Threat Detection

AI-Powered Detection

sent1nels uses machine learning models trained on billions of security events to detect threats that traditional signature-based systems miss.

Detection Methods

• Behavioral Analysis - Identifies anomalous user and system behavior
• Pattern Recognition - Detects known attack patterns and TTPs
• Anomaly Detection - Finds deviations from established baselines
• Threat Intelligence - Correlates with global threat feeds

Threat Categories

Malware Detection

Identify malicious software including:

• Ransomware
• Trojans and backdoors
• Cryptominers
• Rootkits

Network Threats

Detect network-based attacks:

• Port scanning and reconnaissance
• DDoS attacks
• Man-in-the-middle attacks
• DNS tunneling

Insider Threats

Monitor for malicious insider activity:

• Unauthorized data access
• Privilege escalation
• Data exfiltration
• Policy violations

Configuration

Enable AI Detection

# Enable AI-powered detection
sent1nels config set ai.detection.enabled true

# Set detection sensitivity (low, medium, high)
sent1nels config set ai.detection.sensitivity high

# Enable specific detection modules
sent1nels config set ai.modules.malware true
sent1nels config set ai.modules.network true
sent1nels config set ai.modules.insider true

Custom Detection Rules

Create custom rules for your environment:

{
  "name": "Suspicious Process Execution",
  "description": "Detect unusual process execution patterns",
  "severity": "high",
  "conditions": {
    "process_name": ["powershell.exe", "cmd.exe"],
    "parent_process": "winword.exe",
    "network_connection": true
  },
  "actions": ["alert", "isolate_host"]
}

Tuning Detection

Optimize detection accuracy for your environment:

• Review false positives and adjust sensitivity
• Create allowlists for known-good behavior
• Enable learning mode to establish baselines
• Regularly update threat intelligence feeds

Next Steps

• Configure Automated Response
• Integrate Threat Intelligence
• View Detected Threats