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TH16104

Detected presence of files that dynamically execute compressed data.

priorityCI/CD statusseverityeffortSAFE levelSAFE assessment
passmediumhighNoneNone

About the issue​

Attackers commonly hide their malicious payloads in layers of packing and code obfuscation. Compression is a common data transformation technique used to reduce binary data size. Detected software behaviors indicate that the code has the ability to execute data upon its decompression. While presence of dynamic code execution does not imply malicious intent, all of its uses in a software package should be documented and approved. When a software package has behavior traits similar to malicious software, it may become flagged by security solutions. One example of acceptable use for dynamic compressed data execution is transfer of software components over the network.

How to resolve the issue​

  • Investigate reported detections as indicators of software tampering.
  • Consult Mitre ATT&CK documentation: T1027 - Obfuscated Files or Information.
  • Consider rewriting the flagged code without using the marked behaviors.

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).