A high-performance log analysis tool that detects security threats and anomalies using advanced time-series algorithms and temporal pattern recognition.
ChronoDance analyzes log streams in real-time to identify:
- Anomalous event patterns - Unusual sequences that deviate from learned baselines
- Event cascades - Rapid bursts of related events indicating active incidents
- Attack chains - Multi-step intrusion patterns following known kill chain stages
- Statistical outliers - Events outside normal temporal distributions
- Change points - Sudden shifts in system behavior
| Format | Description |
|---|---|
| Syslog | RFC 3164, RFC 5424, BSD formats |
| JSON | Structured application logs (ELK, cloud-native) |
| Custom | Extensible parser framework |
Auto-detection intelligently identifies log formats without configuration.
| Algorithm | Purpose |
|---|---|
| Statistical Bands | Identifies values outside normal variance |
| Change Detection | Detects mean shifts in event rates |
| Sequence Analysis | Learns normal patterns, flags anomalies |
| Cascade Detection | Identifies self-exciting event bursts |
| Temporal Logic | Matches multi-step attack signatures |
┌─────────────────┐
Log Files ──┤ │
│ ChronoDance ├──► Alerts (JSON)
Live Feeds ─┤ │
└─────────────────┘
- Stream processing via stdin for live monitoring
- Batch analysis for forensic investigation
- Sub-millisecond per-event processing
[2024-01-15 10:30:45] CRITICAL
Pattern: error_cascade
Score: 8.50 | Confidence: 0.85
Context: 15 events in 5000ms window
Matched sequence:
10:30:40 ERROR auth service connection refused
10:30:42 ERROR retry attempt 1 failed
10:30:44 ERROR retry attempt 2 failed
10:30:45 FATAL service unavailable
ChronoDance Validation Results
==============================
Total events: 100,000
Confusion Matrix:
TP: 12,345 FP: 234
FN: 567 TN: 86,854
Metrics:
Precision: 0.9814
Recall: 0.9561
F1 Score: 0.9686
- Real-time threat detection from SIEM feeds
- Automated alert triage and prioritization
- Attack chain correlation across log sources
- Rapid forensic timeline analysis
- Anomaly identification in historical logs
- Baseline deviation reporting
- Service degradation early warning
- Cascade failure detection
- Performance anomaly identification
- Continuous monitoring for audit requirements
- Automated anomaly documentation
- Threshold-based alerting
| Metric | Value |
|---|---|
| Throughput | 500,000+ events/sec |
| Latency | < 1ms per event |
| Memory | Bounded (streaming architecture) |
| Startup | < 1 second |
Tested on commodity hardware (4-core, 8GB RAM).
- CLI Tool - Direct command-line usage
- Pipeline Integration - stdin/stdout for Unix pipelines
- Container - Docker-ready for cloud deployment
- Library - Embeddable in Rust applications
- Linux (x86_64, ARM64)
- macOS (Intel, Apple Silicon)
- Windows (x86_64)
ChronoDance is currently in private beta.
Interested in early access?
Contact: [Your contact info or form]
ChronoDance builds on research in:
- Time-series anomaly detection
- Stochastic point processes
- Temporal logic verification
- Statistical process control
The detection engine combines multiple algorithmic approaches with configurable weights, allowing tuning for different operational environments.
Proprietary. All rights reserved.
For licensing inquiries, contact: [Your contact info]
ChronoDance - See threats before they strike.