cyber_threat_intelligence/actors/Python
Marc Ruef d181d02f63 Update 2022-04-01 12:05:45 +02:00
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README.md Update 2022-04-01 12:05:45 +02:00

Python - Cyber Threat Intelligence

These indicators were reported, collected, and generated during the VulDB CTI analysis of the actor known as Python. The activity monitoring correlates data from social media, forums, chat rooms, and darknet markets. It helps to determine associated actors, specific activities, expected intentions, emerging research, and ongoing attacks. Our unique predictive model uses big data to forecast activities and their characteristics.

Live data and more analysis capabilities are available at https://vuldb.com/?actor.python

Countries

These countries are directly (e.g. origin of attacks) or indirectly (e.g. access by proxy) associated with Python:

IOC - Indicator of Compromise

These indicators of compromise (IOC) indicate associated network resources which are known to be part of research and attack activities of Python.

ID IP address Hostname Campaign Confidence
1 23.21.126.66 ec2-23-21-126-66.compute-1.amazonaws.com - Medium
2 54.221.253.252 ec2-54-221-253-252.compute-1.amazonaws.com - Medium
3 54.225.66.103 ec2-54-225-66-103.compute-1.amazonaws.com - Medium
4 ... ... ... ...

There are 14 more IOC items available. Please use our online service to access the data.

TTP - Tactics, Techniques, Procedures

Tactics, techniques, and procedures (TTP) summarize the suspected MITRE ATT&CK techniques used by Python. This data is unique as it uses our predictive model for actor profiling.

ID Technique Weakness Description Confidence
1 T1552 CWE-319 Unprotected Storage of Credentials High

References

The following list contains external sources which discuss the actor and the associated activities:

Literature

The following articles explain our unique predictive cyber threat intelligence:

License

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