mirror of
https://github.com/zulip/zulip.git
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bc1ed82620
Fixes #21544. The network prefix (e.g. 64) identifies the network portion which determines which bucket should that IPv6 belong to. Implemented as a generic approach, so we have the option to use different prefix sizes (leading to different buckets) in the future. Add comprehensive assertions for which IPv6s are expected to belong to the same bucket and which are not.
650 lines
23 KiB
Python
650 lines
23 KiB
Python
import logging
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import time
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from abc import ABC, abstractmethod
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from ipaddress import IPv6Network, ip_network
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from typing import Optional, cast
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import orjson
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import redis
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from circuitbreaker import CircuitBreakerError, circuit
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from django.conf import settings
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from django.http import HttpRequest
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from typing_extensions import override
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from zerver.lib import redis_utils
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from zerver.lib.cache import cache_with_key
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from zerver.lib.exceptions import RateLimitedError
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from zerver.lib.redis_utils import get_redis_client
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from zerver.models import UserProfile
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# Implement a rate-limiting scheme inspired by the one described here, but heavily modified
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# https://www.domaintools.com/resources/blog/rate-limiting-with-redis
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client = get_redis_client()
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rules: dict[str, list[tuple[int, int]]] = settings.RATE_LIMITING_RULES
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logger = logging.getLogger(__name__)
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class RateLimiterLockingError(Exception):
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pass
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class RateLimitedObject(ABC):
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def __init__(self, backend: Optional["type[RateLimiterBackend]"] = None) -> None:
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if backend is not None:
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self.backend: type[RateLimiterBackend] = backend
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else:
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self.backend = RedisRateLimiterBackend
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def rate_limit(self) -> tuple[bool, float]:
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# Returns (ratelimited, secs_to_freedom)
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return self.backend.rate_limit_entity(
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self.key(), self.get_rules(), self.max_api_calls(), self.max_api_window()
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)
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def rate_limit_request(self, request: HttpRequest) -> None:
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from zerver.lib.request import RequestNotes
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ratelimited, time = self.rate_limit()
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request_notes = RequestNotes.get_notes(request)
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request_notes.ratelimits_applied.append(
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RateLimitResult(
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entity=self,
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secs_to_freedom=time,
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remaining=0,
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over_limit=ratelimited,
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)
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)
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# Abort this request if the user is over their rate limits
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if ratelimited:
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# Pass information about what kind of entity got limited in the exception:
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raise RateLimitedError(time)
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calls_remaining, seconds_until_reset = self.api_calls_left()
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request_notes.ratelimits_applied[-1].remaining = calls_remaining
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request_notes.ratelimits_applied[-1].secs_to_freedom = seconds_until_reset
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def block_access(self, seconds: int) -> None:
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"""Manually blocks an entity for the desired number of seconds"""
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self.backend.block_access(self.key(), seconds)
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def unblock_access(self) -> None:
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self.backend.unblock_access(self.key())
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def clear_history(self) -> None:
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self.backend.clear_history(self.key())
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def max_api_calls(self) -> int:
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"""Returns the API rate limit for the highest limit"""
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return self.get_rules()[-1][1]
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def max_api_window(self) -> int:
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"""Returns the API time window for the highest limit"""
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return self.get_rules()[-1][0]
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def api_calls_left(self) -> tuple[int, float]:
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"""Returns how many API calls in this range this client has, as well as when
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the rate-limit will be reset to 0"""
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max_window = self.max_api_window()
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max_calls = self.max_api_calls()
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return self.backend.get_api_calls_left(self.key(), max_window, max_calls)
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def get_rules(self) -> list[tuple[int, int]]:
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"""
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This is a simple wrapper meant to protect against having to deal with
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an empty list of rules, as it would require fiddling with that special case
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all around this system. "9999 max request per seconds" should be a good proxy
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for "no rules".
