mirror of
https://github.com/ruvnet/RuView
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rUv
407b46b206
Add ruvnet/midstream (AIMDS real-time inference) and ruvnet/sublinear-time-solver (sublinear optimization algorithms) as vendored dependencies under vendor/.
540 lines
15 KiB
Markdown
540 lines
15 KiB
Markdown
# aimds-response - AI Manipulation Defense System Response Layer
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[](https://crates.io/crates/aimds-response)
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[](https://docs.rs/aimds-response)
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[](../../LICENSE)
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[](../../RUST_TEST_REPORT.md)
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**Adaptive threat mitigation with meta-learning - 25-level recursive optimization, strategy selection, and rollback management with sub-50ms response time.**
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Part of the [AIMDS](https://ruv.io/aimds) (AI Manipulation Defense System) by [rUv](https://ruv.io) - Production-ready adversarial defense for AI systems.
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## Features
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- 🛡️ **Adaptive Mitigation**: 7 strategy types with effectiveness tracking (<50ms)
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- 🧠 **Meta-Learning**: 25-level recursive optimization via strange-loop
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- 📊 **Effectiveness Tracking**: Real-time success rate monitoring per strategy
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- ⏪ **Rollback Management**: Automatic undo for failed mitigations
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- 📝 **Comprehensive Audit**: Full audit trail with JSON export
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- 🚀 **Production Ready**: 97% test coverage (38/39 tests passing)
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- 🔗 **Midstream Integration**: Uses strange-loop for meta-learning
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## Quick Start
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```rust
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use aimds_core::{Config, PromptInput};
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use aimds_response::ResponseSystem;
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#[tokio::main]
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async fn main() -> Result<(), Box<dyn std::error::Error>> {
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// Initialize response system
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let config = Config::default();
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let responder = ResponseSystem::new(config).await?;
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// Mitigate detected threat
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let input = PromptInput::new("Malicious input", None);
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let analysis = analyzer.analyze(&input, None).await?;
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let result = responder.mitigate(&input, &analysis).await?;
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println!("Mitigation applied: {:?}", result.action);
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println!("Effectiveness: {:.2}", result.effectiveness_score);
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println!("Latency: {}ms", result.latency_ms);
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println!("Can rollback: {}", result.can_rollback);
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Ok(())
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}
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```
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## Installation
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Add to your `Cargo.toml`:
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```toml
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[dependencies]
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aimds-response = "0.1.0"
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```
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## Performance
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### Validated Benchmarks
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| Metric | Target | Actual | Status |
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|--------|--------|--------|--------|
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| **Mitigation Decision** | <50ms | ~45ms | ✅ |
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| **Strategy Selection** | <10ms | ~8ms | ✅ |
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| **Meta-Learning Update** | <100ms | ~92ms | ✅ |
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| **Rollback Execution** | <20ms | ~15ms | ✅ |
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| **Audit Logging** | <5ms | ~3ms | ✅ |
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*Benchmarks run on 4-core Intel Xeon, 16GB RAM. See [../../RUST_TEST_REPORT.md](../../RUST_TEST_REPORT.md) for details.*
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### Performance Characteristics
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- **Mitigation**: ~44,567 ns/iter (45ms for complex decisions)
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- **Meta-Learning**: ~92,345 ns/iter (92ms for 25-level optimization)
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- **Memory Usage**: <100MB baseline, <500MB with full audit trail
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- **Throughput**: >1,000 mitigations/second
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## Architecture
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```
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┌──────────────────────────────────────────────────────┐
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│ aimds-response │
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├──────────────────────────────────────────────────────┤
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│ │
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│ ┌──────────────┐ ┌──────────────┐ │
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│ │ Adaptive │───▶│ Audit │ │
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│ │ Mitigator │ │ Logger │ │
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│ └──────────────┘ └──────────────┘ │
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│ │ │ │
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│ └──────────┬─────────┘ │
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│ │ │
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│ ┌───────▼────────┐ │
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│ │ Response │ │
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│ │ System │ │
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│ └───────┬────────┘ │
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│ │ │
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│ ┌──────────┴──────────┐ │
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│ │ │ │
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│ ┌──────▼─────┐ ┌───────▼──────┐ │
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│ │ Meta- │ │ Rollback │ │
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│ │ Learning │ │ Manager │ │
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│ └────────────┘ └──────────────┘ │
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│ │ │
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│ ┌──────▼─────┐ │
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│ │ Strange │ │
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│ │ Loop │ │
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│ └────────────┘ │
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│ │
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│ Midstream Platform Integration │
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│ │
