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Merge pull request #36313 from BerriAI/litellm_backport_1_89_x_bp-189x-0808sec

Browse source 
chore(release): backport #30585, #30867, #31905, #32093, #32405, #34189, #36011 to stable/1.89.x and cut 1.89.7
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yuneng-jiang 2026-08-08 16:16:33 -07:00 • committed by GitHub
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34 changed files with 2576 additions and 492 deletions
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2
docker/build_from_pip/Dockerfile.build_from_pip
View file

@ -36,7 +36,7 @@ RUN uv venv --python python && \
"opentelemetry-api==1.28.0" \
"opentelemetry-sdk==1.28.0" \
"opentelemetry-exporter-otlp==1.28.0" \
"ddtrace==2.19.0" \
"ddtrace==4.11.0" \
"sentry-sdk==2.21.0" \
"mangum==0.17.0" \
"azure-ai-contentsafety==1.0.0" \

2
litellm/litellm_core_utils/dd_tracing.py
View file

@ -10,7 +10,7 @@ from typing import TYPE_CHECKING, Any, Optional, Union
from litellm.secret_managers.main import get_secret_bool
if TYPE_CHECKING:
from ddtrace.tracer import Tracer as DD_TRACER
from ddtrace.trace import Tracer as DD_TRACER
else:
DD_TRACER = Any

29
litellm/litellm_core_utils/initialize_dynamic_callback_params.py
View file

@ -1,7 +1,23 @@
from typing import Dict, Optional
from typing import Any, Dict, Iterator, Optional
from litellm.types.utils import StandardCallbackDynamicParams
_CLIENT_CALLBACK_METADATA_SLOTS: tuple[str, ...] = ("litellm_metadata", "metadata")
def iter_client_callback_metadata_dicts(
kwargs: dict[str, Any],
) -> Iterator[tuple[str, dict[str, Any]]]:
litellm_params = kwargs.get("litellm_params")
if isinstance(litellm_params, dict):
nested = litellm_params.get("metadata")
if isinstance(nested, dict):
yield "litellm_params.metadata", nested
for key in _CLIENT_CALLBACK_METADATA_SLOTS:
candidate = kwargs.get(key)
if isinstance(candidate, dict):
yield key, candidate
def _is_env_reference(value: object) -> bool:
return isinstance(value, str) and "os.environ/" in value
@ -57,6 +73,7 @@ _supported_callback_params = [
"dd_site",
"dd_agent_host",
"dd_agent_port",
"turn_off_message_logging",
]
_request_blocked_callback_params = {
@ -91,20 +108,14 @@ def initialize_standard_callback_dynamic_params(
)
standard_callback_dynamic_params[param] = _param_value # type: ignore
# 2. Fallback: check "metadata" or "litellm_params" -> "metadata"
metadata = (kwargs.get("metadata") or {}).copy()
litellm_params = kwargs.get("litellm_params") or {}
if isinstance(litellm_params, dict):
metadata.update(litellm_params.get("metadata") or {})
if isinstance(metadata, dict):
for slot_label, metadata in iter_client_callback_metadata_dicts(kwargs):
for param in _supported_callback_params:
if param in _request_blocked_callback_params:
continue
if param not in standard_callback_dynamic_params and param in metadata:
_param_value = metadata.get(param)
validate_no_callback_env_reference(
param, _param_value, source="metadata"
param, _param_value, source=slot_label
)
standard_callback_dynamic_params[param] = _param_value # type: ignore

12
litellm/litellm_core_utils/url_utils.py
View file

@ -148,6 +148,18 @@ def _parse_url_destination_allowlist_entry(
return _normalize_host(parsed.hostname), scheme, port
def provider_url_destination_candidates(value: str) -> Tuple[str, ...]:
return tuple(
candidate
for part in value.split(",")
for candidate in (
part.strip(),
part.strip().split("/", 1)[1] if "/" in part.strip() else "",
)
if candidate
)
def is_url_destination_allowed_by_host(url: str, allowed_hosts: List[str]) -> bool:
"""Return True when a credential-bearing provider URL is admin-allowlisted.

68
litellm/llms/anthropic/experimental_pass_through/messages/interceptors/advisor.py
View file

@ -17,7 +17,9 @@ How it works:
import uuid
from typing import Any, AsyncIterator, Dict, List, Optional, Union
import litellm
import litellm.constants as _c
from litellm.litellm_core_utils.url_utils import validate_url
from litellm.llms.anthropic.common_utils import strip_advisor_blocks_from_messages
from litellm.types.llms.anthropic_messages.anthropic_response import (
AnthropicMessagesResponse,
@ -82,10 +84,7 @@ class AdvisorOrchestrationHandler(MessagesInterceptor):
max_uses: int = (
ADVISOR_MAX_USES if _raw_max_uses is None else int(_raw_max_uses)
)
# Optional routing overrides for the advisor sub-call (e.g. proxy routing).
# If not set in the tool definition, litellm resolves from env vars.
advisor_api_key: Optional[str] = advisor_tool.get("api_key")
advisor_api_base: Optional[str] = advisor_tool.get("api_base")
advisor_api_key, advisor_api_base = _resolve_advisor_credentials(advisor_tool)
# Build the synthetic tool definition the provider will receive.
synthetic_advisor_tool = _make_synthetic_advisor_tool()
@ -181,6 +180,67 @@ class AdvisorOrchestrationHandler(MessagesInterceptor):
# ---------------------------------------------------------------------------
def _allow_client_side_advisor_credentials() -> bool:
"""Whether a caller-supplied advisor api_base/api_key may be honored.
Gated on the proxy's ``allow_client_side_credentials`` opt-in. When the
interceptor runs outside the proxy (SDK use), there is no admin boundary
to protect, so client-supplied routing is allowed.
"""
try:
from litellm.proxy.proxy_server import general_settings
except (ImportError, ModuleNotFoundError):
return True
return general_settings.get("allow_client_side_credentials") is True
def _resolve_advisor_credentials(
advisor_tool: dict,
) -> tuple[Optional[str], Optional[str]]:
"""Resolve the (api_key, api_base) override for the advisor sub-call.
A caller-supplied ``api_base`` is only honored alongside a caller-supplied
``api_key``: without one, ``AnthropicModelInfo.get_auth_header()`` falls
back to the proxy's own Anthropic credentials, which would then be sent to
the caller-chosen ``api_base``. A caller-supplied ``api_base`` is also
required to be https with TLS verification on, and SSRF-validated so it
can't target a private/internal/cloud-metadata address, mirroring
``proxy.auth.auth_utils.check_complete_credentials``. https with TLS
verification is required because ``validate_url`` only rewrites the
connection to a DNS-pinned IP for http, or for https with
``litellm.ssl_verify`` disabled; otherwise it returns the URL unchanged
and relies on certificate validation to block DNS rebinding, so this
closes the same gap without threading the pinned URL through the whole
``anthropic_messages()`` call chain.
"""
if not _allow_client_side_advisor_credentials():
return None, None
api_key: Optional[str] = advisor_tool.get("api_key")
api_base: Optional[str] = advisor_tool.get("api_base")
if api_base is None:
return api_key, None
if not api_key:
raise ValueError(
"advisor tool definition sets 'api_base' without 'api_key'. A "
"caller-supplied api_base is only honored alongside a "
"caller-supplied api_key, so the proxy's own credentials are "
"never sent to a caller-chosen destination."
)
if not api_base.startswith("https://"):
raise ValueError(
f"advisor tool definition sets 'api_base'={api_base!r}, which must use the https scheme."
)
if getattr(litellm, "ssl_verify", True) is False:
raise ValueError(
"advisor tool definition sets 'api_base' but the proxy has TLS verification "
"disabled (litellm.ssl_verify=False), so a caller-supplied api_base can't be "
"safely validated against DNS rebinding."
)
if getattr(litellm, "user_url_validation", True):
validate_url(api_base)
return api_key, api_base
def _make_synthetic_advisor_tool() -> Dict:
"""Build a regular tool definition the executor provider can understand."""
return {

62
litellm/llms/bedrock/base_aws_llm.py
View file

@ -10,7 +10,6 @@ from typing import (
Callable,
ClassVar,
Dict,
List,
Literal,
Optional,
Tuple,
@ -210,32 +209,11 @@ class BaseAWSLLM:
"""
Return a boto3.Credentials object
"""
## CHECK IS 'os.environ/' passed in
params_to_check: List[Optional[str]] = [
aws_access_key_id,
aws_secret_access_key,
aws_session_token,
aws_region_name,
aws_session_name,
aws_profile_name,
aws_role_name,
aws_web_identity_token,
aws_sts_endpoint,
aws_external_id,
]
# Iterate over parameters and update if needed
for i, param in enumerate(params_to_check):
if param and param.startswith("os.environ/"):
_v = get_secret(param)
if _v is not None and isinstance(_v, str):
params_to_check[i] = _v
elif param is None: # check if uppercase value in env
key = self.aws_authentication_params[i]
if key.upper() in os.environ:
params_to_check[i] = os.getenv(key.upper())
# Assign updated values back to parameters
# Only config-sourced credentials are expanded against the environment.
# os.environ/<VAR> references in the model config are resolved at load time,
# so any reference still present at this point is caller-supplied input and is
# left as-is rather than expanded into a process environment variable. Each
# unset param falls back to its matching fixed AWS_* ambient env var.
(
aws_access_key_id,
aws_secret_access_key,
@ -247,7 +225,21 @@ class BaseAWSLLM:
aws_web_identity_token,
aws_sts_endpoint,
aws_external_id,
) = params_to_check
) = tuple(
value if value is not None else os.getenv(env_var)
for value, env_var in (
(aws_access_key_id, "AWS_ACCESS_KEY_ID"),
(aws_secret_access_key, "AWS_SECRET_ACCESS_KEY"),
(aws_session_token, "AWS_SESSION_TOKEN"),
(aws_region_name, "AWS_REGION_NAME"),
(aws_session_name, "AWS_SESSION_NAME"),
(aws_profile_name, "AWS_PROFILE_NAME"),
(aws_role_name, "AWS_ROLE_NAME"),
(aws_web_identity_token, "AWS_WEB_IDENTITY_TOKEN"),
(aws_sts_endpoint, "AWS_STS_ENDPOINT"),
(aws_external_id, "AWS_EXTERNAL_ID"),
)
)
verbose_logger.debug(
"in get credentials\n"
@ -845,6 +837,20 @@ class BaseAWSLLM:
f"IN Web Identity Token: {aws_web_identity_token} | Role Name: {aws_role_name} | Session Name: {aws_session_name}"
)
# get_secret() expands environment-variable references (an os.environ/<VAR>
# prefix, or a bare name matching an environment variable). Config-sourced
# references are expanded at load time, so such a reference reaching here is
# caller-supplied input; reject it rather than expanding a process-environment
# value for use as the token.
if (
aws_web_identity_token.startswith("os.environ/")
or aws_web_identity_token in os.environ
):
raise AwsAuthError(
message="Invalid web identity token reference.",
status_code=400,
)
oidc_token = get_secret(aws_web_identity_token)
if oidc_token is None:

2
litellm/llms/huggingface/embedding/handler.py
View file

@ -348,7 +348,7 @@ class HuggingFaceEmbedding(BaseLLM):
)
# print_verbose(f"{model}, {task}")
embed_url = ""
if "https" in model:
if model.startswith(("http://", "https://")):
embed_url = model
elif api_base:
embed_url = api_base

19
litellm/llms/huggingface/embedding/transformation.py
View file

@ -330,25 +330,6 @@ class HuggingFaceEmbeddingConfig(BaseConfig):
return data
def get_api_base(self, api_base: Optional[str], model: str) -> str:
"""
Get the API base for the Huggingface API.
Do not add the chat/embedding/rerank extension here. Let the handler do this.
"""
if "https" in model:
completion_url = model
elif api_base is not None:
completion_url = api_base
elif "HF_API_BASE" in os.environ:
completion_url = os.getenv("HF_API_BASE", "")
elif "HUGGINGFACE_API_BASE" in os.environ:
completion_url = os.getenv("HUGGINGFACE_API_BASE", "")
else:
completion_url = f"https://api-inference.huggingface.co/models/{model}"
return completion_url
def validate_environment(
self,
headers: Dict,

4
litellm/llms/oobabooga/chat/oobabooga.py
View file

@ -34,7 +34,7 @@ def completion(
optional_params=optional_params,
litellm_params=litellm_params,
)
if "https" in model:
if model.startswith(("http://", "https://")):
completion_url = model
elif api_base:
completion_url = api_base
@ -96,7 +96,7 @@ def embedding(
encoding=None,
):
# Create completion URL
if "https" in model:
if model.startswith(("http://", "https://")):
embeddings_url = model
elif api_base:
embeddings_url = f"{api_base}/v1/embeddings"

