Passive vs. Active Liveness: Which is Right for Your Business?
Blog post from Didit
Excluded from normalized aggregate trends after staff review: 3056 posts were attributed to March 2026; 671 shared March 14, 2026. The preceding six-month median was 13.5 posts.
Review evidence: 3,056 posts in March 2026; 671 shared March 14, 2026; preceding six-month median 13.5. Reviewed August 9, 2026.
This company's pages remain public, but its content is excluded from normalized aggregate trends. Unfiltered raw trends and advanced filtering are available to Accelerate and Lead accounts.
In an era where digital identity verification is essential due to the rise of AI-driven fraud techniques, liveness detection plays a crucial role in ensuring that users are who they claim to be during online interactions. Passive liveness detection offers a seamless user experience by analyzing a selfie without requiring user actions, making it ideal for high-volume transactions and initial onboarding. In contrast, active liveness detection enhances security by requiring specific user actions, such as nodding or blinking, to thwart advanced spoofing attempts, making it suitable for high-risk scenarios and regulatory compliance. Businesses often adopt a layered approach, starting with passive detection and escalating to active when necessary, to balance security and user experience. Didit provides integrated solutions for both passive and active detection, allowing businesses to craft risk-adaptive workflows tailored to their needs. These solutions are bolstered by AI-driven accuracy and compliance with rigorous industry standards, ensuring robust identity verification in the face of evolving digital threats.
| Trend | Post Mentions | Total Month Mentions | Posts | Companies | MoM |
|---|---|---|---|---|---|
| Real-time | 1 | 13,979 | 3,441 | 296 | +113% |
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