{"slug":"masriyan-log-analysis-siem-integration","name":"Log Analysis & SIEM Integration","description":"Security log parsing, anomaly detection, SIEM query building, Sigma rule creation, and correlation rule development across Splunk, Elastic, QRadar, and Microsoft Sentinel","long_description":"---\nname: Log Analysis & SIEM Integration\ndescription: Security log parsing, anomaly detection, SIEM query building, Sigma rule creation, and correlation rule development across Splunk, Elastic, QRadar, and Microsoft Sentinel\nversion: 3.0.0\nauthor: Masriyan\ntags: [cybersecurity, log-analysis, siem, splunk, elastic, sentinel, sigma, anomaly-detection, correlation]\n---\n\n# Log Analysis & SIEM Integration\n\n## Purpose\n\nEnable Claude to assist with security log analysis across all major platforms. Claude directly parses and analyzes log samples provided by the user, builds SIEM queries for any platform, creates Sigma rules for portable detection, develops correlation rules, and identifies anomalous patterns in log data.\n\n---\n\n## Activation Triggers\n\nThis skill activates when the user asks about:\n- Parsing Windows Event Logs, Linux syslog, or application logs\n- Building Splunk SPL, Elastic KQL/EQL, QRadar AQL, or Sentinel KQL queries\n- Creating Sigma rules for platform-agnostic detection\n- Detecting anomalies or attack patterns in log data\n- Building SIEM correlation rules for complex attack scenarios\n- Converting queries between SIEM platforms\n- Log source health monitoring and gap analysis\n- Detecting lateral movement, privilege escalation, or persistence in logs\n- EVTX analysis or Windows audit log review\n\n---\n\n## Prerequisites\n\n```bash\npip install pandas pyyaml python-dateutil\n```\n\n**Platform tools:**\n- `Splunk` — Splunk Web, SPL, and SOAR\n- `Elastic Stack` — Kibana, KQL, EQL\n- `Microsoft Sentinel` — KQL, Workbooks\n- `IBM QRadar` — AQL, Rules\n- `Sigma` — Platform-agnostic rule format\n- `python-evtx` — Parse Windows .evtx files without Windows\n\n---\n\n## Core Capabilities\n\n### 1. Log Parsing & Analysis\n\n**When the user pastes logs or provides log files:**\n\nClaude directly reads and analyzes logs to extract security-relevant events.\n\n**Windows Event Log — Critical Event IDs:**\n\n| Event ID | Log | Description |\n|----------|-----|-------------|\n| 4624 | Security | Successful logon — Logon Type 3 (network) is interesting |\n| 4625 | Security | Failed logon — track source IP for brute force |\n| 4648 | Security | Logon with explicit credentials (RunAs) |\n| 4688 | Security | New process created — needs CommandLine auditing enabled |\n| 4698 | Security | Scheduled task created |\n| 4702 | Security | Scheduled task updated |\n| 4720 | Security | User account created |\n| 4728/4732 | Security | Member added to security/local group |\n| 4768/4769 | Security | Kerberos TGT/TGS requested |\n| 4776 | Security | NTLM authentication |\n| 4946 | Security | Windows Firewall rule added |\n| 5140 | Security | Network share accessed |\n| 5145 | Security | Network share file access |\n| 7045 | System | New service installed |\n| 1102 | Security | Audit log cleared |\n| 4103/4104 | PowerShell | PowerShell module/script block logging |\n\n**Linux Log Analysis — Key Patterns:**\n```bash\n# Failed SSH logins\ngrep \"Failed password\" /var/log/auth.log | awk '{print $1,$2,$3,$11}' | sort | uniq -c | sort -rn\n\n# Successful logins after failures (brute force success)\ngrep \"Accepted password\\|Accepted publickey\" /var/log/auth.log\n\n# Sudo usage\ngrep \"sudo:\" /var/log/auth.log | grep -v \"session\"\n\n# Cron job execution\ngrep CRON /var/log/syslog\n\n# New user creation\ngrep \"useradd\\|usermod\" /var/log/auth.log\n\n# Privilege escalation\ngrep \"su\\b\" /var/log/auth.log\n```\n\n**Log parsing script:**\n```bash\npython scripts/log_parser.py --input /var/log/auth.log --format json --output parsed.json\npython scripts/log_parser.py --input events.evtx --normalize ecs --output normalized.json\n```\n\n### 2. SIEM Query Library\n\n**When the user asks to build detection queries:**\n\n#### Splunk SPL — Attack Pattern Queries\n\n```spl\n// Brute force attack detection\nindex=windows EventCode=4625\n| bin _time span=5m\n| stats count as FailedLogins, values(Account_Name) as Accounts by