How to Install and Uninstall unicornscan.x86_64 Package on AlmaLinux 9

Last updated: November 26,2024

1. Install "unicornscan.x86_64" package

Please follow the guidance below to install unicornscan.x86_64 on AlmaLinux 9


    
        
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                sudo dnf update
            
                    
    
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                sudo dnf install
            
                        
                unicornscan.x86_64
            
                    
    
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2. Uninstall "unicornscan.x86_64" package

Please follow the instructions below to uninstall unicornscan.x86_64 on AlmaLinux 9:


    
        
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                sudo dnf remove
            
                        
                unicornscan.x86_64
            
                    
    
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            $
        

        
            
                sudo dnf autoremove
            
                    
    
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3. Information about the unicornscan.x86_64 package on AlmaLinux 9

Last metadata expiration check: 0:41:39 ago on Wed Mar 13 07:41:12 2024.
Available Packages
Name : unicornscan
Version : 0.4.7
Release : 31.el9
Architecture : x86_64
Size : 616 k
Source : unicornscan-0.4.7-31.el9.src.rpm
Repository : epel
Summary : Scalable, accurate, flexible and efficient network probing
URL : https://sourceforge.net/projects/osace/
License : GPLv2+
Description : Unicornscan is an attempt at a user-land distributed TCP/IP stack. It is
: intended to provide a researcher a superior interface for introducing a
: stimulus into and measuring a response from a TCP/IP enabled device or
: network. Although it currently has hundreds of individual features, a main
: set of abilities include: Asynchronous stateless TCP scanning with all
: variations of TCP flags, asynchronous stateless TCP banner grabbing,
: asynchronous protocol specific UDP scanning (sending enough of a signature
: to elicit a response), active and passive remote OS, application and
: component identification by analyzing responses, PCAP file logging and
: filtering, relational database output, custom module support, customized
: data-set views.