109
litellm/proxy/auth/auth_utils.py
View file

@ -2,7 +2,7 @@ import os
import re
import sys
from functools import lru_cache
from typing import Any, Dict, FrozenSet, List, Mapping, Optional, Tuple, Union
from typing import Any, Dict, FrozenSet, Iterator, List, Mapping, Optional, Tuple, Union
from fastapi import HTTPException, Request, status
@ -11,8 +11,14 @@ from litellm import Router, provider_list
from litellm._logging import verbose_proxy_logger
from litellm.constants import STANDARD_CUSTOMER_ID_HEADERS
from litellm.litellm_core_utils.safe_json_loads import safe_json_loads
from litellm.litellm_core_utils.url_utils import SSRFError, validate_url
from litellm.litellm_core_utils.url_utils import (
SSRFError,
is_url_destination_allowed_by_host,
provider_url_destination_candidates,
validate_url,
)
from litellm.proxy._types import *
from litellm.proxy.common_utils.http_parsing_utils import extract_nested_form_metadata
from litellm.types.router import CONFIGURABLE_CLIENTSIDE_AUTH_PARAMS
from litellm.types.utils import CustomPricingLiteLLMParams
@ -279,6 +285,9 @@ _BANNED_REQUEST_BODY_PARAMS: Tuple[str, ...] = (
"s3_endpoint_url",
"sagemaker_base_url",
"deployment_url",
# SDK-only field; also rejected outright in is_request_body_safe.
"model_list",
"vertex_ai_credentials",
# Observability credentials, hosts, and project identifiers: derived
# from the canonical ``_supported_callback_params`` allowlist so new
# integrations are covered automatically. Sorted for stable iteration
@ -331,6 +340,66 @@ def _check_banned_params(
)
_FALLBACK_FIELDS: tuple[str, ...] = (
"fallbacks",
"context_window_fallbacks",
"content_policy_fallbacks",
)
def _iter_fallback_field_values(request_body: Mapping[str, object]) -> Iterator[object]:
override = request_body.get("router_settings_override")
for source in (request_body, override):
if isinstance(source, Mapping):
for field in _FALLBACK_FIELDS:
yield source.get(field)
def _iter_fallback_targets(
value: object, depth: int
) -> Iterator[str | Mapping[str, object]]:
if depth > 2 * litellm.ROUTER_MAX_FALLBACKS:
raise ValueError(
"Rejected Request: fallback nesting exceeds the allowed validation depth."
)
if not isinstance(value, list):
return
for item in value:
if isinstance(item, str):
yield item
elif isinstance(item, Mapping):
values = tuple(item.values())
if not (values and all(isinstance(v, list) for v in values)):
yield item
if isinstance(item.get("model"), str):
for field in _FALLBACK_FIELDS:
yield from _iter_fallback_targets(item.get(field), depth + 1)
else:
for target_list in values:
yield from _iter_fallback_targets(target_list, depth + 1)
def iter_request_fallback_targets(
request_body: Mapping[str, object],
) -> Iterator[str | Mapping[str, object]]:
for value in _iter_fallback_field_values(request_body):
yield from _iter_fallback_targets(value, 0)
def _reject_url_valued_fallback_target(value: str) -> None:
allowed_hosts = getattr(litellm, "provider_url_destination_allowed_hosts", []) or []
for candidate in provider_url_destination_candidates(value):
if not candidate.lower().startswith(("http://", "https://")):
continue
if is_url_destination_allowed_by_host(candidate, allowed_hosts):
continue
raise ValueError(
f"Rejected Request: URL-valued fallback destination '{value}' is not allowed. "
"Configure custom endpoints with api_base instead, or add the destination host to "
"`provider_url_destination_allowed_hosts` in litellm_settings."
)
def is_request_body_safe(
request_body: dict, general_settings: dict, llm_router: Optional[Router], model: str
) -> bool:
@ -359,6 +428,10 @@ def is_request_body_safe(
``litellm_embedding_config.api_base`` (VERIA-6) without exposing a
recursion-depth DoS surface.
"""
if "model_list" in request_body:
raise ValueError(
"Rejected Request: model_list is not allowed in the request body."
)
_check_banned_params(request_body, general_settings, llm_router, model)
for nested_key in _NESTED_CONFIG_KEYS:
nested = _coerce_metadata_to_dict(request_body.get(nested_key))
@ -368,6 +441,38 @@ def is_request_body_safe(
metadata = _coerce_metadata_to_dict(request_body.get(metadata_key))
if metadata is not None:
_check_banned_params(metadata, general_settings, llm_router, model)
if any(
isinstance(key, str) and key.startswith(f"{metadata_key}[")
for key in request_body
):
_check_banned_params(
extract_nested_form_metadata(
form_data=request_body, prefix=f"{metadata_key}["
),
general_settings,
llm_router,
model,
)
for target in iter_request_fallback_targets(request_body):
if isinstance(target, dict):
_check_banned_params(target, general_settings, llm_router, model)
target_model = target.get("model")
if isinstance(target_model, str):
_reject_url_valued_fallback_target(target_model)
elif isinstance(target, str):
_reject_url_valued_fallback_target(target)
litellm_params = _coerce_metadata_to_dict(request_body.get("litellm_params"))
if litellm_params is not None:
litellm_params_metadata = _coerce_metadata_to_dict(
litellm_params.get("metadata")
)
if litellm_params_metadata is not None:
_check_banned_params(
litellm_params_metadata,
general_settings,
llm_router,
model,
)
return True

63
litellm/proxy/auth/user_api_key_auth.py
View file

@ -12,7 +12,7 @@ import fnmatch
import re
import secrets
from datetime import datetime, timezone
from typing import Any, Dict, Iterator, NamedTuple, List, Optional, Tuple, Union, cast
from typing import Any, Dict, NamedTuple, List, Optional, Tuple, Union, cast
import fastapi
from fastapi import HTTPException, Request, WebSocket, status
@ -56,6 +56,7 @@ from litellm.proxy.auth.auth_utils import (
get_model_from_request,
get_request_route,
get_request_route_template,
iter_request_fallback_targets,
normalize_request_route,
pre_db_read_auth_checks,
route_in_additonal_public_routes,
@ -2819,23 +2820,11 @@ async def _enforce_key_and_fallback_model_access(
llm_router=llm_router,
)
# Validate every fallback model name reachable by this request.
# All three fields (``fallbacks``, ``context_window_fallbacks``,
# ``content_policy_fallbacks``) are forwarded to the router as
# per-request kwargs whether they appear at the top level of
# ``request_data`` or nested under ``router_settings_override``.
# Both surfaces must be validated against the API key's model
# allowlist or a caller can smuggle a restricted model. VERIA-44.
fallback_names: List[str] = []
override_settings = request_data.get("router_settings_override")
for _fb_key in ROUTER_FALLBACK_FIELDS:
fallback_names.extend(
iter_router_fallback_model_names(request_data.get(_fb_key))
)
if isinstance(override_settings, dict):
fallback_names.extend(
iter_router_fallback_model_names(override_settings.get(_fb_key))
)
fallback_names = tuple(
name
for target in iter_request_fallback_targets(request_data)
if (name := _fallback_target_model_name(target)) is not None
)
for _name in dict.fromkeys(fallback_names): # dedupe, preserve order
await can_key_call_model(
@ -2851,36 +2840,14 @@ async def _enforce_key_and_fallback_model_access(
)
ROUTER_FALLBACK_FIELDS: Tuple[str, ...] = (
"fallbacks",
"context_window_fallbacks",
"content_policy_fallbacks",
)
def iter_router_fallback_model_names(fallbacks: Any) -> Iterator[str]:
"""Yield leaf model names from any of the supported fallbacks shapes.
Handles the simple top-level shape (``str`` or ``{"model": str}``) and
the nested router-config shape (``[{primary: [fallback_list]}]``).
"""
if not isinstance(fallbacks, list):
return
for entry in fallbacks:
if isinstance(entry, str):
yield entry
elif isinstance(entry, dict):
if isinstance(entry.get("model"), str):
yield entry["model"]
continue
for fallback_list in entry.values():
if not isinstance(fallback_list, list):
continue
for m in fallback_list:
if isinstance(m, str):
yield m
elif isinstance(m, dict) and isinstance(m.get("model"), str):
yield m["model"]
def _fallback_target_model_name(target: object) -> str | None:
if isinstance(target, str):
return target
if isinstance(target, dict):
model = target.get("model")
if isinstance(model, str):
return model
return None
async def _run_post_custom_auth_checks(

8
litellm/proxy/common_request_processing.py
View file

@ -62,7 +62,10 @@ if TYPE_CHECKING:
ProxyConfig = _ProxyConfig
else:
ProxyConfig = Any
from litellm.proxy.litellm_pre_call_utils import add_litellm_data_to_request
from litellm.proxy.litellm_pre_call_utils import (
add_litellm_data_to_request,
reject_url_valued_destination,
)
from litellm.types.utils import ModelResponse, ModelResponseStream, Usage
# Datadog streaming spans are a no-op when ddtrace is not enabled, but the
@ -895,6 +898,9 @@ class ProxyBaseLLMRequestProcessing:
"queue_time_seconds"
] = queue_time_seconds
if isinstance(model, str):
reject_url_valued_destination("model", model)
self.data["model"] = (
general_settings.get("completion_model", None) # server default
or user_model # model name passed via cli args

72
litellm/proxy/health_endpoints/_health_endpoints.py
View file

@ -6,7 +6,7 @@ import secrets
import time
import traceback
from datetime import datetime, timedelta
from typing import Any, Dict, Iterable, Literal, Optional, Union, cast
from typing import Any, Dict, Final, Iterable, Literal, Mapping, Optional, Union, cast
import fastapi
from fastapi import APIRouter, Depends, HTTPException, Request, Response, status
@ -27,6 +27,9 @@ from litellm.proxy._types import (
UserAPIKeyAuth,
WebhookEvent,
)
from litellm.proxy.auth.auth_utils import (
_BANNED_REQUEST_BODY_PARAMS, # pyright: ignore[reportPrivateUsage] # one canonical list, shared with the request-body check
)
from litellm.proxy.auth.user_api_key_auth import user_api_key_auth
from litellm.proxy.db.exception_handler import PrismaDBExceptionHandler
from litellm.proxy.health_check import (
@ -41,6 +44,10 @@ from litellm.proxy.middleware.in_flight_requests_middleware import (
get_in_flight_requests,
)
from litellm.proxy.shutdown.graceful_shutdown_manager import GracefulShutdownManager
from litellm.router_utils.clientside_credential_handler import (
_ADMIN_CONFIG_FIELDS_TO_CLEAR_ON_BASE_OVERRIDE, # pyright: ignore[reportPrivateUsage] # one canonical list, shared with the router path
clientside_credential_keys,
)
#### Health ENDPOINTS ####
@ -80,6 +87,49 @@ def _reject_os_environ_references(params: dict) -> None:
stack.append(value)
_CONFIG_CONNECTION_FIELDS: Final[frozenset[str]] = frozenset(
(
*_ADMIN_CONFIG_FIELDS_TO_CLEAR_ON_BASE_OVERRIDE,
*clientside_credential_keys,
"litellm_credential_name",
)
)
def _config_base_for_health_check(
config_params: Mapping[str, object],
request_params: Mapping[str, object],
allow_client_side_credentials: bool = False,
) -> dict[str, object]:
"""Return the configured parameters to merge under a connection-test request.
A request that sets its own connection fields describes a connection of its
own, so the configuration's credentials are not carried into it: they belong
to the endpoint the configuration names. Anything the request does not set
still comes from the configuration, which is what lets a request name a
configured model and test it as configured.
``litellm_credential_name`` is dropped alongside the literal credential
fields: it names a stored credential that ``load_credentials_from_list``
resolves into the same secrets further down the call, so leaving it in place
would reintroduce them by reference.
``general_settings.allow_client_side_credentials`` is the existing proxy-wide
opt-in for callers supplying their own connection parameters. Where an admin
has enabled it, a request may pair its own endpoint with the configured
credentials, as it could before.
"""
if allow_client_side_credentials:
return dict(config_params)
if not any(param in request_params for param in _BANNED_REQUEST_BODY_PARAMS):
return dict(config_params)
return {
key: value
for key, value in config_params.items()
if key not in _CONFIG_CONNECTION_FIELDS
}
def get_callback_identifier(callback):
"""
Get the callback identifier string, handling both strings and objects.
@ -1854,7 +1904,12 @@ async def test_model_connection(
from litellm.proxy.management_endpoints.model_management_endpoints import (
ModelManagementAuthChecks,
)
from litellm.proxy.proxy_server import llm_router, premium_user, prisma_client
from litellm.proxy.proxy_server import (
general_settings,
llm_router,
premium_user,
prisma_client,
)
from litellm.types.router import Deployment, LiteLLM_Params
try:
@ -1930,8 +1985,17 @@ async def test_model_connection(
)
# Merge: config params (from proxy config) as base, request params override
# This allows users to override specific params while using config for credentials
litellm_params = {**config_litellm_params, **request_litellm_params}
litellm_params = {
**_config_base_for_health_check(
config_litellm_params,
request_litellm_params,
allow_client_side_credentials=general_settings.get(
"allow_client_side_credentials"
)
is True,
),
**request_litellm_params,
}
## Auth check
await ModelManagementAuthChecks.can_user_make_model_call(

4
litellm/proxy/image_endpoints/endpoints.py
View file

@ -70,6 +70,7 @@ async def image_generation(
user_api_key_dict: UserAPIKeyAuth = Depends(user_api_key_auth),
model: Optional[str] = None,
):
from litellm.proxy.litellm_pre_call_utils import reject_url_valued_destination
from litellm.proxy.proxy_server import (
add_litellm_data_to_request,
general_settings,
@ -96,6 +97,9 @@ async def image_generation(
proxy_config=proxy_config,
)
if isinstance(model, str):
reject_url_valued_destination("model", model)
data["model"] = (
model
or general_settings.get("image_generation_model", None) # server default

64
litellm/proxy/litellm_pre_call_utils.py
View file

@ -4,7 +4,7 @@ import json
import re
import time
from collections import OrderedDict
from typing import TYPE_CHECKING, Any, Dict, List, Optional, Union
from typing import TYPE_CHECKING, Any, Dict, Final, List, Optional, Union
from fastapi import HTTPException, Request
from pydantic import ValidationError as PydanticValidationError
@ -15,8 +15,14 @@ from litellm._logging import verbose_logger, verbose_proxy_logger
from litellm._service_logger import ServiceLogging
from litellm.constants import PRE_CALL_EXECUTED_GUARDRAILS_KEY
from litellm.litellm_core_utils.credential_accessor import CredentialAccessor
from litellm.litellm_core_utils.initialize_dynamic_callback_params import (
iter_client_callback_metadata_dicts,
)
from litellm.litellm_core_utils.safe_json_loads import safe_json_loads
from litellm.litellm_core_utils.url_utils import is_url_destination_allowed_by_host
from litellm.litellm_core_utils.url_utils import (
is_url_destination_allowed_by_host,
provider_url_destination_candidates,
)
from litellm.proxy._types import (
AddTeamCallback,
CommonProxyErrors,
@ -208,12 +214,25 @@ def _reject_url_valued_destinations(data: Dict[str, Any]) -> None:
are unaffected, while admins can opt specific hosts back in via
``litellm.provider_url_destination_allowed_hosts``.
"""
allowed_hosts = getattr(litellm, "provider_url_destination_allowed_hosts", []) or []
for field in _URL_DESTINATION_REQUEST_FIELDS:
value = data.get(field)
if not isinstance(value, str) or not value.startswith(("http://", "https://")):
if isinstance(value, str):
reject_url_valued_destination(field, value)
def reject_url_valued_destination(field: str, value: str) -> None:
"""Reject a URL-valued destination identifier unless admin-allowlisted.
Operates on one field/value pair. ``_reject_url_valued_destinations`` applies
it across ``_URL_DESTINATION_REQUEST_FIELDS`` for a request body.
"""
allowed_hosts: Final = (
getattr(litellm, "provider_url_destination_allowed_hosts", []) or []
)
for candidate in provider_url_destination_candidates(value):
if not candidate.lower().startswith(("http://", "https://")):
continue
if is_url_destination_allowed_by_host(value, allowed_hosts):
if is_url_destination_allowed_by_host(candidate, allowed_hosts):
continue
raise HTTPException(
status_code=400,
@ -296,6 +315,28 @@ def _key_or_team_allows_client_pricing_override(
)
def _strip_client_message_redaction_opt_out(data: dict[str, Any]) -> None:
stripped: list[str] = []
if "turn_off_message_logging" in data and _is_false_like(
data["turn_off_message_logging"]
):
stripped.append("turn_off_message_logging")
data.pop("turn_off_message_logging", None)
for slot_label, metadata in iter_client_callback_metadata_dicts(data):
if "turn_off_message_logging" in metadata and _is_false_like(
metadata["turn_off_message_logging"]
):
stripped.append(f"{slot_label}.turn_off_message_logging")
metadata.pop("turn_off_message_logging", None)
if stripped:
verbose_proxy_logger.debug(
"Stripped client-supplied message-redaction opt-out fields from request body: %s. "
"Set `allow_client_message_redaction_opt_out: true` on the key or team metadata "
"to keep these values.",
", ".join(stripped),
)
def _strip_client_pricing_overrides(data: Dict[str, Any]) -> None:
"""Drop pricing overrides from the request body and any metadata variant.
@ -1374,13 +1415,6 @@ async def add_litellm_data_to_request( # noqa: PLR0915
_headers,
allow_client_message_redaction_opt_out=_allow_client_message_redaction_opt_out,
)
if (
not _allow_client_message_redaction_opt_out
and litellm.turn_off_message_logging is True
and "turn_off_message_logging" in data
and _is_false_like(data["turn_off_message_logging"])
):
data.pop("turn_off_message_logging", None)
verbose_proxy_logger.debug(f"Request Headers: {_headers}")
verbose_proxy_logger.debug(f"Raw Headers: {_raw_headers}")
@ -1540,6 +1574,12 @@ async def add_litellm_data_to_request( # noqa: PLR0915
if not _key_or_team_allows_client_pricing_override(user_api_key_dict):
_strip_client_pricing_overrides(data)
if (
not _allow_client_message_redaction_opt_out
and litellm.turn_off_message_logging is True
):
_strip_client_message_redaction_opt_out(data)
# Fill in the proxy_server_request body snapshot now that metadata has
# been parsed. Consumers (standard_logging_payload, lago,
# spend_tracking_utils, streaming_iterator) read `body` to audit the

