Skip to main content

TH17118

Detected presence of files containing URLs that use suspicious top-level domains.

priorityCI/CD statusseverityeffortSAFE levelSAFE assessment
passmediumhighNoneNone

About the issueโ€‹

Uniform Resource Locators (URLs) are structured addresses that point to locations and assets on the internet. URLs allow software developers to build complex applications that exchange data with servers that can be hosted in multiple geographical regions. URLs can commonly be found embedded in documentation, configuration files, source code and compiled binaries. Top-level domains (TLD) are a part of the Domain Name System (DNS), and are used to lookup an Internet Protocol (IP) address of a requested website. There are a few different types of top-level domains. Generic, sponsored and country-code TLDs are generally accessible to the public. Registrars that govern the assignment of domain names within the TLD may choose to sell specific domain names to an interested party. However, some registrars are known to have less strict rules for assigning domain names. Attackers often abuse gaps in governance and actively seek to register their malicious domains in such TLDs. This issue is raised for all domains registered within TLDs that harbor an excessive number of malicious sites. While the presence of suspicious TLDs does not imply malicious intent, all of its uses in a software package should be documented and approved.

How to resolve the issueโ€‹

  • Investigate reported detections.
  • If the software should not include these network references, investigate your build and release environment for software supply chain compromise.
  • You should delay the software release until the investigation is completed, or until the issue is risk accepted.
  • Consider changing the top-level domain to avoid being flagged by security solutions.

Incidence statisticsโ€‹

ReversingLabs periodically collects and analyzes the contents of popular software package repositories for threat research purposes. Analysis results are used to calculate incidence statistics for issues (policy violations) that Spectra Assure can detect in software packages.

This section is updated when new data becomes available.

Total amount of packages analyzed

  • RubyGems: 183K
  • Nuget: 644K
  • PyPi: 628K
  • NPM: 3.72M

Total detections per repository

For every repository, the chart shows the number of packages that triggered the software assurance policy. In other words, it shows how many packages in each package repository were found to have the specific issue described on this page. This information helps you understand how common the issue is across different software communities.

If a repository is absent from the chart, that means none of the packages in that repository triggered this policy during analysis, or the policy was not used during analysis.

Distribution of total detections by project popularity

For every repository, the chart shows how many of the total detections belong to the Top 100 (1-100), Top 1000 (101-1000) and Top 10 000 (1001-10 000) most downloaded projects. This information helps you understand the impact of the issue within each community, making it clearer when the issue affects the most popular projects.

If the chart shows zero values for all of the top project groups, that means all detections were in unranked projects (lower than 10 000 on the list of most downloaded projects).