Analyzing Network Flow Data With Netflow
Overview
Cybersecurity skill for analyzing network flow data with netflow. Follows industry best practices and security standards.
When to Use
Trigger phrases:
"analyzing network flow data with netflow"
"Parse NetFlow v9 and IPFIX records to detect volumetric anomalies, port scanning"
When investigating security incidents that require analyzing network flow data with netflow
When building detection rules or threat hunting queries for this domain
When SOC analysts need structured procedures for this analysis type
When validating security monitoring coverage for related attack techniques
When NOT to Use
- When you lack proper authorization for testing
- For production systems without change management
- When the task requires legal or compliance expertise beyond technical scope
Prerequisites
- Familiarity with network security concepts and tools
- Access to a test or lab environment for safe execution
- Python 3.8+ with required dependencies installed
- Appropriate authorization for any testing activities
Workflow
# Example: IOC detection
import re
IOC_PATTERNS = {
"ip": r"\b(?:\d{1,3}\.){3}\d{1,3}\b",
"domain": r"\b[a-z0-9-]+\.[a-z]{2,}\b",
"hash_md5": r"\b[a-f0-9]{32}\b",
"hash_sha256": r"\b[a-f0-9]{64}\b",
}
def extract_iocs(text: str) -> dict:
return {k: re.findall(v, text) for k, v in IOC_PATTERNS.items()}
- Scope the Analysis — Define what network flow data artifacts or data sources to examine and the investigation timeline.
- Preserve Evidence — Create forensic copies of relevant data. Maintain chain of custody documentation.
- Extract Key Indicators — Use netflow to parse and extract relevant network flow data data points from collected artifacts.
- Correlate Findings — Cross-reference extracted data with other sources (threat intel, logs, timelines).
- Build Timeline — Construct a chronological sequence of events related to network flow data.
- Document Analysis — Write findings report with evidence, conclusions, and recommendations.
Tools
- netflow — Primary tool for this skill
- Forensic Toolkit — Evidence collection and analysis
- Timeline Tools — Chronological event reconstruction
- Log Analysis Platform — Centralized log parsing and search
Process
- Scope — Define research questions, identify data sources, set time boundaries
- Gather — Collect data from primary sources, APIs, and public records
- Synthesize — Analyze findings, identify patterns, produce actionable report
Verification
- All network flow data procedures executed completely and documented
- Findings validated against multiple data sources
- False positives identified and filtered
- Results documented with evidence and timestamps
- Recommendations provided with risk-based prioritization
Anti-Rationalization Table
| Rationalization | Reality |
|---|---|
| "We are too small to be targeted" | Automated attacks target everyone. Size does not matter. |
| "Security slows us down" | A breach slows you down 100x more. Build security in from the start. |
| "We will fix it after launch" | Vulnerabilities in production are exploited within hours. Fix before deploy. |