Adds a configurable Hugging Face model download cache location to Unsloth Studio, selectable from Settings, with per-cache download manifests, scoped deletion, and read-only inventory of previously selected caches.
497 lines
21 KiB
Python
497 lines
21 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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"""Malware / unsafe-file gate for model loads.
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The ``trust_remote_code`` consent gate covers the ``auto_map`` Python vector; this
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covers the other one -- a malicious pickle inside a weight file, which executes
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during ``from_pretrained`` deserialization even with ``trust_remote_code=False``.
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It reads Hugging Face's OWN scan (picklescan + ClamAV) via
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``model_info(securityStatus=True).security_repo_status``. METADATA-ONLY: it never
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downloads, opens, or unpickles the flagged files.
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Policy:
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* Hard block, non-approvable.
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* Block whenever ``filesWithIssues`` lists a non-``safe`` level, regardless of
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``scansDone`` (often false even for clean repos). Unknown/future levels fail
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CLOSED (block) so Hub schema drift cannot silently allow a bad verdict; only a
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small allowlist of clean / not-yet-scanned levels is non-blocking. The sole
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fail-open path is an unavailable status (missing field / offline / error).
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* Scope to the load-path RCE vector: a root-level (or load-subdir-level),
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code-executing file. Inert formats (safetensors / gguf / config / text) and
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subdirectory pickles that no root weight-index references are NOT loaded, so
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they do not block; an index-referenced shard does, wherever it lives. This
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blocks real malware (eicar's root ``*.pkl``/``*.dat``) without false-blocking
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repos like ``nvidia/Nemotron-H-8B-Base-8K`` (flagged NeMo pickles under
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``nemo/`` that no index lists).
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* No first-party exemption (scoping is by load path/format, not org).
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* Local paths are skipped (no Hub scan); a remote ``*.gguf``-named repo is still
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scanned so a repo cannot dodge the gate by suffixing its name.
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"""
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import re
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from dataclasses import dataclass, field
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from pathlib import Path
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from typing import Optional
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from loggers import get_logger
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logger = get_logger(__name__)
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# Pickle-format weight files (plain or sharded) that execute code on load; safetensors/gguf
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# are inert. Grouped by weight family so an inert safetensors only suppresses the pickle it
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# actually replaces: the loader won't use an adapter's safetensors for pytorch_model.bin.
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_PICKLE_WEIGHT_RE = re.compile(
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r"^(model|pytorch_model|adapter_model|consolidated)(-\d+-of-\d+)?"
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r"\.(bin|pt|pth|ckpt|pkl|pickle)$",
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re.IGNORECASE,
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)
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# Base-model safetensors set: HF names the base pickle pytorch_model.bin but the safetensors
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# model.safetensors (stems differ), so a base pickle is replaced only by these, not an adapter's.
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_BASE_SAFETENSORS_RE = re.compile(
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r"^(model(-\d+-of-\d+)?\.safetensors|model\.safetensors\.index\.json)$",
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re.IGNORECASE,
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)
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# Adapter (PEFT) safetensors set: adapter_model.safetensors, its shards, or index.
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_ADAPTER_SAFETENSORS_RE = re.compile(
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r"^(adapter_model(-\d+-of-\d+)?\.safetensors|adapter_model\.safetensors\.index\.json)$",
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re.IGNORECASE,
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)
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# Non-blocking levels: clean or not-yet-finished. Anything else (unsafe/suspicious/
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# malicious or a future label) blocks, so Hub schema drift fails CLOSED.
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_NONBLOCKING_LEVELS = frozenset(
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{"", "safe", "pending", "scanning", "queued", "unscanned", "error", "unknown", "none"}
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)
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# Suffixes that cannot execute code on load (tensor-only safetensors, non-pickle gguf,
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# text/markup/images), so a flag on one is never an RCE vector.
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_INERT_SUFFIXES = frozenset(
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{
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".safetensors",
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".gguf",
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".json",
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".txt",
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".md",
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".rst",
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".yaml",
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".yml",
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".png",
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".jpg",
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".jpeg",
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".gif",
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".webp",
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".svg",
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".bmp",
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".gitattributes",
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".gitignore",
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}
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)
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# Source files are not deserialized by a weight load; executable repo code runs only
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# via auto_map, which is the consent gate's domain. So a flag on a .py is not this
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# gate's vector (else a flagged helper/train script would false-block).
