Threat Detection

Threat Detection

Threat detection skill for proactive discovery of attacker activity through hypothesis-driven hunting, IOC analysis, and behavioral anomaly detection. This is NOT incident response (see incident-response) or red team operations (see red-team) — this is about finding threats that have evaded automated controls.

Table of Contents

• Overview
• Threat Signal Analyzer
• Threat Hunting Methodology
• IOC Analysis
• Anomaly Detection
• MITRE ATT&CK Signal Prioritization
• Deception and Honeypot Integration
• Workflows
• Anti-Patterns
• Cross-References

Overview

What This Skill Does

This skill provides the methodology and tooling for proactive threat detection — finding attacker activity through structured hunting hypotheses, IOC analysis, and statistical anomaly detection before alerts fire.

Distinction from Other Security Skills

Prerequisites

Read access to SIEM/EDR telemetry, endpoint logs, and network flow data. IOC feeds require freshness within 30 days to avoid false positives. Hunting hypotheses must be scoped to the environment before execution.

Threat Signal Analyzer

The threat_signal_analyzer.py tool supports three modes: hunt (hypothesis scoring), ioc (sweep generation), and anomaly (statistical detection).

# Hunt mode: score a hypothesis against MITRE ATT&CK coverage
python3 scripts/threat_signal_analyzer.py --mode hunt \
  --hypothesis "Lateral movement via PtH using compromised service account" \
  --actor-relevance 3 --control-gap 2 --data-availability 2 --json

# IOC mode: generate sweep targets from an IOC feed file
python3 scripts/threat_signal_analyzer.py --mode ioc \
  --ioc-file iocs.json --json

# Anomaly mode: detect statistical outliers in telemetry events
python3 scripts/threat_signal_analyzer.py --mode anomaly \
  --events-file telemetry.json \
  --baseline-mean 100 --baseline-std 25 --json

# List all supported MITRE ATT&CK techniques
python3 scripts/threat_signal_analyzer.py --list-techniques

IOC file format

{
  "ips": ["1.2.3.4", "5.6.7.8"],
  "domains": ["malicious.example.com"],
  "hashes": ["abc123def456..."]
}

Telemetry events file format

[
  {"timestamp": "2024-01-15T14:32:00Z", "entity": "host-01", "action": "dns_query", "volume": 450},
  {"timestamp": "2024-01-15T14:33:00Z", "entity": "host-02", "action": "dns_query", "volume": 95}
]

Exit codes

Threat Hunting Methodology

Structured threat hunting follows a five-step loop: hypothesis → data source identification → query execution → finding triage → feedback to detection engineering.

Hypothesis Scoring

Priority score = (actor_relevance × 3) + (control_gap × 2) + (data_availability × 1)

High-Value Hunt Hypotheses by Tactic

IOC Analysis

IOC analysis determines whether indicators are fresh, maps them to required sweep targets, and filters stale data that generates false positives.

IOC Types and Sweep Priority

IOC Staleness Handling

IOCs older than their threshold are flagged as stale and excluded from sweep target generation. Running sweeps against stale IOCs inflates false positive rates and reduces SOC credibility. Refresh IOC feeds from threat intelligence platforms (MISP, OpenCTI, commercial TI) before every hunt cycle.

Anomaly Detection

Statistical anomaly detection identifies behavior that deviates from established baselines without relying on known-bad signatures.

Z-Score Thresholds

Baseline Requirements

Effective anomaly detection requires at least 14 days of historical telemetry to establish a valid baseline. Baselines must be recomputed after:

• Security incidents (post-incident behavior change)
• Major infrastructure changes (cloud migrations, new SaaS deployments)
• Seasonal usage pattern changes (end of quarter, holiday periods)

High-Value Anomaly Targets

MITRE ATT&CK Signal Prioritization

Each hunting hypothesis maps to one or more ATT&CK techniques. Techniques with multiple confirmed signals in your environment are higher priority.

Tactic Coverage Matrix

| Tactic | Key Techniques | Primary Data Source | |--------|---------------|--------------------|-| | Initial Access | T1190, T1566, T1078 | Web access logs, email gateway, auth logs | | Execution | T1059, T1047, T1218 | Process creation, command-line, script execution | | Persistence | T1053, T1543, T1098 | Scheduled tasks, services, account changes | | Defense Evasion | T1027, T1562, T1070 | Process hollowing, log clearing, encoding | | Credential Access | T1003, T1558, T1110 | LSASS, Kerberos, auth failures | | Lateral Movement | T1550, T1021, T1534 | NTLM auth, remote services, internal spearphish | | Collection | T1074, T1560, T1114 | Staging directories, archive creation, email access | | Exfiltration | T1048, T1041, T1567 | Unusual outbound volume, DNS tunneling, cloud storage | | Command & Control | T1071, T1572, T1568 | Beaconing, protocol tunneling, DNS C2 |