A recommendation engine is software that selects or ranks content by using user interactions, history, and other signals such as clicks, watches, pauses, and follows. It is common in feeds, video platforms, marketplaces, and search-related systems.
In cyber security, recommendation engines matter because they can be influenced, profiled, or abused. Attackers may try to shape rankings with fake engagement, coordinated accounts, or repetitive behavior so harmful content appears more visible. They can also use the engine’s personalization to learn what a target is likely to click, making phishing, lure pages, and malicious ads more convincing. Defenders watch these systems for abnormal interaction patterns, spam amplification, and manipulation of ranking signals. A recommendation engine is not a security tool by itself, but its outputs can strongly affect what users see, trust, and open.