threat-detection

Detect port scans, DoS, and beaconing using exact network thresholds.

4|Updated Feb 22, 2026
One-click install
npx skills add https://github.com/GeneralReasoning/env-skillsbench --skill threat-detection-generalreasoning
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: threat-detection
Source: https://github.com/GeneralReasoning/env-skillsbench/tree/main/dapt-intrusion-detection/environment/skills/threat-detection
Command: npx skills add https://github.com/GeneralReasoning/env-skillsbench --skill threat-detection-generalreasoning

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Exact detection thresholds for identifying malicious network patterns including port scans, DoS attacks, and beaconing behavior.

Core Features & Use Cases

  • Precise, rule-based threat detection using multi-condition thresholds (port scan, DoS, beaconing).
  • Applicable to real-time network monitoring, pcap analysis, and incident triage across enterprise networks.
  • Provides executable guidance with explicit numerical thresholds and sample code snippets for reference.

Quick Start

Configure the detector to flag network threats only when port entropy > 6.0, SYN-only ratio > 0.7, and unique ports > 100, with DoS and beaconing thresholds also enforced.

Frequently Asked Questions about threat-detection

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
What exact thresholds should I use for detecting port scans in network traffic?

To detect port scans in network traffic, apply these explicit thresholds: port entropy must exceed 6.0, the SYN-only ratio must be greater than 0.7, and unique ports must exceed 100. This multi-condition approach accurately identifies malicious scanning patterns.

How do I identify network beaconing behavior using packet capture data?

Identify network beaconing behavior in pcap data by calculating the inter-arrival time (IAT) coefficient of variation (CV). Flag connections as malicious beaconing when the IAT CV is strictly less than 0.5, indicating regular interval communications.

Can I apply these threat detection thresholds to real-time enterprise network monitoring?

Yes, you can apply these exact threat detection thresholds to real-time enterprise network monitoring and incident response. The rule-based thresholds for port scans, DoS, and beaconing are designed for both real-time analysis and pcap processing.

Why use exact numerical thresholds instead of machine learning for intrusion detection?

Using exact numerical thresholds for intrusion detection provides transparent, rule-based identification of malicious patterns without model training overhead. This approach ensures deterministic results for port scans, DoS, and beaconing across enterprise networks.

What are the limitations of using fixed thresholds for network threat detection?

Fixed thresholds for network threat detection may not adapt to evolving attack vectors or benign traffic anomalies that mimic malicious patterns. You should regularly validate these explicit rules against your specific enterprise network baseline to minimize false positives.