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competition-race-condition-state-drift

Reproduce timing and ordering bugs in a CTF sandbox using controlled concurrent requests. Compare normal and racing runs, trace reads and writes, and preserve a minimal sequence that demonstrates duplicate actions or inconsistent state.

中文简介正在准备中。当前显示英语简介。

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Internal downstream skill for ctf-sandbox-orchestrator. CTF-sandbox workflow for race windows, ordering bugs, idempotency failures, lock gaps, concurrent worker drift, and state inconsistencies that produce decisive effects. Use when the user asks to reproduce timing-sensitive bugs, concurrent state corruption, duplicate actions, stale reads, or privilege or balance drift caused by request ordering. Use only after `$ctf-sandbox-orchestrator` has already established sandbox assumptions and routed here.

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适用场景

  • Reproduce bugs triggered by simultaneous requests
  • Investigate duplicate actions and ineffective duplicate prevention
  • Trace stale reads and gaps in locking
  • Demonstrate privilege or balance changes caused by request order

包含的文件(3)

  • SKILL.md2.7 KB
  • agents/openai.yaml375 B
  • references/race-condition-state-drift.md944 B

SKILL.md(原文)

安装前可以查看交给 AI 代理的指令内容。

Competition Race Condition State Drift

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 the decisive behavior depends on request timing, async ordering, lock gaps, or stale state.

Reply in Simplified Chinese unless the user explicitly requests English.

Quick Start

  1. Identify mutable state first: rows, cache keys, queue payloads, session fields, counters, or files.
  2. Reproduce with smallest concurrent sequence and fixed timing assumptions.
  3. Capture one baseline run and one racing run with only one variable changed.
  4. Track read, check, write, enqueue, and commit boundaries separately.
  5. Prove final state drift from a clean reset.

Workflow

1. Map Mutable Boundaries

  • Record transaction scope, lock behavior, retry logic, idempotency keys, cache invalidation, and queue handoff.
  • Note where read-check-write is split across requests, workers, or services.
  • Keep each boundary tied to exact timestamps or sequence numbers.

2. Reproduce Timing Window

  • Build deterministic concurrent inputs with controlled delay, duplicate requests, or reordered worker execution.
  • Compare accepted and rejected paths under identical payloads.
  • Record which condition flips when ordering changes.

3. Reduce To Decisive Race Chain

  • Compress to: request A and B ordering -> stale check or lock gap -> conflicting writes -> resulting capability or artifact.
  • State whether root cause is missing lock, weak idempotency, stale cache read, delayed async commit, or retry side effect.
  • If the path becomes queue-dominant, hand off to queue worker drift skill.

Read This Reference

  • Load references/race-condition-state-drift.md for race harness ideas, evidence blocks, and parity checks.

What To Preserve

  • Mutable keys, transaction boundaries, lock behavior, and idempotency markers
  • Timestamped or sequenced traces for baseline and race runs
  • One minimal replayable concurrent sequence proving drift

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