fix(proxy): stop stale auth cache re-publish so key updates and deletes propagate across replicas (#33565)

With enable_redis_auth_cache and multiple replicas, /key/update and
/key/delete delete the Redis auth blob and the handling pod's in-memory
entry, but two read-path writers re-published the stale blob from any other
replica's per-pod memory back to Redis with a fresh 60s TTL on every
request: the post-auth re-cache in user_api_key_auth and the spend writeback
in update_cache. Replicas whose in-memory entries expired then re-primed
themselves from the poisoned Redis entry, so key limit and access changes
never took effect fleet-wide while traffic continued, and a deleted key kept
authenticating.

The auth object is now written only by the DB-load paths
(IdentityStore._resolve_key, get_key_object): the post-auth re-cache is
removed outright (even a local-only write could race an invalidation and
resurrect a revoked key on this worker) and spend tracking no longer writes
the auth object back at all; spend is tracked through the spend🔑*
counters. The remaining spend writebacks for user, team, end-user, and tag
objects become local-only so they cannot republish stale management objects
either, with one deliberate exception: the proxy-wide
{litellm_proxy_admin_name}:spend scalar keeps its shared Redis write because
the global max_budget check reads it between authoritative DB reloads, and
it carries no limits or permissions so sharing it cannot resurrect an
invalidated auth blob.

DualCache's redis-to-memory read backfill also ignored default_in_memory_ttl,
pinning backfilled entries for InMemoryCache's 600s default instead of the
configured 60s auth TTL; the backfill now injects the configured default like
every write path already does, so a replica primed from Redis converges
within the auth cache TTL as well.

Consolidates the sibling stale-auth-recache branch; the delete-propagation
case is the duplicate ticket LIT-4350.

Resolves LIT-4219

(cherry picked from commit ae8dc1f39f)
This commit is contained in:
Yassin Kortam 2026-07-16 15:00:33 -07:00 committed by Yuneng Jiang
parent 052b5a2169
commit a68439ec0c
No known key found for this signature in database
7 changed files with 348 additions and 34 deletions

View file

@ -103,6 +103,18 @@ class DualCache(BaseCache):
if default_redis_ttl is not None:
self.default_redis_ttl = default_redis_ttl
def _backfill_kwargs(self, kwargs: "dict[str, object]") -> "dict[str, object]":
"""
Kwargs for writing a Redis read result into the in-memory tier.
Applies ``default_in_memory_ttl`` exactly like the write paths do;
without it, backfilled entries fall to ``InMemoryCache``'s own default
TTL and can outlive the TTL this cache was configured with.
"""
if "ttl" not in kwargs and self.default_in_memory_ttl is not None:
return {**kwargs, "ttl": self.default_in_memory_ttl}
return kwargs
def set_cache(self, key, value, local_only: bool = False, **kwargs):
# Update both Redis and in-memory cache
try:
@ -160,7 +172,7 @@ class DualCache(BaseCache):
if redis_result is not None:
# Update in-memory cache with the value from Redis
self.in_memory_cache.set_cache(key, redis_result, **kwargs)
self.in_memory_cache.set_cache(key, redis_result, **self._backfill_kwargs(kwargs))
result = redis_result
@ -226,7 +238,7 @@ class DualCache(BaseCache):
if redis_result is not None:
# Update in-memory cache with the value from Redis
await self.in_memory_cache.async_set_cache(key, redis_result, **kwargs)
await self.in_memory_cache.async_set_cache(key, redis_result, **self._backfill_kwargs(kwargs))
result = redis_result
@ -318,7 +330,7 @@ class DualCache(BaseCache):
result[key_to_index[key]] = value
if value is not None and self.in_memory_cache is not None:
await self.in_memory_cache.async_set_cache(key, value, **kwargs)
await self.in_memory_cache.async_set_cache(key, value, **self._backfill_kwargs(kwargs))
return result
except Exception:

View file

@ -1992,16 +1992,6 @@ async def _user_api_key_auth_builder(
raise HTTPException(401, detail="Invalid API key, no token associated")
api_key = valid_token.token
# Add hashed token to cache
asyncio.create_task(
_cache_key_object(
hashed_token=api_key,
user_api_key_obj=valid_token,
user_api_key_cache=user_api_key_cache,
proxy_logging_obj=proxy_logging_obj,
)
)
valid_token_dict = valid_token.model_dump(exclude_none=True)
valid_token_dict.pop("token", None)
# budget_throttle_pct is excluded from model_dump (it must not leak