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_SOURCE_SUFFIXES = frozenset({".py", ".pyc", ".pyx", ".pyi"})
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# Root weight-index files. from_pretrained reads these to find sharded weights, so a
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# flagged subdir pickle is a load vector iff a root index references it.
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_TRANSFORMERS_INDEX_FILES = (
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"pytorch_model.bin.index.json",
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"model.safetensors.index.json",
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"tf_model.h5.index.json",
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"flax_model.msgpack.index.json",
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)
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def _normalize_repo_path(path: str) -> str:
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"""Strip ``./`` prefixes and normalize separators for repo-relative comparison."""
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p = (path or "").strip().replace("\\", "/")
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while p.startswith("./"):
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p = p[2:]
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return p
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def _file_suffix(path: str) -> str:
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"""Lowercase ``.ext`` of the basename, or ``""`` if none."""
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base = _normalize_repo_path(path).rsplit("/", 1)[-1]
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return "." + base.rsplit(".", 1)[1].lower() if "." in base else ""
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def _load_relative_path(norm: str, load_subdirs) -> str:
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"""``norm`` relative to a ``from_pretrained`` load root. Some loads read from a
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snapshot SUBDIRECTORY (Spark-TTS / BiCodec load ``<snapshot>/LLM``), where a file
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directly under the subdir is root-level, not nested. Strips the matching load-subdir
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prefix, or returns ``norm`` unchanged when it is not under one.
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"""
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for subdir in load_subdirs or ():
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prefix = _normalize_repo_path(subdir).strip("/")
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if prefix and norm.startswith(prefix + "/"):
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return norm[len(prefix) + 1 :]
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return norm
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def _index_prefixes(load_subdirs) -> tuple:
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"""Prefixes to look for weight-index files under: repo root plus each load subdir."""
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prefixes = [""]
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for subdir in load_subdirs or ():
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p = _normalize_repo_path(subdir).strip("/")
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if p:
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prefixes.append(p + "/")
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return tuple(prefixes)
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def _indexed_shard_paths(
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model_name: str,
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hf_token: Optional[str],
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load_subdirs = (),
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):
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"""Repo-relative weight paths a load could fetch via weight-index files. Returns a
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set (empty when the repo ships no index files -- a definitive "nothing sharded"), or
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None when the lookup was inconclusive (transient error) so the caller treats a
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flagged subdir pickle conservatively. Reads only small JSON indexes, never weights.
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Indexes are looked up at the root and each ``load_subdirs`` root, with ``weight_map``
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entries re-prefixed to repo-relative paths.
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"""
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import json
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try:
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from huggingface_hub import hf_hub_download
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from huggingface_hub.utils import EntryNotFoundError
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from utils.hf_cache_settings import active_hf_hub_cache
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except Exception:
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return None
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paths: set = set()
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inconclusive = False
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for prefix in _index_prefixes(load_subdirs):
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for filename in _TRANSFORMERS_INDEX_FILES:
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try:
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index_path = hf_hub_download(
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model_name,
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prefix + filename,
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token = hf_token or None,
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cache_dir = active_hf_hub_cache(),
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)
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except EntryNotFoundError:
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continue # definitively absent, not an error
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except Exception:
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inconclusive = True # transient: an index that might exist could not be read
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continue
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try:
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weight_map = (json.loads(open(index_path).read()) or {}).get("weight_map") or {}
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for shard in weight_map.values():
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shard_norm = _normalize_repo_path(str(shard))
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# weight_map paths are relative to the index file's directory.
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if prefix and not shard_norm.startswith(prefix):
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shard_norm = prefix + shard_norm
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paths.add(shard_norm)
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except Exception:
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inconclusive = True
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# Any transient failure -> inconclusive (the shard could be listed only by the index
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# we could not read), so fail closed (None) and let the caller block. Ships no index
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# files -> EntryNotFoundError for each, empty set, a definitive "nothing sharded".
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if inconclusive:
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return None
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return paths
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# Two-timeout metadata fetch, mirroring hub.workers.hf_download._retry_metadata_fetch.
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_REQUEST_TIMEOUT = 10.0
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_RETRY_TIMEOUT = 20.0
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@dataclass
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class FileSecurityDecision:
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"""Outcome of the Hub security scan for one model repo."""
