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ASN Lookup: Your Secret Weapon Against Online Fraud

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
1,313
Company Posts That Month
Language
English
Hacker News Points
-
Post removed?
No
Summary

Autonomous System Numbers (ASNs) uniquely identify networks operated by entities such as internet service providers, corporations, universities, and data centers, providing context about the origin and likely nature of an IP connection. In fraud prevention, ASN lookup can help distinguish typical residential traffic from potentially higher-risk connections associated with VPNs, proxies, Tor, cloud infrastructure, or data centers, which may be used to conceal location, automate attacks, or create fraudulent accounts. It can support detection of IP hopping, botnets, account takeovers, credential stuffing, geo-restriction circumvention, and suspicious activity in sectors including e-commerce, finance, gaming, gambling, and streaming. The material argues that ASN data is most effective when combined with geolocation, device intelligence, behavioral signals, and identity verification, allowing organizations to apply risk-based actions such as additional checks, manual review, or blocking. It presents Didit’s IP Analysis and workflow tools as an example of a platform that uses real-time ASN-related signals to automate these decisions and reduce fraud while limiting friction for legitimate users.

Trends Found in this Post
Trend Post Mentions Total Month Mentions Posts Companies MoM
Real-time 3 13,979 3,441 296 +113%
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