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litellm/tests/test_litellm/proxy/auth/test_auth_utils.py
Yassin Kortam bf59b7e23d
feat(rust): route /chat/completions through the Rust core for anthropic and bedrock (#37241) 
Adds a chat_completions route module to litellm-core, mirroring the messages
route, plus Anthropic Messages and Bedrock Converse provider configs. The
per-model `rust: true` opt-in now covers /chat/completions for both providers.

The core accepts an allowlisted subset (text conversations, non-streaming) and
returns CoreError::Unsupported for anything else, so tool calls, multimodal
content and streaming fall back to the Python path transparently.

Resolves LIT-5698
2026-08-20 16:15:24 -07:00

3281 lines
122 KiB
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"""
Unit tests for auth_utils functions related to rate limiting and customer ID extraction.
"""
import base64
from typing import Optional
from unittest.mock import MagicMock, patch
import pytest
from fastapi import Request
from litellm.proxy._types import UserAPIKeyAuth
from litellm.proxy.auth.auth_utils import (
_get_customer_id_from_standard_headers,
abbreviate_api_key,
check_complete_credentials,
custom_auth_common_checks_warning,
warn_once_if_custom_auth_skips_common_checks,
get_end_user_id_from_request_body,
get_key_mcp_rpm_limit,
get_key_model_rpm_limit,
get_key_model_tpm_limit,
get_key_tag_rpm_limit,
get_model_from_request,
get_project_model_rpm_limit,
get_project_model_tpm_limit,
get_request_route_template,
is_request_body_safe,
)
class TestCustomAuthCommonChecksWarning:
"""custom_auth_common_checks_warning only warns when custom auth is configured
and the common-checks opt-in is off, since that is the only state where
project/team enforcement silently does nothing."""
def test_warns_when_custom_auth_configured_and_checks_off(self):
warning = custom_auth_common_checks_warning(
custom_auth_configured=True,
run_common_checks=False,
)
assert warning is not None
assert "custom_auth_run_common_checks: true" in warning
assert "https://docs.litellm.ai/docs/proxy/custom_auth" in warning
def test_no_warning_when_common_checks_enabled(self):
assert (
custom_auth_common_checks_warning(
custom_auth_configured=True,
run_common_checks=True,
)
is None
)
def test_no_warning_when_custom_auth_not_configured(self):
assert (
custom_auth_common_checks_warning(
custom_auth_configured=False,
run_common_checks=False,
)
is None
)
assert (
custom_auth_common_checks_warning(
custom_auth_configured=False,
run_common_checks=True,
)
is None
)
class TestWarnOnceIfCustomAuthSkipsCommonChecks:
"""The startup warning must fire at most once per process, since load_config
re-runs on hot-reload / config refresh and would otherwise spam the log."""
@pytest.fixture(autouse=True)
def _reset_sentinel(self, monkeypatch):
monkeypatch.setattr(
"litellm.proxy.auth.auth_utils._custom_auth_common_checks_warning_emitted",
False,
)
def test_warns_only_once_across_repeated_calls(self):
logger = MagicMock()
for _ in range(3):
warn_once_if_custom_auth_skips_common_checks(
custom_auth_configured=True,
run_common_checks=False,
logger=logger,
)
assert logger.warning.call_count == 1
assert "custom_auth_run_common_checks" in logger.warning.call_args[0][0]
def test_does_not_warn_when_common_checks_enabled(self):
logger = MagicMock()
warn_once_if_custom_auth_skips_common_checks(
custom_auth_configured=True,
run_common_checks=True,
logger=logger,
)
assert logger.warning.call_count == 0
class TestGetKeyModelRpmLimit:
"""Tests for get_key_model_rpm_limit function."""
def test_returns_key_metadata_when_present(self):
"""Key metadata takes priority over team metadata."""
user_api_key_dict = UserAPIKeyAuth(
api_key="sk-123",
metadata={"model_rpm_limit": {"gpt-4": 100}},
team_metadata={"model_rpm_limit": {"gpt-4": 50}},
)
result = get_key_model_rpm_limit(user_api_key_dict)
assert result == {"gpt-4": 100}
def test_falls_back_to_team_metadata_when_key_has_other_metadata(self):
"""Should fall back to team metadata when key metadata exists but has no model_rpm_limit."""
user_api_key_dict = UserAPIKeyAuth(
api_key="sk-123",
metadata={
"some_other_key": "value"
}, # Has metadata, but not model_rpm_limit
team_metadata={"model_rpm_limit": {"gpt-4": 50}},
)
result = get_key_model_rpm_limit(user_api_key_dict)
assert result == {"gpt-4": 50}
def test_extracts_from_model_max_budget(self):
"""Should extract rpm_limit from model_max_budget when metadata is empty."""
user_api_key_dict = UserAPIKeyAuth(
api_key="sk-123",
model_max_budget={
"gpt-4": {"rpm_limit": 100, "tpm_limit": 1000},
"gpt-3.5-turbo": {"rpm_limit": 200},
},
)
result = get_key_model_rpm_limit(user_api_key_dict)
assert result == {"gpt-4": 100, "gpt-3.5-turbo": 200}
def test_skips_models_without_rpm_limit(self):
"""Should skip models that don't have rpm_limit in model_max_budget."""
user_api_key_dict = UserAPIKeyAuth(
api_key="sk-123",
model_max_budget={
"gpt-4": {"rpm_limit": 100},
"gpt-3.5-turbo": {"tpm_limit": 1000}, # No rpm_limit
},
)
result = get_key_model_rpm_limit(user_api_key_dict)
assert result == {"gpt-4": 100}
def test_returns_none_when_no_limits_configured(self):
"""Should return None when no rate limits are configured."""
user_api_key_dict = UserAPIKeyAuth(api_key="sk-123")
result = get_key_model_rpm_limit(user_api_key_dict)
assert result is None
def test_team_metadata_empty_rpm_dict_falls_through_to_deployment_default(self):
"""Explicitly empty team model_rpm_limit ({}) should be returned as-is, not fallen through."""
# An empty dict is a valid team limit map (no per-model limits configured).
# It should be returned directly rather than falling through to deployment defaults,
# so a team with an empty map is treated as unconstrained at the team level.
user_api_key_dict = UserAPIKeyAuth(
api_key="sk-123",
team_metadata={"model_rpm_limit": {}},
)
result = get_key_model_rpm_limit(user_api_key_dict)
assert result == {}
class TestGetKeyMcpRpmLimit:
def test_empty_dict_limits_are_returned(self):
key_override = UserAPIKeyAuth(
api_key="sk-123",
metadata={"mcp_rpm_limit": {}},
team_metadata={"mcp_rpm_limit": {"github": 50}},
)
assert get_key_mcp_rpm_limit(key_override) == {}
team_empty = UserAPIKeyAuth(
api_key="sk-123",
team_metadata={"mcp_rpm_limit": {}},
)
assert get_key_mcp_rpm_limit(team_empty) == {}
class TestGetKeyModelTpmLimit:
"""Tests for get_key_model_tpm_limit function."""
def test_returns_key_metadata_when_present(self):
"""Key metadata takes priority over team metadata."""
user_api_key_dict = UserAPIKeyAuth(
api_key="sk-123",
metadata={"model_tpm_limit": {"gpt-4": 10000}},
team_metadata={"model_tpm_limit": {"gpt-4": 5000}},
)
result = get_key_model_tpm_limit(user_api_key_dict)
assert result == {"gpt-4": 10000}
def test_falls_back_to_team_metadata_when_key_has_other_metadata(self):
"""Should fall back to team metadata when key metadata exists but has no model_tpm_limit."""
user_api_key_dict = UserAPIKeyAuth(
api_key="sk-123",
metadata={
"some_other_key": "value"
}, # Has metadata, but not model_tpm_limit
team_metadata={"model_tpm_limit": {"gpt-4": 5000}},
)
result = get_key_model_tpm_limit(user_api_key_dict)
assert result == {"gpt-4": 5000}
def test_extracts_from_model_max_budget(self):
"""Should extract tpm_limit from model_max_budget when metadata is empty."""
user_api_key_dict = UserAPIKeyAuth(
api_key="sk-123",
model_max_budget={
"gpt-4": {"tpm_limit": 10000, "rpm_limit": 100},
"gpt-3.5-turbo": {"tpm_limit": 20000},
},
)
result = get_key_model_tpm_limit(user_api_key_dict)
assert result == {"gpt-4": 10000, "gpt-3.5-turbo": 20000}
def test_skips_models_without_tpm_limit(self):
"""Should skip models that don't have tpm_limit in model_max_budget."""
user_api_key_dict = UserAPIKeyAuth(
api_key="sk-123",
model_max_budget={
"gpt-4": {"tpm_limit": 10000},
"gpt-3.5-turbo": {"rpm_limit": 100}, # No tpm_limit
},
)
result = get_key_model_tpm_limit(user_api_key_dict)
assert result == {"gpt-4": 10000}
def test_returns_none_when_no_limits_configured(self):
"""Should return None when no rate limits are configured."""
user_api_key_dict = UserAPIKeyAuth(api_key="sk-123")
result = get_key_model_tpm_limit(user_api_key_dict)
assert result is None
def test_model_max_budget_priority_over_team(self):
"""model_max_budget should take priority over team_metadata."""
user_api_key_dict = UserAPIKeyAuth(
api_key="sk-123",
model_max_budget={"gpt-4": {"tpm_limit": 10000}},
team_metadata={"model_tpm_limit": {"gpt-4": 5000}},
)
result = get_key_model_tpm_limit(user_api_key_dict)
assert result == {"gpt-4": 10000}
def test_team_metadata_empty_tpm_dict_falls_through_to_deployment_default(self):
"""Explicitly empty team model_tpm_limit ({}) should be returned as-is, not fallen through."""
