executing-red-team-exercise
by mukul975executing-red-team-exercise is a cybersecurity skill for planning and tracking realistic red team exercises. It supports adversary emulation across reconnaissance, technique selection, execution, and detection-gap review, making it useful for Security Audit work and ATT&CK-aligned assessments.
This skill scores 78/100 and is worth listing: it has a clear red-team trigger, a substantial workflow body, and a supporting Python script/API reference that together give agents enough structure to plan an authorized exercise with less guesswork than a generic prompt. For directory users, that means it is a solid install candidate for red-team planning and technique tracking, though not a turnkey offensive runbook.
- Explicit trigger and scope for red-team exercise, adversary emulation, and full-scope offensive security assessment.
- Substantial operational content: 8 H2 sections, 10 H3 sections, code fences, and a script that plans operations and tracks ATT&CK techniques.
- Helpful support files: Python CLI usage, API reference, and MITRE ATT&CK-based technique mapping for concrete agent leverage.
- Repository evidence shows planning/tracking support more than end-to-end execution automation; users expecting a fully orchestrated red-team workflow may need to fill gaps.
- The script depends on downloading MITRE ATT&CK data and only references authorized lab/CTF use, so adoption requires a controlled environment and validation of permissions.
Overview of executing-red-team-exercise skill
What this skill does
executing-red-team-exercise is a cybersecurity skill for planning and tracking a realistic red team exercise. It helps you emulate an adversary across reconnaissance, technique selection, execution, and detection-gap review, rather than just listing vulnerabilities. If you need the executing-red-team-exercise skill for Security Audit work, this is the right fit when the goal is to test whether defenders can spot and respond to an attack path.
Who should use it
Best for security engineers, red teamers, SOC leads, and audit teams that already have authorization to run offensive testing. It is especially useful when you need an ATT&CK-aligned plan, a controlled operation outline, or a way to compare executed techniques against detection coverage.
What makes it different
The skill is built around adversary emulation, not generic pentest checklists. Its supporting script pulls MITRE ATT&CK Enterprise data, maps techniques to a chosen actor, and tracks execution status and detection outcomes. That makes it more decision-useful than a prompt that only asks for “red team ideas.”
How to Use executing-red-team-exercise skill
Install and first-read path
Use the executing-red-team-exercise install flow with your skills manager, then read these files first:
skills/executing-red-team-exercise/SKILL.mdreferences/api-reference.mdscripts/agent.py
Those three files tell you the intended workflow, the data model, and the runtime assumptions. If you only skim one file, start with SKILL.md; if you plan to run the helper, inspect scripts/agent.py before trusting the output shape.
Give the skill a complete mission brief
The executing-red-team-exercise usage pattern works best when you specify:
- the emulated actor or threat profile
- the target environment or org name
- the objective chain
- constraints such as lab-only, time window, or detection focus
- the output format you want
Stronger input:
Plan a red team exercise for a retail org, emulating APT29, with objectives to access POS data and assess SOC detection of lateral movement. Return an ATT&CK-aligned plan and detection gaps.
Weaker input:
Write a red team plan.
Practical workflow and repo reading order
A good executing-red-team-exercise guide is to treat the skill as a planning layer, then validate it against the repository’s helper logic:
- confirm the actor-target-objective trio
- map techniques to ATT&CK terms
- record what is planned vs. executed vs. detected
- review missed techniques after the exercise
The helper script’s CLI example shows the intended structure:
python scripts/agent.py --actor "APT29" --target "Retail Corp" --objectives "Access POS data" "Exfiltrate cardholder data" --output redteam_plan.json
What improves output quality most
Use exact actor names when possible, and define objectives as measurable end states. “Test detection” is too vague; “detect credential theft, privilege escalation, and exfiltration attempts” is better. If you need the skill for Security Audit reporting, ask for a plan plus a detection-gap summary, not just a narrative exercise.
executing-red-team-exercise skill FAQ
Is this only for mature security teams?
No, but it is most useful when there is already a defensive program to test. If your environment cannot support logging, monitoring, or response validation, the skill may produce a plan that is hard to execute meaningfully.
How is it different from a normal prompt?
A normal prompt usually stops at ideas. The executing-red-team-exercise skill is more operational: it aligns techniques to ATT&CK, supports actor emulation, and helps you track whether techniques were detected. That makes it better for repeatable assessments.
Do I need to run the Python script?
Not always. You can use the skill for planning only, but the repository includes scripts/agent.py if you want a structured operation object, ATT&CK technique loading, and a detection-gap report. If you skip the script, you should still mirror its fields in your prompt.
Is it beginner-friendly?
It is beginner-friendly only if you already understand basic red team and authorization concepts. It is not a safe “learn hacking” starter skill; it assumes lawful, approved testing and works best in lab, CTF, or authorized enterprise contexts.
How to Improve executing-red-team-exercise skill
Feed the model the right constraints
The biggest quality jump comes from defining scope clearly: target type, actor, objective, and success criteria. For executing-red-team-exercise, add operational boundaries such as “no destructive actions,” “report only,” or “validate email security and endpoint detection.” That prevents the skill from drifting into generic offensive brainstorming.
Ask for ATT&CK-aligned outputs
If you want a stronger executing-red-team-exercise result, request technique IDs, tactics, and detection notes explicitly. For example: “Return tactics, ATT&CK technique IDs, likely defender telemetry, and a gap summary.” This produces a more useful Security Audit artifact than a plain prose exercise plan.
Watch for common failure modes
The most common miss is overbroad objectives. Another is actor mismatch: choosing a threat actor whose TTPs do not fit the target or assessment goal. A third is treating “stealth” as the only objective; for audit work, the real value is in observable defensive signals and missed detections.
Iterate after the first output
Use the first plan as a draft, then refine it by adding what was missing: environment assumptions, allowed tooling, detection sources, and reporting requirements. If you are using the script, compare planned techniques against what was actually executed and mark detected techniques before asking for a revised detection-gap report.