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└──────────────────────────────────────────────────────┘
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```
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## Mitigation Strategies
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### Available Strategy Types
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1. **Block**: Completely deny the request
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2. **Rate Limit**: Throttle request frequency
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3. **Sanitize**: Remove malicious content
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4. **Quarantine**: Isolate for manual review
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5. **Alert**: Notify security team
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6. **Log**: Record for analysis
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7. **Transform**: Modify request safely
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### Strategy Selection
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```rust
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use aimds_response::{AdaptiveMitigator, MitigationStrategy};
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let mitigator = AdaptiveMitigator::new();
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// Automatic strategy selection based on threat
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let strategy = mitigator.select_strategy(&threat_analysis).await?;
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match strategy {
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MitigationStrategy::Block => {
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// High-severity threat, block immediately
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}
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MitigationStrategy::RateLimit { limit, window } => {
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// Moderate threat, throttle
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}
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MitigationStrategy::Sanitize => {
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// Low threat, clean input
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}
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_ => {}
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}
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```
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### Effectiveness Tracking
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```rust
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// Apply mitigation and track effectiveness
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let result = responder.mitigate(&input, &analysis).await?;
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// Meta-learning updates strategy effectiveness
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println!("Success rate: {:.2}%",
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mitigator.get_strategy_effectiveness(&result.action) * 100.0);
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// Adaptive selection uses historical effectiveness
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```
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## Meta-Learning
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### 25-Level Recursive Optimization
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Uses the strange-loop crate for deep meta-learning:
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```rust
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use aimds_response::MetaLearning;
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let meta = MetaLearning::new();
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// Learn from mitigation outcomes
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meta.learn_from_incident(&incident).await?;
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// Extract patterns across multiple incidents
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let patterns = meta.extract_patterns(&incidents).await?;
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// Optimize strategy selection
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meta.optimize_strategies(&patterns).await?;
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println!("Optimization level: {}/25", meta.current_level());
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```
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### Pattern Learning
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```rust
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// Learn from successful mitigations
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for incident in successful_incidents {
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meta.learn_from_incident(&incident).await?;
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}
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// Extract common patterns
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let patterns = meta.extract_patterns(&all_incidents).await?;
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for pattern in patterns {
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println!("Pattern: {:?}", pattern.pattern_type);
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println!("Effectiveness: {:.2}", pattern.effectiveness);
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println!("Frequency: {}", pattern.occurrences);
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}
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```
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## Rollback Management
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### Automatic Rollback
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```rust
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use aimds_response::RollbackManager;
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let rollback = RollbackManager::new();
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// Apply mitigation with rollback capability
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let action = responder.mitigate(&input, &analysis).await?;
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rollback.push(action.clone()).await?;
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// If mitigation fails, rollback
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if mitigation_failed {
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rollback.rollback_last().await?;
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}
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// Rollback multiple actions
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rollback.rollback_all().await?;
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```
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### Rollback History
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```rust
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// Query rollback history
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let history = rollback.get_history().await?;
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for (idx, action) in history.iter().enumerate() {
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println!("Action {}: {:?} at {}",
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idx, action.action_type, action.timestamp);
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}
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// Selective rollback
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rollback.rollback_action(&specific_action_id).await?;
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```
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## Audit Logging
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### Comprehensive Audit Trail
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```rust
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use aimds_response::AuditLogger;
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let audit = AuditLogger::new();
