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what is shortdot-evidence fr?

phishdestroy/shortdot-evidence — explained in plain English

Analysis updated 2026-05-18

36PythonAudience · researcherComplexity · 2/5LicenseSetup · easy

tl;dr

A daily updated dataset and dashboard tracking millions of suspicious domains registered across seven top level domains, aimed at exposing phishing and brand impersonation activity.

vibe map

mindmap
  root((ShortDot Evidence))
    What it does
      Tracks domain abuse
      Daily auto updated stats
      Publishes IOC data
    Tech stack
      Python
      GitHub Actions
      GitHub Pages
    Use cases
      Threat intelligence feeds
      Phishing domain blocklists
      ICANN compliance evidence
    Audience
      Security researchers
      OSINT analysts
    Setup
      Data files downloadable
      No install needed to view

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what do people make with this?

VIBE 1

Download blocklists of confirmed and high severity phishing domains for a security feed.

VIBE 2

Pull the STIX 2.1 bundle into a threat intelligence platform like MISP or OpenCTI.

VIBE 3

Use the per brand JSON files to check whether a specific company is being impersonated.

VIBE 4

Cite the aggregated statistics as evidence in an ICANN compliance complaint.

what's the stack?

PythonGitHub ActionsGitHub PagesSTIX 2.1

how it stacks up fr

phishdestroy/shortdot-evidenceakmessi/vexdinosn/wp2shell-lab
Stars363636
LanguagePythonPythonPython
Setup difficultyeasymoderatemoderate
Complexity2/53/54/5
Audienceresearchervibe coderresearcher

Figures from each repo's GitHub metadata at analysis time.

how do i run it?

Difficulty · easy time til it works · 5min

The data files can be downloaded and used directly with no setup, running the daily fetch scripts yourself would need Python.

Use freely for any purpose, including commercial use, as long as you keep the copyright notice.

in plain english

This repository is an automated investigation into domain name abuse across seven top level domain zones operated by a registry called ShortDot SA, covering endings like .icu.bond.cyou.sbs.cfd.buzz, and .qpon. The project's own framing is blunt: it claims to have enumerated all 6.2 million domains registered in these zones and found zero verified legitimate businesses among them, while a large share carry brand impersonation attempts against companies like Chase, Binance, MetaMask, and Ledger. It cites a report from Interisle Consulting Group stating these zones account for a meaningful share of global phishing activity. A script runs daily and rebuilds a live statistics table at the top of the README, showing the current domain count, how many are active versus dead with no DNS records, how many have been confirmed malicious, and an estimate of the registry's revenue and the fees it pays to ICANN. A breakdown table shows these same numbers split out per TLD, along with a list of registration burst days and the brand names and keywords most often targeted by the suspicious domains. The repository publishes its underlying data as downloadable files rather than just claims in prose. For each TLD there are full domain lists split into deployed (domains pointing to a live IP) and phantom (registered but never connected to a server) sets. Separate indicator of compromise files list confirmed and high severity malicious domains in plain text and CSV format, and structured JSON files break domains down by targeted brand, by registrant who filed many domains at once, and by shared hosting infrastructure. There is also a bundle in the STIX 2.1 format meant to be imported directly into security tools like MISP or OpenCTI, and a live dashboard hosted on GitHub Pages. The project is released under the MIT license and is tagged TLP CLEAR, meaning the information is meant to be shared without restriction. The full README is longer than what was shown.

prompts (copy fr)

prompt 1
Show me how to parse the data/index.json analytics snapshot from shortdot-evidence into a pandas dataframe.
prompt 2
Write a script that checks a domain name against the ioc/domains_confirmed.txt blocklist from this repo.
prompt 3
Explain what phantom versus deployed domains mean in the shortdot-evidence dataset.
prompt 4
Help me import the stix-bundle.json file from this repo into MISP.

Frequently asked questions

what is shortdot-evidence fr?

A daily updated dataset and dashboard tracking millions of suspicious domains registered across seven top level domains, aimed at exposing phishing and brand impersonation activity.

What language is shortdot-evidence written in?

Mainly Python. The stack also includes Python, GitHub Actions, GitHub Pages.

What license does shortdot-evidence use?

Use freely for any purpose, including commercial use, as long as you keep the copyright notice.

How hard is shortdot-evidence to set up?

Setup difficulty is rated easy, with roughly 5min to a first successful run.

Who is shortdot-evidence for?

Mainly researcher.

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