Detect Python Exposed Metrics Exposure Scanner

The Python Metrics scanner detects vulnerabilities related to the exposure of certain metrics in Python environments. This exposure is commonly found in systems used by developers, data scientists, and IT professionals. It is particularly prevalent in environments where Python is used for data analysis, web development, or system automation. The exposure of Python metrics can inadvertently occur in production environments where metrics should remain confidential. Organizations often use Python's metrics for performance monitoring and optimization, making their security critical. Detection of exposed metrics helps ensure that only authenticated users have access to sensitive system information.

Exposure of Python metrics can lead to unauthorized disclosure of sensitive information pertaining to the system's Garbage Collection process. Such metrics typically reveal details about memory management which, if exposed, could provide insights into the system's performance, vulnerabilities, or state. This exposure might occur due to misconfigured services that inadvertently allow unrestricted access to metric endpoints. Understanding and managing such exposures is vital for maintaining system integrity and security. These vulnerabilities can be exploited by attackers to gather intelligence on a system's operation and weaknesses.

The vulnerability is typically noticed when endpoints meant for internal use become publicly accessible without proper authentication. In this case, the endpoint "/metrics" which displays the garbage collection objects count could become exposed. The critical elements to monitor include the status code of requests to these metric endpoints and specific keywords such as "python_gc_objects_collected_total" and "python_info". These elements indicate the presence of exposed metrics, providing a clear pathway for attackers to gather detailed information about the application's state and performance.

The possible effects of exploiting this vulnerability include unauthorized access to sensitive system metrics that describe the system's performance and resource usage. Malicious actors could use this information for reconnaissance purposes, preparing further attacks that exploit specific system weaknesses. Unauthorized access to such metrics can also lead to a competitive disadvantage if sensitive information about the system's capabilities is leaked. Organizations could face reputational damage and financial loss if exploited data is used maliciously.

REFERENCES

• https://gist.github.com/ruanbekker/e5b1e7895f62b020ff29b5f40767190c