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threat-model-discipline

Use when starting an engagement, before exploitation, or whenever the attack surface changes — build/validate the threat model and detect drift (new unreviewed surface) before advancing

Install / Use

npx skills add hypnguyen1209/offensive-claude --skill threat-model-discipline

Installs into whichever agent you are using.

About this skill
📄

SKILL.md

Installable skill definition

Quality Score

83/100

Category

Security

Supported Platforms

Universal

Our assessment of threat-model-discipline

threat-model-discipline scores 83/100 on our quality scale, 924th of 1,096 Security skills we index.

Its SKILL.md is 2.6 KB long, well organised into 9 sections with 1 code example: a solid amount of guidance for an agent.

It has 377 GitHub stars, a meaningful sign that others use it.

Substance
26/30
Structure
17/20
Description
15/15
Adoption
11/20
Freshness
15/15

Maintenance, license and trust

  • The repository was last updated 14 days ago, so threat-model-discipline is actively maintained.
  • It is released under the MIT license, a permissive license that allows use, modification and commercial use with attribution.
  • Its trust signals score 100/100, with no cautions. These come from repository metadata, not a code audit — read the skill file before letting an agent act on it.

Safety scan

No issues found

Our scan of the whole file found no instruction hijacking, hidden characters, credential access, data exfiltration or destructive commands.

Automated pattern scan on 2026-10-05. It catches known dangerous patterns, not every risk — read a skill before letting an agent act on it.

threat-model-discipline compared with similar skills

All 4 of these similar skills score higher than threat-model-discipline; compare them before choosing.

SkillScoreStarsUpdatedFormat
threat-model-discipline (this skill)by hypnguyen12098337714d agoSKILL.md
algorithmic-artby anthropics100177.9k12d agoSKILL.md
pptxby anthropics100177.9k12d agoSKILL.md
designby nextlevelbuilder100130.2k13d agoSKILL.md
ui-ux-pro-maxby nextlevelbuilder100130.2k13d agoSKILL.md

Frequently asked questions

How do I install threat-model-discipline?
Run npx skills add hypnguyen1209/offensive-claude --skill threat-model-discipline. The install tabs above show the steps for each supported agent.
Which AI agents does threat-model-discipline work with?
It is written for Universal, as a SKILL.md file. Other agents that read the same format can often use it too.
Is threat-model-discipline safe to use?
Our scan of the whole file found no instruction hijacking, hidden characters, credential access, data exfiltration or destructive commands. It is MIT-licensed and scores 100/100 on trust signals. Skills are instructions an agent will follow, so read the file before installing it and do not approve commands you do not understand.
Is threat-model-discipline still maintained?
The repository was last updated 14 days ago, so threat-model-discipline is actively maintained.

name: threat-model-discipline description: Use when starting an engagement, before exploitation, or whenever the attack surface changes — build/validate the threat model and detect drift (new unreviewed surface) before advancing scripts:

  • scripts/threatmodel_lint.py

Threat-Model Discipline

Overview

You cannot test what you have not modeled. A threat model names the assets, entry points, trust boundaries, relevant ATT&CK techniques, and existing mitigations — so coverage is deliberate, not accidental. On a long engagement the surface drifts (a new endpoint, a new dependency); un-reviewed drift is where bugs hide. This skill keeps the model complete and re-checks it for drift.

When to Activate

  • At engagement start (after recon-osint), before weaponize/exploit.
  • Whenever recon is re-run or the target changes — to catch new attack surface.
  • At /engage.gate — the gate refuses to advance on un-acknowledged drift.

The model (JSON, materialized from recon)

threat-model.json (see templates/threat-model/): five required lists — assets, entry_points, trust_boundaries, attck (technique ids), mitigations.

# 1. Lint - every required field present, no placeholders, valid ATT&CK ids
python skills/threat-model-discipline/scripts/threatmodel_lint.py lint .engage/recon/threat-model.json

# 2. Drift - diff a re-run against the reviewed baseline; NEW entry points/assets/boundaries are
#    unreviewed surface and BLOCK the gate until re-reviewed or acknowledged
python skills/threat-model-discipline/scripts/threatmodel_lint.py drift \
    .engage/recon/threat-model.baseline.json .engage/recon/threat-model.json

Or use /engage.threatmodel (materialize | lint | drift).

Red Flags — STOP

  • "We'll model it as we go" — unmodeled surface = untested surface. Model first.
  • "Recon changed but the threat model didn't" — re-run drift; new surface must be re-reviewed.
  • A threat model full of TBD/[fill in] — that is not a model; the lint fails it.
  • A new entry_point appeared and you proceeded anyway — that is the exact gap attackers use.

Rationalizations

| Excuse | Reality | |--------|---------| | "The model is obvious, skip it" | Obvious to you ≠ documented. Coverage you can't diff is coverage you can't trust. | | "Drift is just noise" | A new entry point is new attack surface. Acknowledge it explicitly or re-review. | | "ATT&CK mapping is busywork" | It turns 'we tested stuff' into 'we covered these techniques' — the report's backbone. |

Pairs with scope-discipline (what you may touch) and finding-discipline (what counts as proven).

Related Skills

View on GitHub
GitHub Stars377
CategorySecurity
Updated14d ago
Forks65

Languages

Python

Trust signals

100/100

From repository metadata: license, adoption, age and documentation. Not a code audit — see the Safety scan above for what the skill file itself contains.

No cautions