analyst security skill risk: medium
NetFlow Security Anomaly Analyzer
Instructs on installing netflow, collecting and parsing NetFlow v9/IPFIX data, analyzing flows for port scanning, data exfiltration, C2 beaconing and volumetric anomalies, then gen…
- External action: low
SKILL 4 files · 2 folders
SKILL.md
---
name: analyzing-network-flow-data-with-netflow
description: "Parse NetFlow v9 and IPFIX records to detect volumetric anomalies, port scanning, data exfiltration, and C2 beaconing"
---
# Analyzing Network Flow Data with Netflow
## When to Use
- 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
## 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
## Instructions
1. Install dependencies: `pip install netflow`
2. Collect NetFlow/IPFIX data from routers or use the built-in collector: `python -m netflow.collector -p 9995`
3. Parse captured flow data using `netflow.parse_packet()`.
4. Analyze flows for:
- Port scanning: single source to many destinations on same port
- Data exfiltration: high byte-count outbound flows to unusual destinations
- C2 beaconing: periodic connections with consistent intervals
- Volumetric anomalies: traffic spikes beyond baseline thresholds
5. Generate a prioritized findings report.
```bash
python scripts/agent.py --flow-file captured_flows.json --output netflow_report.json
```
## Examples
### Parse NetFlow v9 Packet
```python
import netflow
data, _ = netflow.parse_packet(raw_bytes, templates={})
for flow in data.flows:
print(flow.IPV4_SRC_ADDR, flow.IPV4_DST_ADDR, flow.IN_BYTES)
```
REQUIRED CONTEXT
- NetFlow v9 or IPFIX flow data
OPTIONAL CONTEXT
- Python environment
- router collector access
EXPECTED OUTPUT
- Format
- markdown
- Constraints
- include prioritized findings report
- follow numbered analysis steps
SUCCESS CRITERIA
- Parse NetFlow/IPFIX data
- Detect port scanning, data exfiltration, C2 beaconing and volumetric anomalies
- Generate a prioritized findings report
EXAMPLES
Includes one example of parsing a NetFlow v9 packet using netflow.parse_packet().
CAVEATS
- Dependencies
- Familiarity with network security concepts and tools
- Access to a test or lab environment
- Python 3.8+ with required dependencies installed
- Appropriate authorization for testing
- Missing context
- Exact output format or schema for the report
- Definition of thresholds or heuristics for anomalies
- Ambiguities
- Does not specify desired output length or format for the 'prioritized findings report'.
- 'unusual destinations' and 'baseline thresholds' are undefined.
QUALITY
- OVERALL
- 0.72
- CLARITY
- 0.85
- SPECIFICITY
- 0.65
- REUSABILITY
- 0.60
- COMPLETENESS
- 0.70
IMPROVEMENT SUGGESTIONS
- Add a required 'Output Format' section specifying JSON schema or report structure.
- Replace vague phrases like 'unusual destinations' with explicit criteria or configurable parameters.
USAGE
Copy the prompt above and paste it into your AI of choice — Claude, ChatGPT, Gemini, or anywhere else you're working. Replace any placeholder sections with your own context, then ask for the output.
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