A method for automatic determining at time of registration whether a new domain name registration is likely to be intended for use for malicious activity or not, comprising the steps of: performing a method for automatic determining of the parameters of ar automated method for automatic determining at time of registration whether a domain name registration is likely to be intended for use for malicious activity or not and this solely based on registrant information, more preferably registrant contact information, of malicious domain name registrations, said method for automatic determining of the parameters comprising: (i) loading for a plurality of malicious domain name registrations ,the corresponding registrant information, more preferably registrant contact information; (ii) determining via machine learning the parameters of said automated method to determine with high likelihood whether a domain name registration is likely to be intended for use for malicious activity or not; and thereafter performing the steps of: (i) loading registrant information, more preferably registrant contact information, of said new domain name registration ; (ii) verifying , by use of said automated method, based on said parameters, said machine learned verification being solely based on said registrant infromation of said new domain name registration, the similarity of said domain name registration with said plurality of malicious domain name registrations, (iii) indicating based thereon that said domain name registration is likely to be intended for use for malicious activity. performing a method for automatic determining of the parameters of ar automated method for automatic determining at time of registration whether a domain name registration is likely to be intended for use for malicious activity or not and this solely based on registrant information, more preferably registrant contact information, of malicious domain name registrations, said method for automatic determining of the parameters comprising: (i) loading for a plurality of malicious domain name registrations ,the corresponding registrant information, more preferably registrant contact information; (ii) determining via machine learning the parameters of said automated method to determine with high likelihood whether a domain name registration is likely to be intended for use for malicious activity or not; and thereafter performing the steps of: (i) loading registrant information, more preferably registrant contact information, of said new domain name registration ; (ii) verifying , by use of said automated method, based on said parameters, said machine learned verification being solely based on said registrant infromation of said new domain name registration, the similarity of said domain name registration with said plurality of malicious domain name registrations, (iii) indicating based thereon that said domain name registration is likely to be intended for use for malicious activity. (i) loading registrant information, more preferably registrant contact information, of said new domain name registration ; (ii) verifying , by use of said automated method, based on said parameters, said machine learned verification being solely based on said registrant infromation of said new domain name registration, the similarity of said domain name registration with said plurality of malicious domain name registrations, (iii) indicating based thereon that said domain name registration is likely to be intended for use for malicious activity. <EOS>