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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
88 lines
2.4 KiB
Markdown
88 lines
2.4 KiB
Markdown
---
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name: analyzing-azure-activity-logs-for-threats
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description: 'Queries Azure Monitor activity logs and sign-in logs via azure-monitor-query
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to detect suspicious administrative operations, impossible travel, privilege escalation,
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and resource modifications. Builds KQL queries for threat hunting in Azure environments.
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Use when investigating suspicious Azure tenant activity or building cloud SIEM detections.
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'
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domain: cybersecurity
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subdomain: security-operations
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tags:
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- azure
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- cloud-security
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- azure-monitor
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- kql
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- threat-hunting
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- activity-logs
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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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- DE.CM-01
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- RS.MA-01
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- GV.OV-01
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- DE.AE-02
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mitre_attack:
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- T1078.004
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- T1098.003
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- T1538
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- T1556.009
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- T1580
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---
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# Analyzing Azure Activity Logs for Threats
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## When to Use
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- When investigating security incidents that require analyzing azure activity logs for threats
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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 security operations 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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Use azure-monitor-query to execute KQL queries against Azure Log Analytics workspaces,
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detecting suspicious admin operations and sign-in anomalies.
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```python
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from azure.identity import DefaultAzureCredential
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from azure.monitor.query import LogsQueryClient
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from datetime import timedelta
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credential = DefaultAzureCredential()
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client = LogsQueryClient(credential)
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response = client.query_workspace(
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workspace_id="WORKSPACE_ID",
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query="AzureActivity | where OperationNameValue has 'MICROSOFT.AUTHORIZATION/ROLEASSIGNMENTS/WRITE' | take 10",
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timespan=timedelta(hours=24),
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)
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```
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Key detection queries:
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1. Role assignment changes (privilege escalation)
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2. Resource group and subscription modifications
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3. Key vault secret access from new IPs
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4. Network security group rule changes
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5. Conditional access policy modifications
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## Examples
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```python
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# Detect new Global Admin role assignments
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query = '''
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AuditLogs
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| where OperationName == "Add member to role"
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| where TargetResources[0].modifiedProperties[0].newValue has "Global Administrator"
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'''
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```
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