AGENT SKILL

performing-log-source-onboarding-in-siem

Perform structured log source onboarding into SIEM platforms (Splunk, Elastic, Sentinel, QRadar, or similar) by prioritizing sources with a tiered value framework, configuring collectors, building parsers, normalizing fields to a common schema (e.g. CIM), and validating data quality. Use when planning or executing the integration of new log sources — such as Active Directory, firewalls, EDR, VPN, DNS, or cloud audit logs — into a SIEM for security monitoring and detection.

License 许可
Apache-2.0
最近更新
2026-08-31
Stars
★ 3.6w
Forks
4.4k

01 前言 Front Matter

name
performing-log-source-onboarding-in-siem
tags
[ "siem", "log-onboarding", "log-management", "data-ingestion", "parsing", "normalization", "soc" ]
author
mahipal
domain
cybersecurity
license
Apache-2.0
version
1.0
nist_csf
[ "DE.CM-01", "DE.AE-02", "RS.MA-01", "DE.AE-06" ]
subdomain
soc-operations
description
Perform structured log source onboarding into SIEM platforms (Splunk, Elastic, Sentinel, QRadar, or similar) by prioritizing sources with a tiered value framework, configuring collectors, building parsers, normalizing fields to a common schema (e.g. CIM), and validating data quality. Use when planning or executing the integration of new log sources — such as Active Directory, firewalls, EDR, VPN, DNS, or cloud audit logs — into a SIEM for security monitoring and detection.
mitre_attack
[ "T1078", "T1685.002", "T1685.005", "T1566" ]

02 资源文件 7

03 SKILL.md 正文

Performing Log Source Onboarding in SIEM

Overview

Log source onboarding is the systematic process of integrating new data sources into a SIEM platform to enable security monitoring and detection. Proper onboarding requires planning data sources, configuring collection agents, building parsers, normalizing fields to a common schema, and validating data quality. According to the UK NCSC, onboarding should prioritize log sources that provide the highest security value relative to their ingestion cost.

When to Use

  • When conducting security assessments that involve performing log source onboarding in siem
  • When following incident response procedures for related security events
  • When performing scheduled security testing or auditing activities
  • When validating security controls through hands-on testing

Prerequisites

  • SIEM platform deployed (Splunk, Elastic, Sentinel, QRadar, or similar)
  • Network access from source systems to SIEM collectors
  • Administrative access on source systems for agent installation
  • Common Information Model (CIM) or equivalent schema documentation
  • Change management approval for production system modifications

Log Source Priority Framework

Tier 1 - Critical (Onboard First)

Source Log Type Security Value
Active Directory Security Event Logs Authentication, privilege escalation
Firewalls Traffic logs Network access, C2 detection
EDR/AV Endpoint alerts Malware, process execution
VPN/Remote Access Connection logs Unauthorized access
DNS Servers Query logs C2 beaconing, data exfiltration
Email Gateway Email security logs Phishing, BEC

Tier 2 - High Priority

Source Log Type Security Value
Web Proxy HTTP/HTTPS logs Web-based attacks, data exfiltration
Cloud platforms (AWS/Azure/GCP) Audit logs Cloud security posture
Database servers Audit/query logs Data access, SQL injection
DHCP/IPAM Address allocation Asset tracking
File servers Access logs Data access monitoring

Tier 3 - Standard

Source Log Type Security Value
Application servers App logs Application-level attacks
Print servers Print logs Data loss prevention
Badge/physical access Access logs Physical security correlation
Network devices (switches/routers) Syslog Network anomalies

Onboarding Process

Step 1: Discovery and Assessment

1. Identify the log source:
   - System type and version
   - Log format (syslog, CEF, JSON, Windows Events, etc.)
   - Log volume estimate (EPS - events per second)
   - Network location and firewall requirements

2. Assess security value:
   - What threats can this source help detect?
   - Which MITRE ATT&CK techniques does it cover?
   - Is there an existing SIEM parser?

