skills/analyzing-network-flow-data-with-netflow/SKILL.md
Parse NetFlow v9 and IPFIX records to detect volumetric anomalies, port scanning, data exfiltration, and C2 beaconing patterns. Uses the Python netflow library to decode flow records, builds traffic baselines, and applies statistical analysis to identify flows with abnormal byte counts, connection durations, and periodic timing patterns.
npx skillsauth add mukul975/anthropic-cybersecurity-skills analyzing-network-flow-data-with-netflowInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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pip install netflowpython -m netflow.collector -p 9995netflow.parse_packet().python scripts/agent.py --flow-file captured_flows.json --output netflow_report.json
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)
data-ai
Detect adversary lateral movement across networks using Splunk SPL queries against Windows authentication logs, SMB traffic, and remote service abuse.
testing
Identifies lateral movement techniques in enterprise networks by analyzing authentication logs, network flows, SMB traffic, and RDP sessions using Zeek, Velociraptor, and SIEM correlation rules to detect attackers moving between systems.
tools
Detect Kerberoasting attacks by monitoring for anomalous Kerberos TGS requests targeting service accounts with SPNs for offline password cracking.
development
Implement User and Entity Behavior Analytics using Elasticsearch/OpenSearch to build behavioral baselines, calculate anomaly scores, perform peer group analysis, and detect insider threat indicators such as data exfiltration, privilege abuse, and unauthorized access patterns.