Home / Companies / Didit / Blog / Post Details
Content Deep Dive

iBeta Level 1 PAD: 0% Attack Success Across 360 Attempts

Blog post from Didit

Aggregate trend data notice

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.

Post Details
Company
Date Published
Author
Didit
Word Count
1,272
Company Posts That Month
190
Language
English
Hacker News Points
-
Post removed?
No
Summary

Didit's biometric liveness system successfully passed iBeta Level 1 Presentation Attack Detection (PAD) testing under the international standard ISO/IEC 30107-3, achieving a 0% attack success rate across 360 attempts. Conducted by the NIST/NVLAP-accredited lab iBeta Quality Assurance, the evaluation confirmed the system's ability to distinguish genuine users from spoofing attempts using various presentation attack species. The test, which took place from January 5 to February 4, 2026, involved six enrolled subjects and utilized Didit Biometric Authentication v2.0 on an Apple iPhone 13 Pro. Didit accurately reported its results as Level 1, without overstating them as Level 2, and highlighted the system's robust anti-spoofing capabilities, essential for regulated onboarding and high-risk verticals. The PAD compliance letter can be distributed to support anti-spoofing claims in marketing and regulatory contexts, underscoring the system's reliability in preventing identity fraud through liveness detection.

Trends Found in this Post

No tracked trend matches for this post yet.

Use This Data

Use this post, company, and trend context to find content marketing opportunities, perform competitive analysis, or address product feature gaps via the Plushcap MCP server or the Plushcap API.