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model_name: str
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blocked: bool
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unsafe_files: list = field(default_factory = list) # [{"path", "level"}]
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reason: str = ""
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def response_payload(self) -> dict:
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"""Machine-readable detail merged into the preflight payload the dialog reads."""
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return {
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"unsafe_files": self.unsafe_files,
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"security_blocked": self.blocked,
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"reason": self.reason,
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}
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def security_load_subdirs(model_name: str, hf_token: Optional[str] = None) -> tuple:
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"""Snapshot subdirectories a load calls ``from_pretrained`` on, for scoping the scan.
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Most models load from the root (``()``); Spark-TTS / BiCodec load ``<snapshot>/LLM``,
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so ``LLM/`` is a load root for them. Metadata-only (tokenizer special tokens), cached.
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"""
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try:
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from utils.models.model_config import detect_audio_type, load_model_defaults
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if detect_audio_type(model_name, hf_token = hf_token) == "bicodec":
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return ("LLM",)
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# Tokenizer detection can fail (network/gated/unresolved alias); the YAML default
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# also pins the audio type, so fall back to it (else a flagged LLM/ pickle is
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# treated as an ignored subdir artifact).
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if (load_model_defaults(model_name) or {}).get("audio_type") == "bicodec":
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return ("LLM",)
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except Exception:
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pass
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return ()
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def _load_scan_target(model_name: str, load_subdirs: tuple) -> tuple:
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"""Map a load alias to the ``(repo_id, load_subdirs)`` the load actually fetches. The
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Spark-TTS / BiCodec alias ``<parent>/LLM`` is downloaded by the trainer as
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``unsloth/<parent>`` and loaded from ``LLM/``, so scan that repo with ``LLM`` as a
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load root (the literal alias 404s and fails open). Everything else is unchanged.
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"""
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try:
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from utils.paths import is_local_path
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if is_local_path(model_name):
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return model_name, load_subdirs
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except Exception:
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return model_name, load_subdirs
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name = (model_name or "").strip().strip("/")
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# Rewrite ONLY a registry-known bicodec alias, never any repo ending in "/LLM"
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# (e.g. "evil/LLM" would scan unsloth/evil and fail open on the real repo).
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if name.endswith("/LLM") and name.count("/") == 1:
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try:
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from utils.models.model_config import load_model_defaults
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if (load_model_defaults(name) or {}).get("audio_type") == "bicodec":
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parent = name[: -len("/LLM")]
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return f"unsloth/{parent}", tuple(dict.fromkeys((*load_subdirs, "LLM")))
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except Exception:
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pass
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return model_name, load_subdirs
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def _fetch_security_status(model_name: str, hf_token: Optional[str]):
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"""``security_repo_status`` (a dict) or None if unavailable. Hub metadata only;
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retries once on a transient error, then returns None so the caller fails open.
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"""
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from huggingface_hub import model_info as hf_model_info
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token_arg = hf_token if hf_token else False
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last_exc = None
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for attempt, timeout in enumerate((_REQUEST_TIMEOUT, _RETRY_TIMEOUT)):
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try:
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info = hf_model_info(
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model_name,
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token = token_arg,
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securityStatus = True,
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timeout = timeout,
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)
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return getattr(info, "security_repo_status", None)
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except Exception as exc: # network/offline/gated/404/unsupported-client
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last_exc = exc
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if attempt == 0:
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continue
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logger.debug(
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"HF security scan unavailable for '%s' (%s); failing open.",
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model_name,
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type(last_exc).__name__ if last_exc else "unknown",
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)
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return None
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def _st_load_roots(snapshot: Path) -> list:
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"""Directories a SentenceTransformer load deserializes weights from: the snapshot root plus
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each module path in modules.json. Local, no network. Mirrors the online gate (which ignores
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unreferenced nested pickles ST never loads) so the offline gate doesn't over-block."""
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roots = [snapshot]
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try:
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import json
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modules = json.loads((snapshot / "modules.json").read_text())
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except (OSError, ValueError):
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return roots # no / invalid modules.json -> snapshot root is the only load root
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for module in modules or ():
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path = str((module or {}).get("path", "")).strip().strip("/")
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# Relative module path only; ignore a crafted "../" escape.
