A critical security vulnerability has been discovered in LangChain Experimental (before version .1.8) that allows an attacker to bypass previous security fixes (CVE-2023-44467) and execute arbitrary code. This is made possible through the use of certain "magic" attributes in Python code that are not restricted by the existing security measures in the pal_chain/base.py file.

The vulnerability is designated as CVE-2024-27444 and affects LangChain Experimental versions before .1.8. In this post, we will discuss the details of this security flaw, show a code snippet demonstrating the exploit, provide links to original references, and suggest possible mitigations to prevent exploitation.

Exploit Details

LangChain Experimental is a powerful natural language processing (NLP) framework designed for research and development purposes. However, it contains a critical security flaw that could allow a malicious user to execute arbitrary code on the system running the LangChain application.

The issue arises from the insufficient restrictions placed on certain attributes in Python code, such as __import__, __subclasses__, __builtins__, __globals__, __getattribute__, __bases__, __mro__, and __base__. These attributes are known as "magic" or "dunder" attributes and enable powerful functionality in Python programs, but also pose a significant security risk if used maliciously.

By utilizing these magic attributes in a Python script, an attacker can circumvent the security measures implemented in the pal_chain/base.py file, effectively bypassing the CVE-2023-44467 fix. As a result, arbitrary code can be executed on the system running the LangChain Experimental application.

Code Snippet

Here is a Python code snippet demonstrating the use of the __subclasses__ magic attribute to exploit the vulnerability in LangChain Experimental:

# exploit.py
def exploit():
    print("[*] Exploiting CVE-2024-27444 in LangChain Experimental...")
    subclasses = ().__class__.__base__.__subclasses__()
    for subclass in subclasses:
        if subclass.__name__ == 'S_ISREG':
            print("[*] Found a vulnerable class for arbitrary code execution.")
            eval('os.system("whoami")')
            break
    else:
        print("[!] Exploit failed: Unable to find a suitable class.")

This exploit attempts to use the __subclasses__ attribute to find a suitable class for arbitrary code execution, then uses the eval() function to execute a simple command (whoami) on the system.

Original References

1. LangChain Experimental GitHub Repository: https://github.com/langchain/langchain_experimental

2. CVE-2023-44467 Security Fix: https://nvd.nist.gov/vuln/detail/CVE-2023-44467v

Mitigations

To protect your LangChain Experimental application from this vulnerability, update to version .1.8 or later, which includes a fix for this issue. If you are unable to update immediately, consider disabling the use of potentially dangerous "magic" attributes in your Python code by modifying the pal_chain/base.py file:

1. Add a list of prohibited attributes to pal_chain/base.py, e.g.,

_PROHIBITED_ATTRIBUTES = [
    '__import__',
    '__subclasses__',
    '__builtins__',
    '__globals__',
    '__getattribute__',
    '__bases__',
    '__mro__',
    '__base__',
]

Implement a check to raise an exception if such an attribute is used

for attr in _PROHIBITED_ATTRIBUTES:
    if attr in my_code:  # Replace my_code with a reference to your code
        raise ValueError(f"Use of {attr} is prohibited.")

Conclusion

CVE-2024-27444 is a critical security vulnerability in LangChain Experimental that allows an attacker to bypass existing security measures and execute arbitrary code. To protect your application, update to the latest version of LangChain Experimental or implement stricter restrictions on the use of "magic" attributes in your Python code. Keep up to date on security fixes and be cautious when using powerful language features that can introduce potential risks.

Timeline

Published on: 02/26/2024 16:28:00 UTC
Last modified on: 08/06/2024 16:35:07 UTC