Using ML-based anomaly detection, such as the unsupervised ML jobs in the Elastic stack, we can shrink the dwell time for this malware persistence mechanism from 46 days to less than one day, a decrease by a factor of 1100!

In this blog, we walk users through identifying beaconing malware in their environment using our beaconing identification framework.

In this blog, we walk users through identifying beaconing malware in their environment using our beaconing identification framework.

Neste post do blog, anunciamos nossa primeira integração de segurança e ML supervisionado, oferecendo aos usuários um pacote de solução de ML supervisionado para detectar a atividade do algoritmo de geração de domínio (DGA) nos seus dados de rede.