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analyzing-azure-activity-logs-for-threats
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Basierend auf der SOC-Berufsklassifikation
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Comprehensive reconnaissance methodology covering OSINT, subdomain enumeration, technology fingerprinting, DNS reconnaissance, and attack surface mapping. Includes passive and active recon techniques with OPSEC considerations.
Comprehensive SQL injection testing methodology covering Union-based, Error-based, Blind (Boolean/Time-based), Stacked queries, and WAF bypass techniques. Includes database-specific payloads for MySQL, PostgreSQL, MSSQL, Oracle, SQLite, and NoSQL injection.
Comprehensive Server-Side Request Forgery (SSRF) testing methodology covering basic SSRF, blind SSRF, DNS rebinding, cloud metadata exploitation, and gopher/redis attacks. Includes bypass techniques and automation.
| name | analyzing-azure-activity-logs-for-threats |
| description | > |
Use azure-monitor-query to execute KQL queries against Azure Log Analytics workspaces, detecting suspicious admin operations and sign-in anomalies.
from azure.identity import DefaultAzureCredential
from azure.monitor.query import LogsQueryClient
from datetime import timedelta
credential = DefaultAzureCredential()
client = LogsQueryClient(credential)
response = client.query_workspace(
workspace_id="WORKSPACE_ID",
query="AzureActivity | where OperationNameValue has 'MICROSOFT.AUTHORIZATION/ROLEASSIGNMENTS/WRITE' | take 10",
timespan=timedelta(hours=24),
)
Key detection queries:
# Detect new Global Admin role assignments
query = '''
AuditLogs
| where OperationName == "Add member to role"
| where TargetResources[0].modifiedProperties[0].newValue has "Global Administrator"
'''