A First Look at Brand Indicators for Message Identification (BIMI)

Masanori Yajima*, Daiki Chiba, Yoshiro Yoneya, Tatsuya Mori

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution


As promising approaches to thwarting the damage caused by phishing emails, DNS-based email security mechanisms, such as the Sender Policy Framework (SPF), Domain-based Message Authentication, Reporting & Conformance (DMARC) and DNS-based Authentication of Named Entities (DANE), have been proposed and widely adopted. Nevertheless, the number of victims of phishing emails continues to increase, suggesting that there should be a mechanism for supporting end-users in correctly distinguishing such emails from legitimate emails. To address this problem, the standardization of Brand Indicators for Message Identification (BIMI) is underway. BIMI is a mechanism that helps an email recipient visually distinguish between legitimate and phishing emails. With Google officially supporting BIMI in July 2021, the approach shows signs of spreading worldwide. With these backgrounds, we conduct an extensive measurement of the adoption of BIMI and its configuration. The results of our measurement study revealed that, as of November 2022, 3,538 out of the one million most popular domain names have a set BIMI record, whereas only 396 (11%) of the BIMI-enabled domain names had valid logo images and verified mark certificates. The study also revealed the existence of several misconfigurations in such logo images and certificates.

Original languageEnglish
Title of host publicationPassive and Active Measurement - 24th International Conference, PAM 2023, Proceedings
EditorsAnna Brunstrom, Marcel Flores, Marco Fiore
PublisherSpringer Science and Business Media Deutschland GmbH
Number of pages17
ISBN (Print)9783031284854
Publication statusPublished - 2023
Event24th International Conference on Passive and Active Measurement, PAM 2023 - Virtual, Online
Duration: 2023 Mar 212023 Mar 23

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume13882 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference24th International Conference on Passive and Active Measurement, PAM 2023
CityVirtual, Online


  • BIMI
  • Email
  • Measurement

ASJC Scopus subject areas

  • Theoretical Computer Science
  • General Computer Science


Dive into the research topics of 'A First Look at Brand Indicators for Message Identification (BIMI)'. Together they form a unique fingerprint.

Cite this