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FabledGrimoire/src/grimoire/rate_limit.py
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bvandeusenandClaude Opus 5.5 753a6ccb31
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feat(6866): the proxy hop count is an admin setting, and the server shows what each count reads
An admin can save how many reverse proxies stand in front of Grimoire.
A saved count wins over TRUSTED_PROXY_HOPS, which stays the starting
value. Each worker loads it at startup (under a deadline) and re-reads
it every 30s; the worker that saves applies it at once.

GET/PUT /api/admin/proxy returns the count, where it came from, and a
readout of the admin's own request: the socket peer, the forwarding
chains, what counts 0-3 would read, and the count that reads
Cloudflare's visitor when Cloudflare's headers are present. Saves are
audit-logged. A "too many attempts" reply now says where to look when
everyone is being blocked.

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
2026-11-05 09:55:42 -05:00

36 lines
1.3 KiB
Python

"""In-process sliding-window rate limiter.
IMPORTANT — deployment note:
Rate limit counters are stored in memory and are lost on process restart.
The bucket key is the client address from grimoire/proxy.py, read by the
proxy hop count (Settings → Config). A count that is too low keys every
caller on the proxy's address, so they all share one bucket.
"""
import asyncio
import time
from collections import defaultdict
# Said beside every "too many attempts" reply, because the one case a person
# can't diagnose on their own is everybody being blocked at once: the proxy
# count is too low, so every visitor reads as the proxy and shares one bucket.
SHARED_ADDRESS_HINT = (
"If everyone is being blocked, an admin should check the reverse proxy count "
"in Settings → Config: every visitor may be reading as the proxy's address."
)
_buckets: dict[str, list[float]] = defaultdict(list)
_lock = asyncio.Lock()
async def is_rate_limited(key: str, max_requests: int, window_seconds: int) -> bool:
"""Returns True if request should be blocked (limit exceeded)."""
async with _lock:
now = time.monotonic()
cutoff = now - window_seconds
_buckets[key] = [t for t in _buckets[key] if t > cutoff]
if len(_buckets[key]) >= max_requests:
return True
_buckets[key].append(now)
return False