src_ip, _time\n| where FailedLogins > 20\n| sort -FailedLogins\n\n// Pass-the-Hash detection (Logon Type 3 with NTLM)\nindex=windows EventCode=4624 Logon_Type=3 Authentication_Package=NTLM\n| where NOT (Account_Name=\"ANONYMOUS LOGON\" OR Account_Name=\"*$\")\n| stats count by Account_Name, Workstation_Name, src_ip\n| where count > 1\n\n// Lateral movement via PsExec / admin shares\nindex=windows EventCode=5145\n| where (ShareName=\"\\\\\\\\*\\\\ADMIN$\" OR ShareName=\"\\\\\\\\*\\\\C$\") \n    AND RelativeTargetName=\"*PSEXESVC*\"\n| table _time, SubjectUserName, IpAddress, ShareName\n\n// PowerShell encoded command execution\nindex=windows (source=\"WinEventLog:Microsoft-Windows-PowerShell/Operational\" EventCode=4104)\n    OR (EventCode=4688 CommandLine=\"*powershell*\")\n| search CommandLine IN (\"*-EncodedCommand*\", \"*-enc *\", \"*-e *\", \"*-nop*\", \n                          \"*DownloadString*\", \"*IEX*\", \"*Invoke-Expression*\")\n| table _time, ComputerName, User, CommandLine\n\n// Scheduled task creation for persistence\nindex=windows EventCode=4698\n| rex field=TaskContent \"<Command>(?P<command>[^<]+)</Command>\"\n| where NOT match(command, \"(?i)\\\\\\\\windows\\\\\\\\|\\\\\\\\microsoft\\\\\\\\|\\\\\\\\system32\\\\\\\\\")\n| table _time, ComputerName, SubjectUserName, TaskName, command\n\n// LSASS memory access (credential dumping)\nindex=sysmon EventCode=10 TargetImage=\"*lsass.exe\"\n| where NOT (SourceImage IN \n    (\"C:\\\\Windows\\\\System32\\\\*\", \"C:\\\\Windows\\\\SysWOW64\\\\*\",\n     \"C:\\\\Program Files\\\\*\", \"C:\\\\Program Files (x86)\\\\*\"))\n| table _time, SourceImage, GrantedAccess, CallTrace\n\n// DCSync detection\nindex=windows EventCode=4662 \n    (ObjectType=\"*domainDNS*\" OR ObjectType=\"*19195a5b-6da0-11d0-afd3-00c04fd930c9*\")\n    (Properties=\"*Replicating Directory Changes All*\" OR Properties=\"*1131f6ad*\")\n| where NOT match(SubjectUserName, \"(?i)^.*\\$$\") \n| table _time, SubjectUserName, SubjectDomainName, Properties\n\n// Kerberoasting detection\nindex=windows EventCode=4769 Ticket_Encryption_Type=0x17\n| where NOT (Account_Name=\"*$\" OR Service_Name IN (\"krbtgt\", \"kadmin/changepw\"))\n| stats count by Account_Name, Client_Address, Service_Name\n| where count > 3\n```\n\n#### Microsoft Sentinel KQL — Queries\n\n```kql\n// Impossible Travel (logins from geographically impossible locations)\nlet TimeDelta = 2h;\nSigninLogs\n| where ResultType == 0  // Successful logins only\n| where TimeGenerated > ago(7d)\n| project UserPrincipalName, Location, TimeGenerated, IPAddress\n| sort by UserPrincipalName asc, TimeGenerated asc\n| serialize\n| extend PreviousLogin = prev(TimeGenerated), PreviousLocation = prev(Location)\n| where UserPrincipalName == prev(UserPrincipalName)\n| extend TimeDiff = TimeGenerated - PreviousLogin\n| where TimeDiff < TimeDelta and Location != PreviousLocation\n| project UserPrincipalName, Location, PreviousLocation, TimeDiff, IPAddress\n\n// Azure AD privilege escalation\nAuditLogs\n| where OperationName in (\"Add member to role\", \"Add eligible member to role\")\n| extend TargetUser = tostring(TargetResources[0].userPrincipalName)\n| extend RoleAdded = tostring(TargetResources[0].displayName)  \n| where RoleAdded in (\"Global Administrator\", \"Security Administrator\", \n                       \"Exchange Administrator\", \"SharePoint Administrator\")\n| project TimeGenerated, TargetUser, RoleAdded, \n           InitiatedBy=tostring(InitiatedBy.user.userPrincipalName)\n\n// Suspicious PowerShell activity\nSecurityEvent\n| where EventID == 4104\n| where TimeGenerated > ago(24h)\n| where ScriptBlockText has_any(\"IEX\", \"DownloadString\", \"EncodedCommand\", \n                                  \"WebClient\", \"Invoke-Expression\", \"bypass\", \"-nop\")\n| project TimeGenerated, Computer, Account, ScriptBlockText\n| extend RiskScore = case(\n    ScriptBlockText has \"IEX\" and ScriptBlockText has \"DownloadString\", 10,\n    ScriptBlockText has \"EncodedCommand\", 7,\n    ScriptBlockText has \"bypass\", 5, 3)\n| where RiskScore >= 5\n| order by RiskScore desc\n```\n\n#### Elastic EQL — Sequence Detection\n\n```eql\n// Detect fileless malware execution chain\nsequence by host.name with maxspan=5m\n  [process where event.type == \"start\" and\n   