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AVSystem / Anjay

C implementation of the client-side OMA LwM2M protocol
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Add CodeQL Workflow for Code Security Analysis #72

Closed b4yuan closed 12 months ago

b4yuan commented 12 months ago

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

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.

b4yuan commented 12 months ago

I want to clarify that fail_on_error.py is a script that forces the step to fail if an error is found within the code (which in turn makes the entire workflow seem like it failed). However, looking at the steps, the workflow successfully built Anjay, analyzed it, and uploaded the results.

Additionally, it was actually a member of our team found the following error with CodeQL: https://github.com/AVSystem/Anjay/pull/62; we believe that this is a valuable addition to Anjay

Kucmasz commented 12 months ago

Hi, Thanks for your interest in Anjay code quality and security. We currently rely on several different tools (Coverity, scan-build, valgrind) and we are not interested in introducing CodeQL at this moment. Regards