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# ZERO-NOISE: Agentic SOC-in-a-Box
**Real-time Threat Intelligence & Analysis Pipeline**
A powerful Security Operations Center (SOC) dashboard powered by AMD-optimized modular agentic architecture. ZERO-NOISE intelligently analyzes massive log volumes to identify and present only critical anomalies and security threats.
---
## Features
- **Real-Time Threat Detection**: Automatically scans and analyzes security logs in real-time
- **Anomaly Filtering**: Processes thousands of logs but displays only the anomalous incidents (0.42% detection rate)
- **Risk Scoring**: Automatically categorizes threats as CRITICAL (πŸ”΄), MEDIUM (🟠), or LOW (🟒)
- **Agentic AI Analysis**:
- **Agent 1 (Parser)**: Extracts and parses security events from logs
- **Agent 2 (Analyst)**: Performs intelligent threat analysis and recommendations
- **Live Log Scanning**: Visual indicator showing log processing progress
- **Professional Dashboard**: Modern dark-mode UI with gradient effects and smooth animations
- **Incident Intelligence Feed**: Displays detailed threat information with:
- Attack vector details
- Attacker IP addresses
- Threat summaries
- Security recommendations
---
## πŸ—οΈ Architecture
```
β”Œβ”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”
β”‚ ZERO-NOISE Dashboard (Streamlit) β”‚
β”œβ”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€
β”‚ β”‚
β”‚ β”Œβ”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β” β”Œβ”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β” β”‚
β”‚ β”‚ Incident Intelligence β”‚ β”‚ Log Analysis Panel β”‚ β”‚
β”‚ β”‚ Feed (Main) β”‚ β”‚ - Total Logs: 32 β”‚ β”‚
β”‚ β”‚ β”‚ β”‚ - Anomalies Found β”‚ β”‚
β”‚ β”‚ β€’ SQL Injection β”‚ β”‚ - Progress Bar β”‚ β”‚
β”‚ β”‚ β€’ XSS Attacks β”‚ β”‚ - Scan Status β”‚ β”‚
β”‚ β”‚ β€’ Path Traversal β”‚ β”‚ β”‚ β”‚
β”‚ β”‚ β€’ Privilege Escalation β”‚ β”‚ Pipeline Config β”‚ β”‚
β”‚ β”‚ β”‚ β”‚ - Filter: Regex β”‚ β”‚
β”‚ β”‚ β”‚ β”‚ - Parser: Qwen2-7B β”‚ β”‚
β”‚ β”‚ β”‚ β”‚ - Analyst: Qwen2-7B β”‚ β”‚
β”‚ β””β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”˜ β””β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”˜ β”‚
β”‚ β”‚
β””β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”˜
↓
FINAL_REPORT.md
(Incident Database)
```
---
## πŸ“‹ Project Structure
```
amd-hackathon/
β”œβ”€β”€ main.py # Entry point for the application
β”œβ”€β”€ app.py # Main Streamlit dashboard application
β”œβ”€β”€ agent1.py # Parser agent - extracts & parses security events
β”œβ”€β”€ agent2.py # Analyst agent - performs threat analysis
β”œβ”€β”€ logs.json # Raw log data for analysis
β”œβ”€β”€ FINAL_REPORT.md # Incident database with threat data
β”œβ”€β”€ requirements.txt # Python dependencies
└── README.md # This file
```
---
## πŸš€ Getting Started
### Prerequisites
- Python 3.8+
- pip package manager
### Installation
1. **Clone or navigate to the project directory**:
```bash
cd amd-hackathon
```
2. **Create a virtual environment** (optional but recommended):
```bash
python -m venv venv
source venv/bin/activate # On Windows: venv\Scripts\activate
```
3. **Install required dependencies**:
```bash
pip install streamlit
```
### Running the Application
Start the Streamlit dashboard:
```bash
streamlit run app.py
```
The application will open in your default browser at `http://localhost:8501`
---
## πŸ“Š Dashboard Overview
### Status Metrics
- **System Status**: Real-time protection status
- **Latency**: Average response time for threat analysis
### Log Analysis Panel (Right Sidebar)
- **Total Logs**: Shows scanning progress (0-32 logs)
- **Anomalies Found**: Number of threats detected
- **Progress Bar**: Visual representation of scan completion
- **Scan Status**: Real-time percentage indicator
### Incident Intelligence Feed (Main Area)
Displays detected threats with:
- **Threat Title**: Type of attack (SQL Injection, XSS, etc.)
- **Severity Badge**: CRITICAL πŸ”΄ | MEDIUM 🟠 | LOW 🟒
- **Attacker IP**: Source IP address of the attack
- **Summary**: Detailed description of the attack
- **Recommendation**: Security remediation steps
---
## πŸ”§ Customization
### Adjusting Scan Speed
Edit the delay values in `app.py`:
```python
time.sleep(0.5) # Log counter increment
time.sleep(2) # Incident display delay
```
```markdown
### Threat Name (Risk Score: X)
**Attacker IP:** IP_ADDRESS
**Summary:** Description of the threat
**Recommendation:** Security recommendations
---
```
### Modifying Risk Score Thresholds
Edit the threat classification in `app.py`:
```python
if risk_score >= 8: # CRITICAL
threat_class = "threat-high"
elif risk_score >= 5: # HIGH
threat_class = "threat-medium"
else: # LOW
threat_class = "threat-low"
```
---
## 🎨 UI/UX Highlights
- **Professional Dark Theme**: Blue/purple gradient aesthetic
- **Responsive Design**: Optimized for various screen sizes
- **Smooth Animations**: Hover effects and transitions
- **Real-time Updates**: Dynamic counter and progress indicators
- **Glass Morphism**: Modern backdrop blur effects on panels
- **Typography**: Inter font for UI, IBM Plex Mono for code/specs
---
## πŸ” Security Features
- **Deterministic Regex Filtering**: Initial log filtering stage
- **Qwen2-7B Parser**: AI-powered event extraction
- **Qwen2-7B Analyst**: Intelligent threat analysis
- **AMD MI300X Optimization**: GPU-accelerated inference
- **Risk Scoring System**: Automated severity classification
---
## πŸ“ˆ Performance
- **Scan Rate**: Up to 0.5 second per log update
- **Detection Time**: 2-3 seconds per threat analysis
- **Memory Efficient**: Handles 32+ logs per scan cycle
- **GPU Optimized**: Leverages AMD MI300X for inference
---
## πŸ› οΈ Troubleshooting
### Issue: App doesn't load
- Ensure Streamlit is installed: `pip install streamlit`
- Check that `FINAL_REPORT.md` exists in the project directory
### Issue: Incidents not displaying
- Verify `FINAL_REPORT.md` format matches the expected structure
- Check that incidents are separated by `---`
### Issue: Slow performance
- Reduce the number of incidents in `FINAL_REPORT.md`
- Increase the `time.sleep()` values to slow down updates
---
## πŸ“ License
This project is part of the AMD Hackathon 2026. All rights reserved.
---
## πŸ‘₯ Contributing
Feel free to extend ZERO-NOISE with:
- Additional threat detection modules
- Real-time log ingestion from SIEM systems
- Enhanced visualization dashboards
- Machine learning-based anomaly detection
- Integration with external threat intelligence APIs
---