Add CodeQL Workflow for Code Security Analysis

[b4yuan]

Summary

This pull request introduces a CodeQL workflow to enhance the security analysis of this repository.

What is CodeQL

CodeQL is a static analysis tool that helps identify and mitigate security vulnerabilities. It is primarily intra-function but does provide some support for inter-function analysis. By integrating CodeQL into a GitHub Actions workflow, it can proactively identify and address potential issues before they become security threats.

For more information on CodeQL and how to interpret its results, refer to the GitHub documentation and the CodeQL documentation (https://codeql.github.com/ and https://codeql.github.com/docs/).

What this PR does

We added a new CodeQL workflow file (.github/workflows/codeql.yml) that

• Runs on every pull request (functionality to run on every push to main branches is included as a comment for convenience).
• Runs daily.
• Excludes queries with a high false positive rate or low-severity findings.
• Does not display results for git submodules, focusing only on our own codebase.

Validation

To validate the functionality of this workflow, we have run several test scans on the codebase and reviewed the results. The workflow successfully compiles the project, identifies issues, and provides actionable insights while reducing noise by excluding certain queries and third-party code.

Using the workflow results

If this pull request is merged, the CodeQL workflow will be automatically run on every push to the main branch and on every pull request to the main branch. To view the results of these code scans, follow these steps:

1. Under the repository name, click on the Security tab.
2. In the left sidebar, click Code scanning alerts.

Is this a good idea?

We are researchers at Purdue University in the USA. We are studying the potential benefits and costs of using CodeQL on open-source repositories of embedded software.

We wrote up a report of our findings so far. The TL;DR is “CodeQL outperforms the other freely-available static analysis tools, with fairly low false positive rates and lots of real defects”. You can read about the report here: https://arxiv.org/abs/2310.00205

Review of engineering hazards

License: see the license at https://github.com/github/codeql-cli-binaries/blob/main/LICENSE.md:

Here's what you may also do with the Software, but only with an Open Source Codebase and subject to the License Restrictions provisions below:

Perform analysis on the Open Source Codebase.

If the Open Source Codebase is hosted and maintained on GitHub.com, generate CodeQL databases for or during automated analysis, CI, or CD.

False positives: We find that around 20% of errors are false positives, but that these FPs are polarized and only a few rules contribute to most FPs. We find that the top rules contributing to FPs are: cpp/uninitialized-local, cpp/missing-check-scanf, cpp/suspicious-pointer-scaling, cpp/unbounded-write, cpp/constant-comparison, and cpp/inconsistent-null-check. Adding a filter to filter out certain rules that contribute to a high FP rate can be done simply in the workflow file.

[github-advanced-security]

This pull request sets up GitHub code scanning for this repository. Once the scans have completed and the checks have passed, the analysis results for this pull request branch will appear on this overview. Once you merge this pull request, the 'Security' tab will show more code scanning analysis results (for example, for the default branch). Depending on your configuration and choice of analysis tool, future pull requests will be annotated with code scanning analysis results. For more information about GitHub code scanning, check out the documentation.

[bk138]

What about https://github.com/LibVNC/libvncserver/blob/master/.github/workflows/codeql-analysis.yml - how does this PR relate?

[b4yuan]

This wf file allows rules to be filtered out (which can also combat false positives); it uploads the CodeQL results as an artifact, and uploads the results to code scanning (Security tab -> code scanning) to see all vulnerability defects found.