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hunt-exceptional-conditions

Test APIs and forms with unexpected input to uncover error responses that expose internal details. The skill checks response bodies for stack traces, server paths, and library information, preserving specific evidence rather than treating every server error as a vulnerability.

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Hunt mishandling of exceptional conditions — feed an endpoint malformed/unexpected input (wrong type, broken JSON, oversized field, null byte) and make it fail OPEN or leak internals: a verbose stack-trace / framework error page that discloses ORM internals, server file paths, library versions, or a language traceback. Use on any input-accepting endpoint (JSON APIs, forms, query params). Medium-High when the leak exposes internal structure that arms a deeper attack.

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适用场景

  • Checking JSON API error handling
  • Testing form and query parameter boundaries
  • Identifying internal details in error responses
  • Recording evidence from disclosed stack traces

包含的文件(1)

  • SKILL.md3.1 KB

SKILL.md(原文)

安装前可以查看交给 AI 代理的指令内容。

HUNT-EXCEPTIONAL-CONDITIONS — Verbose Errors / Fail-Open (A10:2025)

What actually pays

Well-built apps catch errors and return a clean, generic message. A broken app, when handed input it didn't expect, throws an unhandled exception and renders a developer error page straight to the client — leaking the stack trace, the ORM/query internals, server-side file paths, and framework/library versions. That disclosure is the finding (and it arms SQLi/RCE/path attacks next).

Recon

Any endpoint that parses input is a candidate; the richest are:

JSON APIs that expect typed fields:  POST /api/* with {numbers, ids, enums}
Endpoints with numeric/id path or query params:  /item/{id}, ?page=, ?quantity=
Search / filter / sort params
File or content-type sensitive uploads

Attack — send what the code didn't anticipate

Take a known-good request and break ONE assumption at a time:

  • Wrong type: a field the app expects to be a number/string is sent as an array or object — {"rating":"x","comment":[1,2,3]}, {"quantity":{}}.
  • Malformed body: truncated/!invalid JSON, an unterminated string, a stray brace, a wrong/missing Content-Type.
  • Boundary/oversized: a very long string, a huge/negative/overflow number.
  • Null byte / control chars embedded in a value.
POST /api/Feedbacks   {"rating":"notanumber","comment":[1,2,3]}
GET  /item/' OR /item/%00   (also exercises the error path)

Watch the RESPONSE BODY, not just the status: a 500 (or even a 200/400) whose body contains a stack trace or framework error page is the signal.

What counts as a leak (the success signal)

A finding is confirmed when the response body contains a cross-framework error-disclosure signature:

  • Node/Express + Sequelize: SequelizeDatabaseError, node_modules/sequelize, a JS stack with internal paths.
  • PHP: <b>Warning</b> ... /var/www/.../file.php on line N.
  • Python: Traceback (most recent call last), werkzeug.exceptions.
  • Java: at com.app.Foo(Foo.java:42) stack frames.
  • .NET: Server Error in '/' Application, a [System.XxxException: ...] YSOD.

A clean JSON error ({"error":"Invalid input"}) with no internals is NOT a finding — that's correct handling. Disclosure of internal structure is.

Validation discipline

  • Capture the exact leaked artifact (path, ORM class, version, stack frame) — that's the evidence. "It returned 500" alone is not disclosure.
  • Note what the leak enables next (e.g. a disclosed SQL error → hunt-sqli; a disclosed absolute path → hunt-lfi).

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