threat-model

Construire un modèle de menace pour une base de code cible. Trois modes : « interview » guide un propriétaire d'application à travers le cadre des quatre questions et produit un modèle de menace…

npx skills add https://github.com/anthropics/defending-code-reference-harness --skill threat-model

threat-model

A threat model answers "what could go wrong with this system, who would do it, and what should we do about it?" independently of whether any specific bug has been found yet. It is the map; vulnerability discovery is the metal detector. A good threat model tells the pipeline where to look and tells triage which findings matter.

Litmus test: If patching one line of code makes an entry disappear, it was a vulnerability, not a threat. A threat ("attacker achieves RCE via untrusted media parsing") still stands after every known bug is fixed; a vulnerability ("dr_wav.h:412 doesn't bounds-check chunk_size") does not. This skill produces threats. Vulnerabilities appear only as evidence that raises a threat's likelihood score.

Invocation: /threat-model [bootstrap-then-interview|bootstrap|interview] <target-dir> [flags]


Step 0 — Safety preamble (always runs first)

This skill performs static analysis only. It reads source, git history, and any vulnerability reports the user supplies, and writes a single output file (<target-dir>/THREAT_MODEL.md). It does not build, execute, fuzz, or modify the target, and does not make network requests against the target's infrastructure.

Before proceeding, confirm and state in your first response:

  1. The target directory exists and is a local checkout you can read.
  2. You will not execute any code from the target directory.
  3. If --vulns points at a URL or you are asked to "fetch CVEs", you will query only public advisory databases (NVD, GitHub Security Advisories, the project's own issue tracker) and never the target's live deployment.

If the user asks you to validate a threat by running an exploit, decline and point them at the vuln-pipeline (README Step 2) instead.


Step 1 — Route to a mode

Parse $ARGUMENTS:

First tokenRoute to
interviewRead interview.md in this directory and follow it.
bootstrapRead bootstrap.md in this directory and follow it.
bootstrap-then-interviewBootstrap first, then interview seeded from the draft. See below.
anything else, or emptyAsk the user: "Is someone who owns or built this system available to answer questions in this session?" Yes and the codebase is checked out → recommend bootstrap-then-interview. Yes but no codebase → interview.md. No → bootstrap.md.

All modes write the same artifact (THREAT_MODEL.md, schema in schema.md) so downstream consumers (pipeline recon/judge, verifier agents) do not need to know which mode produced it.

interviewbootstrap
NeedsAn application owner present in the sessionA local checkout; optionally past vulns
MethodFour-question framework: conversational walk through what are we working on → what can go wrong → what are we going to do about it → did we do a good jobFive stages: parallel research swarm → synthesize sections 1-3 + vuln table → generalize vulns into threat classes → STRIDE gap-fill → emit
Best forNew systems, design reviews, systems where the risk lives in business logic the code doesn't showInherited systems, third-party code, OSS dependencies, anything with a CVE history
Provenance taginterviewbootstrap

Context durability. Interview mode is multi-turn; tool results from early reads may be evicted before you need them. To stay resilient:

  • Do not read interview.md or bootstrap.md in full up front. Read the mode file (or the relevant section of it) at the point you need it, one question or stage at a time.
  • If a re-read via the Read tool is refused as "file unchanged", the prior result was evicted; reload with cat <path> via Bash instead.

Interview backbone (so you can proceed even if interview.md is unavailable mid-session):

QQuestionFills schema sections
Q1What are we working on?section 1 context, section 2 assets, section 3 entry points
Q2What can go wrong?section 4 threat rows (id, threat, actor, surface, asset)
Q3What are we going to do about it?section 4 impact/likelihood/status/controls; section 5 deprioritized; section 8 recommended mitigations
Q4Did we do a good job?validate ranking, coverage check, section 6 open questions

bootstrap-then-interview mode

When the owner is available and the codebase is checked out, this is the recommended path: the owner's time goes to refining a code-grounded draft instead of describing the system from scratch.

  1. Tell the owner: "I'll read the code first and come back with a draft (about 5-10 min), then we'll walk it together. Want that, or would you rather start cold?" Only proceed if they opt in; otherwise fall back to interview.md.
  2. Read bootstrap.md and follow it end-to-end. Write <target-dir>/THREAT_MODEL.md.
  3. Immediately continue into interview mode: read interview.md and follow it with --seed <target-dir>/THREAT_MODEL.md in effect. The section 6 open questions from bootstrap become your Q1-Q4 prompts; the owner confirms, corrects, and adds rather than starting from nothing.
  4. Overwrite <target-dir>/THREAT_MODEL.md with the refined model. Set provenance mode: bootstrap-then-interview.

The same flow is available manually: run bootstrap first, then interview --seed <THREAT_MODEL.md> in a later session.


Step 2 — Shared output contract

All modes MUST emit <target-dir>/THREAT_MODEL.md conforming to schema.md in this directory. Read schema.md immediately before you write the file, not at routing time; in interview mode the gap between routing and emit can be many turns, and an early read will be evicted before it's used.

After writing the file, print to the user:

  1. The path to THREAT_MODEL.md.
  2. The top 5 threats by likelihood × impact (id, one-line description, L×I).
  3. For bootstrap: any open questions the code could not answer (these seed a later interview pass).
  4. For interview: any owner statements that could not be verified in code (these seed follow-up code review).

References

Plus de skills de anthropic

access
anthropic
Gérer l'accès aux canaux Discord — approuver les appariements, modifier les listes d'autorisation, définir la politique de MP/groupes. Utiliser lorsque l'utilisateur demande d'appairer, d'approuver quelqu'un, de vérifier qui est autorisé,…
official
session-report
anthropic
Générer un rapport HTML explorable de l'utilisation de la session Claude Code (tokens, cache, sous-agents, compétences, prompts coûteux) à partir des transcriptions de ~/.claude/projects.
official
build-mcp-server
anthropic
Cette compétence doit être utilisée lorsque l'utilisateur demande de "construire un serveur MCP", "créer un MCP", "faire une intégration MCP", "encapsuler une API pour Claude", "exposer des outils à…
official
cookbook-audit
anthropic
Auditer un notebook du Anthropic Cookbook selon une grille d'évaluation. À utiliser lorsqu'une révision ou un audit de notebook est demandé.
official
handle-complaint
anthropic
Gère une réclamation client de bout en bout — extrait le contexte, rédige une réponse et suggère une correction opérationnelle. Accepte un email ou un ID de ticket en option…
official
use-case-triage
anthropic
Déterminer rapidement si une activité de traitement nécessite une PIA, une DPIA obligatoire au titre du RGPD, ou peut se poursuivre — détecte les conflits de politique de confidentialité et oriente vers la bonne…
official
board-minutes
anthropic
Rédige les procès-verbaux des réunions du conseil ou du comité dans votre format maison. Détecte automatiquement les réunions à venir du conseil et des comités à partir de votre calendrier, demande l'ordre du jour et…
official
renewal-tracker
anthropic
Affiche les contrats dont les échéances de résiliation approchent et prévient avant la fermeture des fenêtres de préavis, en travaillant à partir d’un registre de renouvellement tenu à jour. Utiliser lorsque l’utilisateur demande…
official