Webapp Implementing Siem Correlation Rules For Apt

---
name: webapp-implementing-siem-correlation-rules-for-apt
description: Write multi-event correlation rules that detect APT lateral movement by chaining Windows authentication events, process execution telemetry, and network connection logs across hosts.
domain: webapp
category: security-operations
hide: true
license: Apache-2.0
metadata:
  manifest_entry: src/corpus/webapp-implementing-siem-correlation-rules-for-apt/SKILL.md
---
## Helper prerequisites

This bundled skill supplies operational methodology; execution should use evidence_exec or the documented underlying security binaries directly in accordance with engagement scope.



# 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
evidence_exec --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
```