View file

@ -2768,21 +2768,6 @@ async def update_cache(
)
# set cooldown on alert
if existing_spend_obj is not None and getattr(existing_spend_obj, "team_spend", None) is not None:
existing_team_spend = existing_spend_obj.team_spend or 0
# Calculate the new cost by adding the existing cost and response_cost
existing_spend_obj.team_spend = existing_team_spend + response_cost
if existing_spend_obj is not None and getattr(existing_spend_obj, "team_member_spend", None) is not None:
existing_team_member_spend = existing_spend_obj.team_member_spend or 0
# Calculate the new cost by adding the existing cost and response_cost
existing_spend_obj.team_member_spend = existing_team_member_spend + response_cost
# Existing spend_obj is mutated; UserApiKeyCache.async_set_cache_pipeline turns
# BaseModel values into dicts for Redis (same Codec path as async_set_cache).
existing_spend_obj.spend = new_spend
values_to_update_in_cache.append((hashed_token, existing_spend_obj))
### UPDATE USER SPEND ###
async def _update_user_cache():
## UPDATE CACHE FOR USER ID + GLOBAL PROXY
@ -2986,13 +2971,27 @@ async def update_cache(
if tags is not None:
await _update_tag_cache()
asyncio.create_task(
user_api_key_cache.async_set_cache_pipeline(
cache_list=values_to_update_in_cache,
ttl=get_management_object_ttl(user_api_key_cache),
litellm_parent_otel_span=parent_otel_span,
global_proxy_spend_key = "{}:spend".format(litellm_proxy_admin_name)
local_object_updates = tuple((k, v) for k, v in values_to_update_in_cache if k != global_proxy_spend_key)
shared_scalar_updates = tuple((k, v) for k, v in values_to_update_in_cache if k == global_proxy_spend_key)
if local_object_updates:
asyncio.create_task(
user_api_key_cache.async_set_cache_pipeline(
cache_list=list(local_object_updates),
ttl=get_management_object_ttl(user_api_key_cache),
litellm_parent_otel_span=parent_otel_span,
local_only=True,
)
)
if shared_scalar_updates:
asyncio.create_task(
user_api_key_cache.async_set_cache_pipeline(
cache_list=list(shared_scalar_updates),
ttl=get_management_object_ttl(user_api_key_cache),
litellm_parent_otel_span=parent_otel_span,
)
)
)
def run_ollama_serve():

View file

@ -88,6 +88,60 @@ async def test_dual_cache_async_set_cache_injects_default_in_memory_ttl():
assert expiry <= after + 60
@pytest.mark.asyncio
async def test_dual_cache_redis_backfill_injects_default_in_memory_ttl():
"""
A Redis-hit backfill into the in-memory tier must honor
default_in_memory_ttl the same way the write paths do. Without it, the
backfilled entry falls to InMemoryCache's own default_ttl (600s), so a
replica that primed a management object (e.g. a virtual key's auth blob)
from Redis keeps serving it for 10 minutes after the object was updated
and invalidated, instead of re-reading within the configured TTL.
"""
in_memory_cache = InMemoryCache(default_ttl=600)
redis_cache = MagicMock()
redis_cache.async_get_cache = AsyncMock(return_value="redis_value")
dual_cache = DualCache(
in_memory_cache=in_memory_cache,
redis_cache=redis_cache,
default_in_memory_ttl=60,
)
before = time.time()
result = await dual_cache.async_get_cache(key="backfill_key")
after = time.time()
assert result == "redis_value"
expiry = in_memory_cache.ttl_dict["backfill_key"]
assert expiry >= before + 60
assert expiry <= after + 60
@pytest.mark.asyncio
async def test_dual_cache_batch_redis_backfill_injects_default_in_memory_ttl():
"""async_batch_get_cache's Redis-to-memory backfill must honor
default_in_memory_ttl, same as the single-key path."""
in_memory_cache = InMemoryCache(default_ttl=600)
mock_redis = MagicMock(spec=RedisCache)
mock_redis.async_batch_get_cache = AsyncMock(
return_value={"batch_backfill_key": "redis_value"}
)
dual_cache = DualCache(
in_memory_cache=in_memory_cache,
redis_cache=mock_redis,
default_in_memory_ttl=60,
)
before = time.time()
result = await dual_cache.async_batch_get_cache(keys=["batch_backfill_key"])
after = time.time()
assert result == ["redis_value"]
expiry = in_memory_cache.ttl_dict["batch_backfill_key"]
assert expiry >= before + 60
assert expiry <= after + 60
@pytest.mark.asyncio
async def test_dual_cache_async_set_cache_respects_explicit_ttl():
"""