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"""
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rules_list = self.rules()
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return rules_list or [(1, 9999)]
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@abstractmethod
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def key(self) -> str:
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pass
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@abstractmethod
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def rules(self) -> list[tuple[int, int]]:
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pass
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class RateLimitedUser(RateLimitedObject):
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def __init__(self, user: UserProfile, domain: str = "api_by_user") -> None:
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self.user_id = user.id
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self.rate_limits = user.rate_limits
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self.domain = domain
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if settings.RUNNING_INSIDE_TORNADO and domain in settings.RATE_LIMITING_DOMAINS_FOR_TORNADO:
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backend: type[RateLimiterBackend] | None = TornadoInMemoryRateLimiterBackend
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else:
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backend = None
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super().__init__(backend=backend)
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@override
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def key(self) -> str:
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return f"{type(self).__name__}:{self.user_id}:{self.domain}"
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@override
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def rules(self) -> list[tuple[int, int]]:
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# user.rate_limits are general limits, applicable to the domain 'api_by_user'
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if self.rate_limits != "" and self.domain == "api_by_user":
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result: list[tuple[int, int]] = []
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for limit in self.rate_limits.split(","):
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(seconds, requests) = limit.split(":", 2)
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result.append((int(seconds), int(requests)))
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return result
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return rules[self.domain]
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class RateLimitedIPAddr(RateLimitedObject):
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def __init__(
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self, ip_addr: str, domain: str = "api_by_ip", ipv6_network_prefix: int = 64
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) -> None:
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self.ip_addr = ip_addr
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self.ipv6_network_prefix = ipv6_network_prefix
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self.domain = domain
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if settings.RUNNING_INSIDE_TORNADO and domain in settings.RATE_LIMITING_DOMAINS_FOR_TORNADO:
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backend: type[RateLimiterBackend] | None = TornadoInMemoryRateLimiterBackend
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else:
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backend = None
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super().__init__(backend=backend)
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@override
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def key(self) -> str:
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if self.ip_addr != "tor-exit-node" and isinstance(
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network := ip_network(self.ip_addr), IPv6Network
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):
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# For IPv6 we use the network portion of that IPv6.
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# This essentially tells us which bucket should this IPv6 belong to.
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# For example:
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# The network portion of 2001:0db8:ce1:12::8a2e:0370
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# is 2001:db8:ce1:12::/64
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ip_addr_key = str(network.supernet(new_prefix=self.ipv6_network_prefix))
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else:
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ip_addr_key = self.ip_addr
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# The angle brackets are important since an IPv6 address contains :
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return f"{type(self).__name__}:<{ip_addr_key}>:{self.domain}"
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@override
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def rules(self) -> list[tuple[int, int]]:
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return rules[self.domain]
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class RateLimitedEndpoint(RateLimitedObject):
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def __init__(self, endpoint_name: str) -> None:
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self.endpoint_name = endpoint_name
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super().__init__()
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@override
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def key(self) -> str:
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return f"{type(self).__name__}:{self.endpoint_name}"
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@override
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def rules(self) -> list[tuple[int, int]]:
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return settings.ABSOLUTE_USAGE_LIMITS_BY_ENDPOINT[self.endpoint_name]
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class RateLimiterBackend(ABC):
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@classmethod
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@abstractmethod
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def block_access(cls, entity_key: str, seconds: int) -> None:
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"""Manually blocks an entity for the desired number of seconds"""
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@classmethod
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@abstractmethod
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def unblock_access(cls, entity_key: str) -> None:
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pass
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@classmethod
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@abstractmethod
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def clear_history(cls, entity_key: str) -> None:
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pass
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@classmethod
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@abstractmethod
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def get_api_calls_left(
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cls, entity_key: str, range_seconds: int, max_calls: int
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) -> tuple[int, float]:
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pass
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@classmethod
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@abstractmethod
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def rate_limit_entity(
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cls, entity_key: str, rules: list[tuple[int, int]], max_api_calls: int, max_api_window: int
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) -> tuple[bool, float]:
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# Returns (ratelimited, secs_to_freedom)
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pass
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class TornadoInMemoryRateLimiterBackend(RateLimiterBackend):
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# reset_times[rule][key] is the time at which the event
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# request from the rate-limited key will be accepted.