process.name in (\"outlook.exe\", \"winword.exe\", \"excel.exe\")]\n  [process where event.type == \"start\" and\n   process.name in (\"powershell.exe\", \"cmd.exe\", \"wscript.exe\", \"cscript.exe\")]\n  [network where network.direction == \"egress\" and\n   not network.destination.ip in (\"127.0.0.0/8\", \"10.0.0.0/8\", \"192.168.0.0/16\")]\n\n// Ransomware detection: mass file extension changes + shadow copy deletion\nsequence by host.name with maxspan=30m\n  [file where event.type == \"creation\" and\n   file.extension in (\"locked\", \"encrypted\", \"crypted\", \"enc\", \"readme\")]\n  [file where event.type == \"creation\" and\n   file.name in (\"README.txt\", \"DECRYPT.txt\", \"HOW_TO_DECRYPT.txt\")]\n  [process where event.type == \"start\" and\n   process.command_line : \"* delete shadows *\"]\n```\n\n### 3. Anomaly Detection Methodology\n\n**When the user asks to detect anomalies in log data:**\n\n**Statistical Anomaly Detection:**\n\n```python\n# Claude's approach to analyzing log data for anomalies:\nimport pandas as pd\nfrom datetime import timedelta\n\n# 1. Volume anomalies\n# Calculate rolling average, flag if current > mean + 3*stddev\n\n# 2. Time-based anomalies (off-hours activity)\n# Business hours: Mon-Fri 08:00-18:00 local time\n# Flag: admin activities on weekends, logins at 03:00 UTC\n\n# 3. Never-before-seen entities\n# - New admin account created\n# - First-time login from country\n# - New process never seen before\n# - New domain in DNS queries\n\n# 4. Impossible travel\n# Calculate geographic distance / time delta\n# Flag if impossible to travel physically in the time window\n```\n\n```bash\npython scripts/anomaly_detector.py --logs parsed.json --baseline baseline.json --output anomalies.json\n```\n\n**Anomaly Categories:**\n\n| Category | Indicators |\n|----------|-----------|\n| Volume spike | 10x normal event rate in 5 minutes |\n| Off-hours activity | Admin access at 03:00 local time |\n| New geography | Login from country with no prior history |\n| New process | First-ever execution of binary |\n| Large data transfer | Upload > 10x baseline for this user/system |\n| Silent log source | No events received in 30+ minutes |\n| Authentication pattern | Logon Type 3 from non-admin workstation |\n\n### 4. Sigma Rule Development\n\n**When the user asks to create Sigma rules:**\n\n```yaml\ntitle: Credential Dumping via Procdump\nid: e5eb5a27-4a98-4c34-8b39-1fbe552d2aa4\nstatus: stable\ndescription: Detects the use of ProcDump to dump LSASS memory for credential theft\nauthor: SOC Analyst\ndate: 2025/05/28\nreferences:\n  - https://attack.mitre.org/techniques/T1003/001/\n  - https://docs.microsoft.com/en-us/sysinternals/downloads/procdump\ntags:\n  - attack.credential_access\n  - attack.t1003.001\nlogsource:\n  category: process_creation\n  product: windows\ndetection:\n  selection_tool:\n    Image|endswith:\n      - '\\procdump.exe'\n      - '\\procdump64.exe'\n  selection_lsass:\n    CommandLine|contains:\n      - 'lsass'\n      - '-ma 4'      # PID 4 = System, sometimes used\n  selection_flags:\n    CommandLine|contains|all:\n      - '-accepteula'\n      - '-ma'\n  condition: selection_tool and (selection_lsass or selection_flags)\nfalsepositives:\n  - Legitimate use by administrators for debugging (rare, should be investigated)\nlevel: high\n```\n\n**Sigma rule conversion to SIEM platforms:**\n```bash\n# Install sigma-cli\npip install sigma-cli\n\n# Convert to Splunk SPL\nsigma convert -t splunk -p splunk_windows sigma_rule.yml\n\n# Convert to Elastic KQL\nsigma convert -t elasticsearch -p ecs_windows sigma_rule.yml\n\n# Convert to Microsoft Sentinel KQL  \nsigma convert -t kusto sigma_rule.yml\n```\n\n### 5. Correlation Rule Development\n\n**When the user asks to create correlation rules for multi-event detection:**\n\n```markdown\n## Correlation Rule: Brute Force → Successful Login → Lateral Movement\n\n**Trigger:** \n  Event 1: 4625 (Failed Login) × 20+ in 5 minutes (same source IP)\n  THEN Event 2: 4624 (Successful Login) from same source IP within 10 minutes\n  THEN Event 3: 5145 (Admin Share Access) from same host within 30 minutes\n\n**Logic:**\n```\nStep 1: Bucket failed logins by source IP in 5-minute windows\nStep 2: If count > 20 → mark IP as \"brute f","tagline":"Security