技能 硬件工程 检测Mimikatz凭证窃取行为

检测Mimikatz凭证窃取行为

v20260802
detecting-mimikatz-execution-patterns
提供一套完整的Mimikatz工具和凭证窃取活动检测流程。该方法通过分析命令模式、LSASS访问痕迹、内存行为等多个维度,用于主动进行威胁狩猎、缩小事件响应范围,或在红蓝对抗演练中验证安全检测能力。
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概览

Detecting Mimikatz Execution Patterns

When to Use

  • When proactively hunting for indicators of detecting mimikatz execution patterns in the environment
  • After threat intelligence indicates active campaigns using these techniques
  • During incident response to scope compromise related to these techniques
  • When EDR or SIEM alerts trigger on related indicators
  • During periodic security assessments and purple team exercises

Prerequisites

  • EDR platform with process and network telemetry (CrowdStrike, MDE, SentinelOne)
  • SIEM with relevant log data ingested (Splunk, Elastic, Sentinel)
  • Sysmon deployed with comprehensive configuration
  • Windows Security Event Log forwarding enabled
  • Threat intelligence feeds for IOC correlation

Workflow

  1. Formulate Hypothesis: Define a testable hypothesis based on threat intelligence or ATT&CK gap analysis.
  2. Identify Data Sources: Determine which logs and telemetry are needed to validate or refute the hypothesis.
  3. Execute Queries: Run detection queries against SIEM and EDR platforms to collect relevant events.
  4. Analyze Results: Examine query results for anomalies, correlating across multiple data sources.
  5. Validate Findings: Distinguish true positives from false positives through contextual analysis.
  6. Correlate Activity: Link findings to broader attack chains and threat actor TTPs.
  7. Document and Report: Record findings, update detection rules, and recommend response actions.

Key Concepts

Concept Description
T1003.001 LSASS Memory
T1003.006 DCSync
T1558.003 Kerberoasting
T1558.001 Golden Ticket

Tools & Systems

Tool Purpose
CrowdStrike Falcon EDR telemetry and threat detection
Microsoft Defender for Endpoint Advanced hunting with KQL
Splunk Enterprise SIEM log analysis with SPL queries
Elastic Security Detection rules and investigation timeline
Sysmon Detailed Windows event monitoring
Velociraptor Endpoint artifact collection and hunting
Sigma Rules Cross-platform detection rule format

Common Scenarios

  1. Scenario 1: Standard sekurlsa::logonpasswords credential dump
  2. Scenario 2: PowerShell Invoke-Mimikatz reflective loading
  3. Scenario 3: DCSync from non-DC host
  4. Scenario 4: Golden ticket creation for persistence

Output Format

Hunt ID: TH-DETECT-[DATE]-[SEQ]
Technique: T1003.001
Host: [Hostname]
User: [Account context]
Evidence: [Log entries, process trees, network data]
Risk Level: [Critical/High/Medium/Low]
Confidence: [High/Medium/Low]
Recommended Action: [Containment, investigation, monitoring]
信息
Category 硬件工程
Name detecting-mimikatz-execution-patterns
版本 v20260802
大小 14.31KB
更新时间 2026-08-04
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