competition-request-normalization-smuggling

A CTF workflow for investigating cases where network components interpret the same request differently. Request smuggling exploits differences between proxies, gateways, and backend servers.

In plain words
What is it for?
Use it to examine conflicting headers, path decoding, transfer framing, host handling, proxy routing, and backend request interpretation.
Why use it?
It helps identify which parser or normalization step changes the request and produces the security-relevant behavior.

Skill for Claude CodeCodex

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.

agentmods
npx agentmods add skills/2233admin/reverse-skill-evolver/competition-request-normalization-smuggling
Any agent
npx skills add 2233admin/reverse-skill-evolver --skill competition-request-normalization-smuggling
Clone the repo
git clone --depth 1 https://github.com/2233admin/reverse-skill-evolver

Made for: Claude Code, Codex.

Per session 109 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 556 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin 100% copy Near-identical to another mod 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 $0.00109 $0.00556
Opus 5 $0.00055 $0.00278
Sonnet 5 $0.00022 $0.00111
Haiku 4.5 $0.00011 $0.00056

Measured 2d ago against content hash 9b9dd18133e2, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

competition-request-normalization-smuggling 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 2d 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.

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.

Origin

This is a copy

100% identical to competition-request-normalization-smuggling — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.

CTF-Sandbox-Orchestrator/competition-request-normalization-smuggling/SKILL.md · 51 lines

How it starts

The opening of the file, as written. The whole thing — 51 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Competition Request Normalization Smuggling

Use this skill only as a downstream specialization after $ctf-sandbox-orchestrator is already active and has established sandbox assumptions, node ownership, and evidence priorities. If that has not happened yet, return to $ctf-sandbox-orchestrator first.

Use this skill when request interpretation changes between proxy, middleware, and backend parser layers.

Reply in Simplified Chinese unless the user explicitly requests English.

Quick Start

  1. Map every parsing hop: client-facing proxy, gateway, app server, and downstream service.
  2. Record path normalization, header canonicalization, transfer framing, and host derivation at each hop.
  3. Capture one accepted baseline request and one differential request with minimal delta.
  4. Prove which hop interprets the request differently.
  5. Reproduce one minimal differential path that yields decisive behavior.

Workflow

1. Map Parse And Routing Boundaries

  • Record Host, forwarded headers, path decoding, slash collapsing, dot-segment handling, and case behavior.
  • Note Content-Length, Transfer-Encoding, chunk framing, and connection reuse behavior when relevant.
  • Keep edge parser and backend parser decisions side by side.

2. Prove Differential Interpretation

  • Build paired requests that differ in one canonicalization dimension only.
  • Capture proxy logs, backend logs, route match, and downstream request shape.
  • Show where route, auth scope, or body boundary diverges.

3. Reduce To Decisive Smuggling Chain

  • Compress to: crafted request -> parser differential across hops -> unintended routed request or hidden endpoint reach -> resulting effect.
  • State whether root cause is path normalization drift, header ambiguity, transfer framing differential, or host-derivation confusion.
  • If the chain becomes primarily runtime routing without framing tricks, hand off to runtime routing skill.

Read This Reference

  • Load references/request-normalization-smuggling.md for parse-differential checklist and evidence packaging.

Read the full file on GitHub · 51 lines

Files

What ships with it

2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

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. 2d ago First seen · 51 lines · 109 tokens per session scan A 9b9dd18133e2

Subscribe to this mod's changes

competition-request-normalization-smuggling is a skill published in the GitHub repository 2233admin/reverse-skill-evolver (13 stars, last pushed 22d ago), licensed MIT. It adds 109 tokens to every session and 556 once invoked, about $0.0005 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to competition-request-normalization-smuggling, differing in 0 lines, and is treated as a copy.

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