STRIDE GPT is an AI threat-modeling tool that analyzes an application and generates threat models and attack trees using the STRIDE security methodology. Security practitioners use it through a command-line interface, interactive terminal, or web interface to assess applications, codebases, generative-AI systems, and agentic-AI systems.
Borrowing it
Nothing to install: this file belongs to mrwadams/stride-gpt. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/mrwadams/stride-gpt/master/AGENTS.mdgit clone --depth 1 https://github.com/mrwadams/stride-gptWrote 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.
[](https://agentmods.dev/instructions/mrwadams/stride-gpt/agents-md)<a href="https://agentmods.dev/instructions/mrwadams/stride-gpt/agents-md"><img src="https://agentmods.dev/badge/instructions/mrwadams/stride-gpt/agents-md/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.
<a href="https://agentmods.dev/instructions/mrwadams/stride-gpt/agents-md"><img src="https://agentmods.dev/badge/instructions/mrwadams/stride-gpt/agents-md.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.04428 | $0.04428 |
| Opus 5.5 | $0.01771 | $0.01771 |
| Sonnet 5.5 | $0.00886 | $0.00886 |
| Haiku 4.5 | $0.00443 | $0.00443 |
Grade A, and why
stride-gpt AGENTS.md scanned grade A with 0 findings 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 today.
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.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 188 lines — stays where its author put it; the contents beside it link to each section on GitHub.
AGENTS.md
Orientation for agents (and humans) working in this codebase. Skim the whole file before starting; jump to "Progressive disclosure pattern" if you're looking to reuse that specific idea.
What this project is
STRIDE-GPT is an AI-powered threat modelling tool that produces STRIDE reports for software systems. It ships as two separate products with a shared library between them:
- CLI (
stride_gpt/) — the primary product. Includes an agentic analysis engine that explores a real codebase via filesystem tools and produces a per-subsystem STRIDE report. - Streamlit web UI (
apps/web/) — a hosted single-shot threat modeller. Takes a text description (or a GitHub URL) and produces a one-shot report. Does not use the agentic engine, by design — filesystem/agentic features don't fit Streamlit Community Cloud-style deployments.
Both surfaces share stride_gpt/core/ for prompts, schemas, and the LLM abstraction.
Repository layout
stride_gpt/ # CLI package + shared library
├── cli.py # Typer commands + interactive REPL
├── prompt.py # prompt_toolkit completer (slash commands)
├── config.py # ~/.stride-gpt/config.json + provider registry
├── models.py # model catalogue (id, default tokens, thinking support)
├── agent/ # agentic loop (CLI-only by design)
│ ├── loop.py # run_analysis, per-subsystem agent loop
│ ├── planner.py # phase 1 — classify app type, propose subsystems
│ ├── context.py # context window management + compression
│ ├── tools.py # filesystem tools (read_file, grep, ..., list_references, load_reference)
│ ├── progress.py # Rich-based progress callbacks
│ └── report.py # markdown / JSON / SARIF rendering, save/load
└── core/ # shared between CLI and web
├── llm.py # unified call_llm / call_llm_with_tools via litellm
├── schemas.py # LLMConfig, AnalysisPlan, AnalysisReport, etc.
├── prompts/
│ ├── builder.py # legacy single-shot prompt builder (web UI uses this)
│ ├── variants.py # base_system_prompt(), list_references(), load_reference(), coerce_app_type()
│ └── threat_model/ # packaged reference cards (see "Progressive disclosure")
│ ├── base.md
│ ├── quick_base.md
│ ├── genai.md
│ ├── agentic.md
│ ├── insider_threat.md
│ ├── mitre_enterprise.md
│ └── mitre_atlas.md
└── ... # attack_tree, dread, mitigations, test_cases, threat_model
apps/web/ # Streamlit UI (separate product)
└── ... # imports from stride_gpt.core, NOT stride_gpt.agent
tests/ # pytest, fixtures in conftest.py
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.
- today Changed · +78 tokens per session e43031af24db
- 1mo ago Changed · +69 tokens per session 320841b93b87
- 1mo ago Changed · +1 lines · +159 tokens per session 7fe59ecccca2
- 1mo ago First seen · 187 lines · 4,122 tokens per session scan A a1acc50344c1
stride-gpt AGENTS.md is an instructions file published in the GitHub repository mrwadams/stride-gpt (1,144 stars, last pushed today), licensed MIT. It adds 4,428 tokens to every session, about $0.0177 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other instructions, from other repositories
vscode buildNext.instructions.md
Working notes and architecture documentation for the new esbuild-based build system in build/next. Use when making changes to the new build pipeline (transpile/bundle commands, NLS plugin, source-map handling, resource copying, or self-hosting watch tasks).
next.js AGENTS.md
AGENTS.md instructions for vercel/next.js, covering next.js development guide, codebase structure, monorepo overview, core package: packages/next and other important packages.
vscode oss-third-party-notices.instructions.md
Instructions for microsoft/vscode, covering vs code oss third-party-notices pipeline, architecture, pipeline flow in ci, cache eligibility and rollout and applying the notice (cutover).
langchain AGENTS.md
AGENTS.md instructions for langchain-ai/langchain, covering global development guidelines for the langchain monorepo, corridor security analysis, project architecture and context, monorepo structure and development tools & commands.
vscode copilot-instructions.md
Copilot instructions for microsoft/vscode, covering vs code copilot instructions, project overview, root folders, core architecture (src/ folder) and built-in extensions (extensions/ folder).
deno copilot-instructions.md
Copilot instructions for denoland/deno, covering deno development guide for github copilot, network access, high level overview, key directories and key files to understand first.