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if path and ".." not in path.split("/"):
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candidate = snapshot / path
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if candidate not in roots:
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roots.append(candidate)
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return roots
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def _cached_pickle_weight_files(snapshot: Path) -> list:
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"""Pickle weight files in snapshot's ST load roots, EXCLUDING those whose weight family also
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ships an inert safetensors in the same dir (the loader prefers it): a base pickle is suppressed
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only by a base model.safetensors, an adapter pickle only by adapter_model.safetensors -- an
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unrelated safetensors is no substitute. Load roots only. Raises OSError if the snapshot root is
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unreadable (caller blocks)."""
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blocked = []
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for root in _st_load_roots(snapshot):
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try:
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entries = [p for p in root.iterdir() if p.is_file()]
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except OSError:
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if root == snapshot:
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raise # top-level unreadable -> fail closed
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continue # unreadable module subdir: nothing loadable to attest here
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has_base_safetensors = any(_BASE_SAFETENSORS_RE.match(p.name) for p in entries)
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has_adapter_safetensors = any(_ADAPTER_SAFETENSORS_RE.match(p.name) for p in entries)
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for path in entries:
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if not _PICKLE_WEIGHT_RE.match(path.name):
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continue
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is_adapter = path.name.lower().startswith("adapter_model")
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has_alternative = has_adapter_safetensors if is_adapter else has_base_safetensors
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if not has_alternative:
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blocked.append(path)
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return blocked
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def _evaluate_local_only(model_name: str) -> FileSecurityDecision:
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"""Offline security gate. The Hub scan is unreachable, so inspect the local cache and fail
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CLOSED on an unscanned pickle weight with no inert safetensors alternative, rather than
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failing open or hanging. Safetensors/gguf-only cache loads; nothing cached -> allowed."""
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from utils.utils import hf_cache_snapshot_dir
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try:
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snapshot = hf_cache_snapshot_dir(model_name)
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except Exception:
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logger.warning("Offline gate: could not resolve the cache for '%s'; blocking.", model_name)
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return FileSecurityDecision(
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model_name, True, reason = "offline; could not inspect the local cache"
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)
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if snapshot is None:
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return FileSecurityDecision(model_name, False, reason = "offline; nothing cached to load")
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try:
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pickles = _cached_pickle_weight_files(snapshot)
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except OSError:
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logger.warning("Offline gate: could not read the cache for '%s'; blocking.", model_name)
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return FileSecurityDecision(
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model_name, True, reason = "offline; could not read the local cache"
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)
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if not pickles:
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return FileSecurityDecision(
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model_name, False, reason = "offline; cached weights are inert (safetensors/gguf)"
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)
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# Snapshot-relative posix paths (match the online gate; disambiguate same-named pickles).
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rel_paths = sorted(p.relative_to(snapshot).as_posix() for p in pickles)
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names = ", ".join(rel_paths)
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logger.warning(
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"Blocking offline load of '%s': cached pickle weight(s) cannot be malware-scanned "
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"offline and have no safetensors alternative (%s).",
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model_name,
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names,
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)
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return FileSecurityDecision(
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model_name,
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True,
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unsafe_files = [{"path": rel, "level": "unscanned"} for rel in rel_paths],
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reason = f"offline; unscanned pickle weights with no safetensors alternative: {names}",
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)
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def evaluate_file_security(
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model_name: str,
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hf_token: Optional[str] = None,
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*,
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load_subdirs = (),
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local_only_load: bool = False,
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) -> FileSecurityDecision:
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"""Block a load when HF's security scan flags unsafe serialized files.
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Call UNCONDITIONALLY before any load (independent of trust_remote_code): a malicious
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pickle deserializes during ``from_pretrained`` regardless. Metadata-only; fails open
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when the scan is unavailable.
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``load_subdirs`` names subdirs the load calls ``from_pretrained`` on (e.g. ``("LLM",)``
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for Spark-TTS / BiCodec, loading ``<snapshot>/LLM``): a flagged file directly under one
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is root-level there and blocks, and an index inside it is honored when scoping shards.
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``local_only_load`` marks an offline load: with the Hub scan unreachable, inspect the local
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cache and fail CLOSED on an unscanned pickle weight with no safetensors alternative.
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"""
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# Scan the repo the load actually fetches, not the literal alias (which 404s and
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# fails open): the Spark-TTS "<parent>/LLM" alias is really unsloth/<parent> from LLM/.