3. Estimate ingestion cost:
   - Daily volume in GB
   - License impact (per-GB or per-EPS pricing)
   - Storage retention requirements

Step 2: Configure Log Collection

Syslog-Based Collection (Firewalls, Network Devices)

# rsyslog configuration for receiving syslog
# /etc/rsyslog.d/10-siem-collection.conf

# UDP reception
module(load="imudp")
input(type="imudp" port="514" ruleset="siem_forwarding")

# TCP reception
module(load="imtcp")
input(type="imtcp" port="514" ruleset="siem_forwarding")

# TLS reception
module(load="imtcp" StreamDriver.AuthMode="x509/name"
       StreamDriver.Mode="1" StreamDriver.Name="gtls")
input(type="imtcp" port="6514" ruleset="siem_forwarding")

ruleset(name="siem_forwarding") {
    # Forward to SIEM
    action(type="omfwd" target="siem.company.com" port="9514"
           protocol="tcp" queue.type="LinkedList"
           queue.filename="siem_fwd" queue.maxdiskspace="1g"
           queue.saveonshutdown="on" action.resumeRetryCount="-1")
}

Windows Event Log Collection (Splunk Universal Forwarder)

# inputs.conf on Splunk Universal Forwarder
[WinEventLog://Security]
disabled = 0
index = wineventlog
sourcetype = WinEventLog:Security
evt_resolve_ad_obj = 1
checkpointInterval = 5

[WinEventLog://System]
disabled = 0
index = wineventlog
sourcetype = WinEventLog:System

[WinEventLog://Microsoft-Windows-Sysmon/Operational]
disabled = 0
index = wineventlog
sourcetype = XmlWinEventLog:Microsoft-Windows-Sysmon/Operational
renderXml = true

[WinEventLog://Microsoft-Windows-PowerShell/Operational]
disabled = 0
index = wineventlog
sourcetype = XmlWinEventLog:Microsoft-Windows-PowerShell/Operational

Cloud Log Collection (AWS CloudTrail)

{
  "AWSTemplateFormatVersion": "2010-09-09",
  "Resources": {
    "CloudTrailToSIEM": {
      "Type": "AWS::CloudTrail::Trail",
      "Properties": {
        "TrailName": "siem-cloudtrail",
        "S3BucketName": "company-cloudtrail-logs",
        "IsLogging": true,
        "IsMultiRegionTrail": true,
        "IncludeGlobalServiceEvents": true,
        "EnableLogFileValidation": true,
        "EventSelectors": [
          {
            "ReadWriteType": "All",
            "IncludeManagementEvents": true,
            "DataResources": [
              {
                "Type": "AWS::S3::Object",
                "Values": ["arn:aws:s3"]
              }
            ]
          }
        ]
      }
    }
  }
}

Step 3: Parse and Normalize

Custom Parser Example (Splunk props.conf/transforms.conf)

# props.conf
[custom:firewall:logs]
SHOULD_LINEMERGE = false
LINE_BREAKER = ([\r\n]+)
TIME_PREFIX = ^
TIME_FORMAT = %Y-%m-%dT%H:%M:%S%z
MAX_TIMESTAMP_LOOKAHEAD = 30
TRANSFORMS-firewall = firewall_extract_fields
FIELDALIAS-src = src_addr AS src_ip
FIELDALIAS-dst = dst_addr AS dest_ip
EVAL-action = case(fw_action=="allow", "allowed", fw_action=="deny", "blocked", true(), "unknown")
EVAL-vendor_product = "Custom Firewall"
LOOKUP-geo = geo_ip_lookup ip AS dest_ip OUTPUT country, city, latitude, longitude

# transforms.conf
[firewall_extract_fields]
REGEX = ^(\S+)\s+(\S+)\s+action=(\w+)\s+src=(\S+):(\d+)\s+dst=(\S+):(\d+)\s+proto=(\w+)\s+bytes=(\d+)
FORMAT = timestamp::$1 hostname::$2 fw_action::$3 src_addr::$4 src_port::$5 dst_addr::$6 dst_port::$7 protocol::$8 bytes::$9

CIM Field Mapping

Raw Field CIM Field Data Model
src_addr src_ip Network_Traffic
dst_addr dest_ip Network_Traffic
dst_port dest_port Network_Traffic
fw_action action Network_Traffic
bytes_sent + bytes_recv bytes Network_Traffic
user_name user Authentication
login_result action Authentication
process_path process Endpoint

Step 4: Validate Data Quality

# Verify events are arriving
index=new_source earliest=-1h
| stats count by sourcetype, host, source

# Check field extraction quality
index=new_source earliest=-1h
| stats count(src_ip) as has_src count(dest_ip) as has_dest count(action) as has_action count by sourcetype
| eval src_coverage=round(has_src/count*100,1)
| eval dest_coverage=round(has_dest/count*100,1)
| eval action_coverage=round(has_action/count*100,1)

# Verify CIM compliance
| datamodel Network_Traffic search
| search sourcetype=new_sourcetype
| stats count by source, sourcetype