25
litellm/proxy/proxy_server.py
View file

@ -4958,6 +4958,19 @@ class ProxyConfig:
deleted_deployments += 1
return deleted_deployments
def _resolve_db_litellm_param(self, key: str, value: object) -> object:
if not isinstance(value, str):
return value
decrypted_value = decrypt_value_helper(
value=value, key=key, return_original_value=True
)
if isinstance(decrypted_value, str) and decrypted_value.startswith(
"os.environ/"
):
return get_secret(decrypted_value)
return decrypted_value
def _add_deployment(self, db_models: list) -> int:
"""
Iterate through db models
@ -4978,12 +4991,7 @@ class ProxyConfig:
if isinstance(_litellm_params, dict):
# decrypt values
for k, v in _litellm_params.items():
if isinstance(v, str):
# decrypt value - returns original value if decryption fails or no key is set
_value = decrypt_value_helper(
value=v, key=k, return_original_value=True
)
_litellm_params[k] = _value
_litellm_params[k] = self._resolve_db_litellm_param(key=k, value=v)
_litellm_params = LiteLLM_Params(**_litellm_params)
else:
@ -5016,10 +5024,7 @@ class ProxyConfig:
if isinstance(_litellm_params, dict):
# decrypt values
for k, v in _litellm_params.items():
decrypted_value = decrypt_value_helper(
value=v, key=k, return_original_value=True
)
_litellm_params[k] = decrypted_value
_litellm_params[k] = self._resolve_db_litellm_param(key=k, value=v)
_litellm_params = LiteLLM_Params(**_litellm_params)
else:
verbose_proxy_logger.error(

17
pyproject.toml
View file

@ -1,6 +1,6 @@
[project]
name = "litellm"
version = "1.89.6"
version = "1.89.7"
description = "Library to easily interface with LLM API providers"
readme = "README.md"
requires-python = ">=3.10, <3.14"
@ -23,7 +23,7 @@ dependencies = [
"tokenizers>=0.21.0,<1.0",
"click>=8.0.0,<9.0",
"jinja2>=3.1.6,<4.0",
"aiohttp>=3.10,<4.0",
"aiohttp>=3.14.2,<4.0",
"pydantic>=2.10.0,<3.0.0",
"jsonschema>=4.0.0,<5.0",
]
@ -55,7 +55,7 @@ proxy = [
"fastapi-sso>=0.19.0,<1.0",
"PyJWT>=2.12.0,<3.0",
"python-multipart>=0.0.27,<1.0",
"cryptography>=48.0.1,<49.0",
"cryptography>=50.0.0,<51.0",
"pynacl>=1.6.2,<2.0",
"websockets>=15.0.1,<16.0",
"boto3>=1.43.1,<2.0",
@ -120,7 +120,7 @@ proxy-runtime = [
"opentelemetry-sdk==1.28.0",
"opentelemetry-exporter-otlp==1.28.0",
"opentelemetry-instrumentation-fastapi==0.49b0",
"ddtrace>=2.19.0,<3.0",
"ddtrace>=4.8.2,<5.0",
"sentry-sdk>=2.21.0,<3.0",
"mangum>=0.17.0,<1.0",
"azure-ai-contentsafety>=1.0.0,<2.0",
@ -190,7 +190,7 @@ ci = [
# protobuf, Pillow is a compiled C extension).
"tenacity==8.5.0",
"google-generativeai==0.8.6",
"Pillow==12.2.0",
"Pillow==12.3.0",
# Azure batch E2E tests still import psycopg2 directly.
"psycopg2-binary==2.9.11",
"pytest-codspeed==4.3.0",
@ -230,7 +230,10 @@ build-backend = "uv_build"
[tool.uv]
constraint-dependencies = [
"tornado>=6.5.6",
"aiohttp>=3.14.1,<4.0",
"aiohttp>=3.14.2,<4.0",
]
override-dependencies = [
"cryptography>=50.0.0,<51.0",
]
default-groups = ["dev"]
required-version = ">=0.10.9"
@ -261,7 +264,7 @@ source-exclude = [
profile = "black"
[tool.commitizen]
version = "1.89.6"
version = "1.89.7"
version_files = [
"pyproject.toml:^version",
]

1
ruff.toml
View file

@ -14,6 +14,7 @@ exclude = ["litellm/types/*", "litellm/__init__.py", "litellm/proxy/example_conf
"litellm/llms/azure_ai/rerank/__init__.py" = ["F401"]
"litellm/llms/bedrock/chat/__init__.py" = ["F401"]
"litellm/proxy/utils.py" = ["F401", "PLR0915"]
"litellm/proxy/common_request_processing.py" = ["PLR0915"]
"litellm/proxy/guardrails/guardrail_hooks/litellm_content_filter/content_filter.py" = ["PLR0915"]
"litellm/proxy/guardrails/guardrail_hooks/guardrail_benchmarks/test_eval.py" = ["PLR0915"]
"litellm/responses/streaming_iterator.py" = ["PLR0915"]

1
tests/code_coverage_tests/recursive_detector.py
View file

@ -50,6 +50,7 @@ IGNORE_FUNCTIONS = [
"_resolve", # OCI: $ref resolver bounded by `resolving_stack` cycle guard.
"resolve_oci_schema_anyof", # OCI: bounded by JSON-schema tree depth (no cycles possible in well-formed input).
"sanitize_oci_schema", # OCI: bounded by JSON-schema tree depth.
"_iter_fallback_targets", # max depth set (2 * ROUTER_MAX_FALLBACKS); fails closed by raising ValueError at the cap.
]

71
tests/local_testing/test_basic_python_version.py
View file

@ -92,6 +92,77 @@ def test_package_dependencies():
)
AIOHTTP_POOL_POISONING_RANGE = ">=3.14.0,<3.14.2"
AIOHTTP_POOL_POISONING_RELEASES = ("3.14.0", "3.14.1")
def _load_toml(path):
try:
import tomllib as tomli
except ImportError:
try:
import tomli
except ImportError:
pytest.skip("tomli/tomllib not available - skipping dependency check")
with open(path, "rb") as f:
return tomli.load(f)
def _declared_aiohttp_specifier():
from packaging.requirements import Requirement
pyproject = _load_toml(os.path.join(PROJECT_ROOT, "pyproject.toml"))
for requirement in pyproject["project"]["dependencies"]:
parsed = Requirement(requirement)
if parsed.name.lower() == "aiohttp":
return parsed.specifier
pytest.fail("aiohttp is no longer a declared runtime dependency of litellm")
def _locked_aiohttp_version():
lock = _load_toml(os.path.join(PROJECT_ROOT, "uv.lock"))
for package in lock["package"]:
if package["name"].lower() == "aiohttp":
return package["version"]
pytest.fail("aiohttp is missing from uv.lock")
def test_declared_aiohttp_floor_excludes_pool_poisoning_releases():
"""aiohttp 3.14.0/3.14.1 re-arm the sock_read timer on a keep-alive connection
after it is back in the idle pool, so the next request to reuse it fails
instantly with a bogus timeout (aio-libs/aiohttp#12953, fixed in 3.14.2).
The wheel's own metadata is what pip resolves against, so the floor declared
here - not just the lockfile - has to exclude that range.
"""
specifier = _declared_aiohttp_specifier()
admitted = [v for v in AIOHTTP_POOL_POISONING_RELEASES if specifier.contains(v)]
assert not admitted, (
f"litellm declares aiohttp{specifier}, which still admits {admitted}. "
"Those releases poison pooled keep-alive connections and cause "
"cross-provider sub-millisecond 'Connection timed out' failures; "
"keep the floor at >=3.14.2."
)
def test_locked_aiohttp_version_is_not_pool_poisoning():
"""uv.lock is what the published Docker images install (uv sync --frozen), so a
lock that drifts back onto 3.14.0/3.14.1 ships the regression regardless of
what pyproject.toml declares.
"""
from packaging.specifiers import SpecifierSet
locked = _locked_aiohttp_version()
assert not SpecifierSet(AIOHTTP_POOL_POISONING_RANGE).contains(locked), (
f"uv.lock resolves aiohttp {locked}, which is inside the pool-poisoning "
f"range {AIOHTTP_POOL_POISONING_RANGE} (aio-libs/aiohttp#12953). "
"Re-run `uv lock` against an aiohttp>=3.14.2 floor."
)
import os
import subprocess
import time

59
tests/logging_callback_tests/test_logging_redaction_e2e_test.py
View file

@ -56,69 +56,56 @@ async def test_global_redaction_on():
)
@pytest.mark.parametrize("turn_off_message_logging", [True, False])
@pytest.mark.parametrize(
"dynamic_turn_off, expect_redacted",
[(True, True), (False, False)],
)
@pytest.mark.asyncio
async def test_global_redaction_ignores_dynamic_param(turn_off_message_logging):
"""
Request-body `turn_off_message_logging` is no longer honored as a dynamic
callback param — global setting (or admin-configured key/team config) wins.
With global redaction ON, the caller cannot disable redaction via the
request body.
"""
async def test_dynamic_turn_off_message_logging_overrides_global_on(dynamic_turn_off, expect_redacted):
litellm.turn_off_message_logging = True
test_custom_logger = TestCustomLogger()
litellm.callbacks = [test_custom_logger]
response = await litellm.acompletion(
await litellm.acompletion(
model="gpt-5-mini",
messages=[{"role": "user", "content": "hi"}],
turn_off_message_logging=turn_off_message_logging,
turn_off_message_logging=dynamic_turn_off,
mock_response="hello",
)
await asyncio.sleep(1)
standard_logging_payload = test_custom_logger.logged_standard_logging_payload
assert standard_logging_payload is not None
print(
"logged standard logging payload",
json.dumps(standard_logging_payload, indent=2),
)
response = standard_logging_payload["response"]
assert response["choices"][0]["message"]["content"] == "redacted-by-litellm"
assert standard_logging_payload["messages"][0]["content"] == "redacted-by-litellm"
expected_response_content = "redacted-by-litellm" if expect_redacted else "hello"
expected_message_content = "redacted-by-litellm" if expect_redacted else "hi"
assert standard_logging_payload["response"]["choices"][0]["message"]["content"] == expected_response_content
assert standard_logging_payload["messages"][0]["content"] == expected_message_content
@pytest.mark.parametrize("turn_off_message_logging", [True, False])
@pytest.mark.parametrize(
"dynamic_turn_off, expect_redacted",
[(True, True), (False, False)],
)
@pytest.mark.asyncio
async def test_global_redaction_off_ignores_dynamic_param(turn_off_message_logging):
"""
Request-body `turn_off_message_logging` is no longer honored as a dynamic
callback param — global setting (or admin-configured key/team config) wins.
With global redaction OFF, the caller cannot enable redaction via the
request body.
"""
async def test_dynamic_turn_off_message_logging_overrides_global_off(dynamic_turn_off, expect_redacted):
litellm.turn_off_message_logging = False
test_custom_logger = TestCustomLogger()
litellm.callbacks = [test_custom_logger]
response = await litellm.acompletion(
await litellm.acompletion(
model="gpt-5-mini",
messages=[{"role": "user", "content": "hi"}],
turn_off_message_logging=turn_off_message_logging,
turn_off_message_logging=dynamic_turn_off,
mock_response="hello",
)
await asyncio.sleep(1)
standard_logging_payload = test_custom_logger.logged_standard_logging_payload
assert standard_logging_payload is not None
print(
"logged standard logging payload",
json.dumps(standard_logging_payload, indent=2),
)
assert (
standard_logging_payload["response"]["choices"][0]["message"]["content"]
== "hello"
)
assert standard_logging_payload["messages"][0]["content"] == "hi"
expected_response_content = "redacted-by-litellm" if expect_redacted else "hello"
expected_message_content = "redacted-by-litellm" if expect_redacted else "hi"
assert standard_logging_payload["response"]["choices"][0]["message"]["content"] == expected_response_content
assert standard_logging_payload["messages"][0]["content"] == expected_message_content
@pytest.mark.asyncio

85
tests/test_litellm/litellm_core_utils/test_initialize_dynamic_callback_params.py
View file

