What type of detection mechanism is primarily used to mitigate phishing attacks?

The primary mechanism used to mitigate phishing attacks is AI and machine learning. These technologies are adept at analyzing vast amounts of data to identify patterns and anomalies that might indicate phishing attempts. By employing advanced algorithms, AI and machine learning can continuously learn from new data inputs, improving their ability to detect the subtle variations of phishing tactics that evolve over time.

In the context of phishing prevention, AI systems can evaluate email content, such as links, attachments, and the overall structure, to determine if they exhibit characteristics typical of phishing scams. This capability allows organizations to block or flag potentially harmful emails before they reach end-users, significantly reducing the risk of successful phishing attempts.

Other options, such as human oversight, can be helpful in identifying phishing attempts but are limited in their scalability and responsiveness. Network traffic analysis provides valuable insights into general network behavior but may not specifically target phishing attempts. Static code scanning is primarily used in software development to identify vulnerabilities in code, making it less relevant to real-time phishing threat mitigation. AI and machine learning stand out as the most effective and adaptive solution in combating phishing effectively.