New research from cybersecurity firm Egress‘ Threat Intelligence team is raising the alarm over a surge in romance-based phishing attacks in the run to Valentine’s Day. According to them, there was a 43% increase in attacks mimicking dating apps like Tinder and Hinge between the 1st of January – 5th of February compared to the same period last year. 

The research suggests that Tinder has emerged as the primary target, with 53% of recorded attacks impersonating the platform. The attacks, which are primarily conducted through email, employ techniques like impersonation and sextortion to deceive targets.

Egress’ analysis also reveals that 85% of attacks target male recipients, suggesting cyber-criminals’ perception of males as more susceptible to romance-based impersonation attacks.

This is done primarily by harnessing AI and open source intelligence, and by doing so, attackers can personalise phishing emails to mimic trusted dating app brands. Leveraging AI, attackers tailor the subject lines and content to exploit recipients’ vulnerabilities, particularly during the Valentine’s Day season.

After finding stylised templates which mimic branding and tone of legitimate platforms, the attacker will then gather information on the user by planting a malicious URL in the email. After which, the attackers engage victims in conversation to extract more personal information. After enough information is gathered, the attacker will threaten the user with the dissemination of alleged compromised material to continue extortion attempts. 

Recommended reading

• More Than Half of Online Daters Leave Themselves Vulnerable to Scams
• AI Tools Make it Harder to Spot Scams, Advice Direct Scotland Warns
• NCSC Releases New SMB Cybersecurity Guide

Egress points out that the attackers usually use polymorphic subdomains to evade detection by security measures, making it challenging to block phishing campaigns based on sender addresses.

To combat the threats, the research suggests adopting anti-phishing technologies, which employ AI, zero-trust models, linguistic, contextual, and behavioural analysis to detect and neutralise emerging threats