OSINT Intelligence Cycle

We will now focus on the OSINT intelligence cycle which is as follows:

• Planning and direction – Investigation prerequisites and question outline, before gathering OSINT, operators should have a clear idea of the types of information they require, how to discover those sources, and what they expect to accomplish with the information gathered.
• Collection –  OSINT resources include any freely available online assets, such as news stories, social media posts, and blogs, for information collection. Teams can collect this data using their preferred collecting methodologies and resources.
• Processing and Exploration – Refine the information gathered; once you’ve collected your data, you can begin processing it. Then you should organize it into a centralized evidence repository, chronology, or report.
• Analysis – Analyzed and also by the final report, Following the first processing of the obtained data, your teams will need to conduct an in-depth analysis of the material. This is an important step in the OSINT cycle since it allows your teams to understand and anticipate events using the data they’ve gathered.
• Dissemination – final distribution of other analytic products for use by others, as far as this process is concerned, the report should be easy and understandable by everybody.
• Feedback – it’s important to take feedback to improve your skills on OSINT skills.

OSINT(Open-Source Intelligence) is a multi-methods methodology for collecting, analyzing, and making decisions about data accessible in the public domain. Whether carried out by IT security experts, malicious hackers, or state-sanctioned intelligence operatives, OSINT operations use cutting-edge tools to sift through a sizable haystack of visible data for the needles they need to accomplish their goals and uncover information that many people are unaware is public. 

In this context, the phrase “open source” does not refer to the open-source software movement, though many OSINT technologies do; rather, it refers to the open nature of the data being analyzed.