correlating-security-events-in-qradar

correlating-security-events-in-qradar is a skill for Claude Code, Codex from Youngmaidainon/Agent-Level-Up. It costs 78 tokens per session (2,571 once invoked), scanned A, a copy of correlating-security-events-in-qradar, MIT.

A guide to correlating security events in IBM QRadar, a SIEM that collects and analyzes logs and alerts. It uses QRadar's query language, rules, and offense management to connect activity across networks, endpoints, and applications.

In plain words
What is it for?
Use it to investigate QRadar offenses, query contributing events, build custom correlation rules, and manage allowlists or watchlists.
Why use it?
Individual alerts may look harmless when viewed alone, while related events can reveal a multi-stage attack. Correlation also helps reduce false alarms and improve detection quality.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit Use it to investigate QRadar offenses, query contributing events, build custom correlation rules, and manage allowlists or watchlists.

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Install with agentmods
npx agentmods add skills/youngmaidainon/agent-level-up/correlating-security-events-in-qradar
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add Youngmaidainon/Agent-Level-Up --skill correlating-security-events-in-qradar
Clone the repo
git clone --depth 1 https://github.com/Youngmaidainon/Agent-Level-Up

Made for: Claude Code, Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for correlating-security-events-in-qradar

README.md
[![agentmods](https://agentmods.dev/badge/skills/youngmaidainon/agent-level-up/correlating-security-events-in-qradar/github.svg)](https://agentmods.dev/skills/youngmaidainon/agent-level-up/correlating-security-events-in-qradar)
Your own site
<a href="https://agentmods.dev/skills/youngmaidainon/agent-level-up/correlating-security-events-in-qradar"><img src="https://agentmods.dev/badge/skills/youngmaidainon/agent-level-up/correlating-security-events-in-qradar/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for correlating-security-events-in-qradar

Your own site · 80×15
<a href="https://agentmods.dev/skills/youngmaidainon/agent-level-up/correlating-security-events-in-qradar"><img src="https://agentmods.dev/badge/skills/youngmaidainon/agent-level-up/correlating-security-events-in-qradar.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 78 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,571 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 1 finding. A grade says what 26 rules found in the file — not that it is safe.
Origin 100% copy Near-identical to another mod in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00078 $0.02571
Opus 5 $0.00039 $0.01286
Sonnet 5 $0.00016 $0.00514
Haiku 4.5 $0.00008 $0.00257

Measured 8d ago against content hash e93700ad34d3, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

correlating-security-events-in-qradar scanned grade A with 1 finding against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 8d ago.

The scan reads SKILL.md. This mod also ships 1 executable file (scripts/agent.py), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Makes network callslowCapability

Not a fault in itself. Listed so you know the mod talks to something, and to what.

curl -X POST "https://qradar.example.com/api/reference_data/sets" \
Origin

This is a copy

100% identical to correlating-security-events-in-qradar — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.

cyber-security/ctf/correlating-security-events-in-qradar/SKILL.md · 296 lines

How it starts

The opening of the file, as written. The whole thing — 296 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Correlating Security Events in QRadar

When to Use

Use this skill when:

  • SOC analysts need to investigate QRadar offenses and correlate events across multiple log sources
  • Detection engineers build custom correlation rules to identify multi-stage attacks
  • Alert tuning is required to reduce false positive offenses and improve signal quality
  • The team migrates from basic event monitoring to behavior-based correlation

Do not use for log source onboarding or parsing — that requires QRadar administrator access and DSM editor knowledge.

Prerequisites

  • IBM QRadar SIEM 7.5+ with offense management enabled
  • AQL knowledge for ad-hoc event and flow queries
  • Log sources normalized with proper QID mappings (Windows, firewall, proxy, endpoint)
  • User role with offense management, rule creation, and AQL search permissions
  • Reference sets/maps configured for whitelist and watchlist management

Workflow

Step 1: Investigate an Offense with AQL

Open an offense in QRadar and query contributing events using AQL (Ariel Query Language):

SELECT DATEFORMAT(startTime, 'yyyy-MM-dd HH:mm:ss') AS event_time,
       sourceIP, destinationIP, username,
       LOGSOURCENAME(logSourceId) AS log_source,
       QIDNAME(qid) AS event_name,
       category, magnitude
FROM events
WHERE INOFFENSE(12345)
ORDER BY startTime ASC
LIMIT 500

Pivot on the source IP to find all activity:

SELECT DATEFORMAT(startTime, 'yyyy-MM-dd HH:mm:ss') AS event_time,
       destinationIP, destinationPort, username,
       QIDNAME(qid) AS event_name,
       eventCount, category
FROM events
WHERE sourceIP = '192.168.1.105'
  AND startTime > NOW() - 24*60*60*1000
ORDER BY startTime ASC
LIMIT 1000

Step 2: Build a Custom Correlation Rule

Create a multi-condition rule detecting brute force followed by successful login:

Rule 1 — Brute Force Detection (Building Block):

Rule Type: Event
Rule Name: BB: Multiple Failed Logins from Same Source
Tests:
  - When the event(s) were detected by one or more of [Local]
  - AND when the event QID is one of [Authentication Failure (5000001)]
  - AND when at least 10 events are seen with the same Source IP
    in 5 minutes
Rule Action: Dispatch new event (Category: Authentication, QID: Custom_BruteForce)

Read the full file on GitHub · 296 lines

Files

What ships with it

2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 8d ago First seen · 296 lines · 78 tokens per session scan A e93700ad34d3

Subscribe to this mod's changes

correlating-security-events-in-qradar is a skill published in the GitHub repository Youngmaidainon/Agent-Level-Up (3 stars, last pushed 18d ago), licensed MIT. It adds 78 tokens to every session and 2,571 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). It is 100% identical to correlating-security-events-in-qradar, differing in 0 lines, and is treated as a copy.

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