Threat Modeling

Threat Modeling is a skill for Claude Code from robisson/build-like-amazon-agent-skills. It costs 40 tokens per session (3,880 once invoked), scanned B, original, MIT.

A design-stage security review that identifies how a system could be attacked and how to reduce those risks. It covers data, access permissions, encryption, trust boundaries, and the potential spread of a breach.

In plain words
What is it for?
Use it when designing services, handling customer data or credentials, changing login permissions, exposing APIs, connecting third-party services, or changing service-to-service access.
Why use it?
It finds weaknesses in the system's design before code is written. This complements penetration testing, which looks for security problems in an implemented system.

Skill for Claude Code

Written for Claude Code: shipped in a Claude Code plugin.

Part of the build-like-amazon plugin — 28 skills, 14 commands shipped together

Good fit Use it when designing services, handling customer data or credentials, changing login permissions, exposing APIs, connecting third-party services, or changing service-to-service access.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/robisson/build-like-amazon-agent-skills/threat-modeling
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 robisson/build-like-amazon-agent-skills --skill threat-modeling
Clone the repo
git clone --depth 1 https://github.com/robisson/build-like-amazon-agent-skills

Made for: Claude Code.

Or install build-like-amazon, the plugin that ships this one along with the rest of its 28 skills, 14 commands.

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 Threat Modeling

README.md
[![agentmods](https://agentmods.dev/badge/skills/robisson/build-like-amazon-agent-skills/threat-modeling/github.svg)](https://agentmods.dev/skills/robisson/build-like-amazon-agent-skills/threat-modeling)
Your own site
<a href="https://agentmods.dev/skills/robisson/build-like-amazon-agent-skills/threat-modeling"><img src="https://agentmods.dev/badge/skills/robisson/build-like-amazon-agent-skills/threat-modeling/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 Threat Modeling

Your own site · 80×15
<a href="https://agentmods.dev/skills/robisson/build-like-amazon-agent-skills/threat-modeling"><img src="https://agentmods.dev/badge/skills/robisson/build-like-amazon-agent-skills/threat-modeling.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 40 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 3,880 The whole file, excluding the scripts and references it only reads on demand.
Security scan B 1 finding. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found 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 $0.00040 $0.03880
Opus 5 $0.00020 $0.01940
Sonnet 5 $0.00008 $0.00776
Haiku 4.5 $0.00004 $0.00388

Measured 10d ago against content hash ffe80e776e29, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-09, from the pricing page.

Security

Grade B, and why

Threat Modeling scanned grade B 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 10d ago.

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.

Cloud metadata endpointmediumServer-side request forgery

One request to 169.254.169.254 can return temporary IAM credentials.

| Instance metadata accessible | SSRF → credential theft via 169.254.169.254 | IMDSv2 (require token); restrict network access to metadata |

Downgraded: this mod is about security review, or the phrase is quoted, so it is likely naming the pattern rather than instructing it.

skills/threat-modeling/SKILL.md · 276 lines

How it starts

The opening of the file, as written. The whole thing — 276 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Threat Modeling

Overview

Threat modeling is the systematic identification of security threats to a system BEFORE the system is built. It answers four questions: What are we building? What can go wrong? What are we going to do about it? Did we do a good enough job? You cannot secure a system by adding security after the fact—security must be designed in. Threat modeling is how you design it in.

A threat model is not a penetration test. Penetration testing finds bugs in implementation. Threat modeling finds flaws in design. A perfectly implemented system with a flawed design is still insecure. You do threat modeling at design time; you do pen testing at implementation time. Both are required; neither replaces the other.

When to Use

  • During the design phase of any new service or feature
  • When adding new data flows (especially customer data or credentials)
  • When changing authentication or authorization mechanisms
  • When adding new external-facing endpoints (API, web, mobile)
  • When integrating with a new third-party service
  • When changing trust boundaries (new service-to-service communication)
  • When an incident reveals a class of vulnerability (model similar systems)
  • Before any Design Bar Raiser review for systems handling sensitive data

Agent Persona

Load agents/security-guardian.md when reviewing the threat model. Use it to challenge trust boundaries, data classification, least privilege, encryption, blast radius, and missing abuse cases.

Amazon Context

Threat models are living documents maintained alongside design documents. They are updated when the system changes, when new threat intelligence emerges, or when incidents reveal gaps. Every system that handles customer data, credentials, or payment information requires a formal threat model reviewed by security teams before launch.

The principle of "blast radius minimization" is paramount: design systems so that a compromise of one component cannot cascade to compromise the entire system. This drives decisions about service boundaries, IAM scope, encryption key separation, and network isolation.

Read the full file on GitHub · 276 lines

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. 10d ago First seen · 276 lines · 40 tokens per session scan B ffe80e776e29

Subscribe to this mod's changes

Threat Modeling is a skill published in the GitHub repository robisson/build-like-amazon-agent-skills (15 stars, last pushed 3mo ago), licensed MIT. It adds 40 tokens to every session and 3,880 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it B with 1 finding (cloud metadata endpoint). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

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