Further details on the Domain Reputation Dataset

What data is listed?

Every domain observed and analyzed by our researchers is listed in this dataset. Via various API calls, metadata relating to each domain is provided, including:

  • High-level domain data – returns general domain-related insights, including when the domain was last seen if it’s compromised, what domain clusters are associated with it, and the domain’s reputation score. This score is now a number: Zero is the mid-point, with positive scores equating to a more positive reputation and negative scores indicating a poorer reputation.
  • Reputation dimensions – reputation is assessed across multiple areas, called dimensions. This enables users to understand which areas of their reputation need strengthening.
  • Domain contexts – insight into where researchers observed the domain, for example, “dkim-header”.
  • Domain listing data – see if a domain is listed in a DNS Blocklist and when the listing is due to expire.
  • Domain senders data – IP addresses sending emails for the queried domain.
  • Nameserver reputation – a list of authoritative nameservers for the queried domain.


  • A Records reputation – a list of the A records the domain resolves to.
  • Clusters –used to correlate related domains across certain areas, including email authentication, registration, and infrastructure.
  • Hostnames listed – those that are (or have been) listed on a Spamhaus DNS Blocklist for a specific domain in the recent past (if available).
  • Malware – the malware name associated with the domain, including the last seen timestamp.

Benefits of using the data

  1. Tailored insight

    Various APIs enable you to build a detailed picture of the domain queried. Meeting your specific use cases.

  2. Breadth of contextual actionable data

    Includes live and historical data relating to ALL domains Spamhaus researchers observe. Multiple data points provide a rich and detailed overview of the domains queried.

  3. Real time updates

    Domains are included in this dataset as soon as they are observed.