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reset_times: dict[tuple[int, int], dict[str, float]] = {}
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# last_gc_time is the last time when the garbage was
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# collected from reset_times for rule (time_window, max_count).
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last_gc_time: dict[tuple[int, int], float] = {}
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# timestamps_blocked_until[key] contains the timestamp
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# up to which the key has been blocked manually.
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timestamps_blocked_until: dict[str, float] = {}
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@classmethod
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def _garbage_collect_for_rule(cls, now: float, time_window: int, max_count: int) -> None:
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keys_to_delete = []
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reset_times_for_rule = cls.reset_times.get((time_window, max_count), None)
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if reset_times_for_rule is None:
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return
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keys_to_delete = [
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entity_key
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for entity_key in reset_times_for_rule
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if reset_times_for_rule[entity_key] < now
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]
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for entity_key in keys_to_delete:
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del reset_times_for_rule[entity_key]
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if not reset_times_for_rule:
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del cls.reset_times[(time_window, max_count)]
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@classmethod
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def need_to_limit(cls, entity_key: str, time_window: int, max_count: int) -> tuple[bool, float]:
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"""
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Returns a tuple of `(rate_limited, time_till_free)`.
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For simplicity, we have loosened the semantics here from
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- each key may make at most `count * (t / window)` request within any t
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time interval.
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to
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- each key may make at most `count * [(t / window) + 1]` request within
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any t time interval.
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Thus, we only need to store reset_times for each key which will be less
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memory-intensive. This also has the advantage that you can only ever
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lock yourself out completely for `window / count` seconds instead of
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`window` seconds.
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"""
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now = time.time()
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# Remove all timestamps from `reset_times` that are too old.
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if cls.last_gc_time.get((time_window, max_count), 0) <= now - time_window / max_count:
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cls.last_gc_time[(time_window, max_count)] = now
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cls._garbage_collect_for_rule(now, time_window, max_count)
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reset_times_for_rule = cls.reset_times.setdefault((time_window, max_count), {})
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new_reset = max(reset_times_for_rule.get(entity_key, now), now) + time_window / max_count
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if new_reset > now + time_window:
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# Compute for how long the bucket will remain filled.
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time_till_free = new_reset - time_window - now
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return True, time_till_free
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reset_times_for_rule[entity_key] = new_reset
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return False, 0.0
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@classmethod
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@override
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def get_api_calls_left(
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cls, entity_key: str, range_seconds: int, max_calls: int
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) -> tuple[int, float]:
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now = time.time()
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if (range_seconds, max_calls) in cls.reset_times and entity_key in cls.reset_times[
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(range_seconds, max_calls)
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]:
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reset_time = cls.reset_times[(range_seconds, max_calls)][entity_key]
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else:
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return max_calls, 0
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calls_remaining = (now + range_seconds - reset_time) * max_calls // range_seconds
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return int(calls_remaining), reset_time - now
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@classmethod
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@override
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def block_access(cls, entity_key: str, seconds: int) -> None:
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now = time.time()
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cls.timestamps_blocked_until[entity_key] = now + seconds
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@classmethod
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@override
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def unblock_access(cls, entity_key: str) -> None:
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del cls.timestamps_blocked_until[entity_key]
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@classmethod
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@override
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def clear_history(cls, entity_key: str) -> None:
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for reset_times_for_rule in cls.reset_times.values():
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reset_times_for_rule.pop(entity_key, None)
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cls.timestamps_blocked_until.pop(entity_key, None)
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@classmethod
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@override
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def rate_limit_entity(
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cls, entity_key: str, rules: list[tuple[int, int]], max_api_calls: int, max_api_window: int
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) -> tuple[bool, float]:
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now = time.time()
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if entity_key in cls.timestamps_blocked_until:
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# Check whether the key is manually blocked.