View file

@ -522,6 +522,49 @@ async def test_get_key_object_should_raise_if_reconnect_fails_on_db_connection_e
assert mock_prisma_client.get_data.await_count == 1
def _fake_redis_cache():
fake_redis = MagicMock()
fake_redis.async_get_cache = AsyncMock(return_value=None)
fake_redis.async_set_cache = AsyncMock()
fake_redis.async_set_cache_pipeline = AsyncMock()
fake_redis.async_delete_cache = AsyncMock()
return fake_redis
class TestAuthCacheRedisWritePolicy:
"""Redis auth-cache entries may only be written from fresh DB loads.
With ``enable_redis_auth_cache`` and multiple replicas, a pod that re-publishes
a cache-derived key object to Redis can resurrect a stale auth blob after
``/key/update`` or ``/key/delete`` already deleted it, so limit changes never
propagate fleet-wide while traffic keeps refreshing the stale entry's TTL.
"""
@pytest.mark.asyncio
async def test_get_key_object_db_load_publishes_to_redis(self):
mock_prisma_client = MagicMock()
mock_prisma_client.get_data = AsyncMock(
return_value=UserAPIKeyAuth(token="hashed-token-db")
)
fake_redis = _fake_redis_cache()
cache = UserApiKeyCache()
cache.redis_cache = fake_redis
key_obj = await get_key_object(
hashed_token="hashed-token-db",
prisma_client=mock_prisma_client,
user_api_key_cache=cache,
)
assert key_obj.token == "hashed-token-db"
fake_redis.async_set_cache.assert_awaited_once()
assert (
fake_redis.async_set_cache.await_args.kwargs.get("key")
or fake_redis.async_set_cache.await_args.args[0]
) == "hashed-token-db"
def test_get_cli_jwt_auth_token_default_expiration(valid_sso_user_defined_values):
"""Test generating CLI JWT token with default 24-hour expiration"""
token = ExperimentalUIJWTToken.get_cli_jwt_auth_token(valid_sso_user_defined_values)

View file

@ -1,3 +1,4 @@
import asyncio
import json
import os
import sys
@ -4087,6 +4088,99 @@ async def test_auth_path_caches_team_object_under_canonical_team_id_key():
assert cache.get_cache(key=None) is None
@pytest.mark.asyncio
async def test_auth_does_not_rewrite_cached_key_object_back_into_cache():
"""A cache-hit auth must not write the token back into the cache.
Re-writing on every auth let a replica holding a stale in-memory token
republish it to shared Redis with a fresh TTL on each request, so
/key/update and /key/delete never propagated across replicas or regional
Redis while the key kept calling (stale auth re-cache feedback loop).
Only the DB-load paths (IdentityStore._resolve_key / get_key_object) may
populate the cache.
"""
from fastapi import Request
from starlette.datastructures import URL
import litellm.proxy.proxy_server as _proxy_server_mod
from litellm.proxy.auth.user_api_key_auth import _user_api_key_auth_builder
from litellm.proxy.common_utils.user_api_key_cache import UserApiKeyCache
from litellm.proxy.proxy_server import hash_token
api_key = "sk-lit-cached-key-no-rewrite"
hashed_key = hash_token(api_key)
key_cache = UserApiKeyCache()
stale_token = UserAPIKeyAuth(
api_key=api_key,
token=hashed_key,
metadata={"model_rpm_limit": {"gpt-5.4-mini": 3}},
last_refreshed_at=1000.0,
)
await key_cache.async_set_cache(
key=hashed_key, value=stale_token, model_type=UserAPIKeyAuth
)
fetch_from_db = AsyncMock(
side_effect=AssertionError("cache-hit auth must not touch the DB")
)
proxy_logging_obj = MagicMock()
proxy_logging_obj.internal_usage_cache = MagicMock()
proxy_logging_obj.internal_usage_cache.dual_cache = AsyncMock()
proxy_logging_obj.post_call_failure_hook = AsyncMock(return_value=None)
attrs = {
"prisma_client": MagicMock(),
"user_api_key_cache": key_cache,
"proxy_logging_obj": proxy_logging_obj,
"master_key": "sk-test-master",
"general_settings": {},
"llm_model_list": [],
"llm_router": None,
"open_telemetry_logger": None,
"model_max_budget_limiter": MagicMock(),
"user_custom_auth": None,
"jwt_handler": None,
"litellm_proxy_admin_name": "admin",
}
originals = {a: getattr(_proxy_server_mod, a, None) for a in attrs}
try:
for k, v in attrs.items():
setattr(_proxy_server_mod, k, v)
request = Request(scope={"type": "http"})
request._url = URL(url="/chat/completions")
with patch(
"litellm.proxy.auth.resolvers.store._fetch_key_object_from_db_with_reconnect",
fetch_from_db,
):
result = await _user_api_key_auth_builder(
request=request,
api_key=f"Bearer {api_key}",
azure_api_key_header="",
anthropic_api_key_header=None,
google_ai_studio_api_key_header=None,
azure_apim_header=None,
request_data={},
)
pending = [t for t in asyncio.all_tasks() if t is not asyncio.current_task()]
if pending:
await asyncio.wait(pending, timeout=5)
assert result.token == hashed_key
fetch_from_db.assert_not_called()
cached_after = await key_cache.async_get_cache(
key=hashed_key, model_type=UserAPIKeyAuth
)
assert cached_after is not None
assert cached_after.last_refreshed_at == 1000.0
assert cached_after.metadata == {"model_rpm_limit": {"gpt-5.4-mini": 3}}
finally:
for k, v in originals.items():
setattr(_proxy_server_mod, k, v)
class TestCheckKeyModelBudgetWithFallback:
"""`_check_key_model_budget_with_fallback` must reroute a request to the
first configured `budget_fallbacks` entry still within its own budget,