@ -7,9 +7,53 @@ sys.path.insert(0, os.path.abspath("../../.."))
from litellm.litellm_core_utils.initialize_dynamic_callback_params import (
initialize_standard_callback_dynamic_params,
iter_client_callback_metadata_dicts,
)
def test_iter_client_callback_metadata_dicts_covers_all_read_paths():
md = {"m": 1}
lm = {"lm": 1}
lp_md = {"lp": 1}
slots = dict(
iter_client_callback_metadata_dicts(
{
"metadata": md,
"litellm_metadata": lm,
"litellm_params": {"metadata": lp_md},
}
)
)
assert slots == {
"metadata": md,
"litellm_metadata": lm,
"litellm_params.metadata": lp_md,
}
def test_iter_client_callback_metadata_dicts_skips_non_dict_slots():
slots = list(
iter_client_callback_metadata_dicts(
{
"metadata": "not-a-dict",
"litellm_metadata": None,
"litellm_params": {"metadata": []},
}
)
)
assert slots == []
def test_extractor_reads_turn_off_message_logging_from_every_slot():
for kwargs in (
{"metadata": {"turn_off_message_logging": True}},
{"litellm_metadata": {"turn_off_message_logging": True}},
{"litellm_params": {"metadata": {"turn_off_message_logging": True}}},
):
params = initialize_standard_callback_dynamic_params(kwargs)
assert params.get("turn_off_message_logging") is True, kwargs
def test_resolves_plain_values_at_top_level():
kwargs = {
"langfuse_public_key": "pk-test",
@ -36,6 +80,33 @@ def test_resolves_plain_values_from_metadata():
assert params.get("langfuse_host") == "https://test.langfuse.com"
def test_litellm_params_metadata_overrides_metadata():
kwargs = {
"metadata": {
"langfuse_public_key": "pk-meta",
},
"litellm_params": {
"metadata": {
"langfuse_public_key": "pk-litellm-params",
}
},
}
params = initialize_standard_callback_dynamic_params(kwargs)
assert params.get("langfuse_public_key") == "pk-litellm-params"
def test_top_level_kwargs_overrides_metadata_slots():
kwargs = {
"langfuse_public_key": "from-top-level",
"metadata": {"langfuse_public_key": "from-metadata"},
"litellm_params": {"metadata": {"langfuse_public_key": "from-litellm-params"}},
}
params = initialize_standard_callback_dynamic_params(kwargs)
assert params.get("langfuse_public_key") == "from-top-level"
def test_env_reference_at_top_level_raises_with_guidance():
kwargs = {"langfuse_public_key": "os.environ/LANGFUSE_PUBLIC_KEY"}
@ -100,11 +171,17 @@ def test_non_string_values_are_not_flagged():
assert params.get("langsmith_sampling_rate") == 0.5
def test_turn_off_message_logging_not_extracted_from_request():
"""turn_off_message_logging is admin-only — must not be settable via request."""
kwargs = {"turn_off_message_logging": True}
@pytest.mark.parametrize(
"kwargs,expected",
[
({"turn_off_message_logging": False}, False),
({"turn_off_message_logging": "False"}, "False"),
({"metadata": {"turn_off_message_logging": True}}, True),
],
)
def test_turn_off_message_logging_extracted_from_kwargs(kwargs, expected):
params = initialize_standard_callback_dynamic_params(kwargs)
assert params.get("turn_off_message_logging") is None
assert params.get("turn_off_message_logging") == expected
def test_empty_kwargs_returns_empty_params():

403
tests/test_litellm/llms/anthropic/messages/test_advisor_orchestration.py
View file

@ -516,3 +516,406 @@ async def test_max_uses_none_falls_back_to_default():
)
assert str(_c.ADVISOR_MAX_USES) in str(exc_info.value)
# ---------------------------------------------------------------------------
# 12. Defense-in-depth: client-supplied advisor api_base/api_key are dropped
# unless the proxy admin opted into clientside credentials
# ---------------------------------------------------------------------------
ADVISOR_TOOL_WITH_CREDS = {
"type": "advisor_20260301",
"name": "advisor",
"model": "claude-opus-4-6",
"api_base": "https://other.example",
"api_key": "sk-other",
}
async def _run_advisor_and_capture_subcall_kwargs():
"""Run one advisor turn and return the kwargs of the advisor sub-call."""
from litellm.llms.anthropic.experimental_pass_through.messages.interceptors.advisor import (
AdvisorOrchestrationHandler,
)
advisor_tool_use_resp = _make_advisor_tool_use_response(tool_id="toolu_01")
advisor_advice_resp = _make_text_response("advice", model="claude-opus-4-6")
final_resp = _make_text_response("final answer")
captured = {}
call_count = 0
async def mock_call(model, messages, tools, stream, max_tokens, **kwargs):
nonlocal call_count
call_count += 1
if call_count == 1:
return advisor_tool_use_resp
if call_count == 2:
# The advisor sub-call — capture its routing kwargs.
captured["api_key"] = kwargs.get("api_key")
captured["api_base"] = kwargs.get("api_base")
return advisor_advice_resp
return final_resp
with (
patch(
"litellm.llms.anthropic.experimental_pass_through.messages.interceptors.advisor._call_messages_handler",
side_effect=mock_call,
),
patch(
"litellm.llms.anthropic.experimental_pass_through.messages.interceptors.advisor.validate_url",
),
):
h = AdvisorOrchestrationHandler()
await h.handle(
model="openai/gpt-4o-mini",
messages=MESSAGES,
tools=[ADVISOR_TOOL_WITH_CREDS],
stream=False,
max_tokens=512,
custom_llm_provider="openai",
)
return captured
@pytest.mark.asyncio
async def test_advisor_creds_dropped_when_proxy_opt_in_disabled():
"""On the proxy without opt-in, the caller's advisor api_base/api_key must
NOT reach the sub-call (would redirect it / leak the server key)."""
with patch(
"litellm.llms.anthropic.experimental_pass_through.messages.interceptors.advisor._allow_client_side_advisor_credentials",
return_value=False,
):
captured = await _run_advisor_and_capture_subcall_kwargs()
assert captured["api_key"] is None
assert captured["api_base"] is None
@pytest.mark.asyncio
async def test_advisor_creds_honored_when_proxy_opt_in_enabled():
"""With the admin opt-in, the documented clientside routing still works."""
with patch(
"litellm.llms.anthropic.experimental_pass_through.messages.interceptors.advisor._allow_client_side_advisor_credentials",
return_value=True,
):
captured = await _run_advisor_and_capture_subcall_kwargs()
assert captured["api_key"] == "sk-other"
assert captured["api_base"] == "https://other.example"
# ---------------------------------------------------------------------------
# 13. The proxy gate itself: _allow_client_side_advisor_credentials() and the
# full handle() driven by the real proxy general_settings flag.
# ---------------------------------------------------------------------------
def _fake_proxy_server(general_settings: Dict):
"""A stand-in litellm.proxy.proxy_server module exposing general_settings.
The real proxy_server pulls in heavy optional deps that may be absent in a
unit-test environment, so the gate's
``from litellm.proxy.proxy_server import general_settings`` is satisfied by
injecting this lightweight module into sys.modules.
"""
import types
module = types.ModuleType("litellm.proxy.proxy_server")
module.general_settings = general_settings # type: ignore[attr-defined]
return module
def test_allow_client_side_advisor_credentials_reads_proxy_flag():
"""The gate mirrors the proxy's allow_client_side_credentials opt-in."""
import sys
from litellm.llms.anthropic.experimental_pass_through.messages.interceptors.advisor import (
_allow_client_side_advisor_credentials,
)
cases = (
({"allow_client_side_credentials": True}, True),
({"allow_client_side_credentials": False}, False),
# Flag absent entirely -> default deny on the proxy.
({}, False),
)
for settings, expected in cases:
with patch.dict(
sys.modules,
{"litellm.proxy.proxy_server": _fake_proxy_server(settings)},
):
assert _allow_client_side_advisor_credentials() is expected
def test_allow_client_side_advisor_credentials_defaults_true_outside_proxy():
"""Outside the proxy (proxy_server import unavailable), there is no admin
boundary, so the gate permits client-supplied routing."""
import builtins
import sys
from litellm.llms.anthropic.experimental_pass_through.messages.interceptors.advisor import (
_allow_client_side_advisor_credentials,
)
real_import = builtins.__import__
def _blocked_import(name, *args, **kwargs):
if name == "litellm.proxy.proxy_server":
raise ImportError("proxy server unavailable")
return real_import(name, *args, **kwargs)
with patch.dict(sys.modules):
sys.modules.pop("litellm.proxy.proxy_server", None)
with patch.object(builtins, "__import__", _blocked_import):
assert _allow_client_side_advisor_credentials() is True
def test_advisor_gate_propagates_non_import_errors():
"""Non-ImportError failures during the proxy module probe must not
default permissive. If the proxy is partially loaded and raises
RuntimeError, the gate should surface that rather than silently
returning True."""
import sys
from litellm.llms.anthropic.experimental_pass_through.messages.interceptors import (
advisor,
)
original = sys.modules.get("litellm.proxy.proxy_server")
class _Broken:
def __getattr__(self, _name):
raise RuntimeError("partial proxy boot")
sys.modules["litellm.proxy.proxy_server"] = _Broken()
try:
with pytest.raises(RuntimeError, match="partial proxy boot"):
advisor._allow_client_side_advisor_credentials()
finally:
if original is None:
sys.modules.pop("litellm.proxy.proxy_server", None)
else:
sys.modules["litellm.proxy.proxy_server"] = original
@pytest.mark.asyncio
async def test_advisor_ignores_tool_credentials_when_clientside_disabled():
"""Driven by the real proxy flag (not a patched gate): with
allow_client_side_credentials False, the tool-supplied api_base/api_key must
not reach the advisor sub-call."""
import sys
with patch.dict(
sys.modules,
{
"litellm.proxy.proxy_server": _fake_proxy_server(
{"allow_client_side_credentials": False}
)
},
):
captured = await _run_advisor_and_capture_subcall_kwargs()
assert captured["api_key"] is None
assert captured["api_base"] is None
@pytest.mark.asyncio
async def test_advisor_uses_tool_credentials_when_clientside_enabled():
"""Driven by the real proxy flag: with allow_client_side_credentials True,
the tool-supplied api_base/api_key flow through to the advisor sub-call."""
import sys
with patch.dict(
sys.modules,
{
"litellm.proxy.proxy_server": _fake_proxy_server(
{"allow_client_side_credentials": True}
)
},
):
captured = await _run_advisor_and_capture_subcall_kwargs()
assert captured["api_key"] == "sk-other"
assert captured["api_base"] == "https://other.example"
# ---------------------------------------------------------------------------
# 14. _resolve_advisor_credentials: api_base is only honored alongside a
# caller-supplied api_key, and is SSRF-validated before use.
# ---------------------------------------------------------------------------
def test_resolve_advisor_credentials_returns_none_when_gate_closed():
from litellm.llms.anthropic.experimental_pass_through.messages.interceptors.advisor import (
_resolve_advisor_credentials,
)
with patch(
"litellm.llms.anthropic.experimental_pass_through.messages.interceptors.advisor._allow_client_side_advisor_credentials",
return_value=False,
):
result = _resolve_advisor_credentials(ADVISOR_TOOL_WITH_CREDS)
assert result == (None, None)
def test_resolve_advisor_credentials_allows_api_key_without_api_base():
from litellm.llms.anthropic.experimental_pass_through.messages.interceptors.advisor import (
_resolve_advisor_credentials,
)
tool = {**ADVISOR_TOOL, "api_key": "sk-other"}
with (
patch(
"litellm.llms.anthropic.experimental_pass_through.messages.interceptors.advisor._allow_client_side_advisor_credentials",
return_value=True,
),
patch(
"litellm.llms.anthropic.experimental_pass_through.messages.interceptors.advisor.validate_url",
side_effect=AssertionError("validate_url must not run without an api_base"),
),
):
result = _resolve_advisor_credentials(tool)
assert result == ("sk-other", None)
def test_resolve_advisor_credentials_rejects_api_base_without_api_key():
from litellm.llms.anthropic.experimental_pass_through.messages.interceptors.advisor import (
_resolve_advisor_credentials,
)
tool = {**ADVISOR_TOOL, "api_base": "https://other.example"}
with patch(
"litellm.llms.anthropic.experimental_pass_through.messages.interceptors.advisor._allow_client_side_advisor_credentials",
return_value=True,
):
with pytest.raises(ValueError, match="api_base"):
_resolve_advisor_credentials(tool)
def test_resolve_advisor_credentials_validates_api_base_before_use():
from litellm.llms.anthropic.experimental_pass_through.messages.interceptors.advisor import (
_resolve_advisor_credentials,
)
with (
patch(
"litellm.llms.anthropic.experimental_pass_through.messages.interceptors.advisor._allow_client_side_advisor_credentials",
return_value=True,
),
patch(
"litellm.llms.anthropic.experimental_pass_through.messages.interceptors.advisor.validate_url"
) as mock_validate,
):
result = _resolve_advisor_credentials(ADVISOR_TOOL_WITH_CREDS)
mock_validate.assert_called_once_with("https://other.example")
assert result == ("sk-other", "https://other.example")
def test_resolve_advisor_credentials_propagates_ssrf_error():
from litellm.litellm_core_utils.url_utils import SSRFError
from litellm.llms.anthropic.experimental_pass_through.messages.interceptors.advisor import (
_resolve_advisor_credentials,
)
with (
patch(
"litellm.llms.anthropic.experimental_pass_through.messages.interceptors.advisor._allow_client_side_advisor_credentials",
return_value=True,
),
patch(
"litellm.llms.anthropic.experimental_pass_through.messages.interceptors.advisor.validate_url",
side_effect=SSRFError("URL targets a blocked address"),
),
):
with pytest.raises(SSRFError):
_resolve_advisor_credentials(ADVISOR_TOOL_WITH_CREDS)
def test_resolve_advisor_credentials_skips_validation_when_url_validation_disabled():
import litellm
from litellm.llms.anthropic.experimental_pass_through.messages.interceptors.advisor import (
_resolve_advisor_credentials,
)
with (
patch(
"litellm.llms.anthropic.experimental_pass_through.messages.interceptors.advisor._allow_client_side_advisor_credentials",
return_value=True,
),
patch.object(litellm, "user_url_validation", False),
patch(
"litellm.llms.anthropic.experimental_pass_through.messages.interceptors.advisor.validate_url",
side_effect=AssertionError("validate_url must not run when user_url_validation is disabled"),
),
):
result = _resolve_advisor_credentials(ADVISOR_TOOL_WITH_CREDS)
assert result == ("sk-other", "https://other.example")
def test_resolve_advisor_credentials_blocks_real_cloud_metadata_address():
"""End-to-end (no mocked validate_url): a caller can't redirect the
advisor sub-call to the cloud-metadata address even with an api_key."""
from litellm.litellm_core_utils.url_utils import SSRFError
from litellm.llms.anthropic.experimental_pass_through.messages.interceptors.advisor import (
_resolve_advisor_credentials,
)
tool = {
**ADVISOR_TOOL,
"api_key": "sk-other",
"api_base": "https://169.254.169.254/latest/meta-data/",
}
with patch(
"litellm.llms.anthropic.experimental_pass_through.messages.interceptors.advisor._allow_client_side_advisor_credentials",
return_value=True,
):
with pytest.raises(SSRFError):
_resolve_advisor_credentials(tool)
def test_resolve_advisor_credentials_rejects_non_https_api_base():
from litellm.llms.anthropic.experimental_pass_through.messages.interceptors.advisor import (
_resolve_advisor_credentials,
)
tool = {**ADVISOR_TOOL, "api_key": "sk-other", "api_base": "http://8.8.8.8"}
with patch(
"litellm.llms.anthropic.experimental_pass_through.messages.interceptors.advisor._allow_client_side_advisor_credentials",
return_value=True,
):
with pytest.raises(ValueError, match="https"):
_resolve_advisor_credentials(tool)
def test_resolve_advisor_credentials_rejects_api_base_when_ssl_verify_disabled():
import litellm
from litellm.llms.anthropic.experimental_pass_through.messages.interceptors.advisor import (
_resolve_advisor_credentials,
)
tool = {**ADVISOR_TOOL, "api_key": "sk-other", "api_base": "https://8.8.8.8"}
with (
patch(
"litellm.llms.anthropic.experimental_pass_through.messages.interceptors.advisor._allow_client_side_advisor_credentials",
return_value=True,
),
patch.object(litellm, "ssl_verify", False),
):
with pytest.raises(ValueError, match="ssl_verify"):
_resolve_advisor_credentials(tool)
def test_resolve_advisor_credentials_allows_real_public_ip_address():
"""End-to-end (no mocked validate_url): a globally-routable literal IP
api_base is honored when paired with an api_key."""
from litellm.llms.anthropic.experimental_pass_through.messages.interceptors.advisor import (
_resolve_advisor_credentials,
)
tool = {**ADVISOR_TOOL, "api_key": "sk-other", "api_base": "https://8.8.8.8"}
with patch(
"litellm.llms.anthropic.experimental_pass_through.messages.interceptors.advisor._allow_client_side_advisor_credentials",
return_value=True,
):
result = _resolve_advisor_credentials(tool)
assert result == ("sk-other", "https://8.8.8.8")

