🔍 Log Analyzer

Log Analyzer is a tool for analyzing and detecting suspicious patterns in logs, with a focus on cybersecurity. The project is built using Spring Boot, GraalVM Native, and integrates with Loki for log collection and Prometheus for metrics exposure.

🚀 Main Features:

✅ Detects common attacks, such as Brute Force, SQL Injection, XSS, RCE, and Path Traversal.

✅ Loki integration, enabling efficient log analysis in distributed systems.

✅ Exports metrics to Prometheus, allowing monitoring via Grafana.

✅ Optimized with caching and multithreading for high-performance log processing.

✅ GraalVM native build, making the binary faster and more efficient.

⚡ Getting Started

Prerequisites

• Java 21 (GraalVM)
• Docker (for Loki, Prometheus, and Grafana)
• Gradle

Required Infrastructure

This project depends on log monitoring infrastructure for containerized services like Loki, Prometheus, and Grafana.

You can find the Docker setup in the following repository:

🔗 Log Monitoring Infrastructure: https://github.com/adlermedrado/log-monitoring-infra

Clone and start the infrastructure before running the application.

Steps to Run

1️⃣ Clone this repository

git clone https://github.com/seu-usuario/log-analyzer.git
cd log-analyzer

2️⃣ Start Loki, Prometheus, and Grafana:

cd ../log-monitoring-infra
docker-compose up -d

3️⃣ Compile the project:

./gradlew nativeCompile

4️⃣ Run the application:

./build/native/nativeCompile/log-analyzer

📊 Monitoring

• Metrics Endpoint: http://localhost:8080/actuator/prometheus
• Grafana Dashboard: http://localhost:3000 (Username: admin / Password: admin)
• Loki API: http://localhost:3100/loki/api/v1/query_range

🔥 Roadmap

✅ Phase 1 – Manual Rule-Based Detection

🔹 Implement security event detectors for common attacks.

🔹 Integrate with Loki for efficient log queries.

🔹 Export security metrics to Prometheus and Grafana.

🚧 Phase 2 – Optimization & Expansion (In Progress…)

🔹 Add AI-driven anomaly detection using Ollama and Llama3 models.

🔹 Improve detection with contextual log analysis.

🔹 Expand automated testing for increased reliability.

🚀 Phase 3 – Future Enhancements (Planned)

🔹 Support for new log sources and formats.

🔹 Implement alerting via Webhook, Slack, and Telegram.

🔹 Develop an alternative Rust version for higher performance.

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⚖️ License

This project is open-source and distributed under the MIT License.

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🎯 Contributions are welcome!

If you have suggestions, feel free to open an issue or submit a pull request. 🚀