# An empty dict is a valid team limit map (no per-model limits configured).
# It should be returned directly rather than falling through to deployment defaults,
# so a team with an empty map is treated as unconstrained at the team level.
user_api_key_dict = UserAPIKeyAuth(
api_key="sk-123",
team_metadata={"model_tpm_limit": {}},
)
result = get_key_model_tpm_limit(user_api_key_dict)
assert result == {}
def test_skips_deployments_with_malformed_limit_value(self):
"""Deployments with non-integer-parseable limit values are skipped without raising."""
user_api_key_dict = UserAPIKeyAuth(api_key="sk-123")
mock_router = MagicMock()
mock_router.get_model_list.return_value = [
{
"model_name": "model1",
"litellm_params": {"default_api_key_tpm_limit": "not-a-number"},
},
_make_deployment_dict("model1", tpm=500),
]
with patch(_ROUTER_PATCH, mock_router):
result = get_key_model_tpm_limit(user_api_key_dict, model_name="model1")
# The malformed deployment is skipped; the valid one provides 500
assert result == {"model1": 500}
class TestGetCustomerIdFromStandardHeaders:
"""Tests for _get_customer_id_from_standard_headers helper function."""
def test_should_return_customer_id_from_x_litellm_customer_id_header(self):
"""Should extract customer ID from x-litellm-customer-id header."""
headers = {"x-litellm-customer-id": "customer-123"}
result = _get_customer_id_from_standard_headers(request_headers=headers)
assert result == "customer-123"
def test_should_return_customer_id_from_x_litellm_end_user_id_header(self):
"""Should extract customer ID from x-litellm-end-user-id header."""
headers = {"x-litellm-end-user-id": "end-user-456"}
result = _get_customer_id_from_standard_headers(request_headers=headers)
assert result == "end-user-456"
def test_should_return_none_when_headers_is_none(self):
"""Should return None when headers is None."""
result = _get_customer_id_from_standard_headers(request_headers=None)
assert result is None
def test_should_return_none_when_no_standard_headers_present(self):
"""Should return None when no standard customer ID headers are present."""
headers = {"x-other-header": "some-value"}
result = _get_customer_id_from_standard_headers(request_headers=headers)
assert result is None
class TestGetEndUserIdFromRequestBodyWithStandardHeaders:
"""Tests for get_end_user_id_from_request_body with standard customer ID headers."""
def test_should_prioritize_standard_header_over_body_user(self):
"""Standard customer ID header should take precedence over body user field."""
headers = {"x-litellm-customer-id": "header-customer"}
request_body = {"user": "body-user"}
with patch("litellm.proxy.proxy_server.general_settings", {}):
result = get_end_user_id_from_request_body(
request_body=request_body, request_headers=headers
)
assert result == "header-customer"
def test_should_fall_back_to_body_when_no_standard_header(self):
"""Should fall back to body user when no standard headers are present."""
headers = {"x-other-header": "value"}
request_body = {"user": "body-user"}
with patch("litellm.proxy.proxy_server.general_settings", {}):
result = get_end_user_id_from_request_body(
request_body=request_body, request_headers=headers
)
assert result == "body-user"
def _request_dispatched_to(endpoint) -> Request:
"""Build a minimal Request whose FastAPI-resolved endpoint is ``endpoint``,
mirroring what Starlette sets in ``scope`` once routing has matched."""
return Request(scope={"type": "http", "headers": [], "endpoint": endpoint})
def _pass_through_endpoint():
from litellm.types.passthrough_endpoints.pass_through_endpoints import (
LITELLM_PASS_THROUGH_ENDPOINT_MARKER,
)
def endpoint(): # stand-in for create_pass_through_route's handler
...
setattr(endpoint, LITELLM_PASS_THROUGH_ENDPOINT_MARKER, True)
return endpoint
def test_get_model_from_request_skips_pass_through_dispatched_request():
"""When FastAPI dispatched the request to a user-defined pass-through handler,
the body `model` names an upstream model and must not be treated as a LiteLLM
model for allowlist/budget enforcement."""
assert (
get_model_from_request(
request_data={"model": "upstream-special-model"},
route="/my-custom-endpoint",
request=_request_dispatched_to(_pass_through_endpoint()),
)
is None
)
def test_get_model_from_request_enforces_when_builtin_handler_dispatched():
"""A custom pass-through path that collides with a built-in route resolves to the
built-in handler (no marker), so the body `model` must still be extracted and
enforced. Same request path as above, but dispatched to a non-pass-through
endpoint: the model must NOT be suppressed."""
def builtin_chat_completions():
...
assert (
get_model_from_request(
request_data={"model": "gpt-4o"},
route="/v1/chat/completions",
request=_request_dispatched_to(builtin_chat_completions),
)
== "gpt-4o"
)
def test_get_model_from_request_no_request_extracts_model():
"""Callers without a request object (e.g. budget reservation) still extract the
model; the pass-through suppression only applies to a dispatched pass-through
handler."""
assert (
get_model_from_request(
request_data={"model": "gpt-4o"},
route="/v1/chat/completions",
)
== "gpt-4o"
)
def test_get_model_from_request_supports_google_model_names_with_slashes():
assert (
get_model_from_request(
request_data={},
route="/v1beta/models/bedrock/claude-sonnet-3.7:generateContent",
)
== "bedrock/claude-sonnet-3.7"
)
assert (
get_model_from_request(
request_data={},
route="/models/hosted_vllm/gpt-oss-20b:generateContent",
)
== "hosted_vllm/gpt-oss-20b"
)
def test_get_model_from_request_vertex_passthrough_still_works():
route = "/vertex_ai/v1/projects/p/locations/l/publishers/google/models/gemini-1.5-pro:generateContent"
assert get_model_from_request(request_data={}, route=route) == "gemini-1.5-pro"
def test_get_model_from_request_openai_deployment_route_still_works():
assert (
get_model_from_request(
request_data={},
route="/openai/deployments/my-azure-deployment/chat/completions",
)
== "my-azure-deployment"
)
def test_get_model_from_request_includes_file_endpoint_header_model():
assert (
get_model_from_request(
request_data={},
route="/v1/files",
request_headers={"X-LiteLLM-Model": "restricted-model"},
)
== "restricted-model"
)
def test_get_model_from_request_ignores_routing_header_on_standard_llm_routes():
assert (
get_model_from_request(
request_data={"model": "allowed-model"},
route="/v1/chat/completions",
request_headers={"x-litellm-model": "restricted-model"},
)
== "allowed-model"
)
def test_get_model_from_request_authorizes_all_file_routing_model_sources():
models = get_model_from_request(
request_data={"model": "body-model"},
route="/v1/files",
request_headers={"x-litellm-model": "header-model"},
request_query_params={"target_model_names": "query-model-a,query-model-b"},
)
assert isinstance(models, list)
assert set(models) == {
"body-model",
"query-model-a",
"query-model-b",
"header-model",
}
def test_get_model_from_request_extracts_simple_encoded_file_id_model():
from litellm.proxy.openai_files_endpoints.common_utils import (
encode_file_id_with_model,
)
file_id = encode_file_id_with_model(
file_id="file-provider-id",
model="restricted-model",
)
assert (
get_model_from_request(
request_data={"file_id": file_id},
route="/v1/files/{file_id}",
)
== "restricted-model"
)
def test_get_model_from_request_extracts_unified_file_id_models():
raw_unified_file_id = (
"litellm_proxy:application/octet-stream;unified_id,test-id;"
"target_model_names,model-a,model-b;llm_output_file_id,file-provider-id"
)
encoded_unified_file_id = (
base64.urlsafe_b64encode(raw_unified_file_id.encode()).decode().rstrip("=")
)
assert get_model_from_request(
request_data={"file_id": encoded_unified_file_id},
route="/v1/files/{file_id}",
) == ["model-a", "model-b"]
def test_get_model_from_request_extracts_eval_completion_model():
assert (
get_model_from_request(
request_data={"completion": {"model": "judge-model"}},
route="/v1/evals/{eval_id}/runs",
)
== "judge-model"
)
def test_get_model_from_request_includes_fine_tuning_target_model_query():
assert (
get_model_from_request(
request_data={},
route="/v1/fine_tuning/jobs",
request_query_params={"target_model_names": "fine-tune-model"},
)
== "fine-tune-model"
)
def test_get_model_from_request_extracts_video_id_model():
from litellm.types.videos.utils import encode_video_id_with_provider
video_id = encode_video_id_with_provider(
video_id="video-provider-id",
provider="openai",
model_id="video-model",
)
assert (
get_model_from_request(
request_data={"video_id": video_id},
route="/v1/videos/{video_id}",
)
== "video-model"
)
def test_get_model_from_request_resolves_video_id_model_with_router():
from litellm.types.videos.utils import encode_video_id_with_provider
provider_video_id = (
"projects/test-project/locations/us-central1/publishers/google/models/"
"veo-3.1-generate-001/operations/operation-id"
)
video_id = encode_video_id_with_provider(
video_id=provider_video_id,
provider="vertex_ai",
model_id="veo-3.1-generate-001",
)
llm_router = MagicMock()
llm_router.resolve_model_name_from_model_id.return_value = (
"gcp/google/veo-3.1-generate-001"
)
assert (
get_model_from_request(
request_data={"video_id": video_id},
route="/v1/videos/{video_id}",
llm_router=llm_router,
)
== "gcp/google/veo-3.1-generate-001"
)
llm_router.resolve_model_name_from_model_id.assert_called_once_with(
"veo-3.1-generate-001"
)
_BATCH_DEPLOYMENT_ID = "8d0eaa7e6c6f54a425dfd0062cb6b0dc"
def _managed_batch_router():
from litellm.router import Router
return Router(
model_list=[
{
"model_name": "bedrock-batch-model",
"litellm_params": {
"model": "bedrock/global.anthropic.claude-haiku-4-5-20251001-v1:0",
},
"model_info": {"id": _BATCH_DEPLOYMENT_ID},
},
{
"model_name": "some-other-model",
"litellm_params": {"model": "openai/gpt-4o-mini", "api_key": "test-key"},
"model_info": {"id": "a-different-deployment-id"},
},
]
)
def _encode_managed_id(decoded: str) -> str:
return base64.urlsafe_b64encode(decoded.encode()).decode().rstrip("=")
_MANAGED_BATCH_ID = _encode_managed_id(
f"litellm_proxy;model_id:{_BATCH_DEPLOYMENT_ID};llm_batch_id:provider-batch-123"
)
_MANAGED_BATCH_OUTPUT_FILE_ID = _encode_managed_id(
f"litellm_proxy;model_id:{_BATCH_DEPLOYMENT_ID};llm_batch_id:provider-batch-123;"
"llm_output_file_id:provider-file-456"
)
@pytest.mark.parametrize(
"route, request_data",
[
("/v1/batches/{batch_id}", {"batch_id": _MANAGED_BATCH_ID}),
("/v1/batches/{batch_id}/cancel", {"batch_id": _MANAGED_BATCH_ID}),
("/v1/files/{file_id}", {"file_id": _MANAGED_BATCH_OUTPUT_FILE_ID}),
("/v1/files/{file_id}/content", {"file_id": _MANAGED_BATCH_OUTPUT_FILE_ID}),
],
)
def test_get_model_from_request_resolves_batch_id_deployment_to_model_name(route, request_data):
"""Regression for #32580: managed batch retrieve/cancel and managed batch output
file reads encode the deployment model_id into the resource id. The auth layer must
resolve that id back to the public model group name so model-access checks compare
against the model group, not the raw deployment id."""
assert (
get_model_from_request(
request_data=request_data,
route=route,
llm_router=_managed_batch_router(),
)
== "bedrock-batch-model"
)
@pytest.mark.asyncio
@pytest.mark.parametrize(
"route, request_data",
[
("/v1/batches/{batch_id}", {"batch_id": _MANAGED_BATCH_ID}),
("/v1/batches/{batch_id}/cancel", {"batch_id": _MANAGED_BATCH_ID}),
("/v1/files/{file_id}/content", {"file_id": _MANAGED_BATCH_OUTPUT_FILE_ID}),
],
)
async def test_managed_batch_routes_pass_team_model_access_check(route, request_data):
"""End-to-end regression for #32580: a team scoped to the batch model group got
``team_model_access_denied`` on retrieve/cancel because the deployment id, not the
model group, was authorized. Fails pre-fix with the deployment id in the message."""