128
tests/test_litellm/llms/bedrock/test_base_aws_llm.py
View file

@ -163,6 +163,134 @@ def test_aws_profile_path_not_cached_in_iam_cache():
assert mock_profile.call_count == 2
def test_get_credentials_does_not_expand_request_env_reference():
"""
A parameter of the form os.environ/<VAR> reaching get_credentials is left as-is
rather than expanded against the process environment, so the downstream auth
helper only ever receives the literal value.
"""
env = _os_environ_without_aws_keys()
env["SERVER_ONLY_VALUE"] = "config-managed-value"
base = BaseAWSLLM()
with patch.dict(os.environ, env, clear=True), patch.object(
base,
"_auth_with_aws_profile",
return_value=(Credentials("ak", "sk", None), None),
) as mock_profile:
base.get_credentials(aws_profile_name="os.environ/SERVER_ONLY_VALUE")
assert mock_profile.call_args.args[0] == "os.environ/SERVER_ONLY_VALUE"
assert "config-managed-value" not in str(mock_profile.call_args)
def test_get_credentials_falls_back_to_ambient_aws_profile_name_env():
"""
The fixed AWS_* ambient fallback keeps working: an unset aws_profile_name
resolves from the AWS_PROFILE_NAME environment variable.
"""
env = _os_environ_without_aws_keys()
env["AWS_PROFILE_NAME"] = "ambient-profile"
base = BaseAWSLLM()
with patch.dict(os.environ, env, clear=True), patch.object(
base,
"_auth_with_aws_profile",
return_value=(Credentials("ak", "sk", None), None),
) as mock_profile:
base.get_credentials(aws_profile_name=None)
assert mock_profile.call_args.args[0] == "ambient-profile"
def test_get_credentials_ambient_fallback_resolves_aws_external_id():
"""
Each unset param falls back to its own AWS_* env var. Regression for an index
misalignment between the value list and the env-name list, which left
AWS_EXTERNAL_ID unresolved.
"""
env = _os_environ_without_aws_keys()
env["AWS_EXTERNAL_ID"] = "ext-from-env"
base = BaseAWSLLM()
with patch.dict(os.environ, env, clear=True), patch.object(
base,
"_auth_with_aws_role",
return_value=(Credentials("ak", "sk", "tok"), None),
) as mock_role:
base.get_credentials(
aws_role_name="arn:aws:iam::123456789012:role/x",
aws_session_name="s",
)
assert mock_role.call_args.kwargs["aws_external_id"] == "ext-from-env"
def _capturing_sts_client(captured: Dict[str, Any]) -> MagicMock:
sts = MagicMock()
def _assume(**params):
captured["WebIdentityToken"] = params.get("WebIdentityToken")
return {
"Credentials": {
"AccessKeyId": "AKIA",
"SecretAccessKey": "sk",
"SessionToken": "tok",
},
"PackedPolicySize": 10,
}
sts.assume_role_with_web_identity.side_effect = _assume
return sts
@pytest.mark.parametrize(
"token_ref",
["os.environ/SERVER_ONLY_VALUE", "SERVER_ONLY_VALUE"],
ids=["os_environ_prefix", "bare_env_name"],
)
def test_web_identity_token_env_reference_not_expanded(token_ref):
"""
A web-identity token that is an environment-variable reference (an os.environ/
prefix, or a bare name matching an env var) is rejected rather than expanded, so
the process-environment value is never used as the token.
"""
env = _os_environ_without_aws_keys()
env["SERVER_ONLY_VALUE"] = "server-only-value"
captured: Dict[str, Any] = {}
base = BaseAWSLLM()
with patch.dict(os.environ, env, clear=True), patch(
"boto3.client", side_effect=lambda *a, **k: _capturing_sts_client(captured)
), patch("boto3.Session", return_value=MagicMock()):
with pytest.raises(AwsAuthError):
base.get_credentials(
aws_web_identity_token=token_ref,
aws_role_name="arn:aws:iam::123456789012:role/x",
aws_session_name="s",
aws_sts_endpoint="https://custom-sts.example",
)
assert "server-only-value" not in str(captured)
def test_web_identity_token_oidc_reference_still_resolved():
"""
The env-reference guard does not over-reject: an oidc/ reference still flows to
get_secret (mocked to None here), surfacing the existing 401 rather than the 400
used for rejected env-var references.
"""
base = BaseAWSLLM()
env = _os_environ_without_aws_keys()
with patch.dict(os.environ, env, clear=True), patch(
"litellm.llms.bedrock.base_aws_llm.get_secret", return_value=None
):
with pytest.raises(AwsAuthError) as exc:
base.get_credentials(
aws_web_identity_token="oidc/circleci/",
aws_role_name="arn:aws:iam::123456789012:role/x",
aws_session_name="s",
)
assert exc.value.status_code == 401
def test_web_identity_path_not_cached_in_iam_cache():
base = BaseAWSLLM()
with patch.object(

14
tests/test_litellm/llms/huggingface/embedding/test_huggingface_embedding_handler.py
View file

@ -121,6 +121,20 @@ class TestHuggingFaceEmbedding:
assert response.usage.prompt_tokens > 0
assert response.usage.total_tokens == response.usage.prompt_tokens
def test_model_name_with_https_substring_uses_api_base(self):
api_base = "https://legit.example/embed"
litellm.embedding(
model="huggingface/my-https-endpoint",
input=["hello world"],
input_type="embed",
api_base=api_base,
)
self.mock_http.assert_called_once()
called_url = self.mock_http.call_args[0][0]
assert called_url == api_base
def test_embedding_with_sentence_similarity_task(self):
"""Test embedding when task type is sentence-similarity (requires 2+ sentences)"""

55
tests/test_litellm/llms/oobabooga/chat/test_oobabooga.py Normal file
View file

@ -0,0 +1,55 @@
import os
import sys
from unittest.mock import MagicMock, patch
sys.path.insert(0, os.path.abspath("../../../../.."))
import litellm
MOCK_COMPLETION_RESPONSE = {
"choices": [{"message": {"role": "assistant", "content": "hi there"}}],
"usage": {"prompt_tokens": 3, "completion_tokens": 2, "total_tokens": 5},
}
def _mock_post_response():
mock_response = MagicMock()
mock_response.status_code = 200
mock_response.text = "ok"
mock_response.json.return_value = MOCK_COMPLETION_RESPONSE
return mock_response
def test_model_name_with_https_substring_uses_api_base():
api_base = "https://legit.example"
with patch(
"litellm.llms.custom_httpx.http_handler.HTTPHandler.post"
) as mock_post:
mock_post.return_value = _mock_post_response()
litellm.completion(
model="oobabooga/my-https-model",
messages=[{"role": "user", "content": "hello"}],
api_base=api_base,
)
mock_post.assert_called_once()
called_url = mock_post.call_args[0][0]
assert called_url == f"{api_base}/v1/chat/completions"
def test_url_valued_model_still_targets_that_url():
with patch(
"litellm.llms.custom_httpx.http_handler.HTTPHandler.post"
) as mock_post:
mock_post.return_value = _mock_post_response()
litellm.completion(
model="oobabooga/https://sdk-user.example",
messages=[{"role": "user", "content": "hello"}],
)
mock_post.assert_called_once()
called_url = mock_post.call_args[0][0]
assert called_url == "https://sdk-user.example/v1/chat/completions"