log parsing, anomaly detection, SIEM query building, Sigma rule creation, and correlation rule development across Splunk, Elastic, QRadar, and Microsoft Sentinel","category":"security","tags":["cybersecurity","log-analysis","siem","splunk","elastic","sentinel","sigma","anomaly-detection","correlation","agent-skill"],"author":"Masriyan","verified":false,"attribution":{"status":"registry_indexed","statusLabel":"Registry indexed","shortLabel":"REGISTRY INDEXED","sourceLabel":"github candidate review","sourceDetail":"Masriyan/Claude-Code-CyberSecurity-Skill","creatorName":"Masriyan","creatorUrl":"https://github.com/Masriyan","sourceUrl":"https://github.com/Masriyan/Claude-Code-CyberSecurity-Skill/tree/main/skills/12-log-analysis","indexedBy":"OpenAgentSkill community index","claimUrl":"https://www.openagentskill.com/skills/masriyan-log-analysis-siem-integration#claim-this-skill","claimCta":"Claim this skill","trustNote":"This listing was indexed from public sources and is not marked official until a maintainer claim is approved.","publicNote":"Attribution links to the public repository or creator profile. Creators can claim the listing to update ownership signals."},"stats":{"stars":397,"forks":75,"verified_installs":0,"successful_runs":0,"total_outcomes":0,"rating":0,"review_count":0,"quality_score":45.6},"quality":{"score":77,"tier":"strong","label":"Strong","summary":"Solid option that is likely worth shortlisting for production workflows.","signals":[{"label":"GitHub stars","value":"397","tone":"neutral"},{"label":"Freshness","value":"2d ago","tone":"positive"},{"label":"Install ready","value":"Yes","tone":"positive"},{"label":"License","value":"MIT","tone":"neutral"}],"warnings":["The SKILL.md excerpt contains a truncated SPL query example (ends with `| where NOT match(command, \"(?i)\\\\windows\\\\|\\\\microsoft`) that is incomplete."]},"trust":{"version":"trust-score-v5","score":59,"base_score":67,"outcome_confidence":0,"tier":"risk","label":"Do not auto-install","summary":"Trust Score v5 found insufficient evidence for agent installation. 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Skill purpose: Security log parsing, anomaly detection, SIEM query building, Sigma rule creation, and correlation rule development across Splunk, Elastic, QRadar, and Microsoft Sentinel After the install attempt, report the result to https://www.openagentskill.com/api/agent/outcome with POST JSON {\"event_id\":\"install_<unique-id>\",\"skill_slug\":\"masriyan-log-analysis-siem-integration\",\"task\":\"Install Log Analysis & SIEM Integration\",\"agent\":\"cursor\",\"outcome\":\"success\",\"install_used\":true}. Replace event_id with a unique value and outcome with success or failed. 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Report success only after the skill is installed and a minimal verification passes."},{"id":"claude-code","label":"Claude Code","kind":"agent-prompt","value":"Add \"Log Analysis & SIEM Integration\" as a Claude Code skill from https://github.com/Masriyan/Claude-Code-CyberSecurity-Skill/tree/main/skills/12-log-analysis. Inspect the skill instructions, place the reusable skill files in the appropriate local skills location for this project, and report the activation steps. Skill purpose: Security log parsing, anomaly detection, SIEM query building, Sigma rule creation, and correlation rule development across Splunk, Elastic, QRadar, and Microsoft Sentinel After the install attempt, report the result to https://www.openagentskill.com/api/agent/outcome with POST JSON {\"event_id\":\"install_<unique-id>\",\"skill_slug\":\"masriyan-log-analysis-siem-integration\",\"task\":\"Install Log Analysis & SIEM Integration\",\"agent\":\"claude-code\",\"outcome\":\"success\",\"install_used\":true}. 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require human review before any live investment decision","The SKILL.md excerpt contains a truncated SPL query example (ends with `| where NOT match(command, \"(?i)\\\\windows\\\\|\\\\microsoft`) that is incomplete.","The prerequisites mention `python-evtx` as a platform tool but it is not included in the `pip install` command; it may need separate installation."]