from litellm.proxy._types import LiteLLM_TeamTable
from litellm.proxy.auth.auth_checks import can_team_access_model
llm_router = _managed_batch_router()
model = get_model_from_request(request_data=request_data, route=route, llm_router=llm_router)
assert (
await can_team_access_model(
model=model,
team_object=LiteLLM_TeamTable(team_id="team-batch", models=["bedrock-batch-model"]),
llm_router=llm_router,
)
is True
)
with pytest.raises(Exception, match="team not allowed to access model"):
await can_team_access_model(
model=model,
team_object=LiteLLM_TeamTable(team_id="team-other", models=["some-other-model"]),
llm_router=llm_router,
)
def test_get_model_from_request_resolves_character_id_model_with_router():
from litellm.types.videos.utils import encode_character_id_with_provider
character_id = encode_character_id_with_provider(
character_id="character-provider-id",
provider="vertex_ai",
model_id="veo-3.1-generate-001",
)
llm_router = MagicMock()
llm_router.resolve_model_name_from_model_id.return_value = (
"gcp/google/veo-3.1-generate-001"
)
assert (
get_model_from_request(
request_data={"character_id": character_id},
route="/v1/videos/characters/{character_id}",
llm_router=llm_router,
)
== "gcp/google/veo-3.1-generate-001"
)
llm_router.resolve_model_name_from_model_id.assert_called_once_with(
"veo-3.1-generate-001"
)
def test_get_model_from_request_only_runs_media_decoders_for_matching_fields():
with (
patch(
"litellm.types.videos.utils.decode_video_id_with_provider",
return_value={"model_id": "video-model"},
) as video_decoder,
patch(
"litellm.types.videos.utils.decode_character_id_with_provider",
return_value={"model_id": "character-model"},
) as character_decoder,
):
assert (
get_model_from_request(
request_data={"file_id": "file-provider-id"},
route="/v1/files/{file_id}",
)
is None
)
video_decoder.assert_not_called()
character_decoder.assert_not_called()
assert (
get_model_from_request(
request_data={"video_id": "video-provider-id"},
route="/v1/videos/{video_id}",
)
== "video-model"
)
video_decoder.assert_called_once_with("video-provider-id")
character_decoder.assert_not_called()
video_decoder.reset_mock()
character_decoder.reset_mock()
assert (
get_model_from_request(
request_data={"character_id": "character-provider-id"},
route="/v1/videos/{character_id}",
)
== "character-model"
)
video_decoder.assert_not_called()
character_decoder.assert_called_once_with("character-provider-id")
def test_get_model_from_request_handles_managed_id_decoder_failures():
with (
patch(
"litellm.proxy.openai_files_endpoints.common_utils.decode_model_from_file_id",
side_effect=Exception("decode failed"),
),
patch(
"litellm.llms.base_llm.managed_resources.utils.parse_unified_id",
side_effect=Exception("parse failed"),
),
patch(
"litellm.types.videos.utils.decode_video_id_with_provider",
side_effect=Exception("video decode failed"),
),
):
assert (
get_model_from_request(
request_data={"file_id": "not-a-managed-resource-id"},
route="/v1/files/{file_id}",
)
is None
)
assert (
get_model_from_request(
request_data={"video_id": "not-a-managed-resource-id"},
route="/v1/videos/{video_id}",
)
is None
)
@pytest.mark.parametrize(
"route",
[
"/realtime/client_secrets",
"/v1/realtime/client_secrets",
"/openai/v1/realtime/client_secrets",
"/realtime/calls",
"/v1/realtime/calls",
"/openai/v1/realtime/calls",
],
)
def test_get_model_from_request_extracts_realtime_session_model(route):
"""The effective realtime model lives in ``session.model`` (not the
top-level ``model``). It must be surfaced so can_key_call_model() can
validate the model a restricted key is actually requesting.
Regression test for the model-access bypass on the GA Realtime WebRTC
HTTP routes (https://github.com/BerriAI/litellm/issues/29923).
"""
assert (
get_model_from_request(
request_data={"session": {"type": "realtime", "model": "gpt-realtime"}},
route=route,
)
== "gpt-realtime"
)
def test_get_model_from_request_realtime_includes_top_level_and_session_model():
"""When both top-level and session model are present, both are returned so
neither path can smuggle a disallowed model past the model-access check."""
models = get_model_from_request(
request_data={
"model": "gpt-4o-realtime-preview",
"session": {"type": "realtime", "model": "gpt-realtime"},
},
route="/v1/realtime/client_secrets",
)
assert models == ["gpt-4o-realtime-preview", "gpt-realtime"]
def test_get_model_from_request_ignores_session_model_on_non_realtime_routes():
"""A nested ``session.model`` must not leak into model resolution for
unrelated routes."""
assert (
get_model_from_request(
request_data={"session": {"type": "realtime", "model": "gpt-realtime"}},
route="/v1/chat/completions",
)
is None
)
def test_abbreviate_api_key():
assert abbreviate_api_key("sk-test-1234-abcdefgh") == "sk-...efgh"
assert abbreviate_api_key("sk-abcdefghijklm") == "sk-...jklm"
def test_abbreviate_api_key_short_key_is_fully_masked():
"""Regression test for LIT-4355: for keys shorter than the enforced minimum,
showing the last 4 characters can reveal the entire key (sk-1234 -> sk-...1234)."""
assert abbreviate_api_key("sk-1234") == "sk-..."
assert abbreviate_api_key("sk-test-1234") == "sk-..."
assert abbreviate_api_key("") == "sk-..."
def test_get_customer_user_header_returns_none_when_no_customer_role():
from litellm.proxy.auth.auth_utils import get_customer_user_header_from_mapping
mappings = [
{"header_name": "X-OpenWebUI-User-Id", "litellm_user_role": "internal_user"}
]
result = get_customer_user_header_from_mapping(mappings)
assert result is None
def test_get_customer_user_header_returns_none_for_single_non_customer_mapping():
from litellm.proxy.auth.auth_utils import get_customer_user_header_from_mapping
mapping = {"header_name": "X-Only-Internal", "litellm_user_role": "internal_user"}
result = get_customer_user_header_from_mapping(mapping)
assert result is None
def test_get_customer_user_header_from_mapping_returns_customer_header():
from litellm.proxy.auth.auth_utils import get_customer_user_header_from_mapping
mappings = [
{"header_name": "X-OpenWebUI-User-Id", "litellm_user_role": "internal_user"},
{"header_name": "X-OpenWebUI-User-Email", "litellm_user_role": "customer"},
]
result = get_customer_user_header_from_mapping(mappings)
assert result == ["x-openwebui-user-email"]
def test_get_customer_user_header_returns_customers_header_in_config_order_when_multiple_exist():
from litellm.proxy.auth.auth_utils import get_customer_user_header_from_mapping
mappings = [
{"header_name": "X-OpenWebUI-User-Id", "litellm_user_role": "internal_user"},
{"header_name": "X-OpenWebUI-User-Email", "litellm_user_role": "customer"},
{"header_name": "X-User-Id", "litellm_user_role": "customer"},
]
result = get_customer_user_header_from_mapping(mappings)
assert result == ["x-openwebui-user-email", "x-user-id"]
def test_get_end_user_id_returns_id_from_user_header_mappings():
from litellm.proxy.auth.auth_utils import get_end_user_id_from_request_body
mappings = [
{"header_name": "x-openwebui-user-id", "litellm_user_role": "internal_user"},
{"header_name": "x-openwebui-user-email", "litellm_user_role": "customer"},
]
general_settings = {"user_header_mappings": mappings}
headers = {"x-openwebui-user-email": "1234"}
with (
patch(
"litellm.proxy.auth.auth_utils._get_customer_id_from_standard_headers",
return_value=None,
),
patch("litellm.proxy.proxy_server.general_settings", general_settings),
):
result = get_end_user_id_from_request_body(
request_body={}, request_headers=headers
)
assert result == "1234"
def test_get_end_user_id_returns_first_customer_header_when_multiple_mappings_exist():
from litellm.proxy.auth.auth_utils import get_end_user_id_from_request_body
mappings = [
{"header_name": "x-openwebui-user-id", "litellm_user_role": "internal_user"},
{"header_name": "x-user-id", "litellm_user_role": "customer"},
{"header_name": "x-openwebui-user-email", "litellm_user_role": "customer"},
]
general_settings = {"user_header_mappings": mappings}
headers = {
"x-user-id": "user-456",
"x-openwebui-user-email": "user@example.com",
}
with (
patch(
"litellm.proxy.auth.auth_utils._get_customer_id_from_standard_headers",
return_value=None,
),
patch("litellm.proxy.proxy_server.general_settings", general_settings),
):
result = get_end_user_id_from_request_body(
request_body={}, request_headers=headers
)
assert result == "user-456"
def test_get_end_user_id_returns_none_when_no_customer_role_in_mappings():
from litellm.proxy.auth.auth_utils import get_end_user_id_from_request_body
mappings = [
{"header_name": "x-openwebui-user-id", "litellm_user_role": "internal_user"},
]
general_settings = {"user_header_mappings": mappings}
headers = {"x-openwebui-user-id": "user-789"}
with (
patch(
"litellm.proxy.auth.auth_utils._get_customer_id_from_standard_headers",
return_value=None,
),
patch("litellm.proxy.proxy_server.general_settings", general_settings),
):
result = get_end_user_id_from_request_body(
request_body={}, request_headers=headers
)
assert result is None
def test_get_end_user_id_falls_back_to_deprecated_user_header_name():
from litellm.proxy.auth.auth_utils import get_end_user_id_from_request_body
general_settings = {"user_header_name": "x-custom-user-id"}
headers = {"x-custom-user-id": "user-legacy"}
with (
patch(
"litellm.proxy.auth.auth_utils._get_customer_id_from_standard_headers",
return_value=None,
),
patch("litellm.proxy.proxy_server.general_settings", general_settings),
):
result = get_end_user_id_from_request_body(
request_body={}, request_headers=headers
)
assert result == "user-legacy"
class TestCoerceUserIdToStr:
"""Unit tests for the _coerce_user_id_to_str helper."""
def test_plain_string_is_returned_verbatim(self):
from litellm.proxy.auth.auth_utils import _coerce_user_id_to_str
assert _coerce_user_id_to_str("alice@example.com") == "alice@example.com"
def test_string_is_stripped(self):
from litellm.proxy.auth.auth_utils import _coerce_user_id_to_str
assert _coerce_user_id_to_str(" bob ") == "bob"
def test_codex_opaque_identifier_is_preserved(self):
from litellm.proxy.auth.auth_utils import _coerce_user_id_to_str
codex_id = (
"user_8a4a360c36621665b341e06fb76041d9b6def732bb183eea148d4abc9d97c1de"
"_account__session_a2bce4a5-8887-44ef-b491-fbf0a55c6569"
)
assert _coerce_user_id_to_str(codex_id) == codex_id
def test_none_returns_none(self):
from litellm.proxy.auth.auth_utils import _coerce_user_id_to_str
assert _coerce_user_id_to_str(None) is None
def test_empty_string_returns_none(self):
from litellm.proxy.auth.auth_utils import _coerce_user_id_to_str
assert _coerce_user_id_to_str("") is None
assert _coerce_user_id_to_str(" ") is None
def test_dict_returns_none(self):
from litellm.proxy.auth.auth_utils import _coerce_user_id_to_str
payload = {
"device_id": "abc",
"account_uuid": "",
"session_id": "c284b8cb",
}
assert _coerce_user_id_to_str(payload) is None
def test_list_returns_none(self):
from litellm.proxy.auth.auth_utils import _coerce_user_id_to_str
assert _coerce_user_id_to_str(["a", "b"]) is None
def test_json_encoded_dict_string_passes_through_by_default(self):
"""JSON-encoded dict strings are preserved unless opt-in flag is on.
This preserves backwards compatibility: existing deployments that
intentionally pass JSON-encoded user identifiers keep working.
