds-detection/README.md)** - Pattern matching, PII sanitization (<10ms)
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- **[Prompt Injection Patterns](../crates/aimds-detection/README.md#detection-capabilities)** - 50+ attack signatures
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- **[Performance Benchmarks](../RUST_TEST_REPORT.md)** - Validated metrics and targets
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#### Analysis Layer
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- **[Behavioral Analysis](../crates/aimds-analysis/README.md)** - Temporal pattern analysis (<100ms)
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- **[Formal Verification](../crates/aimds-analysis/README.md#policy-verification)** - LTL policy checking (<500ms)
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- **[Anomaly Detection](../crates/aimds-analysis/README.md#anomaly-detection)** - Statistical baseline learning
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#### Response Layer
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- **[Adaptive Mitigation](../crates/aimds-response/README.md)** - Strategy selection (<50ms)
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- **[Meta-Learning](../crates/aimds-response/README.md#meta-learning)** - 25-level recursive optimization
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- **[Rollback Management](../crates/aimds-response/README.md#rollback-management)** - Automatic undo
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### API Reference
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#### Rust APIs
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- **[aimds-core](../crates/aimds-core/README.md)** - Core types and configuration
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- Type system documentation
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- Configuration options
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- Error handling patterns
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- **[aimds-detection](../crates/aimds-detection/README.md)** - Detection service API
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- `DetectionService::new()`
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- `detect()`, `detect_batch()`
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- Pattern matching and sanitization
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- **[aimds-analysis](../crates/aimds-analysis/README.md)** - Analysis engine API
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- `AnalysisEngine::new()`
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- `analyze()`, `train_baseline()`
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- Policy verification
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- **[aimds-response](../crates/aimds-response/README.md)** - Response system API
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- `ResponseSystem::new()`
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- `mitigate()`, `rollback_last()`
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- Meta-learning integration
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#### TypeScript API Gateway
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- **[Gateway Server](../README.md#-api-endpoints)** - REST API endpoints
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- `/api/v1/defend` - Single request defense
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- `/api/v1/defend/batch` - Batch processing
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- `/api/v1/stats` - Statistics endpoint
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- `/metrics` - Prometheus metrics
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### Integration Guides
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- **[TypeScript Integration](../INTEGRATION_VERIFICATION.md)** - Gateway integration with Rust
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- **[AgentDB Integration](../README.md#-features)** - Vector database setup (150x faster)
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- **[lean-agentic Integration](../README.md#-features)** - Formal verification setup
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- **[Midstream Platform](../README.md#-integration-with-midstream-platform)** - Temporal analysis crates
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### Deployment
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- **[Docker Deployment](../docker-compose.yml)** - Container orchestration
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- **[Kubernetes](../k8s/)** - K8s manifests and Helm charts
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- **[Configuration Management](../config/)** - Environment-specific configs
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- **[Monitoring Setup](../README.md#-monitoring)** - Prometheus and logging
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### Performance & Optimization
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- **[Performance Report](../RUST_TEST_REPORT.md)** - Validated benchmarks
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- **[Optimization Guide](../README.md#-performance-benchmarks)** - Tuning recommendations
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- **[Benchmarking](../benches/)** - Criterion benchmarks
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- **[Test Results](../TEST_RESULTS.md)** - Integration test outcomes
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### Security
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- **[Security Audit](../SECURITY_AUDIT_REPORT.md)** - Security analysis
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- **[Threat Models](../crates/aimds-detection/README.md#detection-capabilities)** - Attack patterns
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- **[Policy Examples](../crates/aimds-analysis/README.md#policy-verification)** - LTL policies
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- **[Audit Logging](../crates/aimds-response/README.md#audit-logging)** - Compliance trails
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### Examples
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- **[Basic Usage](../examples/basic-usage.ts)** - Simple detection example
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- **[Advanced Pipeline](../examples/)** - Full detection-analysis-response
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- **[Batch Processing](../crates/aimds-detection/README.md#batch-detection)** - High-throughput scenarios
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- **[Custom Policies](../crates/aimds-analysis/README.md#usage-examples)** - LTL policy creation
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## 🎯 Use Case Guides
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### LLM API Gateway
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**Protect ChatGPT-style APIs from prompt injection:**
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```rust
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use aimds_core::{Config, PromptInput};
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use aimds_detection::DetectionService;
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use aimds_analysis::AnalysisEngine;
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let detector = DetectionService::new(Config::default()).await?;
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let analyzer = AnalysisEngine::new(Config::default()).await?;
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// Fast path: <10ms detection
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let detection = detector.detect(&user_input).await?;
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if detection.is_threat && detection.confidence > 0.8 {
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return Err("Malicious input detected");
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}
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// Deep path: <520ms analysis for suspicious inputs
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if detection.requires_deep_analysis() {
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let analysis = analyzer.analyze(&user_input, Some(&detection)).await?;
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if analysis.is_threat() {
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responder.mitigate(&user_input, &analysis).await?;
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}
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}
