Implements SIEM detection use cases by designing correlation rules, threshold alerts, and behavioral analytics mapped to MITRE ATT&CK techniques across Splunk, Elastic, and Sentinel. Use when SOC teams need to expand detection coverage, formalize use case lifecycle management, or build a detection library aligned to organizational threat profile.
Use this skill when:
Do not use for ad-hoc hunting queries — use cases are formalized, tested, and maintained detection rules, not exploratory searches.
Map current detection rules to ATT&CK and identify gaps:
import json
# Load current detection rules mapped to ATT&CK
current_rules = [
{"name": "Brute Force Detection", "techniques": ["T1110.001", "T1110.003"]},
{"name": "Malware Hash Match", "techniques": ["T1204.002"]},
{"name": "Suspicious PowerShell", "techniques": ["T1059.001"]},
]
# Load ATT&CK Enterprise techniques
with open("enterprise-attack.json") as f:
attack = json.load(f)
all_techniques = set()
for obj in attack["objects"]:
if obj["type"] == "attack-pattern":
ext = obj.get("external_references", [])
for ref in ext:
if ref.get("source_name") == "mitre-attack":
all_techniques.add(ref["external_id"])
covered = set()
for rule in current_rules:
covered.update(rule["techniques"])
gaps = all_techniques - covered
print(f"Total techniques: {len(all_techniques)}")
print(f"Covered: {len(covered)} ({len(covered)/len(all_techniques)*100:.1f}%)")
print(f"Gaps: {len(gaps)}")
# Prioritize gaps by threat relevance
priority_techniques = [
"T1003", "T1021", "T1053", "T1547", "T1078",
"T1055", "T1071", "T1105", "T1036", "T1070"
]
priority_gaps = [t for t in priority_techniques if t in gaps]
print(f"Priority gaps: {priority_gaps}")
Document each use case with a standardized template:
use_case_id: UC-2024-015