"""
import litellm
from litellm.proxy.auth.auth_utils import _coerce_user_id_to_str
blob = (
'{"device_id":"d5abe9199ee7759a0558974e9371e78c7b38d7621aae26d6609c1de61af6afb0",'
'"account_uuid":"","session_id":"c284b8cb-a050-4278-8599-cc4e016a10ab"}'
)
original = litellm.validate_end_user_id_in_db
litellm.validate_end_user_id_in_db = False
try:
assert _coerce_user_id_to_str(blob) == blob
finally:
litellm.validate_end_user_id_in_db = original
def test_json_encoded_dict_string_returns_none_when_validation_enabled(self):
import litellm
from litellm.proxy.auth.auth_utils import _coerce_user_id_to_str
# Same broken shape we saw in spend logs, but pre-stringified to JSON.
blob = (
'{"device_id":"d5abe9199ee7759a0558974e9371e78c7b38d7621aae26d6609c1de61af6afb0",'
'"account_uuid":"","session_id":"c284b8cb-a050-4278-8599-cc4e016a10ab"}'
)
original = litellm.validate_end_user_id_in_db
litellm.validate_end_user_id_in_db = True
try:
assert _coerce_user_id_to_str(blob) is None
finally:
litellm.validate_end_user_id_in_db = original
def test_json_encoded_list_string_passes_through_by_default(self):
import litellm
from litellm.proxy.auth.auth_utils import _coerce_user_id_to_str
original = litellm.validate_end_user_id_in_db
litellm.validate_end_user_id_in_db = False
try:
assert _coerce_user_id_to_str('["a","b"]') == '["a","b"]'
finally:
litellm.validate_end_user_id_in_db = original
def test_json_encoded_list_string_returns_none_when_validation_enabled(self):
import litellm
from litellm.proxy.auth.auth_utils import _coerce_user_id_to_str
original = litellm.validate_end_user_id_in_db
litellm.validate_end_user_id_in_db = True
try:
assert _coerce_user_id_to_str('["a","b"]') is None
finally:
litellm.validate_end_user_id_in_db = original
def test_int_returns_str(self):
from litellm.proxy.auth.auth_utils import _coerce_user_id_to_str
assert _coerce_user_id_to_str(12345) == "12345"
def test_bool_returns_none(self):
from litellm.proxy.auth.auth_utils import _coerce_user_id_to_str
# bool is an int subclass — reject explicitly, never produce "True"/"False".
assert _coerce_user_id_to_str(True) is None
assert _coerce_user_id_to_str(False) is None
def test_brace_string_that_isnt_json_is_kept(self):
"""A string starting with `{` but failing to parse stays as-is."""
from litellm.proxy.auth.auth_utils import _coerce_user_id_to_str
assert _coerce_user_id_to_str("{not json") == "{not json"
class TestGetEndUserIdDropsMalformedBodyValues:
"""Tests that get_end_user_id_from_request_body drops dict-shaped values
rather than stringifying them into spend logs."""
def test_dict_user_falls_through_to_litellm_metadata(self):
request_body = {
"user": {
"device_id": "abc",
"session_id": "c284b8cb",
},
"litellm_metadata": {"user": "alice@example.com"},
}
with patch("litellm.proxy.proxy_server.general_settings", {}):
result = get_end_user_id_from_request_body(
request_body=request_body, request_headers={}
)
assert result == "alice@example.com"
def test_dict_user_with_no_other_sources_returns_none(self):
request_body = {
"user": {"device_id": "abc", "session_id": "xyz"},
}
with patch("litellm.proxy.proxy_server.general_settings", {}):
result = get_end_user_id_from_request_body(
request_body=request_body, request_headers={}
)
assert result is None
def test_json_encoded_user_string_passes_through_by_default(self):
"""JSON-encoded user strings pass through unless validation is opted in.
Gating behind ``litellm.validate_end_user_id_in_db`` keeps existing
deployments that send JSON-encoded identifiers working until they
explicitly opt into the stricter extraction.
"""
import litellm
blob = (
'{"device_id":"d5abe9199ee7759a","account_uuid":"",'
'"session_id":"c284b8cb-a050-4278-8599-cc4e016a10ab"}'
)
request_body = {"user": blob}
original = litellm.validate_end_user_id_in_db
litellm.validate_end_user_id_in_db = False
try:
with patch("litellm.proxy.proxy_server.general_settings", {}):
result = get_end_user_id_from_request_body(
request_body=request_body, request_headers={}
)
finally:
litellm.validate_end_user_id_in_db = original
assert result == blob
def test_json_encoded_user_string_returns_none_when_validation_enabled(self):
import litellm
request_body = {
"user": (
'{"device_id":"d5abe9199ee7759a","account_uuid":"",'
'"session_id":"c284b8cb-a050-4278-8599-cc4e016a10ab"}'
),
}
original = litellm.validate_end_user_id_in_db
litellm.validate_end_user_id_in_db = True
try:
with patch("litellm.proxy.proxy_server.general_settings", {}):
result = get_end_user_id_from_request_body(
request_body=request_body, request_headers={}
)
finally:
litellm.validate_end_user_id_in_db = original
assert result is None
def test_plain_string_user_is_preserved(self):
request_body = {"user": "alice@example.com"}
with patch("litellm.proxy.proxy_server.general_settings", {}):
result = get_end_user_id_from_request_body(
request_body=request_body, request_headers={}
)
assert result == "alice@example.com"
def test_codex_opaque_user_is_preserved(self):
codex_id = (
"user_8a4a360c36621665b341e06fb76041d9b6def732bb183eea148d4abc9d97c1de"
"_account__session_a2bce4a5-8887-44ef-b491-fbf0a55c6569"
)
request_body = {"user": codex_id}
with patch("litellm.proxy.proxy_server.general_settings", {}):
result = get_end_user_id_from_request_body(
request_body=request_body, request_headers={}
)
assert result == codex_id
def test_int_user_is_coerced_to_string(self):
request_body = {"user": 12345}
with patch("litellm.proxy.proxy_server.general_settings", {}):
result = get_end_user_id_from_request_body(
request_body=request_body, request_headers={}
)
assert result == "12345"
def test_list_user_falls_through(self):
request_body = {
"user": ["a", "b"],
"safety_identifier": "alice@example.com",
}
with patch("litellm.proxy.proxy_server.general_settings", {}):
result = get_end_user_id_from_request_body(
request_body=request_body, request_headers={}
)
assert result == "alice@example.com"
def test_dict_safety_identifier_returns_none(self):
request_body = {
"safety_identifier": {"device_id": "abc"},
}
with patch("litellm.proxy.proxy_server.general_settings", {}):
result = get_end_user_id_from_request_body(
request_body=request_body, request_headers={}
)
assert result is None
def test_dict_metadata_user_id_returns_none(self):
request_body = {
"metadata": {"user_id": {"device_id": "abc"}},
}
with patch("litellm.proxy.proxy_server.general_settings", {}):
result = get_end_user_id_from_request_body(
request_body=request_body, request_headers={}
)
assert result is None
def test_whitespace_user_falls_through(self):
request_body = {"user": " ", "safety_identifier": "alice@example.com"}
with patch("litellm.proxy.proxy_server.general_settings", {}):
result = get_end_user_id_from_request_body(
request_body=request_body, request_headers={}
)
assert result == "alice@example.com"
def test_dict_user_header_falls_through_to_body(self):
"""A dict-shaped value in a configured user-id header is dropped, not stringified."""
general_settings = {"user_header_name": "x-custom-user-id"}
# A header value will normally be a str, but be defensive: the coercion
# must drop anything that isn't a usable identifier.
headers = {"x-custom-user-id": {"device_id": "abc"}}
request_body = {"user": "alice@example.com"}
with (
patch(
"litellm.proxy.auth.auth_utils._get_customer_id_from_standard_headers",
return_value=None,
),
patch("litellm.proxy.proxy_server.general_settings", general_settings),
):
result = get_end_user_id_from_request_body(
request_body=request_body, request_headers=headers
)
assert result == "alice@example.com"
def _make_deployment_dict(
model_name: str, tpm: Optional[int] = None, rpm: Optional[int] = None
) -> dict:
"""Helper to build a minimal deployment dict as returned by router.get_model_list."""
litellm_params: dict = {"model": model_name}
if tpm is not None:
litellm_params["default_api_key_tpm_limit"] = tpm
if rpm is not None:
litellm_params["default_api_key_rpm_limit"] = rpm
return {"model_name": model_name, "litellm_params": litellm_params}
_ROUTER_PATCH = "litellm.proxy.proxy_server.llm_router"
class TestDeploymentDefaultRpmLimit:
"""Tests for deployment default_api_key_rpm_limit fallback in get_key_model_rpm_limit."""
def test_returns_deployment_default_when_key_has_no_limits(self):
"""Case 2 from spec: key has no model-specific limits, falls back to deployment default."""
user_api_key_dict = UserAPIKeyAuth(api_key="sk-123")
mock_router = MagicMock()
mock_router.get_model_list.return_value = [
_make_deployment_dict("model1", rpm=200)
]
with patch(_ROUTER_PATCH, mock_router):
result = get_key_model_rpm_limit(user_api_key_dict, model_name="model1")
assert result == {"model1": 200}
def test_key_model_limit_takes_priority_over_deployment_default(self):
"""Case 1 from spec: key model-specific limit wins over deployment default."""
user_api_key_dict = UserAPIKeyAuth(
api_key="sk-123",
metadata={"model_rpm_limit": {"model1": 10}},
)
mock_router = MagicMock()
mock_router.get_model_list.return_value = [
_make_deployment_dict("model1", rpm=200)
]
with patch(_ROUTER_PATCH, mock_router):
result = get_key_model_rpm_limit(user_api_key_dict, model_name="model1")
assert result == {"model1": 10}
def test_returns_none_when_no_deployment_default_and_no_key_limits(self):
"""Returns None when neither the key nor the deployment has any rpm limit."""
user_api_key_dict = UserAPIKeyAuth(api_key="sk-123")
mock_router = MagicMock()
mock_router.get_model_list.return_value = [
_make_deployment_dict("model1") # no rpm default
]
with patch(_ROUTER_PATCH, mock_router):
result = get_key_model_rpm_limit(user_api_key_dict, model_name="model1")
assert result is None
def test_returns_none_without_model_name_even_when_deployment_has_default(self):
"""No model_name means deployment fallback is skipped."""
user_api_key_dict = UserAPIKeyAuth(api_key="sk-123")
mock_router = MagicMock()
mock_router.get_model_list.return_value = [
_make_deployment_dict("model1", rpm=200)
]
with patch(_ROUTER_PATCH, mock_router):
result = get_key_model_rpm_limit(user_api_key_dict)
assert result is None
def test_returns_none_when_llm_router_is_none(self):
"""No router means deployment fallback returns None gracefully."""
user_api_key_dict = UserAPIKeyAuth(api_key="sk-123")
with patch(_ROUTER_PATCH, None):
result = get_key_model_rpm_limit(user_api_key_dict, model_name="model1")
assert result is None
def test_returns_minimum_across_multiple_deployments(self):
"""When multiple deployments share a model name, the minimum rpm limit is used."""