View file

@ -4490,6 +4490,128 @@ async def test_update_cache_pipeline_honors_user_api_key_cache_ttl():
setattr(litellm.proxy.proxy_server, "user_api_key_cache", original_cache)
@pytest.mark.asyncio
async def test_spend_tracking_never_writes_the_auth_object_back():
"""Spend tracking must never write the auth object back into the cache.
Writing the mutated auth object back after every priced request let a
stale copy be re-published with a fresh TTL: to shared Redis it defeated
/key/update and /key/delete across replicas, and even a local-only write
could race an invalidation and resurrect a revoked key on this worker.
Spend is tracked through the spend:key:* counters, so the auth object is
only ever written by the DB-load paths.
"""
from litellm.proxy.common_utils.user_api_key_cache import UserApiKeyCache
original_cache = litellm.proxy.proxy_server.user_api_key_cache
cache = UserApiKeyCache()
setattr(litellm.proxy.proxy_server, "user_api_key_cache", cache)
try:
hashed_token = "spend-tracking-no-writeback-token"
await cache.async_set_cache(
key=hashed_token,
value=UserAPIKeyAuth(token=hashed_token, spend=1.0),
model_type=UserAPIKeyAuth,
)
with (
patch.object(
cache, "async_set_cache_pipeline", new=AsyncMock()
) as mock_pipeline,
patch.object(cache, "async_set_cache", new=AsyncMock()) as mock_set,
):
await litellm.proxy.proxy_server.update_cache(
token=hashed_token,
user_id=None,
end_user_id=None,
team_id=None,
response_cost=5.0,
parent_otel_span=None,
)
pending = [
t for t in asyncio.all_tasks() if t is not asyncio.current_task()
]
if pending:
await asyncio.wait(pending, timeout=5)
key_pipeline_writes = [
call
for call in mock_pipeline.call_args_list
if any(k == hashed_token for k, _ in call.kwargs["cache_list"])
]
assert key_pipeline_writes == []
mock_set.assert_not_called()
finally:
setattr(litellm.proxy.proxy_server, "user_api_key_cache", original_cache)
@pytest.mark.asyncio
async def test_update_cache_global_proxy_spend_scalar_stays_shared():
"""
The proxy-wide spend estimate must keep flowing to Redis when the spend
writeback goes per-pod: the global max_budget check reads the
``{litellm_proxy_admin_name}:spend`` cache entry between authoritative DB
reloads, so keeping it pod-local would let traffic spread across replicas
exceed the proxy budget by roughly a factor of the replica count within a
cache TTL. Sharing this scalar is safe because it carries no limits or
permissions, so it cannot resurrect an invalidated auth blob.
"""
from litellm.caching.caching import DualCache
admin_name = litellm.proxy.proxy_server.litellm_proxy_admin_name
global_key = "{}:spend".format(admin_name)
async def fake_get(key, **kwargs):
if key == "user-lit":
return {"user_id": "user-lit", "spend": 1.0}
if key == global_key:
return 10.0
return None
original_cache = litellm.proxy.proxy_server.user_api_key_cache
cache = DualCache(default_in_memory_ttl=300)
setattr(litellm.proxy.proxy_server, "user_api_key_cache", cache)
try:
with patch.object(
cache, "async_get_cache", new=AsyncMock(side_effect=fake_get)
):
with patch.object(
cache, "async_set_cache_pipeline", new=AsyncMock()
) as mock_set_cache:
await litellm.proxy.proxy_server.update_cache(
token=None,
user_id="user-lit",
end_user_id=None,
team_id=None,
response_cost=5.0,
parent_otel_span=None,
)
pending = [
t for t in asyncio.all_tasks() if t is not asyncio.current_task()
]
if pending:
await asyncio.wait(pending, timeout=5)
calls = mock_set_cache.await_args_list
local_keys = [
k
for c in calls
if c.kwargs.get("local_only") is True
for k, _ in c.kwargs["cache_list"]
]
shared_keys = [
k
for c in calls
if c.kwargs.get("local_only") is not True
for k, _ in c.kwargs["cache_list"]
]
assert "user-lit" in local_keys
assert global_key not in local_keys
assert shared_keys == [global_key]
finally:
setattr(litellm.proxy.proxy_server, "user_api_key_cache", original_cache)
@pytest.mark.asyncio
async def test_init_sso_settings_in_db():
"""