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TH30108

Detected presence of software components that are impersonating popular software packages.

priorityCI/CD statusseverityeffortSAFE levelSAFE assessment
failhighhigh1tampering: fail
Reason: impersonated components found

About the issue​

Software developers use programming and design knowledge to build reusable software components. Software components are the basic building blocks for modern applications. Software consumed by an enterprise consists of hundreds, and sometimes even thousands of open source components. Software developers publish components they have authored to public repositories. Open source communities use code repositories to facilitate project discovery and simplify software deployment. These code repositories use unique component names as identifiers that developers can later use to specify software components required by their applications during the build or run processes. Since component names are manually written down by the developer within the code, it is possible to mistype them. Simple omissions of characters, such as prefixes, suffixes, plurals, hyphens, and underscores can have serious consequences. Unintended software components might get installed - components that might have been authored by a threat actor. Threat actors are constantly poisoning open source repositories with typosquatted components preying on typos by unsuspecting developers. They typically try to impersonate the most popular software components, as most developers will be using them to build their applications.

How to resolve the issue​

  • Review software component names to ensure there were no accidental package name mistypes.
  • If the software component names differ from expected, investigate the build and release environment for software supply chain compromise.
  • Avoid using this software package until it is vetted as safe.

Incidence statistics​

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: 203K
  • Nuget: 735K
  • PyPi: 838K
  • NPM: 5.12M
  • VS Code: 113K
  • PS Gallery: 17K

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).