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model_name, load_subdirs = _load_scan_target(model_name, tuple(load_subdirs))
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# Local paths (including a local .gguf) have no Hub scan. A remote ref is scanned
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# even if named "*.gguf", so a repo cannot dodge the scan via its name.
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try:
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from utils.paths import is_local_path
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if is_local_path(model_name):
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return FileSecurityDecision(model_name, False, reason = "local path; no Hub scan")
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except Exception:
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# Cannot classify the path -> do not block on that account.
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return FileSecurityDecision(model_name, False, reason = "path check failed; not blocked")
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# Offline: inspect the local cache and fail closed rather than hang on model_info or fail open.
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if local_only_load:
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return _evaluate_local_only(model_name)
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status = _fetch_security_status(model_name, hf_token)
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if not isinstance(status, dict):
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return FileSecurityDecision(
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model_name, False, reason = "scan unavailable; allowed (fail-open)"
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)
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# Block a non-``safe`` flagged file scoped to the load-path RCE vector (root-level,
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# code-executing). Not gated on ``scansDone`` (often false even when clean; a flagged
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# file is flagged regardless). Unknown levels fail closed; in-progress/clean do not.
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# Subdir pickles and inert formats (safetensors/gguf) are not loaded by
|
|
# from_pretrained and do not block. Unavailable status (above) is the only fail-open.
|
|
unsafe = []
|
|
skipped = [] # flagged, but not a load-path RCE vector (subdir artifact / inert)
|
|
maybe_shard = [] # flagged subdir pickle: a load vector ONLY if a root index lists it
|
|
for entry in status.get("filesWithIssues") or []:
|
|
if not isinstance(entry, dict):
|
|
continue
|
|
level = str(entry.get("level", "")).lower()
|
|
if level in _NONBLOCKING_LEVELS:
|
|
continue
|
|
path = entry.get("path", "")
|
|
norm = _normalize_repo_path(path)
|
|
suffix = _file_suffix(norm)
|
|
# Path relative to the load root: a file under a load subdir (e.g. LLM/) is
|
|
# root-level there, not nested.
|
|
load_rel = _load_relative_path(norm, load_subdirs)
|
|
if not norm or suffix in _INERT_SUFFIXES or suffix in _SOURCE_SUFFIXES:
|
|
# Inert formats cannot execute on load; source code is the consent gate's
|
|
# domain (auto_map), not a deserialization vector.
|
|
skipped.append({"path": path, "level": level})
|
|
elif "/" not in load_rel:
|
|
unsafe.append({"path": path, "level": level}) # root pickle -> load vector
|
|
else:
|
|
# Subdir pickle: deserialized only if a weight index references it.
|
|
maybe_shard.append({"path": path, "level": level, "norm": norm})
|
|
|
|
if maybe_shard:
|
|
indexed = _indexed_shard_paths(model_name, hf_token, load_subdirs)
|
|
for m in maybe_shard:
|
|
# Block if a root index lists this shard, or if the lookup was inconclusive
|
|
# (transient error -> stay conservative). A definitive "no index / not listed"
|
|
# stays non-blocking (e.g. NeMo nemo/*.distcp).
|
|
if indexed is None or m["norm"] in indexed:
|
|
unsafe.append({"path": m["path"], "level": m["level"]})
|
|
else:
|
|
skipped.append({"path": m["path"], "level": m["level"]})
|
|
|
|
if not unsafe:
|
|
if skipped:
|
|
# Flagged files exist, but none the load deserializes (subdir pickle or inert
|
|
# format) -> allow, but log them so they stay visible.
|
|
logger.info(
|
|
"'%s': Hugging Face flagged files, but none are a load-path RCE "
|
|
"vector (subdir/inert); allowing the load. Flagged: %s",
|
|
model_name,
|
|
", ".join(f"{s['path']}({s['level']})" for s in skipped),
|
|
)
|
|
return FileSecurityDecision(model_name, False, reason = "no unsafe files in the load path")
|
|
|
|
names = ", ".join(u["path"] for u in unsafe if u["path"]) or "unknown files"
|
|
logger.warning(
|
|
"Blocking load of '%s': Hugging Face security scan flagged unsafe files (%s).",
|
|
model_name,
|
|
names,
|
|
)
|
|
return FileSecurityDecision(
|
|
model_name,
|
|
True,
|
|
unsafe_files = unsafe,
|
|
reason = f"Hugging Face security scan flagged unsafe files: {names}",
|
|
)
|