485
tests/test_litellm/proxy/auth/test_auth_utils.py
View file

@ -1385,7 +1385,7 @@ class TestGetDynamicLitellmParamsClearsAdminConfigOnBaseOverride:
}
out = get_dynamic_litellm_params(
litellm_params=dict(admin_params),
request_kwargs={"base_url": "https://attacker.example"},
request_kwargs={"base_url": "https://attacker.example", "api_key": "sk-caller"},
)
assert "aws_access_key_id" not in out
assert "aws_secret_access_key" not in out
@ -1413,6 +1413,7 @@ class TestGetDynamicLitellmParamsClearsAdminConfigOnBaseOverride:
},
request_kwargs={
"api_base": "https://attacker.example",
"api_key": "sk-caller",
"organization": "org-attacker",
"extra_body": {"attacker": "value"},
},
@ -1436,6 +1437,7 @@ class TestGetDynamicLitellmParamsClearsAdminConfigOnBaseOverride:
},
request_kwargs={
"api_base": "https://attacker.example",
"api_key": "sk-caller",
"organization": "",
"extra_body": "",
},
@ -1463,6 +1465,310 @@ class TestGetDynamicLitellmParamsClearsAdminConfigOnBaseOverride:
assert out["api_version"] == "2026-04-01"
assert out["api_base"] == "https://admin.upstream/v1"
def test_client_api_key_used_when_supplied_with_base_override(self):
from litellm.router_utils.clientside_credential_handler import (
get_dynamic_litellm_params,
)
out = get_dynamic_litellm_params(
litellm_params={
"model": "gpt-4",
"api_key": "sk-admin-secret",
"api_base": "https://admin.upstream/v1",
},
request_kwargs={
"api_base": "https://attacker.example",
"api_key": "sk-client-byok",
},
)
assert out["api_key"] == "sk-client-byok"
assert "sk-admin-secret" not in str(out)
_OPENAI_CHAT_RESPONSE = {
"id": "chatcmpl-x",
"object": "chat.completion",
"created": 1,
"model": "gpt-4",
"choices": [{"index": 0, "message": {"role": "assistant", "content": "hi"}, "finish_reason": "stop"}],
"usage": {"prompt_tokens": 1, "completion_tokens": 1, "total_tokens": 2},
}
class TestClientsideBaseOverrideOutboundKey:
"""Drive a completion through the router and assert on the outbound request
when the caller overrides ``api_base``."""
def _router(self):
from litellm import Router
return Router(
model_list=[
{
"model_name": "gpt-4",
"litellm_params": {
"model": "openai/gpt-4",
"api_key": "sk-SERVER-CONFIG",
"api_base": "https://admin.upstream/v1",
},
}
]
)
@pytest.fixture(autouse=True)
def _ambient_server_key(self, monkeypatch):
import litellm
monkeypatch.setenv("OPENAI_API_KEY", "sk-SERVER-ENV")
monkeypatch.setattr(litellm, "api_key", None, raising=False)
def test_caller_key_override_sends_caller_key_never_server_key(self):
import httpx
import respx
with respx.mock:
route = respx.post("https://caller.example/v1/chat/completions").mock(
return_value=httpx.Response(200, json=_OPENAI_CHAT_RESPONSE)
)
self._router().completion(
model="gpt-4",
messages=[{"role": "user", "content": "hi"}],
api_base="https://caller.example/v1",
api_key="sk-CALLER",
)
authorization = route.calls.last.request.headers.get("authorization")
assert authorization == "Bearer sk-CALLER"
assert "SERVER" not in (authorization or "")
def _rounds_deep_api_base_payload(rounds, field):
"""Build a fallbacks payload with ``api_base`` on a target nested ``rounds``
fallback-rounds deep, each round wrapped in its own grouping dict."""
node = {"model": "leaf", "api_base": "https://attacker.example"}
for i in range(rounds):
node = {"model": f"m{i}", field: [{"grp": [node]}]}
return {"model": "gpt-4", field: [{"grp": [node]}]}
class TestIsRequestBodySafeBlocksFallbackSmuggle:
"""``is_request_body_safe`` runs the banned-param check on every dict target
inside the fallback lists."""
@pytest.fixture(autouse=True)
def _disable_url_validation(self, monkeypatch):
import litellm
monkeypatch.setattr(litellm, "user_url_validation", False, raising=False)
@pytest.mark.parametrize(
"fallback_key",
["fallbacks", "context_window_fallbacks", "content_policy_fallbacks"],
)
def test_api_base_smuggled_via_nested_fallback_is_rejected(self, fallback_key):
with pytest.raises(ValueError, match="api_base"):
is_request_body_safe(
request_body={
"model": "gpt-4",
fallback_key: [
{
"gpt-4": [
{"model": "evil", "api_base": "https://attacker.example"},
]
}
],
},
general_settings={},
llm_router=None,
model="gpt-4",
)
def test_string_only_fallbacks_are_accepted(self):
assert (
is_request_body_safe(
request_body={
"model": "gpt-4",
"fallbacks": [{"gpt-4": ["gpt-3.5-turbo", "claude-3-haiku"]}],
},
general_settings={},
llm_router=None,
model="gpt-4",
)
is True
)
def test_benign_dict_fallback_entry_is_accepted(self):
assert (
is_request_body_safe(
request_body={
"model": "gpt-4",
"fallbacks": [{"gpt-4": [{"model": "gpt-3.5-turbo"}]}],
},
general_settings={},
llm_router=None,
model="gpt-4",
)
is True
)
def test_smuggled_fallback_allowed_under_proxy_wide_opt_in(self):
assert (
is_request_body_safe(
request_body={
"model": "gpt-4",
"fallbacks": [
{"gpt-4": [{"model": "byok", "api_base": "https://my-byok.example"}]}
],
},
general_settings={"allow_client_side_credentials": True},
llm_router=None,
model="gpt-4",
)
is True
)
@pytest.mark.parametrize(
"fallback_field",
["fallbacks", "context_window_fallbacks", "content_policy_fallbacks"],
)
@pytest.mark.parametrize("surface", ["top_level", "router_settings_override"])
def test_deeply_nested_api_base_smuggle_rejected_on_both_surfaces(self, fallback_field, surface):
nested = [
{
"always-fail": [
{
"model": "x",
fallback_field: [
{"x": [{"model": "deepseek-chat", "api_base": "http://attacker"}]}
],
}
]
}
]
request_body = {"model": "gpt-4"}
if surface == "top_level":
request_body[fallback_field] = nested
else:
request_body["router_settings_override"] = {fallback_field: nested}
with pytest.raises(ValueError, match="api_base"):
is_request_body_safe(
request_body=request_body,
general_settings={},
llm_router=None,
model="gpt-4",
)
def test_router_settings_override_single_level_api_base_rejected(self):
with pytest.raises(ValueError, match="api_base"):
is_request_body_safe(
request_body={
"model": "gpt-4",
"router_settings_override": {
"fallbacks": [{"gpt-4": [{"model": "x", "api_base": "http://attacker"}]}]
},
},
general_settings={},
llm_router=None,
model="gpt-4",
)
def test_model_less_config_dict_api_base_rejected(self):
with pytest.raises(ValueError, match="api_base"):
is_request_body_safe(
request_body={
"model": "gpt-4",
"fallbacks": [{"gpt-4": [{"api_base": "http://attacker"}]}],
},
general_settings={},
llm_router=None,
model="gpt-4",
)
def test_nested_api_base_caught_across_router_fallback_rounds(self):
"""An ``api_base`` target nested ``ROUTER_MAX_FALLBACKS - 1`` rounds deep
is still reached and rejected."""
import litellm
with pytest.raises(ValueError, match="api_base"):
is_request_body_safe(
request_body=_rounds_deep_api_base_payload(litellm.ROUTER_MAX_FALLBACKS - 1, "fallbacks"),
general_settings={},
llm_router=None,
model="gpt-4",
)
def test_grouping_only_deep_chain_is_rejected_at_depth_limit(self):
"""A deep grouping-only chain (``{"g": [{"g": [...]}]}``) is rejected at the
validation-depth limit rather than accepted or raising RecursionError."""
node: object = ["safe-model"]
for _ in range(5000):
node = [{"grp": node}]
with pytest.raises(ValueError, match="depth"):
is_request_body_safe(
request_body={"model": "gpt-4", "fallbacks": node},
general_settings={},
llm_router=None,
model="gpt-4",
)
def test_pathologically_deep_model_nesting_is_rejected(self):
with pytest.raises(ValueError, match="depth"):
is_request_body_safe(
request_body=_rounds_deep_api_base_payload(5000, "fallbacks"),
general_settings={},
llm_router=None,
model="gpt-4",
)
class TestIsRequestBodySafeRejectsUrlValuedFallback:
@pytest.mark.parametrize("fallback_field", ["fallbacks", "context_window_fallbacks", "content_policy_fallbacks"])
def test_url_valued_string_fallback_is_rejected(self, fallback_field):
with pytest.raises(ValueError, match="URL-valued fallback"):
is_request_body_safe(
request_body={
"model": "gpt-4",
fallback_field: [{"gpt-4": ["huggingface/http://attacker.example/path"]}],
},
general_settings={},
llm_router=None,
model="gpt-4",
)
@pytest.mark.parametrize("fallback_field", ["fallbacks", "context_window_fallbacks", "content_policy_fallbacks"])
def test_url_valued_dict_model_fallback_is_rejected(self, fallback_field):
with pytest.raises(ValueError, match="URL-valued fallback"):
is_request_body_safe(
request_body={
"model": "gpt-4",
fallback_field: [{"gpt-4": [{"model": "huggingface/http://attacker.example/path"}]}],
},
general_settings={},
llm_router=None,
model="gpt-4",
)
def test_ordinary_string_fallback_is_allowed(self):
assert (
is_request_body_safe(
request_body={"model": "gpt-4", "fallbacks": [{"gpt-4": ["gpt-4-backup"]}]},
general_settings={},
llm_router=None,
model="gpt-4",
)
is True
)
def test_ordinary_dict_model_fallback_is_allowed(self):
assert (
is_request_body_safe(
request_body={"model": "gpt-4", "fallbacks": [{"gpt-4": [{"model": "gpt-4-backup"}]}]},
general_settings={},
llm_router=None,
model="gpt-4",
)
is True
)
class TestIsRequestBodySafeBlocksEndpointTargetingFields:
"""
@ -1551,6 +1857,46 @@ class TestIsRequestBodySafeBlocksEndpointTargetingFields:
)
class TestIsRequestBodySafeBlocksVertexCredentialAlias:
@pytest.mark.parametrize("field", ["vertex_ai_credentials"])
def test_field_in_request_body_is_rejected(self, field):
with pytest.raises(ValueError, match=field):
is_request_body_safe(
request_body={"model": "gpt-4", field: "attacker-supplied"},
general_settings={},
llm_router=None,
model="gpt-4",
)
@pytest.mark.parametrize("field", ["vertex_ai_credentials"])
def test_admin_opt_in_proxy_wide_allows(self, field):
assert (
is_request_body_safe(
request_body={"model": "gpt-4", field: "byok-supplied"},
general_settings={"allow_client_side_credentials": True},
llm_router=None,
model="gpt-4",
)
is True
)
def test_legitimate_request_body_param_still_allowed(self):
assert (
is_request_body_safe(
request_body={
"model": "gpt-4",
"temperature": 0.7,
"max_tokens": 128,
"user": "end-user-123",
},
general_settings={},
llm_router=None,
model="gpt-4",
)
is True
)
# ── is_request_body_safe nested-config recursion (VERIA-6) ────────────────────
@ -1770,6 +2116,21 @@ class TestObservabilityCallbackBans:
)
assert field in str(exc.value)
def test_observability_field_in_litellm_params_metadata_is_rejected(self):
with pytest.raises(ValueError) as exc:
is_request_body_safe(
request_body={
"model": "gpt-4",
"litellm_params": {
"metadata": {"turn_off_message_logging": False}
},
},
general_settings={},
llm_router=None,
model="gpt-4",
)
assert "turn_off_message_logging" in str(exc.value)
@pytest.mark.parametrize(
"metadata_key",
["metadata", "litellm_metadata"],
@ -1999,3 +2360,125 @@ class TestGetRequestRouteTemplate:
lambda self: (_ for _ in ()).throw(RuntimeError("boom"))
)
assert get_request_route_template(req) is None
class TestIsRequestBodySafeBlocksModelList:
"""model_list is an SDK-only field with no proxy API meaning; it must
be rejected from the request body regardless of any opt-in."""
def test_model_list_rejected_with_no_opt_in(self):
with pytest.raises(ValueError, match="model_list is not allowed"):
is_request_body_safe(
request_body={
"model": "gpt-4",
"messages": [{"role": "user", "content": "hi"}],
"model_list": [{"model_name": "x", "litellm_params": {}}],
},
general_settings={},
llm_router=None,
model="gpt-4",
)
def test_model_list_rejected_even_with_proxy_wide_opt_in(self):
with pytest.raises(ValueError, match="model_list is not allowed"):
is_request_body_safe(
request_body={
"model": "gpt-4",
"messages": [{"role": "user", "content": "hi"}],
"model_list": [],
},
general_settings={"allow_client_side_credentials": True},
llm_router=None,
model="gpt-4",
)
def test_normal_body_still_passes(self):
assert (
is_request_body_safe(
request_body={
"model": "gpt-4",
"messages": [{"role": "user", "content": "hi"}],
},
general_settings={},
llm_router=None,
model="gpt-4",
)
is True
)
class TestIsRequestBodySafeChecksBracketNotationMetadata:
"""Bracket notation is how multipart callers express nested metadata; it is
validated the same way the dict form is."""
@pytest.mark.parametrize("metadata_key", ["metadata", "litellm_metadata"])
def test_bracket_notation_banned_param_is_rejected(self, metadata_key):
with pytest.raises(ValueError, match="langfuse_host"):
is_request_body_safe(
request_body={
"purpose": "assistants",
f"{metadata_key}[langfuse_host]": "https://example.invalid",
},
general_settings={},
llm_router=None,
model="gpt-4",
)
def test_bracket_notation_api_base_is_rejected(self):
with pytest.raises(ValueError, match="api_base"):
is_request_body_safe(
request_body={"litellm_metadata[api_base]": "https://example.invalid"},
general_settings={},
llm_router=None,
model="gpt-4",
)
def test_bracket_notation_allowed_under_proxy_wide_opt_in(self):
assert (
is_request_body_safe(
request_body={"litellm_metadata[langfuse_host]": "https://byok.example"},
general_settings={"allow_client_side_credentials": True},
llm_router=None,
model="gpt-4",
)
is True
)
def test_benign_bracket_notation_metadata_is_allowed(self):
assert (
is_request_body_safe(
request_body={
"purpose": "assistants",
"litellm_metadata[spend_logs_metadata][owner]": "john",
"litellm_metadata[tags]": "production",
},
general_settings={},
llm_router=None,
model="gpt-4",
)
is True
)
def test_bracket_notation_matches_json_encoding_for_deeper_nesting(self):
"""A value nested below the first level is treated the same either way:
the check descends one level into metadata, for both encodings."""
deep_bracket = {
"litellm_metadata[spend_logs_metadata][langfuse_host]": "https://example.invalid"
}
deep_json = {
"litellm_metadata": {"spend_logs_metadata": {"langfuse_host": "https://example.invalid"}}
}
kwargs = dict(general_settings={}, llm_router=None, model="gpt-4")
assert is_request_body_safe(request_body=deep_bracket, **kwargs) is True
assert is_request_body_safe(request_body=deep_json, **kwargs) is True
def test_body_without_bracket_keys_is_unaffected(self):
assert (
is_request_body_safe(
request_body={"model": "gpt-4", "messages": [{"role": "user", "content": "hi"}]},
general_settings={},
llm_router=None,
model="gpt-4",
)
is True
)

141
tests/test_litellm/proxy/auth/test_router_override_fallback_auth.py
View file

@ -11,12 +11,22 @@ from unittest.mock import AsyncMock, patch
import pytest
from litellm.proxy._types import LitellmUserRoles, UserAPIKeyAuth
from litellm.proxy.auth.auth_utils import iter_request_fallback_targets
from litellm.proxy.auth.user_api_key_auth import (
_enforce_key_and_fallback_model_access,
iter_router_fallback_model_names,
_fallback_target_model_name,
)
def _fallback_model_names(fallbacks):
"""Model names the auth check validates for a top-level ``fallbacks`` value."""
return [
name
for target in iter_request_fallback_targets({"fallbacks": fallbacks})
if (name := _fallback_target_model_name(target)) is not None
]
def _key_with_models(models: List[str]) -> UserAPIKeyAuth:
return UserAPIKeyAuth(
api_key="hashed",
@ -26,37 +36,40 @@ def _key_with_models(models: List[str]) -> UserAPIKeyAuth:
)
# ── iter_router_fallback_model_names ─────────────────────────────────────────
# ── fallback model-name extraction ───────────────────────────────────────────
def testiter_router_fallback_model_names_router_config_shape():
def test_fallback_model_names_router_config_shape():
"""Router-config shape: ``[{primary: [fallback_list]}]``."""
assert list(
iter_router_fallback_model_names(
[{"gpt-3.5-turbo": ["gpt-4", "claude-3"]}, {"gpt-4o": ["o1"]}]
)
assert _fallback_model_names(
[{"gpt-3.5-turbo": ["gpt-4", "claude-3"]}, {"gpt-4o": ["o1"]}]
) == ["gpt-4", "claude-3", "o1"]
def testiter_router_fallback_model_names_simple_string_shape():
def test_fallback_model_names_simple_string_shape():
"""Simple top-level shape: list of strings."""
assert list(iter_router_fallback_model_names(["gpt-4", "claude-3"])) == [
assert _fallback_model_names(["gpt-4", "claude-3"]) == ["gpt-4", "claude-3"]
def test_fallback_model_names_client_side_shape():
"""ClientSideFallbackModel shape: ``[{"model": "..."}]``."""
assert _fallback_model_names([{"model": "gpt-4"}, {"model": "claude-3"}]) == [
"gpt-4",
"claude-3",
]
def testiter_router_fallback_model_names_client_side_shape():
"""ClientSideFallbackModel shape: ``[{"model": "..."}]``."""
assert list(
iter_router_fallback_model_names([{"model": "gpt-4"}, {"model": "claude-3"}])
) == ["gpt-4", "claude-3"]
def test_fallback_model_names_nested_deployment_fallbacks():
"""A deployment target's own nested fallback field is unrolled too."""
assert _fallback_model_names(
[{"primary": [{"model": "gpt-4", "fallbacks": [{"gpt-4": ["deepseek-chat"]}]}]}]
) == ["gpt-4", "deepseek-chat"]
def testiter_router_fallback_model_names_empty_or_none():
assert list(iter_router_fallback_model_names(None)) == []
assert list(iter_router_fallback_model_names([])) == []
assert list(iter_router_fallback_model_names("not a list")) == []
def test_fallback_model_names_empty_or_none():
assert _fallback_model_names(None) == []
assert _fallback_model_names([]) == []
assert _fallback_model_names("not a list") == []
# ── _enforce_key_and_fallback_model_access ────────────────────────────────────
@ -200,6 +213,98 @@ async def test_top_level_fallback_fields_validated(fallback_field):
assert "top-level-smuggled" in seen
@pytest.mark.asyncio
async def test_nested_deployment_fallback_inner_model_validated():
"""A model name nested several fallback rounds deep, inside a deployment
target's own ``fallbacks``, is extracted and passed to can_key_call_model."""
valid_token = _key_with_models(["gpt-3.5-turbo"])
request_data = {
"model": "gpt-3.5-turbo",
"fallbacks": [
{
"gpt-3.5-turbo": [
{
"model": "gpt-3.5-turbo",
"fallbacks": [{"gpt-3.5-turbo": ["deep-smuggled-model"]}],
}
]
}
],
}
seen: List[str] = []
async def fake_can_key_call_model(model, llm_model_list, valid_token, llm_router):
seen.append(model)
with (
patch(
"litellm.proxy.auth.user_api_key_auth.can_key_call_model",
side_effect=fake_can_key_call_model,
),
patch(
"litellm.proxy.auth.user_api_key_auth.is_valid_fallback_model",
new=AsyncMock(),
),
):
await _enforce_key_and_fallback_model_access(
valid_token=valid_token,
request_data=request_data,
route="/v1/chat/completions",
request=None,
llm_model_list=None,
llm_router=None,
)
assert "deep-smuggled-model" in seen
@pytest.mark.asyncio
async def test_model_less_fallback_dict_is_skipped_never_passed_as_none():
"""A fallback target dict without a ``model`` key is skipped, never passed
as ``None`` into can_key_call_model / is_valid_fallback_model."""
valid_token = _key_with_models(["gpt-3.5-turbo"])
request_data = {
"model": "gpt-3.5-turbo",
"fallbacks": [
{
"gpt-3.5-turbo": [
{"model": "real-fallback"},
{"api_base": "http://attacker"},
"string-fallback",
]
}
],
}
seen: List[str] = []
async def fake_can_key_call_model(model, llm_model_list, valid_token, llm_router):
seen.append(model)
with (
patch(
"litellm.proxy.auth.user_api_key_auth.can_key_call_model",
side_effect=fake_can_key_call_model,
),
patch(
"litellm.proxy.auth.user_api_key_auth.is_valid_fallback_model",
new=AsyncMock(),
),
):
await _enforce_key_and_fallback_model_access(
valid_token=valid_token,
request_data=request_data,
route="/v1/chat/completions",
request=None,
llm_model_list=None,
llm_router=None,
)
assert None not in seen
assert seen == ["gpt-3.5-turbo", "real-fallback", "string-fallback"]
@pytest.mark.asyncio
async def test_router_override_without_fallbacks_does_not_break_auth():
"""``router_settings_override`` set without any fallback fields is a