user_api_key_dict = UserAPIKeyAuth(api_key="sk-123")
mock_router = MagicMock()
mock_router.get_model_list.return_value = [
_make_deployment_dict("model1", rpm=200),
_make_deployment_dict("model1", rpm=50),
_make_deployment_dict("model1", rpm=150),
]
with patch(_ROUTER_PATCH, mock_router):
result = get_key_model_rpm_limit(user_api_key_dict, model_name="model1")
assert result == {"model1": 50}
def test_ignores_deployments_without_default_when_others_have_it(self):
"""Deployments missing the field are skipped; min is taken over those that have it."""
user_api_key_dict = UserAPIKeyAuth(api_key="sk-123")
mock_router = MagicMock()
mock_router.get_model_list.return_value = [
_make_deployment_dict("model1"), # no rpm default
_make_deployment_dict("model1", rpm=75),
]
with patch(_ROUTER_PATCH, mock_router):
result = get_key_model_rpm_limit(user_api_key_dict, model_name="model1")
assert result == {"model1": 75}
def test_skips_deployments_with_malformed_limit_value(self):
"""Deployments with non-integer-parseable limit values are skipped without raising."""
user_api_key_dict = UserAPIKeyAuth(api_key="sk-123")
mock_router = MagicMock()
mock_router.get_model_list.return_value = [
{
"model_name": "model1",
"litellm_params": {"default_api_key_rpm_limit": "not-a-number"},
},
_make_deployment_dict("model1", rpm=100),
]
with patch(_ROUTER_PATCH, mock_router):
result = get_key_model_rpm_limit(user_api_key_dict, model_name="model1")
# The malformed deployment is skipped; the valid one provides 100
assert result == {"model1": 100}
class TestDeploymentDefaultTpmLimit:
"""Tests for deployment default_api_key_tpm_limit fallback in get_key_model_tpm_limit."""
def test_returns_deployment_default_when_key_has_no_limits(self):
"""Case 2 from spec: key has no model-specific limits, falls back to deployment default."""
user_api_key_dict = UserAPIKeyAuth(api_key="sk-123")
mock_router = MagicMock()
mock_router.get_model_list.return_value = [
_make_deployment_dict("model1", tpm=100)
]
with patch(_ROUTER_PATCH, mock_router):
result = get_key_model_tpm_limit(user_api_key_dict, model_name="model1")
assert result == {"model1": 100}
def test_key_model_limit_takes_priority_over_deployment_default(self):
"""Case 1 from spec: key model-specific limit wins over deployment default."""
user_api_key_dict = UserAPIKeyAuth(
api_key="sk-123",
metadata={"model_tpm_limit": {"model1": 20}},
)
mock_router = MagicMock()
mock_router.get_model_list.return_value = [
_make_deployment_dict("model1", tpm=100)
]
with patch(_ROUTER_PATCH, mock_router):
result = get_key_model_tpm_limit(user_api_key_dict, model_name="model1")
assert result == {"model1": 20}
def test_returns_none_when_no_deployment_default_and_no_key_limits(self):
"""Returns None when neither the key nor the deployment has any tpm limit."""
user_api_key_dict = UserAPIKeyAuth(api_key="sk-123")
mock_router = MagicMock()
mock_router.get_model_list.return_value = [
_make_deployment_dict("model1") # no tpm default
]
with patch(_ROUTER_PATCH, mock_router):
result = get_key_model_tpm_limit(user_api_key_dict, model_name="model1")
assert result is None
def test_returns_none_without_model_name_even_when_deployment_has_default(self):
"""No model_name means deployment fallback is skipped."""
user_api_key_dict = UserAPIKeyAuth(api_key="sk-123")
mock_router = MagicMock()
mock_router.get_model_list.return_value = [
_make_deployment_dict("model1", tpm=100)
]
with patch(_ROUTER_PATCH, mock_router):
result = get_key_model_tpm_limit(user_api_key_dict)
assert result is None
def test_returns_none_when_llm_router_is_none(self):
"""No router means deployment fallback returns None gracefully."""
user_api_key_dict = UserAPIKeyAuth(api_key="sk-123")
with patch(_ROUTER_PATCH, None):
result = get_key_model_tpm_limit(user_api_key_dict, model_name="model1")
assert result is None
def test_returns_minimum_across_multiple_deployments(self):
"""When multiple deployments share a model name, the minimum tpm limit is used."""
user_api_key_dict = UserAPIKeyAuth(api_key="sk-123")
mock_router = MagicMock()
mock_router.get_model_list.return_value = [
_make_deployment_dict("model1", tpm=1000),
_make_deployment_dict("model1", tpm=300),
_make_deployment_dict("model1", tpm=700),
]
with patch(_ROUTER_PATCH, mock_router):
result = get_key_model_tpm_limit(user_api_key_dict, model_name="model1")
assert result == {"model1": 300}
def test_ignores_deployments_without_default_when_others_have_it(self):
"""Deployments missing the field are skipped; min is taken over those that have it."""
user_api_key_dict = UserAPIKeyAuth(api_key="sk-123")
mock_router = MagicMock()
mock_router.get_model_list.return_value = [
_make_deployment_dict("model1"), # no tpm default
_make_deployment_dict("model1", tpm=400),
]
with patch(_ROUTER_PATCH, mock_router):
result = get_key_model_tpm_limit(user_api_key_dict, model_name="model1")
assert result == {"model1": 400}
class TestGetProjectModelRpmLimit:
"""Tests for get_project_model_rpm_limit function."""
def test_returns_project_metadata_rpm_limit(self):
user_api_key_dict = UserAPIKeyAuth(
api_key="sk-123",
project_metadata={"model_rpm_limit": {"gpt-4": 200}},
)
result = get_project_model_rpm_limit(user_api_key_dict)
assert result == {"gpt-4": 200}
def test_returns_none_when_no_project_metadata(self):
user_api_key_dict = UserAPIKeyAuth(api_key="sk-123")
result = get_project_model_rpm_limit(user_api_key_dict)
assert result is None
def test_returns_none_when_project_metadata_missing_key(self):
user_api_key_dict = UserAPIKeyAuth(
api_key="sk-123",
project_metadata={"other_key": "value"},
)
result = get_project_model_rpm_limit(user_api_key_dict)
assert result is None
class TestGetProjectModelTpmLimit:
"""Tests for get_project_model_tpm_limit function."""
def test_returns_project_metadata_tpm_limit(self):
user_api_key_dict = UserAPIKeyAuth(
api_key="sk-123",
project_metadata={"model_tpm_limit": {"gpt-4": 50000}},
)
result = get_project_model_tpm_limit(user_api_key_dict)
assert result == {"gpt-4": 50000}
def test_returns_none_when_no_project_metadata(self):
user_api_key_dict = UserAPIKeyAuth(api_key="sk-123")
result = get_project_model_tpm_limit(user_api_key_dict)
assert result is None
def test_returns_none_when_project_metadata_missing_key(self):
user_api_key_dict = UserAPIKeyAuth(
api_key="sk-123",
project_metadata={"other_key": "value"},
)
result = get_project_model_tpm_limit(user_api_key_dict)
assert result is None
class TestCheckCompleteCredentials:
"""Tests for the api_key validation in check_complete_credentials."""
def test_returns_false_when_api_key_missing(self):
result = check_complete_credentials({"model": "gpt-4"})
assert result is False
def test_returns_false_when_api_key_is_none(self):
result = check_complete_credentials({"model": "gpt-4", "api_key": None})
assert result is False
def test_returns_false_when_api_key_is_empty_string(self):
result = check_complete_credentials({"model": "gpt-4", "api_key": ""})
assert result is False
def test_returns_false_when_api_key_is_whitespace(self):
result = check_complete_credentials({"model": "gpt-4", "api_key": " "})
assert result is False
def test_returns_true_when_api_key_is_valid(self):
result = check_complete_credentials({"model": "gpt-4", "api_key": "sk-valid"})
assert result is True
class TestCheckCompleteCredentialsBlocksSSRF:
"""
Even with credentials supplied, ``api_base`` / ``base_url`` must not
point at private / internal / cloud-metadata addresses. Without this
the gate accepts ``api_key=anything`` plus a malicious target and the
proxy is used as an SSRF pivot.
The check only runs when ``litellm.user_url_validation`` is True, so
every test in this class flips the toggle. Tests stay mock-only — no
real DNS is performed.
"""
@pytest.fixture(autouse=True)
def _enable_url_validation(self, monkeypatch):
import litellm
monkeypatch.setattr(litellm, "user_url_validation", True, raising=False)
@pytest.mark.parametrize(
"url_field",
["api_base", "base_url"],
)
@pytest.mark.parametrize(
"blocked_url",
[
"http://169.254.169.254/latest/meta-data/iam/security-credentials/",
"http://metadata.google.internal/computeMetadata/v1/",
"http://127.0.0.1:8080/admin",
"http://10.0.0.1/",
"http://192.168.1.1/",
],
)
def test_rejects_private_or_metadata_targets(self, url_field, blocked_url):
from litellm.litellm_core_utils.url_utils import SSRFError
with patch(
"litellm.proxy.auth.auth_utils.validate_url",
side_effect=SSRFError(f"blocked: {blocked_url}"),
):
with pytest.raises(ValueError) as exc_info:
check_complete_credentials(
{
"model": "gpt-4",
"api_key": "sk-some-clientside-key",
url_field: blocked_url,
}
)
assert url_field in str(exc_info.value)
assert "SSRF" in str(exc_info.value)
def test_allows_public_target_when_validate_url_passes(self):
# ``validate_url`` is mocked so no real DNS is performed.
with patch(
"litellm.proxy.auth.auth_utils.validate_url",
return_value=("https://api.openai.com/v1", "api.openai.com"),
):
result = check_complete_credentials(
{
"model": "gpt-4",
"api_key": "sk-some-clientside-key",
"api_base": "https://api.openai.com/v1",
}
)
assert result is True
def test_skips_url_validation_when_toggle_is_off(self, monkeypatch):
# Admins who disable ``user_url_validation`` (default) should not
# have requests rejected at the proxy boundary even if the URL
# would fail the SSRF guard.
import litellm
monkeypatch.setattr(litellm, "user_url_validation", False, raising=False)
with patch(
"litellm.proxy.auth.auth_utils.validate_url",
) as mocked:
result = check_complete_credentials(
{
"model": "gpt-4",
"api_key": "sk-some-clientside-key",
"api_base": "http://127.0.0.1:8080/admin",
}
)
assert result is True
mocked.assert_not_called()
class TestGetDynamicLitellmParamsClearsAdminConfigOnBaseOverride:
"""
When the caller redirects ``api_base`` / ``base_url`` to their own
server, admin-set fields like ``OpenAI-Organization``, ``extra_body``,
AWS / Vertex / Azure tokens, and per-deployment ``api_version`` must
NOT flow through to that destination.
