Machine Learning

More than 1.5 million malicious and spam emails were sent from thousands of compromised Office 365 accounts in March 2019 alone, a new report reveals.

A new report found that of 546,247 phishing attacks deployed against Office 365, 25% were able to bypass its security.

A new business email compromise (BEC) scheme, where attacker tricks the recipients into rerouting paychecks by direct deposit, has emerged.

Personal health information of over 350,000 consumers were potentially compromised after nine employees of the Oregon Department of Human Services (DHS) fell victim to a phishing attack.

A recently published paper warns of the prospect of advanced techniques being used to throw machine learning (ML) systems off.

As cybersecurity technology becomes better at detecting email-based threats, attackers continue to employ leveled up social engineering tactics – such as phishing – to increase the likelihood of users falling for fraud, identity theft, or spoofing.

To provide organizations a comprehensive view of the email threat landscape, we look at notable occurrences of advanced email threats used by cybercriminals as well as advanced security techniques that can effectively defend against them.

Catching malware outbreaks early keeps users, communities, enterprises, and governments safe. But if malware samples are scarce, can machine learning help analyze, detect, and end an outbreak?

As of 2018, global losses to BEC have exceeded US$12 billion. To keep abreast of the landscape that scammers are operating in, we look back on some of the noteworthy incidents and trends that made BEC a headline staple this year.