Criminal IP, an OSINT-based search engine, officially launched its service on April 17 after a year of solid beta service. In cybersecurity, OSINT detects sensitive information such as personal data, national security, and confidential corporate data, in addition to predicting potential security threats known as ‘Cyber Threat Intelligence (CTI)’.
Using AI technology, Criminal IP collects and analyzes IP addresses from around the world on a daily basis, enabling the detection of cyber threats. Users can choose from four search options (Asset, Domain, Image, Exploit) and efficiently retrieve desired information from large data sets using filters and tags.
Criminal IP operated on a beta service for about one year before its official service launched on April 17, 2023. Providing the service in English, Japanese, and Korean, Criminal IP has gained global notoriety in cybersecurity, with 2 million visitors from over 200 countries during its beta phase.
The official service of Criminal IP is offered with three main plans: Lite (for individual users), Medium (for small-sized enterprises), and Pro (for medium-sized enterprises). These subscription plans can be paid for online using credit cards or PayPal. Additionally, there is the option to request a customized Enterprise plan with unlimited data access for large-sized enterprises and an Academic plan available at a discounted rate for academic institutions and research purposes.
In the cybersecurity industry, Criminal IP has gained recognition for its innovative technology from various global IT communities and platforms such as GitHub, Reddit, LinkedIn, and other forums. As a result, current users have expressed their excitement and high expectations for the official release of Criminal IP’s service. Furthermore, the platform’s reliability of technology and data has been further validated by integrating with VirusTotal, Splunk, IP Location, Zabbix, and many more. Criminal IP has plans to expand and improve its features in the near future.
From The Shadows Emerges Knowledge