"""
def test_clears_admin_organization_and_extra_body_on_base_override(self):
from litellm.router_utils.clientside_credential_handler import (
get_dynamic_litellm_params,
)
admin_params = {
"model": "gpt-4",
"api_key": "sk-admin-key",
"api_base": "https://admin.upstream/v1",
"organization": "org-admin-corp",
"extra_body": {"x-admin-secret": "super-secret"},
"api_version": "2026-04-01",
}
out = get_dynamic_litellm_params(
litellm_params=dict(admin_params),
request_kwargs={
"api_key": "sk-attacker",
"api_base": "https://attacker.example",
},
)
assert out["api_base"] == "https://attacker.example"
assert out["api_key"] == "sk-attacker"
assert "organization" not in out
assert "extra_body" not in out
assert "api_version" not in out
def test_clears_aws_and_vertex_secrets_on_base_override(self):
from litellm.router_utils.clientside_credential_handler import (
get_dynamic_litellm_params,
)
admin_params = {
"model": "bedrock/claude-3",
"aws_access_key_id": "AKIA-EXAMPLE",
"aws_secret_access_key": "secret-example",
"aws_session_token": "session-example",
"vertex_credentials": '{"private_key":"-----BEGIN..."}',
"vertex_project": "admin-gcp-project",
}
out = get_dynamic_litellm_params(
litellm_params=dict(admin_params),
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
assert "aws_session_token" not in out
assert "vertex_credentials" not in out
assert "vertex_project" not in out
def test_clears_nvcf_function_id_on_base_override(self):
from litellm.router_utils.clientside_credential_handler import (
get_dynamic_litellm_params,
)
admin_params = {
"model": "nvidia_riva/parakeet",
"api_base": "grpc.nvcf.nvidia.com:443",
"api_key": "nvapi-admin",
"nvcf_function_id": "admin-pinned-function",
}
out = get_dynamic_litellm_params(
litellm_params=dict(admin_params),
request_kwargs={"api_base": "self-hosted.example.com:50051", "api_key": "sk-caller"},
)
assert out["api_base"] == "self-hosted.example.com:50051"
assert "nvcf_function_id" not in out
def test_clears_use_ssl_on_base_override(self):
from litellm.router_utils.clientside_credential_handler import (
get_dynamic_litellm_params,
)
admin_params = {
"model": "nvidia_riva/parakeet",
"api_base": "grpc.nvcf.nvidia.com:443",
"api_key": "nvapi-admin",
"use_ssl": True,
}
out = get_dynamic_litellm_params(
litellm_params=dict(admin_params),
request_kwargs={"api_base": "self-hosted.example.com:50051", "api_key": "sk-caller"},
)
assert out["api_base"] == "self-hosted.example.com:50051"
assert "use_ssl" not in out
def test_caller_resupplied_value_overrides_admin_value_on_base_override(self):
# When the caller redirects ``api_base`` and *also* supplies their
# own value for one of the admin fields (e.g. ``organization``),
# the caller's value must win — never the admin's. The naive
# ``if field not in request_kwargs: pop`` shape lets a caller echo
# the field name with any value (or empty string) to keep the
# admin's value forwarded, which is the exfiltration vector this
# test guards against.
from litellm.router_utils.clientside_credential_handler import (
get_dynamic_litellm_params,
)
out = get_dynamic_litellm_params(
litellm_params={
"api_base": "https://admin.upstream/v1",
"organization": "org-admin",
"extra_body": {"admin": "value"},
},
request_kwargs={
"api_base": "https://attacker.example",
"api_key": "sk-caller",
"organization": "org-attacker",
"extra_body": {"attacker": "value"},
},
)
assert out["organization"] == "org-attacker"
assert out["extra_body"] == {"attacker": "value"}
def test_field_echo_does_not_preserve_admin_value(self):
# Regression: a caller that echoes an admin-config field name with
# an *empty* value (or any value) must not be able to keep the
# admin's value in ``litellm_params``.
from litellm.router_utils.clientside_credential_handler import (
get_dynamic_litellm_params,
)
out = get_dynamic_litellm_params(
litellm_params={
"api_base": "https://admin.upstream/v1",
"organization": "org-admin-secret",
"extra_body": {"x-admin-only": "secret"},
},
request_kwargs={
"api_base": "https://attacker.example",
"api_key": "sk-caller",
"organization": "",
"extra_body": "",
},
)
assert out["organization"] == ""
assert out["extra_body"] == ""
assert "org-admin-secret" not in str(out)
def test_no_clearing_when_only_api_key_overridden(self):
from litellm.router_utils.clientside_credential_handler import (
get_dynamic_litellm_params,
)
# Caller only overrides api_key (BYOK pattern); admin's organization /
# extra_body / region still apply because the destination is unchanged.
out = get_dynamic_litellm_params(
litellm_params={
"api_base": "https://admin.upstream/v1",
"organization": "org-admin",
"api_version": "2026-04-01",
},
request_kwargs={"api_key": "sk-byok"},
)
assert out["organization"] == "org-admin"
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:
"""
``is_request_body_safe`` rejects request-body fields that retarget the
outbound request to a caller-controlled host. Beyond the original
``api_base`` / ``base_url``, the same protection must apply to:
* ``aws_bedrock_runtime_endpoint`` — Bedrock endpoint redirect; an
attacker-controlled value coerces the proxy to authenticate against
their host with the admin's AWS creds.
* ``langsmith_base_url`` — Langsmith callback host; attacker-controlled
values exfiltrate the entire request payload (incl. message content)
via the observability hook.
* ``langfuse_host`` — same exfil vector via the Langfuse hook.
"""
@pytest.fixture(autouse=True)
def _disable_url_validation(self, monkeypatch):
# The new banned-params entries should be rejected even when
# ``user_url_validation`` is off — the gate isn't the URL guard,
# it's the banned-params list.
import litellm
monkeypatch.setattr(litellm, "user_url_validation", False, raising=False)
@pytest.mark.parametrize(
"field",
[
"aws_bedrock_runtime_endpoint",
"langsmith_base_url",
"langfuse_host",
"posthog_host",
"braintrust_host",
"slack_webhook_url",
"s3_endpoint_url",
"sagemaker_base_url",
"deployment_url",
],
)
def test_endpoint_targeting_field_in_request_body_is_rejected(self, field):
with pytest.raises(ValueError) as exc:
is_request_body_safe(
request_body={"model": "gpt-4", field: "https://attacker.example"},
general_settings={},
llm_router=None,
model="gpt-4",
)
# The function lists the offending param name in the error.
assert field in str(exc.value)
@pytest.mark.parametrize(
"field",
["api_base", "base_url", "user_config", "langfuse_host", "slack_webhook_url"],
)
def test_api_key_does_not_bypass_blocklist(self, field):
# Regression: the historical ``check_complete_credentials`` clause
# made the entire blocklist a no-op for any caller that supplied
# a non-empty ``api_key``. That bypass turned every missing entry
# on the blocklist into an SSRF / credential-exfil hole. Verify
# that supplying an api_key (alongside the banned param) does NOT
# bypass the gate — it can only be opened by an admin opt-in.
with pytest.raises(ValueError) as exc:
is_request_body_safe(
request_body={
"model": "gpt-4",
"api_key": "sk-anything",
field: "https://attacker.example",
},
general_settings={},
llm_router=None,
model="gpt-4",
)
assert field in str(exc.value)
def test_admin_opt_in_proxy_wide_still_allows(self):
# ``general_settings.allow_client_side_credentials = True`` remains
# the documented proxy-wide BYOK opt-in.
assert (
is_request_body_safe(
request_body={"model": "gpt-4", "api_base": "https://my-byok.example"},
general_settings={"allow_client_side_credentials": True},
llm_router=None,
model="gpt-4",
)
is True
)
class TestIsRequestBodySafeBlocksBedrockProjectOverride:
"""``aws_bedrock_project_id`` pins a deployment to a Bedrock project so
that project's data-retention policy applies to its requests. A
caller-supplied value would run the request under any project reachable
with the deployment's shared AWS credentials, bypassing the configured
retention/accounting association."""
def test_project_id_in_request_body_is_rejected(self):
with pytest.raises(ValueError, match="aws_bedrock_project_id"):
is_request_body_safe(
request_body={
"model": "gpt-4",
"aws_bedrock_project_id": "proj_attacker000000",
},
general_settings={},
llm_router=None,
model="gpt-4",
)
def test_admin_opt_in_proxy_wide_allows_project_id(self):
assert (
is_request_body_safe(
request_body={
"model": "gpt-4",
"aws_bedrock_project_id": "proj_byok000000",
},
general_settings={"allow_client_side_credentials": True},
llm_router=None,
model="gpt-4",
)
is True
)
class TestIsRequestBodySafeBlocksRustOptIn:
"""``rust`` hands the whole call to the Rust core, which signs and sends
with its own HTTP client rather than the one the deployment configured, and
reports no ``post_call``. The proxy splats the request body straight into
the router, and ``rust`` is a litellm param, so it lands in
``litellm_params`` and the gate honours it: without this entry any
authenticated caller picks a transport and a callback surface the admin
never chose. It stays a deployment decision, liftable only by the same
admin opt-in as the rest of the list."""
def test_rust_in_request_body_is_rejected(self):
with pytest.raises(ValueError, match="rust"):
is_request_body_safe(
request_body={"model": "gpt-4", "rust": True},
general_settings={},
llm_router=None,
model="gpt-4",
)
def test_rust_under_extra_body_is_rejected(self):
with pytest.raises(ValueError, match="not allowed in request body"):
is_request_body_safe(
request_body={"model": "gpt-4", "extra_body": {"rust": True}},
general_settings={},
llm_router=None,
model="gpt-4",
)
def test_api_key_does_not_bypass_the_rust_block(self):
with pytest.raises(ValueError, match="rust"):
is_request_body_safe(
request_body={"model": "gpt-4", "api_key": "sk-anything", "rust": True},
general_settings={},
llm_router=None,
model="gpt-4",
)
def test_admin_opt_in_proxy_wide_allows_rust(self):
assert (
is_request_body_safe(
request_body={"model": "gpt-4", "rust": True},
general_settings={"allow_client_side_credentials": True},
llm_router=None,
model="gpt-4",
)
is True
)
def test_body_without_rust_is_still_allowed(self):
assert (
is_request_body_safe(
request_body={"model": "gpt-4", "temperature": 0.7},
general_settings={},
llm_router=None,
model="gpt-4",
)
is True
)
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
)
class TestIsRequestBodySafeBlocksNVCFFunctionOverride:
"""``nvcf_function_id`` is rejected as a request-body param unless the
admin opted in proxy-wide or per-deployment."""
def test_nvcf_function_id_in_request_body_is_rejected(self):
with pytest.raises(ValueError, match="nvcf_function_id"):
is_request_body_safe(
request_body={
"model": "nvidia_riva/parakeet",
"nvcf_function_id": "caller-supplied",
},
general_settings={},
llm_router=None,
model="nvidia_riva/parakeet",
)
def test_nvcf_function_id_with_api_key_still_rejected(self):
with pytest.raises(ValueError, match="nvcf_function_id"):
is_request_body_safe(
request_body={
"model": "nvidia_riva/parakeet",
"api_key": "sk-anything",
"nvcf_function_id": "caller-supplied",
},
general_settings={},
llm_router=None,
model="nvidia_riva/parakeet",
)
def test_admin_opt_in_proxy_wide_allows_nvcf_function_id(self):
assert (
is_request_body_safe(
request_body={
"model": "nvidia_riva/parakeet",
"nvcf_function_id": "byok-function-id",
},
general_settings={"allow_client_side_credentials": True},
llm_router=None,
model="nvidia_riva/parakeet",
)
is True
)
def test_admin_opt_in_per_deployment_allows_nvcf_function_id(self, monkeypatch):
"""The error message lists per-deployment ``configurable_clientside_auth_params``
as a second opt-in. Cover that path too so it can't silently regress."""