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if now < cls.timestamps_blocked_until[entity_key]:
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blocking_ttl = cls.timestamps_blocked_until[entity_key] - now
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return True, blocking_ttl
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else:
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del cls.timestamps_blocked_until[entity_key]
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assert rules
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for time_window, max_count in rules:
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ratelimited, time_till_free = cls.need_to_limit(entity_key, time_window, max_count)
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if ratelimited:
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break
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return ratelimited, time_till_free
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class RedisRateLimiterBackend(RateLimiterBackend):
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@classmethod
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def get_keys(cls, entity_key: str) -> list[str]:
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return [
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f"{redis_utils.REDIS_KEY_PREFIX}ratelimit:{entity_key}:{keytype}"
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for keytype in ["list", "zset", "block"]
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]
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@classmethod
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@override
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def block_access(cls, entity_key: str, seconds: int) -> None:
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"""Manually blocks an entity for the desired number of seconds"""
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_, _, blocking_key = cls.get_keys(entity_key)
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with client.pipeline() as pipe:
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pipe.set(blocking_key, 1)
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pipe.expire(blocking_key, seconds)
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pipe.execute()
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@classmethod
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@override
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def unblock_access(cls, entity_key: str) -> None:
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_, _, blocking_key = cls.get_keys(entity_key)
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client.delete(blocking_key)
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@classmethod
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@override
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def clear_history(cls, entity_key: str) -> None:
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for key in cls.get_keys(entity_key):
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client.delete(key)
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@classmethod
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@override
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def get_api_calls_left(
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cls, entity_key: str, range_seconds: int, max_calls: int
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) -> tuple[int, float]:
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list_key, set_key, _ = cls.get_keys(entity_key)
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# Count the number of values in our sorted set
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# that are between now and the cutoff
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now = time.time()
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boundary = now - range_seconds
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with client.pipeline() as pipe:
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# Count how many API calls in our range have already been made
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pipe.zcount(set_key, boundary, now)
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# Get the newest call so we can calculate when the ratelimit
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# will reset to 0
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pipe.lindex(list_key, 0)
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results = pipe.execute()
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count: int = results[0]
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newest_call: bytes | None = results[1]
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calls_left = max_calls - count
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if newest_call is not None:
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time_reset = now + (range_seconds - (now - float(newest_call)))
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else:
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time_reset = now
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return calls_left, time_reset - now
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@classmethod
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def is_ratelimited(cls, entity_key: str, rules: list[tuple[int, int]]) -> tuple[bool, float]:
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"""Returns a tuple of (rate_limited, time_till_free)"""
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assert rules
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list_key, set_key, blocking_key = cls.get_keys(entity_key)
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# Go through the rules from shortest to longest,
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# seeing if this user has violated any of them. First
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# get the timestamps for each nth items
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with client.pipeline() as pipe:
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for _, request_count in rules:
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pipe.lindex(list_key, request_count - 1) # 0-indexed list
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# Get blocking info
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pipe.get(blocking_key)
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pipe.ttl(blocking_key)
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rule_timestamps: list[bytes | None] = pipe.execute()
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# Check if there is a manual block on this API key
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blocking_ttl_b = rule_timestamps.pop()
