BotNet News

During the holiday season, cyberthreat news and scams dominate the headlines. This has prompted researchers to develop automated techniques for extracting cyberthreat related information from textual sources. These techniques may help security experts understand the threat landscape and build tools to protect their organizations from future malicious attacks.

The darknet is a rich source of cybersecurity-related content, including documents, scripts, hacking tools, and malware. Researchers have found that aggregating these resources can provide an insight into emerging threats and attack methodologies. A proposed AZSecure platform can make it easy to scan for such cutting edge cyberattacks.

A few examples of such content include articles, blogs, forums, and reports written by cybersecurity experts. These publications can provide useful information such as threat actor profiles, attack vectors, and payloads. They also describe steps to follow in the event of an attack.

Another reputable source of cybersecurity-related information is social media posts. Many reputable security practitioners and vendors publish content on Facebook and Twitter. Cyberthreat researchers post cutting-edge news and reports on these sites. Using CTI to analyze these texts can provide useful insights into emerging threat-related issues and cutting-edge hacking tools.

One of the more popular approaches to CTI is using data collected from Twitter and other social media channels. These text-based feeds have been analyzed for relevant information such as cybersecurity-related events and keywords. Some of these methods have incorporated clustering, k-means, and ainity propagation.

The best way to extract CTI from these sources is to use a semi-structured format that may not require significant human intervention.