Threat-Model: Instructions file for Claude Code

AGENTS.md

Threat-Model AGENTS.md is an instructions file for Claude Code, Codex, OpenCode from suyogpawar88/Threat-Model. It costs 1,275 tokens per session, scanned A, original, MIT.

Instructions for running a security threat model, a structured review of how a service could be attacked, across application, API, and AI systems. It gathers context from project tools and produces scored threats mapped to security standards.

In plain words
What is it for?
Use it to assess services and infrastructure, create a STRIDE threat register, run the more detailed PASTA method, analyze AI or machine-learning threats, and map findings to OWASP guidance.
Why use it?
It turns system information into a documented list of attack risks, including AI-specific risks such as prompt injection and data poisoning.

Instructions file for Claude CodeCodexOpenCode

Written for Claude Code and Codex and OpenCode: Claude Code plugin machinery, but also reads ~/.codex or $CODEX_HOME. Also seen: mentions Claude Code; mentions AGENTS.md; mentions Codex.

This is suyogpawar88/Threat-Model's own configuration. It tells Claude Code, Codex and OpenCode how to work on Threat-Model itself, so it is not a mod to install elsewhere. Copy it as a starting point and replace the rules that are about this project. Everything Threat-Model configures →

Reuse

Borrowing it

Nothing to install: this file belongs to suyogpawar88/Threat-Model. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.

Copy the file
curl -O https://raw.githubusercontent.com/suyogpawar88/Threat-Model/main/AGENTS.md
Clone the repo
git clone --depth 1 https://github.com/suyogpawar88/Threat-Model

Made for: Claude Code, Codex, OpenCode.

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README.md
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<a href="https://agentmods.dev/instructions/suyogpawar88/threat-model/agents-md"><img src="https://agentmods.dev/badge/instructions/suyogpawar88/threat-model/agents-md.svg" alt="Measured on agentmods" height="20"></a>
Per session 1,275 This file is loaded in full into every session.
When invoked 1,275 The same file — it is already loaded in full.
Security scan A 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 $0.01275 $0.01275
Opus 5 $0.00638 $0.00638
Sonnet 5 $0.00255 $0.00255
Haiku 4.5 $0.00128 $0.00128

Measured 8d ago against content hash a293f2fbfd10, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-07, from the pricing page.

Security

Grade A, and why

Threat-Model AGENTS.md 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.

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.

Reads agent configuration directorieslowAgent snooping

.claude/, .codex/, .gemini/ hold keys, settings and other credentials a mod has no legitimate need for.

register them in `~/.codex/config.toml` (or a trusted project-scoped `.codex/config.toml`) using

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

AGENTS.md · 89 lines

How it starts

The opening of the file, as written. The whole thing — 89 lines — stays where its author put it; the contents beside it link to each section on GitHub.

AGENTS.md — Threat Modeling Repo

This file is read automatically by AGENTS.md-compliant coding agents (OpenAI Codex CLI, and others that follow the same convention). It's the agent-agnostic entry point into the same workflow that's packaged as a Claude Code / Cowork plugin (.claude-plugin/) and as Cursor project rules (.cursor/rules/threat-modeling.mdc) elsewhere in this repo — all three point at the same skills/threat-modeling/ instructions and scripts, so behavior is consistent regardless of which agent is driving.

What this repo does

Runs an end-to-end security threat model for a service or system — conventional application/API infrastructure and AI/ML/LLM infrastructure alike — pulling live context from Jira, Jenkins, ServiceNow, and a code repository, then producing:

  • A STRIDE threat register scored for likelihood and business impact (optionally the full 7-stage PASTA process for higher-rigor engagements)
  • AI/ML-specific threats (prompt injection, training/RAG data poisoning, model extraction, excessive agency, insecure output handling, unbounded consumption) when the system has AI/ML components
  • Every threat mapped to OWASP Top 10 (2021), OWASP API Security Top 10 (2023), and/or OWASP Top 10 for LLM Applications (2025)
  • Attack-chain mapping with MITRE ATT&CK (Enterprise) and MITRE ATLAS technique tagging
  • Compensating-controls, mitigation-assurance, and compliance-gap analysis
  • A draw.io-compatible DFD, a draw.io-compatible threat-model diagram, a Word report, and/or an Excel risk register

Before doing anything: read the skill

Read skills/threat-modeling/SKILL.md in full and follow its 9 steps in order. It is the canonical, tool-agnostic instruction set — do not shortcut to writing a threat list without walking Steps 1-3 (scoping, context pull, DFD/trust-boundary modeling) first. Its references/ directory has the full methodology detail:

Reference Covers
references/stride-methodology.md The six STRIDE categories, minimum-threats rule, Likelihood x Impact scoring
references/pasta-methodology.md Full 7-stage PASTA process for higher-rigor engagements
references/ai-threat-taxonomy.md AI/ML/LLM pipeline threats layered onto STRIDE
references/owasp-mappings.md OWASP Top 10 / API Security Top 10 / LLM Top 10 ID tables
references/mitre-mappings.md MITRE ATT&CK and ATLAS tactic/technique tagging
references/attack-chain-mapping.md How to build a valid multi-step attack chain
references/compensating-controls-and-gaps.md Compensating controls, residual risk, compliance gaps
references/report-data-schema.json The JSON shape the report-builder scripts consume
references/examples/ Worked examples: sample_* (conventional app), sample_ai_* (AI/RAG/agent system)

Read the full file on GitHub · 89 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. 8d ago First seen · 89 lines · 1,275 tokens per session scan A a293f2fbfd10

Subscribe to this mod's changes

Threat-Model AGENTS.md is an instructions file published in the GitHub repository suyogpawar88/Threat-Model (6 stars, last pushed 1mo ago), licensed MIT. It adds 1,275 tokens to every session, about $0.0064 per session on Opus 5. A static security scan graded it A with 1 finding (reads agent configuration directories). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.

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