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9e6561a1ec
# What does this PR do? The goal of this PR is code base modernization. Schema reflection code needed a minor adjustment to handle UnionTypes and collections.abc.AsyncIterator. (Both are preferred for latest Python releases.) Note to reviewers: almost all changes here are automatically generated by pyupgrade. Some additional unused imports were cleaned up. The only change worth of note can be found under `docs/openapi_generator` and `llama_stack/strong_typing/schema.py` where reflection code was updated to deal with "newer" types. Signed-off-by: Ihar Hrachyshka <ihar.hrachyshka@gmail.com>
86 lines
3.1 KiB
Python
86 lines
3.1 KiB
Python
# Copyright (c) Meta Platforms, Inc. and affiliates.
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# All rights reserved.
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#
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# This source code is licensed under the terms described in the LICENSE file in
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# the root directory of this source tree.
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from typing import Any
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from llama_stack.distribution.datatypes import AccessAttributes
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from llama_stack.log import get_logger
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logger = get_logger(__name__, category="core")
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def check_access(
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obj_identifier: str,
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obj_attributes: AccessAttributes | None,
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user_attributes: dict[str, Any] | None = None,
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) -> bool:
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"""Check if the current user has access to the given object, based on access attributes.
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Access control algorithm:
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1. If the resource has no access_attributes, access is GRANTED to all authenticated users
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2. If the user has no attributes, access is DENIED to any object with access_attributes defined
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3. For each attribute category in the resource's access_attributes:
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a. If the user lacks that category, access is DENIED
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b. If the user has the category but none of the required values, access is DENIED
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c. If the user has at least one matching value in each required category, access is GRANTED
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Example:
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# Resource requires:
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access_attributes = AccessAttributes(
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roles=["admin", "data-scientist"],
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teams=["ml-team"]
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)
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# User has:
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user_attributes = {
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"roles": ["data-scientist", "engineer"],
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"teams": ["ml-team", "infra-team"],
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"projects": ["llama-3"]
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}
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# Result: Access GRANTED
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# - User has the "data-scientist" role (matches one of the required roles)
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# - AND user is part of the "ml-team" (matches the required team)
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# - The extra "projects" attribute is ignored
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Args:
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obj_identifier: The identifier of the resource object to check access for
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obj_attributes: The access attributes of the resource object
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user_attributes: The attributes of the current user
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Returns:
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bool: True if access is granted, False if denied
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"""
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# If object has no access attributes, allow access by default
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if not obj_attributes:
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return True
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# If no user attributes, deny access to objects with access control
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if not user_attributes:
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return False
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dict_attribs = obj_attributes.model_dump(exclude_none=True)
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if not dict_attribs:
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return True
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# Check each attribute category (requires ALL categories to match)
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# TODO: formalize this into a proper ABAC policy
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for attr_key, required_values in dict_attribs.items():
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user_values = user_attributes.get(attr_key, [])
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if not user_values:
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logger.debug(f"Access denied to {obj_identifier}: missing required attribute category '{attr_key}'")
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return False
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if not any(val in user_values for val in required_values):
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logger.debug(
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f"Access denied to {obj_identifier}: "
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f"no match for attribute '{attr_key}', required one of {required_values}"
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)
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return False
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logger.debug(f"Access granted to {obj_identifier}")
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return True
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