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Prompts SIEM APT Lateral Movement Correlation Rules

security analyst security skill risk: medium

SIEM APT Lateral Movement Correlation Rules

Write multi-event correlation rules that detect APT lateral movement by chaining Windows authentication events, including Sigma YAML rules and Splunk SPL queries.

  • Policy sensitive
  • Human review
  • External action: high

SKILL 4 files · 2 folders

SKILL.md
---
name: implementing-siem-correlation-rules-for-apt
description: "Write multi-event correlation rules that detect APT lateral movement by chaining Windows authentication events,"
---
# Implementing SIEM Correlation Rules for APT


## When to Use

- When deploying or configuring implementing siem correlation rules for apt capabilities in your environment
- When establishing security controls aligned to compliance requirements
- When building or improving security architecture for this domain
- When conducting security assessments that require this implementation

## Prerequisites

- Familiarity with security operations concepts and tools
- Access to a test or lab environment for safe execution
- Python 3.8+ with required dependencies installed
- Appropriate authorization for any testing activities

## Instructions

1. Install dependencies: `pip install requests pyyaml sigma-cli`
2. Connect to the Splunk REST API and define correlation searches that chain multiple event types across hosts.
3. Build Sigma rules in YAML that express multi-step detection logic for lateral movement patterns:
   - RDP logon (4624 LogonType=10) followed by service installation (7045) on same target within 15 minutes
   - Pass-the-Hash: NTLM logon (4624 LogonType=3) followed by process creation (4688) of admin tools
   - PsExec-style: Named pipe creation (Sysmon 17/18) correlated with remote service creation (7045)
4. Convert Sigma rules to Splunk SPL using `sigma-cli convert`.
5. Deploy correlation searches to Splunk ES via the REST API.
6. Run the agent to generate and install correlation rules, then audit existing rules for coverage gaps.

```bash
python scripts/agent.py --splunk-url https://localhost:8089 --username admin --password changeme --output correlation_report.json
```

## Examples

### Detect RDP Lateral Movement Chain
```
index=wineventlog (EventCode=4624 Logon_Type=10) OR (EventCode=7045)
| transaction Computer maxspan=15m startswith=(EventCode=4624) endswith=(EventCode=7045)
| where eventcount >= 2
| table _time Computer Account_Name ServiceName
```

### Sigma Rule for PsExec Lateral Movement
```yaml
title: PsExec Lateral Movement Detection
logsource:
  product: windows
  service: sysmon
detection:
  pipe_created:
    EventID: 17
    PipeName|startswith: '\PSEXESVC'
  service_installed:
    EventID: 7045
    ServiceFileName|contains: 'PSEXESVC'
  timeframe: 5m
  condition: pipe_created | near service_installed
level: high
```

REQUIRED CONTEXT

  • Splunk REST API access
  • Windows event logs

OPTIONAL CONTEXT

  • test environment
  • Python 3.8+

TOOLS REQUIRED

  • sigma-cli

EXPECTED OUTPUT

Format
markdown
Constraints
  • include Sigma YAML rules
  • include Splunk SPL examples
  • follow provided step-by-step instructions

EXAMPLES

Includes one SPL transaction query example for RDP lateral movement and one YAML Sigma rule example for PsExec detection.

CAVEATS

Dependencies
  • Splunk REST API access
  • Python 3.8+ with dependencies
  • test or lab environment
Missing context
  • Target SIEM platform (hard-coded to Splunk)
  • Exact schema or expected output of correlation_report.json
  • Error handling or validation criteria for generated rules
Ambiguities
  • Description sentence is truncated/incomplete
  • 'When to Use' section contains repetitive phrasing ('deploying or configuring implementing siem')
  • Step 6 refers to 'the agent' without defining what agent.py does or its source

QUALITY

OVERALL
0.52
CLARITY
0.72
SPECIFICITY
0.68
REUSABILITY
0.25
COMPLETENESS
0.60

IMPROVEMENT SUGGESTIONS

  • Replace hard-coded Splunk/Sigma specifics with placeholders so the prompt can be reused for other SIEMs
  • Add explicit output format and success criteria for the generated correlation rules
  • Fix truncated description and repetitive text in the 'When to Use' section

USAGE

Copy the prompt above and paste it into your AI of choice — Claude, ChatGPT, Gemini, or anywhere else you're working. Replace any placeholder sections with your own context, then ask for the output.

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