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SQ30112

Detected presence of suspicious files by a heuristic or machine learning algorithm.

priorityCI/CD statusseverityeffortSAFE levelSAFE assessment
passmediumhighNonemalware: warning
Reason: suspicious components found

About the issue​

Proprietary ReversingLabs malware detection algorithms have determined that the software package contains one or more suspicious files. The detection was made by either a heuristic algorithm, or a machine learning model. This malware detection method is considered predictive, and can typically identify the malware family by name.

How to resolve the issue​

  • Suspicious detections are a lower confidence detection, so you should first review them for malicious intent.
  • If the software intent does not relate to malicious behavior, investigate the build and release environment for software supply chain compromise.
  • Proceed with increased caution when using this software package.

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: 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).