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SQ14111

Detected Windows executable files that are not large address aware while trying to use high entropy ASLR.

priorityCI/CD statusseverityeffortSAFE levelSAFE assessment
passmediumlowNonehardening: warning
Reason: reduced effectiveness mitigations

About the issue​

High Entropy Address Space Layout Randomization (HEASLR) is a vulnerability mitigation option that forces software components to load on a different memory base address each time they are used. This mitigation is detected as enabled, but rendered ineffective due to image not being large address aware. For HEASLR to work properly on 64-bit images, it is required that they know how to handle addresses above the lowest 2 GB memory range. If they can't use the larger address space, they should not opt in to high entropy address randomization.

How to resolve the issue​

  • Review the programming language linker options.
  • In Microsoft VisualStudio, you can enable HEASLR mitigation by setting the linker option /LARGEADDRESSAWARE to ON.

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).