93
tests/test_litellm/proxy/health_endpoints/test_health_endpoints.py
View file

@ -1823,3 +1823,96 @@ def test_clean_endpoint_data_strips_credentials_keeps_routing_fields():
assert "aws_access_key_id" not in cleaned
assert cleaned.get("api_base") == "https://example.test/v1"
assert cleaned.get("api_version") == "2024-10-21"
class TestConfigBaseForHealthCheck:
"""A request that sets its own connection fields gets a base without the
configuration's credentials; anything it leaves unset still comes from
the configuration."""
CONFIG = {
"model": "openai/gpt-4o",
"api_key": "sk-configured",
"api_base": "https://configured.example/v1",
"vertex_credentials": "configured-creds",
"rpm": 100,
}
def _base(self, config, request, allow_client_side_credentials=False):
from litellm.proxy.health_endpoints._health_endpoints import (
_config_base_for_health_check,
)
return _config_base_for_health_check(
config, request, allow_client_side_credentials=allow_client_side_credentials
)
def test_request_without_connection_fields_inherits_config(self):
base = self._base(self.CONFIG, {"model": "openai/gpt-4o"})
assert base["api_key"] == "sk-configured"
assert base["api_base"] == "https://configured.example/v1"
def test_request_setting_api_base_does_not_inherit_config_credentials(self):
base = self._base(self.CONFIG, {"api_base": "https://caller.example/v1"})
assert "api_key" not in base
assert "api_base" not in base
assert "vertex_credentials" not in base
assert base["rpm"] == 100
def test_add_model_flow_keeps_its_own_credentials(self):
"""Adding a second deployment for an already-configured name sends a
complete connection; it is tested as sent, not as configured."""
request = {
"model": "openai/gpt-4o",
"api_base": "https://new-deployment.example/v1",
"api_key": "sk-new-deployment",
}
merged = {**self._base(self.CONFIG, request), **request}
assert merged["api_base"] == "https://new-deployment.example/v1"
assert merged["api_key"] == "sk-new-deployment"
assert "sk-configured" not in str(merged)
def test_destination_override_without_own_key_inherits_no_credential(self):
"""A request that redirects the destination but supplies no credential
of its own gets none from the configuration."""
request = {"api_base": "https://elsewhere.example"}
merged = {**self._base(self.CONFIG, request), **request}
assert "api_key" not in merged
assert "sk-configured" not in str(merged)
def test_non_api_base_destination_field_also_drops_credentials(self):
base = self._base(
{**self.CONFIG, "aws_secret_access_key": "configured-secret"},
{"aws_bedrock_runtime_endpoint": "https://caller.example"},
)
assert "api_key" not in base
assert "aws_secret_access_key" not in base
def test_opt_in_restores_configured_credentials_under_a_request_endpoint(self):
"""With general_settings.allow_client_side_credentials enabled, a request
may pair its own endpoint with the configured credentials, as before."""
base = self._base(
self.CONFIG,
{"api_base": "https://caller.example/v1"},
allow_client_side_credentials=True,
)
assert base["api_key"] == "sk-configured"
def test_stored_credential_reference_is_dropped_with_the_credentials(self):
"""A stored-credential name resolves to the same secrets downstream, so a
request that redirects the destination must not keep it either."""
config = {**self.CONFIG, "litellm_credential_name": "OpenAI-prod"}
base = self._base(config, {"api_base": "https://caller.example/v1"})
assert "litellm_credential_name" not in base
assert "api_key" not in base
def test_stored_credential_reference_kept_when_request_sets_no_connection(self):
"""The Admin UI tests a configured model by naming it plus its stored
credential and nothing else; that keeps working."""
config = {**self.CONFIG, "litellm_credential_name": "OpenAI-prod"}
base = self._base(
config,
{"model": "openai/gpt-4o", "litellm_credential_name": "OpenAI-prod", "custom_llm_provider": "openai"},
)
assert base["litellm_credential_name"] == "OpenAI-prod"
assert base["api_key"] == "sk-configured"

25
tests/test_litellm/proxy/image_endpoints/test_azure_routes.py
View file

@ -120,3 +120,28 @@ def test_azure_image_edit_route(client_no_auth):
assert called_kwargs["prompt"] == "A cute baby sea otter"
assert response.status_code == 200
assert response.json()["data"]
def test_azure_image_generation_route_rejects_url_valued_path_model(client_no_auth):
"""A URL-valued deployment segment is refused before any provider call."""
client, mock_aimage_generation, _ = client_no_auth
response = client.post(
"/openai/deployments/oobabooga/https://example.invalid/images/generations",
json={"prompt": "A cute baby sea otter", "n": 1, "size": "1024x1024"},
)
assert response.status_code == 400
assert "URL-valued" in response.text
mock_aimage_generation.assert_not_called()
def test_azure_image_generation_route_allows_ordinary_path_model(client_no_auth):
"""A deployment name that merely contains a provider prefix still routes."""
client, mock_aimage_generation, _ = client_no_auth
response = client.post(
"/openai/deployments/dall-e-3/images/generations",
json={"prompt": "A cute baby sea otter", "n": 1, "size": "1024x1024"},
)
assert response.status_code == 200
mock_aimage_generation.assert_called_once()

203
tests/test_litellm/proxy/proxy_server/test_proxy_config.py
View file

@ -795,6 +795,172 @@ def test_ProxyConfig__add_deployment_invalid_litellm_params_skips(monkeypatch):
assert pc._add_deployment(db_models=[bad]) == 0
def test_ProxyConfig__add_deployment_resolves_env_refs_after_db_decrypt(monkeypatch):
"""Every ``os.environ/`` value on an admin-scoped DB row resolves at
load time, regardless of the field name. Replaces the earlier
behavior where only fields in ``_DB_LITELLM_PARAM_ENV_REF_KEYS``
resolved: the whitelist has been removed so the resolver applies to
every string field."""
monkeypatch.setenv("LITELLM_DB_MODEL_API_KEY", "resolved-secret")
monkeypatch.setenv("LITELLM_MASTER_KEY", "master-secret")
monkeypatch.setattr(
"litellm.proxy.proxy_server.decrypt_value_helper",
lambda value, key, return_original_value: value,
)
fake_router = MagicMock()
fake_router.upsert_deployment = MagicMock(return_value=True)
monkeypatch.setattr("litellm.proxy.proxy_server.llm_router", fake_router)
pc = ProxyConfig()
db_model = SimpleNamespace(
model_id="model-1",
model_name="env-model",
model_info={"id": "model-1"},
litellm_params={
"model": "openai/gpt-4o-mini",
"api_key": "os.environ/LITELLM_DB_MODEL_API_KEY",
"api_base": "os.environ/LITELLM_MASTER_KEY",
},
blocked=False,
)
added = pc._add_deployment(db_models=[db_model])
deployment = fake_router.upsert_deployment.call_args.kwargs["deployment"]
assert added == 1
assert deployment.litellm_params.api_key == "resolved-secret"
assert deployment.litellm_params.api_base == "master-secret"
def test_ProxyConfig__add_deployment_resolves_team_env_refs(monkeypatch):
"""Team-scoped DB rows now resolve ``os.environ/`` refs the same way
admin rows do. The prior team-scoped short-circuit and the
field-by-field whitelist have both been removed; the write-side team
auth check in ``ModelManagementAuthChecks.can_user_make_model_call``
remains the single trust boundary. A literal (non-``os.environ/``)
value still passes through unchanged."""
monkeypatch.setenv("LITELLM_MASTER_KEY", "master-secret")
monkeypatch.setattr(
"litellm.proxy.proxy_server.decrypt_value_helper",
lambda value, key, return_original_value: value,
)
fake_router = MagicMock()
fake_router.upsert_deployment = MagicMock(return_value=True)
monkeypatch.setattr("litellm.proxy.proxy_server.llm_router", fake_router)
pc = ProxyConfig()
db_model = SimpleNamespace(
model_id="model-1",
model_name="model_name_team-1_abc",
model_info={"id": "model-1", "team_id": "team-1"},
litellm_params={
"model": "openai/gpt-4o-mini",
"api_key": "os.environ/LITELLM_MASTER_KEY",
"api_base": "https://team.example",
},
blocked=False,
)
added = pc._add_deployment(db_models=[db_model])
deployment = fake_router.upsert_deployment.call_args.kwargs["deployment"]
assert added == 1
assert deployment.litellm_params.api_key == "master-secret"
assert deployment.litellm_params.api_base == "https://team.example"
def test_ProxyConfig__add_deployment_resolves_env_refs_for_aws_bedrock_auth_params(
monkeypatch,
):
"""Regression: DB-stored Bedrock/SageMaker auth params like
``aws_role_name: os.environ/BEDROCK_ASSUME_ROLE_ARN`` must resolve at
DB-load time. PR #30867 removed request-time expansion in
``BaseAWSLLM.get_credentials``; without DB-load resolution the literal
string reaches STS and fails with ``ValidationError: ... is invalid``."""
aws_env = {
"aws_session_token": ("BEDROCK_SESSION_TOKEN", "resolved-session-token"),
"aws_region_name": ("BEDROCK_REGION", "us-east-1"),
"aws_session_name": ("BEDROCK_SESSION_NAME", "resolved-session"),
"aws_profile_name": ("BEDROCK_PROFILE", "resolved-profile"),
"aws_role_name": (
"BEDROCK_ASSUME_ROLE_ARN",
"arn:aws:iam::123456789012:role/resolved",
),
"aws_web_identity_token": ("BEDROCK_WEB_IDENTITY_TOKEN", "resolved-token"),
"aws_sts_endpoint": (
"BEDROCK_STS_ENDPOINT",
"https://sts.us-east-1.amazonaws.com",
),
"aws_external_id": ("BEDROCK_EXTERNAL_ID", "resolved-external-id"),
"aws_bedrock_runtime_endpoint": (
"BEDROCK_RUNTIME_ENDPOINT",
"https://bedrock-runtime.us-east-1.amazonaws.com",
),
"aws_bedrock_project_id": ("BEDROCK_PROJECT_ID", "resolved-project-id"),
"aws_batch_role_arn": (
"BEDROCK_BATCH_ROLE_ARN",
"arn:aws:iam::123456789012:role/batch",
),
"aws_workspace_id": ("BEDROCK_WORKSPACE_ID", "resolved-workspace-id"),
}
for _, (env_name, env_value) in aws_env.items():
monkeypatch.setenv(env_name, env_value)
monkeypatch.setattr(
"litellm.proxy.proxy_server.decrypt_value_helper",
lambda value, key, return_original_value: value,
)
fake_router = MagicMock()
fake_router.upsert_deployment = MagicMock(return_value=True)
monkeypatch.setattr("litellm.proxy.proxy_server.llm_router", fake_router)
pc = ProxyConfig()
litellm_params: Dict[str, Any] = {"model": "bedrock/anthropic.claude-v2"}
for key, (env_name, _) in aws_env.items():
litellm_params[key] = f"os.environ/{env_name}"
db_model = SimpleNamespace(
model_id="model-1",
model_name="bedrock-model",
model_info={"id": "model-1"},
litellm_params=litellm_params,
blocked=False,
)
added = pc._add_deployment(db_models=[db_model])
deployment = fake_router.upsert_deployment.call_args.kwargs["deployment"]
assert added == 1
for key, (_, expected) in aws_env.items():
assert getattr(deployment.litellm_params, key) == expected, key
def test_ProxyConfig__add_deployment_resolves_env_refs_on_arbitrary_field(monkeypatch):
"""A made-up field name that was never on the removed whitelist still
resolves ``os.environ/`` refs. Pins the "no whitelist" invariant:
the resolver applies to every string field, not a curated list."""
monkeypatch.setenv("SOME_CUSTOM_ENV", "resolved-custom-value")
monkeypatch.setattr(
"litellm.proxy.proxy_server.decrypt_value_helper",
lambda value, key, return_original_value: value,
)
fake_router = MagicMock()
fake_router.upsert_deployment = MagicMock(return_value=True)
monkeypatch.setattr("litellm.proxy.proxy_server.llm_router", fake_router)
pc = ProxyConfig()
db_model = SimpleNamespace(
model_id="model-1",
model_name="custom-field-model",
model_info={"id": "model-1"},
litellm_params={
"model": "openai/gpt-4o-mini",
"some_future_field": "os.environ/SOME_CUSTOM_ENV",
},
blocked=False,
)
added = pc._add_deployment(db_models=[db_model])
deployment = fake_router.upsert_deployment.call_args.kwargs["deployment"]
assert added == 1
assert deployment.litellm_params.some_future_field == "resolved-custom-value"
# ---------------------------------------------------------------------------
# ProxyConfig.decrypt_model_list_from_db
# ---------------------------------------------------------------------------
@ -837,6 +1003,43 @@ def test_ProxyConfig_decrypt_model_list_from_db_invalid_params_skips():
assert out == []
def test_ProxyConfig_decrypt_model_list_from_db_resolves_env_refs_after_db_decrypt(
monkeypatch,
):
"""Path B (feeding /v2/model/info fallback and /model/info fallback)
resolves every ``os.environ/`` field on admin-scoped rows, mirroring
path A. Both paths now share the same universal-resolution shape."""
monkeypatch.setenv("LITELLM_DB_MODEL_API_KEY", "resolved-secret")
monkeypatch.setenv("LITELLM_MASTER_KEY", "master-secret")
monkeypatch.setattr(
"litellm.proxy.proxy_server.decrypt_value_helper",
lambda value, key, return_original_value: (
"os.environ/LITELLM_DB_MODEL_API_KEY"
if key == "api_key"
else "os.environ/LITELLM_MASTER_KEY"
if key == "api_base"
else value
),
)
pc = ProxyConfig()
m = SimpleNamespace(
model_id="model-1",
model_name="env-model",
model_info={"id": "model-1"},
litellm_params={
"api_key": "encrypted-env-ref",
"api_base": "encrypted-api-base-env-ref",
"model": "openai/gpt-4o-mini",
},
blocked=False,
)
out = pc.decrypt_model_list_from_db(new_models=[m])
assert out[0]["litellm_params"]["api_key"] == "resolved-secret"
assert out[0]["litellm_params"]["api_base"] == "master-secret"
# ---------------------------------------------------------------------------
# ProxyConfig._update_llm_router
# ---------------------------------------------------------------------------

