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mukul975
757f1c8eae
- implementing-vulnerability-management-with-greenbone: python-gvm GMP API, scan task creation, XML report parsing - detecting-email-account-compromise: Microsoft Graph inbox rules, impossible travel detection, OAuth grant analysis - performing-threat-intelligence-sharing-with-misp: PyMISP event creation, attribute management, sharing validation - analyzing-cobaltstrike-malleable-c2-profiles: dissect.cobaltstrike C2Profile parsing, Suricata rule generation - hunting-for-registry-run-key-persistence: Sysmon Event 13 analysis, T1547.001 detection, Sigma rule generation
2.1 KiB
2.1 KiB
SIEM Use Case Tuning API Reference
Splunk Notable Event Export
Export Notables via SPL
| inputlookup notable_events
| search status_label IN ("New", "In Progress", "Resolved")
| table rule_name, _time, status_label, src, dest, user, urgency
| rename status_label as disposition, _time as timestamp
| outputlookup alert_export.csv
Splunk ES Correlation Search Tuning
# Measure FP rate per correlation search over 30 days
| inputlookup notable_events where earliest=-30d
| eval is_fp=if(status_label="Resolved" AND disposition="False Positive", 1, 0)
| stats count as total, sum(is_fp) as fp_count by rule_name
| eval fp_rate=round(fp_count/total, 4)
| sort -fp_rate
Update Correlation Search Threshold
POST /servicesNS/nobody/SplunkEnterpriseSecuritySuite/saved/searches/{search_name}
Content-Type: application/x-www-form-urlencoded
search=<updated_spl_with_new_threshold>
Elastic Detection Rule Tuning
List Detection Rules
GET /_security/detection_engine/rules/_find?per_page=100
Authorization: ApiKey <base64_api_key>
Add Exception to Rule
POST /_security/detection_engine/rules/exceptions
{
"rule_id": "rule-uuid",
"name": "Whitelist scanner IPs",
"entries": [
{
"field": "source.ip",
"operator": "is_one_of",
"value": ["10.0.1.50", "10.0.1.51"],
"type": "match_any"
}
]
}
Query Rule Execution Stats (Kibana)
event.kind: "signal" AND kibana.alert.rule.name: "Brute Force Detection"
| stats count by kibana.alert.workflow_status
Alert Tuning Metrics
| Metric | Formula | Target |
|---|---|---|
| False Positive Rate | FP / (FP + TP) | < 30% |
| Precision | TP / (TP + FP) | > 70% |
| Alert-to-Incident Ratio | Incidents / Total Alerts | > 20% |
| Mean Time to Triage | avg(triage_end - alert_time) | < 15 min |
CLI Usage
# Analyze alert CSV export
python agent.py --alert-csv notable_export.csv --output tuning.json
# Adjust FP threshold for whitelist candidates
python agent.py --alert-csv alerts.csv --fp-threshold 0.9 --top-rules 10
# CSV format: rule_name,timestamp,disposition,source,user,severity