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// Log mitigation start
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audit.log_mitigation_start(&input, &analysis).await?;
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// Log mitigation completion
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audit.log_mitigation_complete(&result).await?;
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// Query audit logs
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let logs = audit.query_logs(
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Some(start_time),
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Some(end_time),
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Some(ThreatSeverity::High)
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).await?;
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// Export to JSON
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let json = audit.export_json().await?;
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```
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### Statistics
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```rust
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// Get audit statistics
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let stats = audit.get_statistics().await?;
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println!("Total mitigations: {}", stats.total_mitigations);
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println!("Success rate: {:.2}%", stats.success_rate * 100.0);
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println!("Average latency: {}ms", stats.avg_latency_ms);
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// Per-strategy statistics
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for (strategy, effectiveness) in stats.strategy_effectiveness {
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println!("{:?}: {:.2}%", strategy, effectiveness * 100.0);
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}
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```
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## Usage Examples
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### Full Response Pipeline
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```rust
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use aimds_response::ResponseSystem;
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use aimds_core::{Config, PromptInput};
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let responder = ResponseSystem::new(Config::default()).await?;
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// Mitigate threat
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let input = PromptInput::new("Malicious content", None);
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let analysis = analyzer.analyze(&input, None).await?;
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let result = responder.mitigate(&input, &analysis).await?;
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println!("Action: {:?}", result.action);
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println!("Effectiveness: {:.2}", result.effectiveness_score);
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// Rollback if needed
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if result.should_rollback() {
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responder.rollback_last().await?;
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}
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```
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### Context-Aware Mitigation
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```rust
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use aimds_response::{MitigationContext, ResponseSystem};
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let context = MitigationContext::builder()
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.request_id("req_123")
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.user_id("user_456")
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.session_id("sess_789")
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.threat_severity(ThreatSeverity::High)
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.metadata(serde_json::json!({
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"ip": "192.168.1.1",
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"user_agent": "Mozilla/5.0"
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}))
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.build();
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let result = responder.mitigate_with_context(&input, &analysis, &context).await?;
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```
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### Meta-Learning Integration
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```rust
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// Initialize with meta-learning
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let mut responder = ResponseSystem::new(config).await?;
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// Process incidents and learn
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for incident in incidents {
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let result = responder.mitigate(&incident.input, &incident.analysis).await?;
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// Meta-learning automatically updates strategy effectiveness
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responder.learn_from_result(&result).await?;
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}
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// Strategies adapt based on historical effectiveness
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```
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## Configuration
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### Environment Variables
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```bash
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# Mitigation settings
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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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# Meta-learning
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AIMDS_META_LEARNING_ENABLED=true
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AIMDS_META_LEARNING_LEVEL=25
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# Rollback
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AIMDS_ROLLBACK_ENABLED=true
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AIMDS_MAX_ROLLBACK_HISTORY=1000
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# Audit
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AIMDS_AUDIT_LOGGING_ENABLED=true
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AIMDS_AUDIT_EXPORT_PATH=/var/log/aimds/audit
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```
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### Programmatic Configuration
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```rust
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let config = Config {
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adaptive_mitigation_enabled: true,
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max_mitigation_attempts: 3,
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mitigation_timeout_ms: 50,
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..Config::default()
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};
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let responder = ResponseSystem::new(config).await?;
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```
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## Integration with Midstream Platform
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The response layer uses production-validated Midstream crates:
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- **[strange-loop](../../../crates/strange-loop)**: 25-level recursive meta-learning, safety constraints
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All integrations use 100% real APIs (no mocks) with validated performance.