from litellm.proxy.auth import auth_utils
monkeypatch.setattr(
auth_utils,
"_allow_model_level_clientside_configurable_parameters",
lambda model, param, request_body_value, llm_router: param == "nvcf_function_id",
)
assert (
is_request_body_safe(
request_body={
"model": "nvidia_riva/parakeet",
"nvcf_function_id": "byok-function-id",
},
general_settings={},
llm_router=None,
model="nvidia_riva/parakeet",
)
is True
)
class TestIsRequestBodySafeBlocksRivaUseSsl:
"""``use_ssl`` is rejected as a request-body param unless the admin
opted in proxy-wide or per-deployment."""
def test_use_ssl_in_request_body_is_rejected(self):
with pytest.raises(ValueError, match="use_ssl"):
is_request_body_safe(
request_body={
"model": "nvidia_riva/parakeet",
"use_ssl": False,
},
general_settings={},
llm_router=None,
model="nvidia_riva/parakeet",
)
def test_admin_opt_in_proxy_wide_allows_use_ssl(self):
assert (
is_request_body_safe(
request_body={
"model": "nvidia_riva/parakeet",
"use_ssl": True,
},
general_settings={"allow_client_side_credentials": True},
llm_router=None,
model="nvidia_riva/parakeet",
)
is True
)
def test_admin_opt_in_per_deployment_allows_use_ssl(self, monkeypatch):
from litellm.proxy.auth import auth_utils
monkeypatch.setattr(
auth_utils,
"_allow_model_level_clientside_configurable_parameters",
lambda model, param, request_body_value, llm_router: param == "use_ssl",
)
assert (
is_request_body_safe(
request_body={
"model": "nvidia_riva/parakeet",
"use_ssl": True,
},
general_settings={},
llm_router=None,
model="nvidia_riva/parakeet",
)
is True
)
class TestIsRequestBodySafeBlocksBedrockTags:
"""``bedrock_tags`` lands as AWS resource tags on Bedrock batch jobs
created with the proxy's AWS identity, so a caller-supplied value can
forge ownership or cost-allocation labels; like
``aws_bedrock_project_id`` it is blocked without an admin opt-in."""
def test_bedrock_tags_in_request_body_is_rejected(self):
with pytest.raises(ValueError, match="bedrock_tags"):
is_request_body_safe(
request_body={
"model": "bedrock-batch-opus",
"bedrock_tags": [{"key": "application", "value": "genai-proxy"}],
},
general_settings={},
llm_router=None,
model="bedrock-batch-opus",
)
def test_admin_opt_in_proxy_wide_allows_bedrock_tags(self):
assert (
is_request_body_safe(
request_body={
"model": "bedrock-batch-opus",
"bedrock_tags": [{"key": "application", "value": "genai-proxy"}],
},
general_settings={"allow_client_side_credentials": True},
llm_router=None,
model="bedrock-batch-opus",
)
is True
)
def test_admin_opt_in_per_deployment_allows_bedrock_tags(self):
from litellm import Router
router = Router(
model_list=[
{
"model_name": "bedrock-batch-opus",
"litellm_params": {
"model": "bedrock/us.anthropic.claude-opus-4-7",
"configurable_clientside_auth_params": ["bedrock_tags"],
},
}
]
)
assert (
is_request_body_safe(
request_body={
"model": "bedrock-batch-opus",
"bedrock_tags": [{"key": "application", "value": "genai-proxy"}],
},
general_settings={},
llm_router=router,
model="bedrock-batch-opus",
)
is True
)
def test_per_deployment_opt_in_for_other_param_still_rejects_bedrock_tags(self):
from litellm import Router
router = Router(
model_list=[
{
"model_name": "bedrock-batch-opus",
"litellm_params": {
"model": "bedrock/us.anthropic.claude-opus-4-7",
"configurable_clientside_auth_params": ["api_base"],
},
}
]
)
with pytest.raises(ValueError, match="bedrock_tags"):
is_request_body_safe(
request_body={
"model": "bedrock-batch-opus",
"bedrock_tags": [{"key": "application", "value": "genai-proxy"}],
},
general_settings={},
llm_router=router,
model="bedrock-batch-opus",
)
# ── is_request_body_safe nested-config recursion (VERIA-6) ────────────────────
class TestIsRequestBodySafeNestedConfig:
"""The Milvus vector store transformer unpacks
``litellm_embedding_config`` as ``**kwargs`` into ``litellm.embedding(...)``
— same SSRF / credential-exfil surface as a top-level ``api_base`` in
the request body. ``is_request_body_safe`` must recurse into this
nested dict so a banned param can't be smuggled in via nesting."""
def test_root_level_api_base_blocked_when_no_opt_in(self):
"""Sanity check: pre-existing root-level enforcement still works."""
with pytest.raises(ValueError, match="api_base"):
is_request_body_safe(
request_body={"api_base": "https://attacker.example.com"},
general_settings={},
llm_router=None,
model="gpt-4",
)
def test_nested_api_base_in_embedding_config_blocked(self):
"""Smuggling ``api_base`` inside ``litellm_embedding_config`` is
the VERIA-6 bypass — must be blocked by the recursive check."""
with pytest.raises(ValueError, match="api_base"):
is_request_body_safe(
request_body={
"litellm_embedding_config": {
"api_base": "https://attacker.example.com",
"api_key": "leaked-key",
}
},
general_settings={},
llm_router=None,
model="milvus-store",
)
def test_nested_nvcf_function_id_in_metadata_blocked(self):
"""Smuggling ``nvcf_function_id`` via ``metadata`` / ``extra_body``
is the same shape as the VERIA-6 ``api_base`` bypass — must be
rejected by the recursive walk so the NVCF override gate cannot
be sidestepped with nesting."""
with pytest.raises(ValueError, match="nvcf_function_id"):
is_request_body_safe(
request_body={
"model": "nvidia_riva/parakeet",
"litellm_metadata": {"nvcf_function_id": "attacker-via-metadata"},
},
general_settings={},
llm_router=None,
model="nvidia_riva/parakeet",
)
def test_nested_langfuse_host_in_embedding_config_blocked(self):
"""The recursion uses the *full* banned-param list, not a special
subset — so any flag that's banned at the root is also banned
when nested."""
with pytest.raises(ValueError, match="langfuse_host"):
is_request_body_safe(
request_body={
"litellm_embedding_config": {
"langfuse_host": "https://attacker.example.com"
}
},
general_settings={},
llm_router=None,
model="milvus-store",
)
def test_nested_api_base_allowed_when_admin_opts_in(self):
"""Admins who explicitly enable client-side credential passthrough
keep the existing escape hatch — same UX as for root-level."""
assert (
is_request_body_safe(
request_body={
"litellm_embedding_config": {
"api_base": "https://my-azure.example.com"
}
},
general_settings={"allow_client_side_credentials": True},
llm_router=None,
model="milvus-store",
)
is True
)
def test_safe_nested_config_accepted(self):
"""A nested config without any banned params passes — there's no
false-positive on legitimate ``api_version`` / model params."""
assert (
is_request_body_safe(
request_body={
"litellm_embedding_config": {
"api_version": "2024-02-15-preview",
}
},
general_settings={},
llm_router=None,
model="milvus-store",
)
is True
)
def test_non_dict_nested_config_does_not_break_check(self):
"""A bogus type for ``litellm_embedding_config`` (string, list,
None) must not crash the validator — it should just fall through."""
assert (
is_request_body_safe(
request_body={"litellm_embedding_config": "not-a-dict"},
general_settings={},
llm_router=None,
model="x",
)
is True
)
def test_deeply_nested_config_does_not_recurse(self):
"""Greptile P1: ``is_request_body_safe`` is iterative single-level —
a deeply-nested ``litellm_embedding_config`` cannot exhaust the
Python call stack to trigger a 500 ``RecursionError``. Build a
body 1000 levels deep; the validator must complete in O(1)
descent."""
body = {"litellm_embedding_config": {}}
cur = body["litellm_embedding_config"]
for _ in range(1000):
cur["litellm_embedding_config"] = {}
cur = cur["litellm_embedding_config"]
# Banned param at the deepest level shouldn't be reached — single
# level only.
cur["api_base"] = "https://attacker.example.com"
# No exception raised: deeper levels aren't checked.
assert (
is_request_body_safe(
request_body=body,
general_settings={},
llm_router=None,
model="x",
)
is True
)
# ── observability-callback ban (root + metadata) ───────────────────────────
class TestObservabilityCallbackBans:
"""The proxy must reject observability credentials, hosts, and project
identifiers regardless of whether they arrive at the request body root,
in ``metadata`` / ``litellm_metadata``, or in a JSON-string-encoded
metadata blob (multipart/``extra_body`` path).
The ban list is derived from
``litellm.litellm_core_utils.initialize_dynamic_callback_params._supported_callback_params``
minus a small ``_SAFE_CLIENT_CALLBACK_PARAMS`` allow-list, plus
``_EXTRA_BANNED_OBSERVABILITY_PARAMS`` for fields integrations read but
that are not yet in the canonical allow-list. The derivation keeps the
proxy in sync as new integrations are added.
"""
@pytest.fixture(autouse=True)
def _disable_url_validation(self, monkeypatch):
import litellm
monkeypatch.setattr(litellm, "user_url_validation", False, raising=False)
@pytest.mark.parametrize(
"field",
[
"langfuse_public_key",
"langfuse_secret",
"langfuse_secret_key",
"langsmith_api_key",
"langsmith_project",
"langsmith_tenant_id",
"arize_api_key",
"arize_space_key",
"arize_space_id",
"posthog_api_key",
"posthog_api_url",
"braintrust_api_key",
"braintrust_project",
"wandb_api_key",
"weave_project_id",
"gcs_bucket_name",
"gcs_path_service_account",
"humanloop_api_key",
"lunary_public_key",
],
)
def test_observability_field_in_request_body_root_is_rejected(self, field):
with pytest.raises(ValueError) as exc:
is_request_body_safe(
request_body={"model": "gpt-4", field: "attacker-value"},
general_settings={},
llm_router=None,
model="gpt-4",
)
assert field in str(exc.value)
@pytest.mark.parametrize(
"metadata_key",
["metadata", "litellm_metadata"],
)
@pytest.mark.parametrize(
"field",
[
"langfuse_host",
"langfuse_secret_key",
"langsmith_api_key",
"posthog_api_url",
"braintrust_project",
"user_api_key_auth_metadata",
],
)
def test_observability_field_in_metadata_dict_is_rejected(
self, metadata_key, field
):
# Verifies the metadata walk: a value smuggled inside ``metadata``
# or ``litellm_metadata`` is just as dangerous as the same field
# at the body root, and must hit the same gate.
with pytest.raises(ValueError) as exc:
is_request_body_safe(
request_body={
"model": "gpt-4",
metadata_key: {field: "attacker-value"},
},
general_settings={},
llm_router=None,
model="gpt-4",
)
assert field in str(exc.value)
@pytest.mark.parametrize("metadata_key", ["metadata", "litellm_metadata"])
@pytest.mark.parametrize(
"field",
["phoenix_project_name", "phoenix_project_name_override"],
)
def test_phoenix_project_fields_in_metadata_are_accepted(self, metadata_key, field):