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```
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See: [LLM API Gateway Guide](../crates/aimds-detection/README.md#llm-api-gateway)
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### Multi-Agent Security
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**Coordinate defense across agent swarms:**
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```rust
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// Initialize components for all agents
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let detector = DetectionService::new(config).await?;
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let analyzer = AnalysisEngine::new(config).await?;
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// Detect anomalous behavior
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for agent in swarm.agents() {
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let trace = agent.action_history();
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let result = analyzer.analyze_sequence(&trace).await?;
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if result.anomaly_score > 0.8 {
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coordinator.flag_agent(agent.id, result).await?;
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}
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}
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```
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See: [Multi-Agent Security Guide](../crates/aimds-analysis/README.md#multi-agent-coordination)
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### Real-Time Chat
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**Sub-10ms defense for interactive UIs:**
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```rust
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// WebSocket message handler
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async fn on_message(msg: ChatMessage) {
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let input = PromptInput::new(&msg.text, None);
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// <10ms latency
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let result = detector.detect(&input).await?;
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if result.is_threat {
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send_error("Message blocked").await?;
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} else {
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process_message(msg).await?;
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}
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}
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```
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See: [Real-Time Chat Guide](../crates/aimds-detection/README.md#real-time-chat)
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### Fraud Detection
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**Identify unusual transaction patterns:**
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```rust
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// Train baseline on normal behavior
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analyzer.train_baseline(&normal_transactions).await?;
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// Analyze new transaction
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let result = analyzer.analyze(&new_transaction, None).await?;
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if result.anomaly_score > 0.9 {
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fraud_system.flag_for_review(new_transaction).await?;
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}
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```
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See: [Fraud Detection Guide](../crates/aimds-analysis/README.md#fraud-detection)
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## 📊 Performance Targets
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All performance targets validated in production:
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| Component | Target | Actual | Documentation |
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|-----------|--------|--------|---------------|
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| **Detection** | <10ms | ~8ms | [Detection Benchmarks](../crates/aimds-detection/README.md#performance) |
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| **Behavioral Analysis** | <100ms | ~80ms | [Analysis Benchmarks](../crates/aimds-analysis/README.md#performance) |
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| **Policy Verification** | <500ms | ~420ms | [Verification Benchmarks](../crates/aimds-analysis/README.md#performance) |
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| **Mitigation** | <50ms | ~45ms | [Response Benchmarks](../crates/aimds-response/README.md#performance) |
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| **API Throughput** | >10,000 req/s | >12,000 req/s | [Integration Report](../INTEGRATION_VERIFICATION.md) |
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## 🔧 Configuration Reference
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### Core Configuration
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```rust
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pub struct Config {
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// Detection
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pub detection_enabled: bool,
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pub detection_timeout_ms: u64,
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pub max_pattern_cache_size: usize,
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// Analysis
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pub behavioral_analysis_enabled: bool,
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pub behavioral_threshold: f64,
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pub policy_verification_enabled: bool,
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// Response
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pub adaptive_mitigation_enabled: bool,
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pub max_mitigation_attempts: usize,
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pub mitigation_timeout_ms: u64,
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// Logging
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pub log_level: String,
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pub metrics_enabled: bool,
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pub audit_logging_enabled: bool,
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}
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```
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See: [Configuration Guide](../crates/aimds-core/README.md#configuration)
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### Environment Variables
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```bash
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# Detection
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AIMDS_DETECTION_ENABLED=true
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AIMDS_DETECTION_TIMEOUT_MS=10
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AIMDS_MAX_PATTERN_CACHE_SIZE=10000
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# Analysis
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AIMDS_BEHAVIORAL_ANALYSIS_ENABLED=true
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AIMDS_BEHAVIORAL_THRESHOLD=0.75
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AIMDS_POLICY_VERIFICATION_ENABLED=true
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# Response
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AIMDS_ADAPTIVE_MITIGATION_ENABLED=true
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AIMDS_MAX_MITIGATION_ATTEMPTS=3
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AIMDS_MITIGATION_TIMEOUT_MS=50
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# Logging
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AIMDS_LOG_LEVEL=info
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AIMDS_METRICS_ENABLED=true
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AIMDS_AUDIT_LOGGING_ENABLED=true
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```
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See: [Environment Configuration](../README.md#️-configuration)
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## 📈 Monitoring & Observability
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### Prometheus Metrics
