11 releases
0.1.12 | Dec 8, 2024 |
---|---|
0.1.11 | Dec 8, 2024 |
0.1.10 | Sep 11, 2024 |
#73 in #access-control
246 downloads per month
185KB
5K
SLoC
Spawn Access Control
Enterprise-grade security and access control library with advanced monitoring, machine learning capabilities, and real-time threat detection for Rust applications.
Core Features
Security & Access Control
- ๐ Role-Based Access Control (RBAC)
- ๐ก๏ธ Behavioral Pattern Analysis
- ๐ Geo-location Based Security
- ๐ Risk Analysis & Scoring
Machine Learning & Analytics
- ๐ค ML-Powered Anomaly Detection
- ๐ Time Series Analysis
- ๐ฏ Predictive Security Metrics
- ๐งฎ Model Explainability
Monitoring & Alerting
- ๐ Real-time Performance Monitoring
- โก Prometheus Integration
- ๐ง Email & Slack Notifications
- ๐จ Auto-remediation Actions
Infrastructure
- ๐พ Distributed Cache Support
- ๐ WebAssembly Compatibility
- ๐ High Performance (7.5ฮผs avg.)
- ๐ Migration Support
Installation
[dependencies]
spawn-access-control = "0.1.11"
Quick Start
use spawn_access_control::{
SecurityAnalyzer,
AlertManager,
MonitoringConfig,
NotificationHandler,
};
#[tokio::main]
async fn main() -> Result<(), Error> {
// Configure monitoring
let config = MonitoringConfig {
metrics_window_size: 3600,
performance_threshold: 0.8,
security_threshold: 0.7,
alert_cooldown: Duration::seconds(300),
};
// Initialize components
let monitor = ModelMonitor::new(config);
let analyzer = SecurityAnalyzer::new(config);
// Set up notifications
let email_handler = EmailNotificationHandler::new(email_config)?;
let slack_handler = SlackNotificationHandler::new(slack_config)?;
// Start monitoring
monitor.start().await?;
Ok(())
}
Architecture
spawn-access-control/
โโโ Core
โ โโโ Access Control
โ โโโ Security Analysis
โ โโโ Risk Assessment
โโโ ML Components
โ โโโ Behavioral Analysis
โ โโโ Anomaly Detection
โ โโโ Model Optimization
โโโ Monitoring
โ โโโ Metrics Collection
โ โโโ Alert Management
โ โโโ Auto-remediation
โโโ Infrastructure
โโโ Distributed Cache
โโโ WASM Support
โโโ Database Migrations
CLI Tool
# Analyze security patterns
spawn-cli analyze --input data.json --output report.json
# Monitor system
spawn-cli monitor --config config.yaml
# Generate reports
spawn-cli report --type security --from "2023-01-01" --to "2023-12-31"
Benchmarks
security_analysis_1000 time: [7.5358 ยตs 7.5479 ยตs 7.5654 ยตs]
Examples
examples/wasm-demo.html
: WebAssembly integrationexamples/monitoring.rs
: Real-time monitoring setupexamples/ml-security.rs
: ML-based security analysisexamples/distributed.rs
: Distributed cache usage
Configuration
monitoring:
window_size: 3600
performance_threshold: 0.8
security_threshold: 0.7
alert_cooldown: 300
notifications:
email:
enabled: true
smtp_host: smtp.example.com
slack:
enabled: true
webhook_url: https://hooks.slack.com/...
Contributing
- Fork the repository
- Create your feature branch (
git checkout -b feature/amazing-feature
) - Commit your changes (
git commit -m 'Add amazing feature'
) - Push to the branch (
git push origin feature/amazing-feature
) - Open a Pull Request
License
Licensed under either of:
- Apache License, Version 2.0 (LICENSE-APACHE)
- MIT license (LICENSE-MIT)
Acknowledgments
- Built with Rust ๐ฆ
- WebAssembly support via wasm-bindgen
- ML components powered by smartcore
Dependencies
~65โ105MB
~2M SLoC