race

Race / TOCTOU playbook

Confirm the target is in scope for stress-style testing (multiple parallel requests can look like abuse). Then identify the candidate operation.

Execution rule: capture a real request for the operation and replay that request with concrete cookies/body values. Never write literal placeholders such as <sess> to files; ask once if a session or replayable request is missing.

Targets worth racing

• Redeem a gift card / promo code (does the second redeem succeed?)
• Cast a vote / claim a one-per-user reward
• Withdraw / transfer balance (does it deduct twice?)
• Submit a 2FA code (can N parallel guesses each be checked against an unused-attempts counter?)
• Apply a discount that's supposed to be once-per-cart
• Send a friend / invite request (creates duplicate rows / privileges)
• Confirm an email (mark verified twice with different addresses)
• Upload then read a file (write safe.png, then race a swap to evil.svg before AV scans)

1. Burp-style "single packet attack" (last-byte sync) — preferred

Modern servers buffer HTTP/2 frames. The classic trick: send N requests where each is fully serialized except the last byte. Then in a single TCP write, flush the final byte of all N. The server receives them effectively simultaneously and dispatches them in parallel — bypassing nearly all software-side rate limiting.

You can do this with a small Go/Python script. Skeleton (Python, HTTP/2):

import asyncio, ssl
import httpx

async def main():
    transport = httpx.AsyncHTTPTransport(http2=True)
    async with httpx.AsyncClient(transport=transport, verify=False) as c:
        # Build N partial requests, then race the last byte.
        # In practice: use turbo-intruder or a Go h2 client for byte-level control.
        ...
asyncio.run(main())

For the highest-fidelity version, use Burp Suite's Turbo Intruder (race-single-packet-attack.py template) — it's the de facto tool. The shell tool can run it if installed.

2. Fallback: HTTP/1.1 pipelined burst

If HTTP/2 isn't available, fire N requests over a single keep-alive connection back-to-back without waiting for responses:

# 50 parallel uses of the same coupon code
seq 50 | xargs -P 50 -I{} curl -s -X POST https://target/redeem \
  -H 'Cookie: session=<sess>' \
  -d 'code=GIFT100'

Less reliable than single-packet but often enough.

3. Confirm a race actually happened

For each candidate operation, measure the invariant twice:

• Before: query balance / count / state.
• Fire N parallel requests.
• After: query balance / count / state.

If invariant differs by more than 1× the per-request delta, you have a race. Example: gift card worth $50, used 5× before lockout → $250 credit. Confirmed.

4. TOCTOU on file/auth flows

Time-Of-Check / Time-Of-Use bugs:

• Upload + scan + serve: race the swap between AV scan and final write.
• "Is admin?" check on session, then long-running task that uses the role: race a logout/role-change between the check and the use.
• Symlink race on file-write tools that write through user-supplied paths.

5. Mitigation patterns (so you know what defeats you)

If you see any of these, the race probably isn't winnable — refocus:

• SELECT ... FOR UPDATE / explicit row lock.
• Optimistic concurrency: every update carries a version field that's CAS'd.
• Idempotency keys on the request: server stores the key+result and replays.
• UNIQUE (user_id, code_id) constraint with ON CONFLICT DO NOTHING.

Reporting

Required for a credible finding:

• The exact race window measured (N=50, mean=20ms apart).
• Before / after invariant query results.
• Concrete impact: "$X credit overspent" / "Y duplicate privileged rows created" / "Z brute-force guesses processed before lockout".

A race with no measurable impact (e.g., creates a second pending order that the next cron job dedupes) is info at best.