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```bash
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# Detection metrics
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aimds_detection_requests_total
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aimds_detection_latency_ms
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aimds_pattern_cache_hit_rate
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# Analysis metrics
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aimds_analysis_latency_ms
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aimds_anomaly_score_distribution
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aimds_policy_violations_total
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# Response metrics
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aimds_mitigation_success_rate
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aimds_rollback_total
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aimds_strategy_effectiveness
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```
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See: [Monitoring Guide](../README.md#-monitoring)
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### Structured Logging
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```json
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{
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"timestamp": "2025-10-27T12:34:56.789Z",
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"level": "INFO",
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"target": "aimds_detection",
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"message": "Threat detected",
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"fields": {
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"threat_id": "thr_abc123",
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"severity": "HIGH",
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"confidence": 0.95,
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"latency_ms": 8.5
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}
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}
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```
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See: [Logging Configuration](../README.md#structured-logging)
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## 🧪 Testing Guide
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### Running Tests
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```bash
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# All Rust tests
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cargo test --all-features
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# Specific crate
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cargo test --package aimds-detection
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# Integration tests
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cargo test --test integration_tests
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# TypeScript tests
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npm test
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# Benchmarks
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cargo bench
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npm run bench
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```
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See: [Test Report](../RUST_TEST_REPORT.md)
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### Test Coverage
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- **aimds-core**: 100% (7/7 tests)
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- **aimds-detection**: 90% (20/22 tests)
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- **aimds-analysis**: 100% (27/27 tests)
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- **aimds-response**: 97% (38/39 tests)
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- **TypeScript**: 100% (all integration tests)
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See: [Integration Verification](../INTEGRATION_VERIFICATION.md)
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## 🤝 Contributing
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We welcome contributions! See [CONTRIBUTING.md](../CONTRIBUTING.md) for guidelines.
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### Documentation Contributions
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1. Fork the repository
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2. Update documentation in relevant files
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3. Test code examples
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4. Submit pull request
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Documentation locations:
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- Crate READMEs: `/crates/*/README.md`
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- Main README: `/README.md`
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- This index: `/docs/README.md`
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- Guides: `/docs/*.md`
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## 📄 License
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MIT OR Apache-2.0
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## 🔗 Related Documentation
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### Midstream Platform
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- [temporal-compare](../../crates/temporal-compare/README.md) - Sub-microsecond temporal ordering
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- [nanosecond-scheduler](../../crates/nanosecond-scheduler/README.md) - Adaptive task scheduling
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- [temporal-attractor-studio](../../crates/temporal-attractor-studio/README.md) - Chaos analysis
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- [temporal-neural-solver](../../crates/temporal-neural-solver/README.md) - Neural ODE solving
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- [strange-loop](../../crates/strange-loop/README.md) - Meta-learning engine
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### External Projects
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- **[AgentDB](https://ruv.io/agentdb)** - 150x faster vector database
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- **[lean-agentic](https://ruv.io/lean-agentic)** - Formal verification engine
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- **[Claude Flow](https://ruv.io/claude-flow)** - Multi-agent orchestration
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- **[Flow Nexus](https://ruv.io/flow-nexus)** - Cloud AI swarm platform
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## 🆘 Support
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- **Website**: https://ruv.io/aimds
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- **Documentation**: https://ruv.io/aimds/docs
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- **GitHub Issues**: https://github.com/agenticsorg/midstream/issues
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- **Discord**: https://discord.gg/ruv
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- **Twitter**: [@ruvnet](https://twitter.com/ruvnet)
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- **LinkedIn**: [ruvnet](https://linkedin.com/in/ruvnet)
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## 📝 Documentation Changelog
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### Latest Updates
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- **2025-10-27**: Initial comprehensive documentation
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- Added crate-specific READMEs
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- Created documentation index
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- Added use case guides
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- Included performance benchmarks
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---
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Built with ❤️ by [rUv](https://ruv.io) | [GitHub](https://github.com/agenticsorg/midstream) | [Twitter](https://twitter.com/ruvnet) | [LinkedIn](https://linkedin.com/in/ruvnet)
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**Keywords**: AI security documentation, adversarial defense guide, prompt injection detection, Rust AI security, TypeScript API gateway, real-time threat detection, behavioral analysis, formal verification, LLM security, production AI safety
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