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key_blocked = rule_timestamps.pop()
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if key_blocked is not None:
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# We are manually blocked. Report for how much longer we will be
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if blocking_ttl_b is None: # nocoverage # defensive code, this should never happen
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blocking_ttl = 0.5
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else:
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blocking_ttl = int(blocking_ttl_b)
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return True, blocking_ttl
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now = time.time()
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for timestamp, (range_seconds, num_requests) in zip(rule_timestamps, rules, strict=False):
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# Check if the nth timestamp is newer than the associated rule. If so,
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# it means we've hit our limit for this rule
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if timestamp is None:
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continue
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boundary = float(timestamp) + range_seconds
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if boundary >= now:
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free = boundary - now
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return True, free
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return False, 0.0
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@classmethod
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def incr_ratelimit(cls, entity_key: str, max_api_calls: int, max_api_window: int) -> None:
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"""Increases the rate-limit for the specified entity"""
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list_key, set_key, _ = cls.get_keys(entity_key)
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now = time.time()
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# Start Redis transaction
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with client.pipeline() as pipe:
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count = 0
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while True:
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try:
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# To avoid a race condition between getting the element we might trim from our list
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# and removing it from our associated set, we abort this whole transaction if
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# another agent manages to change our list out from under us
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# When watching a value, the pipeline is set to Immediate mode
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pipe.watch(list_key)
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# Get the last elem that we'll trim (so we can remove it from our sorted set)
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last_val = cast( # mypy doesn’t know the pipe is in immediate mode
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bytes | None, pipe.lindex(list_key, max_api_calls - 1)
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)
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# Restart buffered execution
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pipe.multi()
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# Add this timestamp to our list
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pipe.lpush(list_key, now)
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# Trim our list to the oldest rule we have
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pipe.ltrim(list_key, 0, max_api_calls - 1)
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|
||
# Add our new value to the sorted set that we keep
|
||
# We need to put the score and val both as timestamp,
|
||
# as we sort by score but remove by value
|
||
pipe.zadd(set_key, {str(now): now})
|
||
|
||
# Remove the trimmed value from our sorted set, if there was one
|
||
if last_val is not None:
|
||
pipe.zrem(set_key, last_val)
|
||
|
||
# Set the TTL for our keys as well
|
||
api_window = max_api_window
|
||
pipe.expire(list_key, api_window)
|
||
pipe.expire(set_key, api_window)
|
||
|
||
pipe.execute()
|
||
|
||
# If no exception was raised in the execution, there were no transaction conflicts
|
||
break
|
||
except redis.WatchError: # nocoverage # Ideally we'd have a test for this.
|
||
if count > 10:
|
||
raise RateLimiterLockingError
|
||
count += 1
|
||
|
||
continue
|
||
|
||
@classmethod
|
||
@override
|
||
def rate_limit_entity(
|
||
cls, entity_key: str, rules: list[tuple[int, int]], max_api_calls: int, max_api_window: int
|
||
) -> tuple[bool, float]:
|
||
ratelimited, time = cls.is_ratelimited(entity_key, rules)
|
||
|
||
if not ratelimited:
|
||
try:
|
||
cls.incr_ratelimit(entity_key, max_api_calls, max_api_window)
|
||
except RateLimiterLockingError:
|
||
logger.warning("Deadlock trying to incr_ratelimit for %s", entity_key)
|
||
# rate-limit users who are hitting the API so hard we can't update our stats.
|
||
ratelimited = True
|
||
|
||
return ratelimited, time
|
||
|
||
|
||
class RateLimitResult:
|
||
def __init__(
|
||
self, entity: RateLimitedObject, secs_to_freedom: float, over_limit: bool, remaining: int
|
||
) -> None:
|
||
if over_limit:
|
||
assert not remaining
|
||
|
||
self.entity = entity
|
||
self.secs_to_freedom = secs_to_freedom
|
||
self.over_limit = over_limit
|
||
self.remaining = remaining
|
||
|
||
|
||
class RateLimitedSpectatorAttachmentAccessByFile(RateLimitedObject):
|
||
def __init__(self, path_id: str) -> None:
|
||
self.path_id = path_id
|
||
super().__init__()
|
||
|
||
@override
|
||
def key(self) -> str:
|
||
return f"{type(self).__name__}:{self.path_id}"
|
||
|
||
@override
|
||
def rules(self) -> list[tuple[int, int]]:
|
||
return settings.RATE_LIMITING_RULES["spectator_attachment_access_by_file"]
|
||
|
||
|
||
def rate_limit_spectator_attachment_access_by_file(path_id: str) -> None:
|
||
ratelimited, _ = RateLimitedSpectatorAttachmentAccessByFile(path_id).rate_limit()
|
||
if ratelimited:
|
||
raise RateLimitedError
|
||
|
||
|
||
def is_local_addr(addr: str) -> bool:
|
||
return addr in ("127.0.0.1", "::1")
|
||
|
||
|
||
@cache_with_key(lambda: "tor_ip_addresses:", timeout=60 * 60)
|
||
@circuit(failure_threshold=2, recovery_timeout=60 * 10)
|
||
def get_tor_ips() -> set[str]:
|
||
if not settings.RATE_LIMIT_TOR_TOGETHER:
|
||
return set()