},"coverageTags":["Coding","Coding agents","security","cybersecurity","log-analysis","siem","splunk","elastic"]},"audit":{"audit_score":78,"risk_level":"needs_review","risk_label":"Needs review","quality_score":77,"trust_score":67,"maintenance_score":100,"security_score":71,"install_score":92,"warnings":["Dependency or permission surface needs review","Permission surface may require sandboxing","Financial research output is not financial advice; require human review before any live investment decision","The SKILL.md excerpt contains a truncated SPL query example (ends with `| where NOT match(command, \"(?i)\\\\windows\\\\|\\\\microsoft`) that is incomplete.","The prerequisites mention `python-evtx` as a platform tool but it is not included in the `pip install` command; it may need separate installation.","Financial research output is not financial advice; require human review before any live investment decision.","Quality score needs review","Permission surface needs review: secrets or environment access, shell or command execution","Dependency/runtime risk: command execution surface, credential or environment access","Permission surface: secrets or environment access, shell or command execution"]},"quality_signals":{"model":"v2","star_score":18.2,"usage_score":0,"review_score":5.4,"metadata_score":7,"freshness_score":15},"platforms":["Claude Code"],"use_cases":[{"slug":"document-processing","title":"Document processing","url":"https://www.openagentskill.com/use-cases/document-processing"},{"slug":"workflow-automation","title":"Workflow automation","url":"https://www.openagentskill.com/use-cases/workflow-automation"},{"slug":"coding-agents","title":"Coding agents","url":"https://www.openagentskill.com/use-cases/coding-agents"},{"slug":"research-agents","title":"Research agents","url":"https://www.openagentskill.com/use-cases/research-agents"}],"stacks":[{"slug":"content-growth-agent","title":"Content growth agent","url":"https://www.openagentskill.com/collections/content-growth-agent"},{"slug":"coding-review-agent","title":"Coding review agent","url":"https://www.openagentskill.com/collections/coding-review-agent"},{"slug":"research-report-agent","title":"Research report agent","url":"https://www.openagentskill.com/collections/research-report-agent"}],"install":"npx skills add Masriyan/Claude-Code-CyberSecurity-Skill --skill Log Analysis & SIEM Integration","install_targets":[{"id":"openagentskill-cli","label":"CLI","title":"OpenAgentSkill CLI","kind":"command","value":"npx --yes https://github.com/Leon-Drq/openagentskill/releases/download/cli-v0.3.0/openagentskill-0.3.0.tgz add masriyan-log-analysis-siem-integration","description":"Resolve policy, run the source installer safely, and report a verified install receipt.","copyLabel":"Copy command"},{"id":"codex","label":"Codex","title":"Codex install prompt","kind":"agent-prompt","value":"Install the \"Log Analysis & SIEM Integration\" agent skill from https://github.com/Masriyan/Claude-Code-CyberSecurity-Skill/tree/main/skills/12-log-analysis. 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Skill purpose: Security log parsing, anomaly detection, SIEM query building, Sigma rule creation, and correlation rule development across Splunk, Elastic, QRadar, and Microsoft Sentinel After the install attempt, report the result to https://www.openagentskill.com/api/agent/outcome with POST JSON {\"event_id\":\"install_<unique-id>\",\"skill_slug\":\"masriyan-log-analysis-siem-integration\",\"task\":\"Install Log Analysis & SIEM Integration\",\"agent\":\"claude-code\",\"outcome\":\"success\",\"install_used\":true}. Replace event_id with a unique value and outcome with success or failed. 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Skill purpose: Security log parsing, anomaly detection, SIEM query building, Sigma rule creation, and correlation rule development across Splunk, Elastic, QRadar, and Microsoft Sentinel After the install attempt, report the result to https://www.openagentskill.com/api/agent/outcome with POST JSON {\"event_id\":\"install_<unique-id>\",\"skill_slug\":\"masriyan-log-analysis-siem-integration\",\"task\":\"Install Log Analysis & SIEM Integration\",\"agent\":\"cursor\",\"outcome\":\"success\",\"install_used\":true}. Replace event_id with a unique value and outcome with success or failed. 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