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分析Azure活动日志以识别威胁

通过azure-monitor-query查询Azure Monitor活动日志和登录日志,检测可疑的管理操作和登录异常。

分析Azure活动日志以识别威胁 是什么?

该技能专注于使用Azure Monitor的日志查询能力,从Azure Log Analytics工作区中检索并分析活动日志和登录日志。它提供了一组预定义的KQL查询模板,能够检测特权提升(例如角色分配变更)、资源组与订阅修改、Key Vault密钥从新IP访问、网络安全组规则变更以及条件访问策略修改等安全威胁。该技能适用于SOC分析师进行事件调查、威胁狩猎以及验证安全监控覆盖范围。它基于Python的`azure-monitor-query`库实现,需要Azure凭据和工作区ID即可运行。

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文档

分析Azure活动日志以识别威胁 是做什么的?

何时使用

  • 调查需要对Azure活动日志进行以威胁为导向的分析的安全事件时
  • 需要为此领域构建检测规则或威胁狩猎查询时
  • SOC分析师需要对该分析类型有结构化的操作流程时
  • 验证相关攻击技术对应的安全监控覆盖范围时

前提条件

  • 熟悉安全运营概念和工具
  • 拥有一个测试或实验环境以安全执行操作
  • Python 3.8+ 及已安装所需依赖
  • 对任何测试活动具有适当的授权

操作说明

使用azure-monitor-query对Azure Log Analytics工作区执行KQL查询,检测可疑的管理操作和登录异常。

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),
)

关键检测查询:

  1. 角色分配变更(特权提升)
  2. 资源组和订阅修改
  3. 从新IP访问Key Vault密钥
  4. 网络安全组规则变更
  5. 条件访问策略修改

示例

# 检测新的全局管理员角色分配
query = '''
AuditLogs
| where OperationName == "Add member to role"
| where TargetResources[0].modifiedProperties[0].newValue has "Global Administrator"
'''

Individual skills in this repo

This repo contains 20 individual skills — each has its own dedicated page.

abusing-dpapi-for-credential-access

Extract and decrypt Windows DPAPI-protected secrets (Credential Manager, browser logins/cookies, Wi-Fi credentials, KeePass keys) online or offline using SharpDPAPI, SharpChrome, Mimikatz, or Impacket

abusing-shadow-credentials-for-privesc

Take over Active Directory accounts by writing attacker-controlled public keys to msDS-KeyCredentialLink (Shadow Credentials) with pyWhisker, Whisker, or Certipy, then authenticate via PKINIT to recover the target

achieving-cmmc-level-2-compliance

>-

acquiring-disk-image-with-dd-and-dcfldd

Create forensically sound bit-for-bit disk images with dd or dcfldd on a Linux forensic workstation, preserving evidence integrity through hash verification (MD5/SHA) during acquisition. Use when imaging a suspect drive, USB device, or memory card for investigation, preserving volatile disk evidence during incident response, or producing a verified copy for legal or law-enforcement proceedings before any destructive analysis.

analyzing-active-directory-acl-abuse

Detect dangerous ACL misconfigurations in Active Directory using ldap3

analyzing-android-malware-with-apktool

Perform static analysis of Android APK malware using apktool for resource decompilation, jadx for Java source recovery, and androguard for manifest inspection, dangerous permission-combination detection, and identification of obfuscated code, dynamic code loading, and reflection-based API calls. Use to statically triage a suspicious APK without executing it or to build mobile malware detection rules.

analyzing-api-gateway-access-logs

Parses API Gateway access logs (AWS API Gateway, Kong, Nginx) to detect

analyzing-apt-group-with-mitre-navigator

Query ATT&CK data with attackcti, mitreattack-python, and stix2, then build MITRE ATT&CK Navigator layers and multi-layer heatmap overlays mapping one or more APT groups

analyzing-bootkit-and-rootkit-samples

Analyzes bootkit and advanced rootkit malware infecting the Master

analyzing-browser-forensics-with-hindsight

Parse Chromium-based browser databases with Hindsight to extract and correlate browsing history, downloads, cookies, cached content, autofill data, saved passwords, and extensions from Chrome, Edge, Brave, Opera, and Vivaldi into a unified timeline (XLSX, JSON, or SQLite output). Use during incident response, insider-threat investigations, or criminal cases when you need to reconstruct a user

analyzing-campaign-attribution-evidence

Systematically evaluate cyber-campaign evidence to attribute an operation to a threat actor, using the Diamond Model and Analysis of Competing Hypotheses (ACH) to weigh infrastructure overlaps, TTP consistency, malware code similarity, and timing/language artifacts into confidence-weighted attribution assessments. Use when an incident investigation needs a defensible attribution confidence level.

analyzing-certificate-transparency-for-phishing

Monitor Certificate Transparency logs using crt.sh and Certstream to

analyzing-cloud-storage-access-patterns

Detect abnormal access in AWS S3, GCS, and Azure Blob Storage by analyzing CloudTrail Data Events, GCS audit logs, and Azure Storage Analytics for after-hours bulk downloads, new-IP access, and API-call spikes (e.g. GetObject) via statistical baselines and time-series anomaly detection. Use when investigating suspected cloud data exfiltration or building related detection rules.

analyzing-cobalt-strike-beacon-configuration

Extract and analyze Cobalt Strike beacon configuration from PE files

analyzing-cobaltstrike-malleable-c2-profiles

Parse and analyze Cobalt Strike Malleable C2 profiles with dissect.cobaltstrike (profiles and beacon-payload configs) and pyMalleableC2 (AST parsing) to extract HTTP/DNS transforms, URIs, headers, sleep/jitter, and injection behavior, then generate network detection signatures. Use when reverse-engineering a captured malleable profile or building detections against Cobalt Strike Beacon traffic.

analyzing-command-and-control-communication

Analyzes malware C2 communication over HTTP, HTTPS, DNS, and custom

analyzing-cyber-kill-chain

Analyzes intrusion activity against the Lockheed Martin Cyber Kill Chain

analyzing-disk-image-with-autopsy

Perform comprehensive forensic analysis of raw (dd), E01, or AFF disk images with Autopsy and The Sleuth Kit, recovering deleted files, examining metadata and embedded artifacts, keyword searching, and building investigation timelines with visual reports. Use for structured analysis of a forensic disk image or when stakeholders need visual reports from evidence.

analyzing-dns-logs-for-exfiltration

Analyzes DNS query logs to detect data exfiltration via DNS tunneling,

analyzing-docker-container-forensics

Investigate compromised Docker containers by analyzing images, layers,

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