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https://github.com/mukul975/Anthropic-Cybersecurity-Skills.git
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mukul975
cb8d79e068
- Add validated mitre_attack frontmatter to all 754 skills (286 distinct techniques), verified against MITRE ATT&CK v19.1 via the official mitreattack-python library: 0 revoked, deprecated, or invalid IDs - Curate precise per-skill technique IDs for forensics, malware-analysis, threat-intel, and red-team skills (e.g. DCSync -> T1003.006, Kerberoasting -> T1558.003, Pass-the-Ticket -> T1550.003) - Reconcile v19.1 tactic restructuring: Defense Evasion split into Stealth (TA0005) and Defense Impairment (TA0112); revoked T1562.* family and T1070.001/.002 remapped to active equivalents (T1685.*) - Normalize word-split tags across 35 skills (remove filename-derived stopword tags, add semantic cybersecurity tags) - Add api-reference.md for 3 skills that were missing it - Update README ATT&CK section with accurate v19.1 tactic distribution
73 lines
2.1 KiB
Markdown
73 lines
2.1 KiB
Markdown
---
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name: analyzing-network-flow-data-with-netflow
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description: Parse NetFlow v9 and IPFIX records to detect volumetric anomalies, port
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scanning, data exfiltration, and C2 beaconing patterns. Uses the Python netflow
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library to decode flow records, builds traffic baselines, and applies statistical
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analysis to identify flows with abnormal byte counts, connection durations, and
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periodic timing patterns.
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domain: cybersecurity
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subdomain: network-security
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tags:
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- analyzing
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- network
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- flow
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- data
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version: '1.0'
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author: mahipal
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license: Apache-2.0
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nist_csf:
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- PR.IR-01
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- DE.CM-01
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- ID.AM-03
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- PR.DS-02
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mitre_attack:
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- T1071
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- T1048
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- T1046
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- T1095
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---
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# Analyzing Network Flow Data with Netflow
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## When to Use
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- When investigating security incidents that require analyzing network flow data with netflow
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- When building detection rules or threat hunting queries for this domain
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- When SOC analysts need structured procedures for this analysis type
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- When validating security monitoring coverage for related attack techniques
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## Prerequisites
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- Familiarity with network security concepts and tools
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- Access to a test or lab environment for safe execution
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- Python 3.8+ with required dependencies installed
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- Appropriate authorization for any testing activities
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## Instructions
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1. Install dependencies: `pip install netflow`
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2. Collect NetFlow/IPFIX data from routers or use the built-in collector: `python -m netflow.collector -p 9995`
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3. Parse captured flow data using `netflow.parse_packet()`.
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4. Analyze flows for:
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- Port scanning: single source to many destinations on same port
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- Data exfiltration: high byte-count outbound flows to unusual destinations
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- C2 beaconing: periodic connections with consistent intervals
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- Volumetric anomalies: traffic spikes beyond baseline thresholds
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5. Generate a prioritized findings report.
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```bash
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python scripts/agent.py --flow-file captured_flows.json --output netflow_report.json
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```
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## Examples
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### Parse NetFlow v9 Packet
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```python
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import netflow
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data, _ = netflow.parse_packet(raw_bytes, templates={})
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for flow in data.flows:
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print(flow.IPV4_SRC_ADDR, flow.IPV4_DST_ADDR, flow.IN_BYTES)
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```
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