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SQ30118

Detected presence of structural file format exploits.

priorityCI/CD statusseverityeffortSAFE levelSAFE assessment
failhighhigh1malware: fail
Reason: malformed components found

About the issue​

File formats are either textual or binary structured object streams. Programs that work with them, called parsers, depend on understanding the format structure. Intentional deviations from the expected file format structure can cause parsing issues, and trigger unintended code execution. Some of these malformations can be linked to abuses of known format parsing vulnerabilities. Such specially crafted files are detected as malicious exploits, and are typically labeled by the vulnerability they are abusing.

How to resolve the issue​

  • If the software intent does not relate to file format validation, 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).