// the instrument
Mapping an app by hand takes hours, and it starts over on every engagement: which hosts, pages and endpoints exist, which page calls what, what the JavaScript names but you never reached, what each role can see. proxy2model does that bookkeeping from the traffic you already capture, so the time goes to testing. It does not scan or attack, and it never calls anything a vulnerability. It tells you what is there, which request proves it, and what the capture could not show.
// field test — the bundled capture
Four OWASP Juice Shop sessions (417 requests as anonymous, user, accounting and admin), modelled in about two seconds on a laptop:
- 001 · The API, mapped — 104 endpoints, and the observed API as OpenAPI 3.0: 68 paths, 88 operations, ready for Postman, ZAP or a fuzzer.
- 002 · Named, never called — 16 endpoints the app's JavaScript names but the browsing never reached:
/rest/admin,/rest/chat,/rest/track-order,/api/SecurityAnswers... - 003 · Anonymous got 200 from admin-looking endpoints, cited to the request:
$ proxy2model cross-role juiceshop --low anon --high user 'anon' reached privileged-looking endpoints (2) GET /rest/admin/application-configuration ev_93 anon=[200] user=[200] unknown: whether the low-role response was authorised or a leak · next: compare 'anon' and 'user' response bodies
Every line cites the request behind it (ev_93), and every lead says what is still unknown and the
next safe check. Reproduce it:
for r in anon user accountant admin; do proxy2model samples/juiceshop-$r.xml -w juiceshop --role $r; done
// intake
| Traffic from | Command |
|---|---|
| Burp (Save items XML), Logger++ CSV, Caido (JSON or CSV), or a HAR (browser, ZAP, mitmproxy) | proxy2model FILE -w app |
| A browser it opens and records while you use the app | proxy2model browse |
| A crawl of a running app | proxy2model crawl URL -w app --yes |
Every value is masked as it is read. One model comes out: a report, a SQLite graph you can query, OpenAPI, and a compact package for an AI. Runs locally.
pip install proxy2model
proxy2model history.xml -w shop # build from an export
proxy2model browse # or open a browser and use the app (asks for URL, scope, mode)
proxy2model query shop help # ask the model; answers cite requests, no AI involved
proxy2model mcp --out "$PWD/proxy2model-out" # or let an AI agent ask (see Using it with an AI)
./demo.sh builds the bundled sample. proxy2model on its own lists the everyday commands;
proxy2model <command> --help explains each.
// what comes out
proxy2model-out/shop/
├── report.html interactive report: overview, what to check, endpoints, map, every request, query console
├── model.json the model, and the request behind every claim
├── openapi.json the observed API, OpenAPI 3.0
├── context.json what to hand an AI instead of raw traffic
├── graph.db SQLite graph, queried with `proxy2model q`
├── exports/ graph.json · graph.graphml · build.svg
└── inputs/ masked records of every capture, merged on rebuild
// boundaries
| It does | It never |
|---|---|
| Read traffic you captured | Upload, forward or replay it |
| Mask every value before the first write | Store a token, cookie, key or PII value |
| Say what it could not observe | Claim coverage it did not have |
| Offer hypotheses and the evidence to test them | Call anything a vulnerability |
A plain build is offline. crawl, browse --active and osint send requests of their own: use
them only on systems you are authorized to test. CI plants fake secrets in the samples and fails if
one reaches any output.
// field manual
- 01 · Capturing traffic — Burp, Caido, HAR,
browse, roles. - 02 · Crawling a running app —
crawland scripted journeys. - 03 · How it works — what is in the model and how it is built.
- 04 · Querying the model —
query, BQL, graph reach, diffs between builds. - 05 · Using it with an AI —
context.jsonand the MCP server. - Skill — the same method as a playbook for an AI, nothing to install.
fa1c0n@recon ~ $ captured traffic in · a model of the app out · every line cited
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