Cybercriminals are increasingly using fake job interviews and malicious test tasks to compromise IT professionals. Attackers often pose as recruiters, sending malicious code via repositories on GitHub, GitLab, or Bitbucket. Once executed, these scripts install backdoors that steal passwords, cryptographic keys, and sensitive data, or provide remote access to the victim's system.
The threat also extends to employers, as attackers use AI-powered deepfakes to impersonate candidates during video interviews. According to Gartner, by 2028, one in four job applicants could be a deepfake. These fraudulent schemes pose significant cybersecurity risks, potentially leading to industrial espionage and financial losses for companies that inadvertently hire non-existent or malicious individuals.
Security experts suggest several methods to detect deepfakes, such as the GOTCHA protocol, which requires candidates to perform specific physical movements like covering parts of their face. Other experimental techniques include analyzing eye-gaze patterns or detecting light reflections in the cornea. These methods have shown varying degrees of accuracy in controlled tests.
To mitigate these risks, organizations are implementing multi-layered security, including rigorous identity verification and background checks. Some companies, such as Cisco, McKinsey, and Google, are returning to in-person interviews as a reliable defense against AI-driven deception, finding that traditional face-to-face meetings are more cost-effective than the potential consequences of hiring a fraudulent candidate.
