f08aef1804
* Rebuild Studio branch on top of main * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci * Fix security and code quality issues for Studio PR #4237 - Validate models_dir query param against allowed directory roots to prevent path traversal in /api/models/local endpoint - Replace string startswith() with Path.is_relative_to() for frontend path traversal check in serve_frontend - Sanitize SSE error messages to not leak exception details to clients (4 locations in inference.py) - Bind port-discovery socket to 127.0.0.1 instead of all interfaces in llama_cpp backend - Import datasets_root and resolve_output_dir in embedding training function to fix NameError and use managed output directory - Remove stale .gitignore entries for package-lock.json and test directories so tests can be tracked in version control - Add venv-reexecution logic to ui CLI command matching the studio command behavior * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci * Move models_dir path validation before try/except block The HTTPException(403) was inside the try/except Exception handler, so it would be caught and re-raised as a 500. Moving the validation before the try block ensures the 403 is returned directly and also makes the control flow clearer for static analysis (path is validated before any filesystem operations). * Use os.path.realpath + startswith for models_dir validation CodeQL py/path-injection does not recognize Path.is_relative_to() as a sanitizer. Switched to os.path.realpath + str.startswith which is a recognized sanitizer pattern in CodeQL's taint analysis. The startswith check uses root_str + os.sep to prevent prefix collisions (e.g. /app/models_evil matching /app/models). * Never pass user input to Path constructor in models_dir validation CodeQL traces taint through Path(resolved) even after a startswith barrier guard. Fix: the user-supplied models_dir is only used as a string for comparison against allowed roots. The Path object passed to _scan_models_dir comes from the trusted allowed_roots list, not from user input. This fully breaks the taint chain. --------- Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
48 lines
1.8 KiB
Python
48 lines
1.8 KiB
Python
# SPDX-License-Identifier: AGPL-3.0-only
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# Copyright 2026-present the Unsloth AI Inc. team. All rights reserved. See /studio/LICENSE.AGPL-3.0
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"""
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Test remote LoRA adapter detection via HuggingFace Hub API.
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Verifies that we can detect whether a remote HF model is a LoRA adapter
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by checking for adapter_config.json in the repo file listing.
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"""
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import pytest
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from huggingface_hub import model_info
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def is_remote_lora_adapter(model_id: str, hf_token: str = None) -> bool:
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"""
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Check if a remote HuggingFace model is a LoRA adapter
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by looking for adapter_config.json in its repo files.
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"""
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try:
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info = model_info(model_id, token = hf_token)
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filenames = [s.rfilename for s in info.siblings]
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return "adapter_config.json" in filenames
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except Exception:
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return False
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class TestRemoteLoRADetection:
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"""Test remote LoRA adapter detection via HF Hub API."""
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def test_lora_adapter_detected(self):
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"""edbeeching/llama-se-rl-adapter is a known LoRA adapter on HF."""
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result = is_remote_lora_adapter("edbeeching/llama-se-rl-adapter")
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assert (
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result is True
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), "Expected edbeeching/llama-se-rl-adapter to be detected as a LoRA adapter"
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def test_base_model_not_detected_as_lora(self):
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"""google/gemma-3-4b-it is a full base model, not a LoRA adapter."""
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result = is_remote_lora_adapter("google/gemma-3-4b-it")
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assert (
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result is False
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), "Expected google/gemma-3-4b-it to NOT be detected as a LoRA adapter"
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def test_nonexistent_model_returns_false(self):
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"""A nonexistent model should return False, not raise."""
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result = is_remote_lora_adapter("this-org-does-not-exist/fake-model-12345")
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assert result is False, "Expected nonexistent model to return False"
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