|
||
|
||
# Cron job in /etc/cron.d/fetch-tor-exit-nodes fetches this
|
||
# hourly; we cache it in memcached to prevent going to disk on
|
||
# every unauth'd request. In case of failures to read, we
|
||
# circuit-break so 2 failures cause a 10-minute backoff.
|
||
|
||
with open(settings.TOR_EXIT_NODE_FILE_PATH, "rb") as f:
|
||
exit_node_list = orjson.loads(f.read())
|
||
|
||
# This should always be non-empty; if it's empty, assume something
|
||
# went wrong with writing and treat it as a non-existent file.
|
||
# Circuit-breaking will ensure that we back off on re-reading the
|
||
# file.
|
||
if len(exit_node_list) == 0:
|
||
raise OSError("File is empty")
|
||
|
||
return set(exit_node_list)
|
||
|
||
|
||
def client_is_exempt_from_rate_limiting(request: HttpRequest) -> bool:
|
||
from zerver.lib.request import RequestNotes
|
||
|
||
# Don't rate limit requests from Django that come from our own servers,
|
||
# and don't rate-limit dev instances
|
||
client = RequestNotes.get_notes(request).client
|
||
return (client is not None and client.name.lower() == "internal") and (
|
||
is_local_addr(request.META["REMOTE_ADDR"]) or settings.DEBUG_RATE_LIMITING
|
||
)
|
||
|
||
|
||
def rate_limit_user(request: HttpRequest, user: UserProfile, domain: str) -> None:
|
||
"""Returns whether or not a user was rate limited. Will raise a RateLimitedError exception
|
||
if the user has been rate limited, otherwise returns and modifies request to contain
|
||
the rate limit information"""
|
||
if not should_rate_limit(request):
|
||
return
|
||
|
||
RateLimitedUser(user, domain=domain).rate_limit_request(request)
|
||
|
||
|
||
def rate_limit_request_by_ip(request: HttpRequest, domain: str) -> None:
|
||
if not should_rate_limit(request):
|
||
return
|
||
|
||
# REMOTE_ADDR is set by SetRemoteAddrFromRealIpHeader in conjunction
|
||
# with the nginx configuration to guarantee this to be *the* correct
|
||
# IP address to use - without worrying we'll grab the IP of a proxy.
|
||
ip_addr = request.META["REMOTE_ADDR"]
|
||
assert ip_addr
|
||
|
||
try:
|
||
# We lump all TOR exit nodes into one bucket; this prevents
|
||
# abuse from TOR, while still allowing some access to these
|
||
# endpoints for legitimate users. Checking for local
|
||
# addresses is a shortcut somewhat for ease of testing without
|
||
# mocking the TOR endpoint in every test.
|
||
if is_local_addr(ip_addr):
|
||
pass
|
||
elif ip_addr in get_tor_ips():
|
||
ip_addr = "tor-exit-node"
|
||
except (OSError, CircuitBreakerError) as err:
|
||
# In the event that we can't get an updated list of TOR exit
|
||
# nodes, assume the IP is _not_ one, and leave it unchanged.
|
||
# We log a warning so that this endpoint being taken out of
|
||
# service doesn't silently remove this functionality.
|
||
logger.warning("Failed to fetch TOR exit node list: %s", err)
|
||
RateLimitedIPAddr(ip_addr, domain=domain).rate_limit_request(request)
|
||
|
||
|
||
def rate_limit_endpoint_absolute(endpoint_name: str) -> None:
|
||
ratelimited, secs_to_freedom = RateLimitedEndpoint(endpoint_name).rate_limit()
|
||
if ratelimited:
|
||
raise RateLimitedError(secs_to_freedom)
|
||
|
||
|
||
def should_rate_limit(request: HttpRequest) -> bool:
|
||
if not settings.RATE_LIMITING:
|
||
return False
|
||
|
||
if client_is_exempt_from_rate_limiting(request):
|
||
return False
|
||
|
||
return True
|