174
tests/test_litellm/proxy/test_litellm_pre_call_utils.py
View file

@ -824,10 +824,19 @@ async def test_add_litellm_data_to_request_strips_client_redaction_bypass_contro
"model": "gpt-3.5-turbo",
"messages": [{"role": "user", "content": "hello"}],
"turn_off_message_logging": False,
"metadata": {"headers": {"litellm-disable-message-redaction": "true"}},
"metadata": {
"headers": {"litellm-disable-message-redaction": "true"},
"turn_off_message_logging": False,
},
"litellm_metadata": json.dumps(
{"headers": {"LiteLLM-Disable-Message-Redaction": "true"}}
{
"headers": {"LiteLLM-Disable-Message-Redaction": "true"},
"turn_off_message_logging": "false",
}
),
"litellm_params": {
"metadata": {"turn_off_message_logging": False},
},
},
request=request_mock,
user_api_key_dict=UserAPIKeyAuth(api_key="hashed-key"),
@ -839,6 +848,9 @@ async def test_add_litellm_data_to_request_strips_client_redaction_bypass_contro
litellm.turn_off_message_logging = original_turn_off_message_logging
assert "turn_off_message_logging" not in updated
assert "turn_off_message_logging" not in (updated.get("litellm_params") or {}).get("metadata", {})
assert "turn_off_message_logging" not in updated["metadata"]
assert "turn_off_message_logging" not in (updated.get("litellm_metadata") or {})
assert "litellm-disable-message-redaction" not in {
header.lower() for header in updated["metadata"]["headers"]
}
@ -859,6 +871,158 @@ async def test_add_litellm_data_to_request_strips_client_redaction_bypass_contro
}
@pytest.mark.parametrize(
"admin_metadata_kwargs",
[
{
"metadata": {
"logging": [
{
"callback_name": "langfuse",
"callback_type": "success_and_failure",
"callback_vars": {"turn_off_message_logging": False},
}
]
}
},
{
"team_metadata": {
"logging": [
{
"callback_name": "langfuse",
"callback_type": "success_and_failure",
"callback_vars": {"turn_off_message_logging": False},
}
]
}
},
],
)
@pytest.mark.asyncio
async def test_add_litellm_data_to_request_admin_callback_vars_turn_off_message_logging_overrides_global(
admin_metadata_kwargs,
):
from litellm.litellm_core_utils.initialize_dynamic_callback_params import (
initialize_standard_callback_dynamic_params,
)
from litellm.litellm_core_utils.redact_messages import should_redact_message_logging
request_mock = MagicMock(spec=Request)
request_mock.url.path = "/v1/chat/completions"
request_mock.url = MagicMock()
request_mock.url.__str__.return_value = "http://localhost/v1/chat/completions"
request_mock.method = "POST"
request_mock.query_params = {}
request_mock.headers = {"Content-Type": "application/json"}
request_mock.client = MagicMock()
request_mock.client.host = "127.0.0.1"
original_turn_off_message_logging = litellm.turn_off_message_logging
litellm.turn_off_message_logging = True
try:
updated = await add_litellm_data_to_request(
data={
"model": "gpt-3.5-turbo",
"messages": [{"role": "user", "content": "hello"}],
},
request=request_mock,
user_api_key_dict=UserAPIKeyAuth(api_key="hashed-key", **admin_metadata_kwargs),
proxy_config=MagicMock(),
general_settings={},
version="test-version",
)
assert updated.get("turn_off_message_logging") == "False"
dynamic_params = initialize_standard_callback_dynamic_params(updated)
assert dynamic_params.get("turn_off_message_logging") == "False"
assert (
should_redact_message_logging(
{"standard_callback_dynamic_params": dynamic_params}
)
is False
)
finally:
litellm.turn_off_message_logging = original_turn_off_message_logging
@pytest.mark.parametrize(
"admin_metadata_kwargs",
[
{
"metadata": {
"logging": [
{
"callback_name": "langfuse",
"callback_type": "success_and_failure",
"callback_vars": {"turn_off_message_logging": True},
}
]
}
},
{
"team_metadata": {
"logging": [
{
"callback_name": "langfuse",
"callback_type": "success_and_failure",
"callback_vars": {"turn_off_message_logging": True},
}
]
}
},
],
)
@pytest.mark.asyncio
async def test_add_litellm_data_to_request_admin_callback_vars_turn_off_message_logging_enables_redaction_when_global_off(
admin_metadata_kwargs,
):
from litellm.litellm_core_utils.initialize_dynamic_callback_params import (
initialize_standard_callback_dynamic_params,
)
from litellm.litellm_core_utils.redact_messages import should_redact_message_logging
request_mock = MagicMock(spec=Request)
request_mock.url.path = "/v1/chat/completions"
request_mock.url = MagicMock()
request_mock.url.__str__.return_value = "http://localhost/v1/chat/completions"
request_mock.method = "POST"
request_mock.query_params = {}
request_mock.headers = {"Content-Type": "application/json"}
request_mock.client = MagicMock()
request_mock.client.host = "127.0.0.1"
original_turn_off_message_logging = litellm.turn_off_message_logging
litellm.turn_off_message_logging = False
try:
updated = await add_litellm_data_to_request(
data={
"model": "gpt-3.5-turbo",
"messages": [{"role": "user", "content": "hello"}],
},
request=request_mock,
user_api_key_dict=UserAPIKeyAuth(api_key="hashed-key", **admin_metadata_kwargs),
proxy_config=MagicMock(),
general_settings={},
version="test-version",
)
assert updated.get("turn_off_message_logging") == "True"
dynamic_params = initialize_standard_callback_dynamic_params(updated)
assert dynamic_params.get("turn_off_message_logging") == "True"
assert (
should_redact_message_logging(
{"standard_callback_dynamic_params": dynamic_params}
)
is True
)
finally:
litellm.turn_off_message_logging = original_turn_off_message_logging
@pytest.mark.parametrize(
"auth_kwargs",
[
@ -891,7 +1055,10 @@ async def test_add_litellm_data_to_request_allows_redaction_opt_out_with_admin_o
"model": "gpt-3.5-turbo",
"messages": [{"role": "user", "content": "hello"}],
"turn_off_message_logging": False,
"metadata": {"headers": {"litellm-disable-message-redaction": "true"}},
"metadata": {
"headers": {"litellm-disable-message-redaction": "true"},
"turn_off_message_logging": False,
},
"litellm_metadata": json.dumps(
{"headers": {"LiteLLM-Disable-Message-Redaction": "true"}}
),
@ -906,6 +1073,7 @@ async def test_add_litellm_data_to_request_allows_redaction_opt_out_with_admin_o
litellm.turn_off_message_logging = original_turn_off_message_logging
assert updated["turn_off_message_logging"] is False
assert updated["metadata"]["turn_off_message_logging"] is False
assert "litellm-disable-message-redaction" in {
header.lower() for header in updated["metadata"]["headers"]
}

53
tests/test_litellm/proxy/test_provider_url_destination_guard.py
View file

@ -39,6 +39,46 @@ class TestRejectUrlValuedDestinations:
assert exc_info.value.status_code == 400
assert exc_info.value.detail["param"] == "model"
def test_provider_prefixed_url_rejected(self):
with pytest.raises(HTTPException) as exc_info:
_reject_url_valued_destinations(
{"model": "huggingface/https://attacker.example/v1"}
)
assert exc_info.value.status_code == 400
assert exc_info.value.detail["param"] == "model"
def test_comma_batch_smuggled_url_rejected(self):
with pytest.raises(HTTPException) as exc_info:
_reject_url_valued_destinations(
{"model": "gpt-4,huggingface/https://attacker.example/v1"}
)
assert exc_info.value.status_code == 400
assert exc_info.value.detail["param"] == "model"
def test_provider_prefixed_uppercase_scheme_url_rejected(self):
with pytest.raises(HTTPException) as exc_info:
_reject_url_valued_destinations(
{"model": "huggingface/HTTPS://evil.example/v1"}
)
assert exc_info.value.status_code == 400
assert exc_info.value.detail["param"] == "model"
def test_provider_prefixed_plain_model_passes(self):
_reject_url_valued_destinations({"model": "huggingface/BAAI/bge-small-en"})
def test_comma_batch_plain_models_pass(self):
_reject_url_valued_destinations({"model": "gpt-4,huggingface/BAAI/bge-small-en"})
def test_provider_prefixed_url_respects_allowlist(self, monkeypatch):
monkeypatch.setattr(
litellm,
"provider_url_destination_allowed_hosts",
["trusted.example"],
)
_reject_url_valued_destinations(
{"model": "huggingface/https://trusted.example/v1"}
)
def test_url_valued_file_id_rejected(self):
with pytest.raises(HTTPException) as exc_info:
_reject_url_valued_destinations(
@ -137,3 +177,16 @@ async def test_add_litellm_data_to_request_rejects_url_valued_model():
)
assert exc_info.value.status_code == 400
assert exc_info.value.detail["param"] == "model"
class TestNonStringDestinationValues:
"""Only string identifiers are inspected. Anything else is left alone for the
request's normal validation to handle."""
@pytest.mark.parametrize("value", [123, None, True, {"a": 1}, ["x"], 1.5])
def test_non_string_model_is_ignored(self, value):
_reject_url_valued_destinations({"model": value})
@pytest.mark.parametrize("value", [123, None, True, {"a": 1}, ["x"]])
def test_non_string_file_id_is_ignored(self, value):
_reject_url_valued_destinations({"file_id": value})

515
uv.lock generated
View file

@ -9,7 +9,7 @@ resolution-markers = [
]
[options]
exclude-newer = "2026-06-29T23:53:46.228718Z"
exclude-newer = "2026-08-05T08:07:59.128698Z"
exclude-newer-span = "P3D"
[manifest]
@ -19,9 +19,10 @@ members = [
"litellm-proxy-extras",
]
constraints = [
{ name = "aiohttp", specifier = ">=3.14.1,<4.0" },
{ name = "aiohttp", specifier = ">=3.14.2,<4.0" },
{ name = "tornado", specifier = ">=6.5.6" },
]
overrides = [{ name = "cryptography", specifier = ">=50.0.0,<51.0" }]
[[package]]
name = "a2a-sdk"
@ -71,7 +72,7 @@ wheels = [
[[package]]
name = "aiohttp"
version = "3.14.1"
version = "3.14.3"
source = { registry = "https://pypi.org/simple" }
dependencies = [
{ name = "aiohappyeyeballs" },
@ -84,85 +85,85 @@ dependencies = [
{ name = "typing-extensions", marker = "python_full_version < '3.13'" },
{ name = "yarl" },
]
sdist = { url = "https://files.pythonhosted.org/packages/82/78/8ea7308cac6934de8c74a14f3d5f65d1c89287426688be79538d0e5c013d/aiohttp-3.14.1.tar.gz", hash = "sha256:307f2cff90a764d329e77040603fa032db89c5c24fdad50c4c15334cba744035", size = 7955794, upload-time = "2026-06-07T21:09:35.529Z" }
sdist = { url = "https://files.pythonhosted.org/packages/58/d9/22ce5786ac0c1653ae8b6c23bded02c1686d11f0dbb45b31ce128e0df985/aiohttp-3.14.3.tar.gz", hash = "sha256:9491196535a88924a60afd5b5f434b5b203b6cc616250878dbdb223a8f7844bc", size = 7971213, upload-time = "2026-07-23T01:57:27.037Z" }
wheels = [
{ url = "https://files.pythonhosted.org/packages/6d/67/58ded4b3f2e10f94972d8928050c85330e249a31dd45a0e5f3c0e9c3fa05/aiohttp-3.14.1-cp310-cp310-macosx_10_9_universal2.whl", hash = "sha256:8f6bb621e5863cfe8fe5ff5468002d200ec31f30f1280b259dc505b02595099e", size = 766140, upload-time = "2026-06-07T21:05:37.471Z" },
{ url = "https://files.pythonhosted.org/packages/18/68/4ae5b4e08943f316594bb68da89957d3baf5760588fa09509594bd777e4b/aiohttp-3.14.1-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:4f7215cb3933784f79ed20e5f050e15984f390424339b22375d5a53c933a0491", size = 519430, upload-time = "2026-06-07T21:05:40.751Z" },
{ url = "https://files.pythonhosted.org/packages/cb/c1/316c8f3549dbe5245f92bfd523ec6f32dd4d98cafe21df3f6a19b1184c75/aiohttp-3.14.1-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:d9d4e294455b23a68c9b8f042d0e8e377a265bcb15332753695f6e5b6819e0ce", size = 514406, upload-time = "2026-06-07T21:05:42.111Z" },
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