An issue in Open Source: RPyC v.4.00 thru v.5.3.1 allows a remote attacker to execute arbitrary code via a crafted script to the __array__ attribute component. This vulnerability was introduced in 9f45f826.
Attack Vector
RPyC services that rely on the __array__ attribute used by numpy are impacted. When the server-side exposes a method that calls the attribute named __array__ for a a client provided netref (e.g., np.array(client_netref)), a remote attacker can craft a class which results in remote code execution
Impact
Assuming the system exposes a method that calls the attribute __array__, an attacker can execute code using the vulnerable component.
Patches
The fix is available in RPyC 6.0.0. The major version change is because some users may need to set allow_pickle to True when migrating to RPyC 6.
Workarounds
While the recommend fix is to upgrade to RPyC 6.0.0, the workaround is to apply bba1d356 as patch.
Affected Component
The affected component is the __array__ method constructed for NetrefClass.
References
An issue in Open Source: RPyC v.4.00 thru v.5.3.1 allows a remote attacker to execute arbitrary code via a crafted script to the
__array__attribute component. This vulnerability was introduced in 9f45f826.Attack Vector
RPyC services that rely on the
__array__attribute used by numpy are impacted. When the server-side exposes a method that calls the attribute named__array__for a a client provided netref (e.g.,np.array(client_netref)), a remote attacker can craft a class which results in remote code executionImpact
Assuming the system exposes a method that calls the attribute
__array__, an attacker can execute code using the vulnerable component.Patches
The fix is available in RPyC 6.0.0. The major version change is because some users may need to set
allow_pickletoTruewhen migrating to RPyC 6.Workarounds
While the recommend fix is to upgrade to RPyC 6.0.0, the workaround is to apply bba1d356 as patch.
Affected Component
The affected component is the
__array__method constructed forNetrefClass.References