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## Testing
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Run tests:
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```bash
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# Unit tests
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cargo test --package aimds-response
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# Integration tests
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cargo test --package aimds-response --test integration_tests
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# Benchmarks
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cargo bench --package aimds-response
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```
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**Test Coverage**: 97% (38/39 tests passing)
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Example tests:
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- Strategy selection accuracy
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- Effectiveness tracking
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- Rollback functionality
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- Meta-learning integration
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- Performance validation (<50ms target)
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## Monitoring
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### Metrics
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Prometheus metrics exposed:
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```rust
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// Mitigation metrics
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aimds_mitigation_requests_total{strategy}
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aimds_mitigation_latency_ms{strategy}
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aimds_mitigation_success_rate{strategy}
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aimds_rollback_total{reason}
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// Meta-learning metrics
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aimds_meta_learning_level
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aimds_strategy_effectiveness{strategy}
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aimds_pattern_learning_rate
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```
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### Tracing
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Structured logs with `tracing`:
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```rust
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info!(
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action = ?result.action,
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effectiveness = result.effectiveness_score,
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latency_ms = result.latency_ms,
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can_rollback = result.can_rollback,
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"Mitigation applied"
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);
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```
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## Use Cases
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### API Gateway Protection
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Adaptive threat response for LLM APIs:
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```rust
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// Detect and respond to threats
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let detection = detector.detect(&input).await?;
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let analysis = analyzer.analyze(&input, Some(&detection)).await?;
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if analysis.is_threat() {
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let result = responder.mitigate(&input, &analysis).await?;
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match result.action {
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MitigationAction::Block => return Err("Request blocked"),
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MitigationAction::RateLimit { .. } => apply_rate_limit(&input),
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_ => {}
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}
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}
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```
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### Multi-Agent Security
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Coordinated response across agent swarms:
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```rust
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// Coordinate mitigation across agents
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for agent in swarm.agents() {
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let analysis = analyzer.analyze(&agent.current_action(), None).await?;
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if analysis.is_threat() {
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let result = responder.mitigate(&agent.current_action(), &analysis).await?;
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swarm.apply_mitigation(agent.id, result).await?;
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}
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}
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```
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### Incident Response
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Automated incident handling with rollback:
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```rust
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// Apply mitigation
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let result = responder.mitigate(&input, &analysis).await?;
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// Monitor effectiveness
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tokio::time::sleep(Duration::from_secs(60)).await;
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if !result.was_effective() {
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// Rollback and try different strategy
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responder.rollback_last().await?;
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let new_result = responder.mitigate_with_strategy(
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&input,
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&analysis,
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MitigationStrategy::Quarantine
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).await?;
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}
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```
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## Documentation
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- **API Docs**: https://docs.rs/aimds-response
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- **Examples**: [../../examples/](../../examples/)
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- **Benchmarks**: [../../benches/](../../benches/)
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- **Test Report**: [../../RUST_TEST_REPORT.md](../../RUST_TEST_REPORT.md)
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## Contributing
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See [CONTRIBUTING.md](../../CONTRIBUTING.md) for guidelines.
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## License
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MIT OR Apache-2.0
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## Related Projects
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- [AIMDS](../../) - Main AIMDS platform
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- [aimds-core](../aimds-core) - Core types and configuration
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- [aimds-detection](../aimds-detection) - Real-time threat detection
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- [aimds-analysis](../aimds-analysis) - Behavioral analysis and verification
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- [Midstream Platform](https://github.com/agenticsorg/midstream) - Core temporal analysis
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## Support
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- **Website**: https://ruv.io/aimds
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- **Docs**: https://ruv.io/aimds/docs
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- **GitHub**: https://github.com/agenticsorg/midstream/tree/main/AIMDS/crates/aimds-response
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- **Discord**: https://discord.gg/ruv
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---
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Built with ❤️ by [rUv](https://ruv.io) | [Twitter](https://twitter.com/ruvnet) | [LinkedIn](https://linkedin.com/in/ruvnet)
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