# The Phoenix integrations only honor the project from
# ``user_api_key_auth_metadata`` on the proxy, so the bare metadata
# fields are inert and must not 400 SDK-style callers that send them.
assert (
is_request_body_safe(
request_body={
"model": "gpt-4",
metadata_key: {field: "client-project"},
},
general_settings={},
llm_router=None,
model="gpt-4",
)
is True
)
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"],
)
def test_observability_field_in_json_string_metadata_is_rejected(
self, metadata_key
):
# Multipart/form-data and ``extra_body`` callers send metadata as a
# JSON-encoded string. The bouncer parses it before applying the
# banned-params check so the JSON-string path can't smuggle past
# the ``isinstance(dict)`` guard.
import json
with pytest.raises(ValueError) as exc:
is_request_body_safe(
request_body={
"model": "gpt-4",
metadata_key: json.dumps(
{"langfuse_host": "https://attacker.example"}
),
},
general_settings={},
llm_router=None,
model="gpt-4",
)
assert "langfuse_host" in str(exc.value)
def test_admin_opt_in_allows_metadata_credential_passthrough(self):
# The opt-in gate covers the metadata path the same way it covers
# the root path — operators running BYO observability with
# clientside creds flip a single flag and both paths work.
assert (
is_request_body_safe(
request_body={
"model": "gpt-4",
"metadata": {
"langfuse_host": "https://my-langfuse.example",
"langfuse_public_key": "pk-mine",
"langfuse_secret_key": "sk-mine",
},
},
general_settings={"allow_client_side_credentials": True},
llm_router=None,
model="gpt-4",
)
is True
)
def test_safe_per_request_observability_metadata_is_allowed(self):
# Informational fields (sampling rate, prompt version) describe
# the request being logged — they don't choose the destination or
# credentials, so they must remain accepted from clients without
# the opt-in flag.
assert (
is_request_body_safe(
request_body={
"model": "gpt-4",
"metadata": {
"langfuse_prompt_version": "v2",
"langsmith_sampling_rate": 0.1,
},
},
general_settings={},
llm_router=None,
model="gpt-4",
)
is True
)
def test_model_level_allow_does_not_skip_subsequent_banned_params(monkeypatch):
"""Greptile P1: ``_check_banned_params`` previously ``return``-ed when a
deployment's ``configurable_clientside_auth_params`` permitted one
banned field, exiting before any later banned field in the same body
was checked. The metadata walk this PR adds multiplies the surface
where that bypass matters: a body pairing a model-level-allowed
``api_base`` with an observability credential like ``langfuse_host``
must still reject on the second field, not silently pass."""
from litellm.proxy.auth import auth_utils
monkeypatch.setattr(
auth_utils,
"_allow_model_level_clientside_configurable_parameters",
lambda model, param, request_body_value, llm_router: param == "api_base",
)
with pytest.raises(ValueError) as exc:
is_request_body_safe(
request_body={
"model": "gpt-4",
"api_base": "https://allowed-by-deployment.example",
"langfuse_host": "https://attacker.example",
},
general_settings={},
llm_router=None,
model="gpt-4",
)
assert "langfuse_host" in str(exc.value)
def test_observability_ban_covers_canonical_supported_callback_params():
"""Guard test: every entry in the canonical
``_supported_callback_params`` allow-list must end up either banned by
the proxy or explicitly safe-listed. New integrations added to that
list are banned by default (the safe failure mode); flagging them as
safe is an explicit decision recorded in
``_SAFE_CLIENT_CALLBACK_PARAMS``."""
from litellm.litellm_core_utils.initialize_dynamic_callback_params import (
_request_blocked_callback_params,
_supported_callback_params,
)
from litellm.proxy.auth.auth_utils import (
_BANNED_REQUEST_BODY_PARAMS,
_SAFE_CLIENT_CALLBACK_PARAMS,
)
banned = set(_BANNED_REQUEST_BODY_PARAMS)
for param in _supported_callback_params:
assert param in banned or param in _SAFE_CLIENT_CALLBACK_PARAMS, (
f"{param} is in _supported_callback_params but neither banned nor "
f"safe-listed. Add it to _SAFE_CLIENT_CALLBACK_PARAMS if it is an "
f"informational per-request field; otherwise the derivation will "
f"ban it automatically."
)
for param in _request_blocked_callback_params:
assert param in banned, (
f"{param} is in _request_blocked_callback_params but is not banned "
"at the proxy request-body boundary."
)
# ── pricing injection (global model cost registry poisoning) ──────────────────
class TestPricingInjectionBlocked:
"""Authenticated clients must not be able to mutate the global
litellm.model_cost registry by supplying pricing fields in the request
body. Any CustomPricingLiteLLMParams field (input_cost_per_token etc.)
passed to completion() is forwarded to register_model(), which overwrites
the shared global dict for ALL users on the instance.
Fix: all CustomPricingLiteLLMParams fields are in _BANNED_REQUEST_BODY_PARAMS,
so is_request_body_safe() rejects them before they reach completion().
"""
@pytest.mark.parametrize(
"field,value",
[
("input_cost_per_token", -0.01),
("output_cost_per_token", 0.0),
("input_cost_per_second", 999.0),
("output_cost_per_second", -1.0),
("cache_read_input_token_cost", 0.0),
("cache_creation_input_token_cost", -0.05),
],
)
def test_pricing_field_rejected_by_default(self, field, value):
with pytest.raises(ValueError) as exc:
is_request_body_safe(
request_body={"model": "gpt-4", field: value},
general_settings={},
llm_router=None,
model="gpt-4",
)
assert field in str(exc.value)
def test_all_custom_pricing_fields_are_banned(self):
from litellm.proxy.auth.auth_utils import _BANNED_REQUEST_BODY_PARAMS
from litellm.types.utils import CustomPricingLiteLLMParams
banned = set(_BANNED_REQUEST_BODY_PARAMS)
for field in CustomPricingLiteLLMParams.model_fields:
assert field in banned, (
f"CustomPricingLiteLLMParams.{field} is not in "
"_BANNED_REQUEST_BODY_PARAMS — clients can poison the global "
"model cost registry by supplying it in the request body."
)
def test_pricing_field_allowed_with_admin_opt_in(self):
assert (
is_request_body_safe(
request_body={"model": "gpt-4", "input_cost_per_token": 0.00001},
general_settings={"allow_client_side_credentials": True},
llm_router=None,
model="gpt-4",
)
is True
)
class TestGetRequestRouteTemplate:
"""get_request_route_template returns the low-cardinality FastAPI route
template (e.g. /v1/threads/{thread_id}/runs) for http.route, distinct
from the literal url.path. None when unavailable."""
def _request(self, scope):
req = MagicMock()
req.scope = scope
return req
def test_returns_route_template(self):
route = MagicMock()
route.path = "/v1/threads/{thread_id}/runs"
req = self._request({"route": route, "path": "/v1/threads/abc123/runs"})
# template, not the literal path — two thread IDs share this value
assert get_request_route_template(req) == "/v1/threads/{thread_id}/runs"
def test_scope_not_dict_returns_none(self):
assert get_request_route_template(self._request("not-a-dict")) is None
def test_no_route_in_scope_returns_none(self):
assert get_request_route_template(self._request({"path": "/x"})) is None
def test_route_without_str_path_returns_none(self):
route = MagicMock()
route.path = 12345 # not a str
assert get_request_route_template(self._request({"route": route})) is None
def test_route_with_empty_path_returns_none(self):
route = MagicMock()
route.path = ""
assert get_request_route_template(self._request({"route": route})) is None
def test_exception_returns_none(self):
req = MagicMock()
type(req).scope = property(
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 TestGetKeyTagRateLimits:
"""Tests for get_key_tag_rpm_limit."""
def test_reads_tag_rpm_limit_from_metadata(self):
key = UserAPIKeyAuth(
api_key="sk-123", metadata={"tag_rpm_limit": {"cell-1": 5}}
)
assert get_key_tag_rpm_limit(key) == {"cell-1": 5}
def test_returns_none_when_unset(self):
key = UserAPIKeyAuth(api_key="sk-123")
assert get_key_tag_rpm_limit(key) is None
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
)
class TestHasUserSetupSso:
"""_has_user_setup_sso must treat SAML IdP metadata as SSO configured.
Regression: UI discovery used this helper for sso_configured, but it only
checked OAuth client IDs, so SAML-only setups left the login button gray.
"""
@pytest.fixture(autouse=True)
def _clear_sso_env(self, monkeypatch):
for key in (
"MICROSOFT_CLIENT_ID",
"GOOGLE_CLIENT_ID",
"GENERIC_CLIENT_ID",
"SAML_IDP_METADATA_URL",
"SAML_IDP_METADATA_XML",
):
monkeypatch.delenv(key, raising=False)
def test_false_when_no_sso_env(self):
from litellm.proxy.auth.auth_utils import _has_user_setup_sso
assert _has_user_setup_sso() is False
def test_true_for_oauth_client_ids(self, monkeypatch):
from litellm.proxy.auth.auth_utils import _has_user_setup_sso
monkeypatch.setenv("GOOGLE_CLIENT_ID", "google-client")
assert _has_user_setup_sso() is True
def test_true_for_saml_metadata_url(self, monkeypatch):
from litellm.proxy.auth.auth_utils import _has_user_setup_sso
monkeypatch.setenv(
"SAML_IDP_METADATA_URL", "https://idp.example.com/metadata.xml"
)
assert _has_user_setup_sso() is True
def test_true_for_saml_metadata_xml(self, monkeypatch):
from litellm.proxy.auth.auth_utils import _has_user_setup_sso
monkeypatch.setenv("SAML_IDP_METADATA_XML", "<EntityDescriptor/>")
assert _has_user_setup_sso() is True
class TestIsRequestBodySafeBlocksAwsIdentitySelectors:
"""A caller must not be able to redirect Bedrock signing to another identity
reachable from the proxy host. ``get_credentials`` prefers a named profile
and the AssumeRole knobs over the deployment's static keys, and the file /
batch endpoints fold the request body and the deployment credentials into a
single params dict, so these have to be rejected at the boundary (#36155).
"""
@pytest.mark.parametrize(
"selector",
["aws_profile_name", "aws_session_name", "aws_external_id"],
)
def test_aws_identity_selector_in_batch_body_is_rejected(self, selector):
with pytest.raises(ValueError, match=selector):
is_request_body_safe(
request_body={
"input_file_id": "file-abc123",
"endpoint": "/v1/chat/completions",
"completion_window": "24h",
"model": "bedrock-batch-model",
selector: "attacker-chosen",
},
general_settings={},
llm_router=None,
model="bedrock-batch-model",
)
@pytest.mark.parametrize(
"selector",
["aws_profile_name", "aws_session_name", "aws_external_id"],
)
def test_aws_identity_selector_under_extra_body_is_rejected(self, selector):
with pytest.raises(ValueError, match=selector):
is_request_body_safe(
request_body={
"model": "bedrock-batch-model",
"extra_body": {selector: "attacker-chosen"},
},
general_settings={},
llm_router=None,
model="bedrock-batch-model",
)
def test_aws_identity_selector_allowed_under_proxy_wide_opt_in(self):
assert (
is_request_body_safe(
request_body={
"model": "bedrock-batch-model",
"aws_profile_name": "admin-approved-profile",
},
general_settings={"allow_client_side_credentials": True},
llm_router=None,
model="bedrock-batch-model",
)
is True
)
def test_upload_body_without_identity_selectors_is_accepted(self):
assert (
is_request_body_safe(
request_body={"purpose": "batch", "model": "bedrock-batch-model"},
general_settings={},
llm_router=None,
model="bedrock-batch-model",
)
is True
)
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