# Check for timestamp parsing issues
index=new_source earliest=-1h
| eval time_diff=abs(_time - _indextime)
| stats avg(time_diff) as avg_lag max(time_diff) as max_lag by host
| where avg_lag > 300

Step 5: Enable Detection Coverage

# Verify existing correlation searches work with new source
index=new_source sourcetype=new_sourcetype
| tstats count from datamodel=Authentication by _time span=1h
| timechart span=1h count

# Create source-specific detection rule
[New Source - Authentication Anomaly]
search = index=new_source sourcetype=new_sourcetype action=failure \
| stats count by src_ip, user \
| where count > 10

Onboarding Checklist

  • [ ] Log source assessed and approved
  • [ ] Network connectivity verified
  • [ ] Collection agent/method configured
  • [ ] Log forwarding confirmed
  • [ ] Parser/field extraction configured
  • [ ] CIM compliance validated
  • [ ] Data model acceleration enabled
  • [ ] Volume within license budget
  • [ ] Retention policy configured
  • [ ] Detection rules enabled/created
  • [ ] Dashboard updated
  • [ ] Documentation completed
  • [ ] SOC team notified

References

04 同仓库更多 Skills

mukul975
mukul975/Anthropic-Cybersecurity-Skills

verifying-build-provenance-with-slsa-sigstore

Verifies artifact signatures and SLSA provenance using Sigstore's cosign (verify, verify-attestation, verify-blob-attestation) and slsa-verifier (verify-artifact), enforcing keyless OIDC builder identity and source repo against SLSA Build levels. Use in CI/CD before deploying artifacts, when consuming third-party attestations, establishing a SLSA Build L3 pipeline, or confirming provenance during incident response or admission control.

Skill与智能体开发
★ 3.6w
mukul975
mukul975/Anthropic-Cybersecurity-Skills

validating-tpm-measured-boot-attestation

Verifies TPM 2.0 measured-boot integrity and remote attestation with tpm2-tools -- reading PCRs (tpm2_pcrread), replaying the boot event log, generating and checking signed quotes (tpm2_quote/tpm2_checkquote), and sealing secrets to a PCR policy. Use to confirm a system booted trusted firmware/kernel for Zero Trust device posture, detect boot-chain tampering via PCR drift, or build a golden-value baseline for fleet attestation.

Skill与智能体开发
★ 3.6w
mukul975
mukul975/Anthropic-Cybersecurity-Skills

validating-backup-integrity-for-recovery

Validates backup integrity through cryptographic hash verification, automated restore testing, corruption detection, and recoverability checks to confirm backups are reliable for disaster recovery and ransomware response. Use before relying on backups for recovery, when building post-backup validation pipelines, auditing backup infrastructure for compliance, or checking immutable/air-gapped backups for silent corruption or tampering.

测试与质量Skill与智能体开发
★ 3.6w
mukul975
mukul975/Anthropic-Cybersecurity-Skills

triaging-windows-with-kape

Runs KAPE (Kroll Artifact Parser and Extractor) to collect targeted forensic artifacts (registry hives, $MFT, event logs, prefetch, browser data) via Targets and parse them with Modules wrapping Eric Zimmerman's EZ Tools (PECmd, MFTECmd, RECmd). Use during early incident containment/triage when full disk imaging is impractical but a defensible, parseable Windows artifact set is needed quickly, including at-scale remote collection.

Skill与智能体开发
★ 3.6w
mukul975
mukul975/Anthropic-Cybersecurity-Skills

triaging-vulnerabilities-with-ssvc-framework

Triages and prioritizes vulnerabilities with CISA's Stakeholder-Specific Vulnerability Categorization (SSVC) decision tree, weighing exploitation status (via the CISA KEV catalog and FIRST EPSS API), technical impact, automatability, and mission prevalence to output Track/Track*/Attend/Act decisions. Use when prioritizing vulnerability scan results (OpenVAS, Nessus, Qualys) for remediation planning beyond raw CVSS scores.

Skill与智能体开发
★ 3.6w
mukul975
mukul975/Anthropic-Cybersecurity-Skills

triaging-security-incident

Performs initial triage of security incidents using the NIST SP 800-61r3 and SANS PICERL frameworks, classifying incident type, assigning priority by business impact, and routing to the appropriate response team. Use when a SIEM/EDR alert needs human classification, concurrent alerts must be prioritized, or a user report or threat-intel IOC match requires initial incident categorization.

Skill与智能体开发
★ 3.6w