Note: This article describes the features available with the version of the CodeQL action and associated CodeQL CLI bundle included in the initial release of this version of GitHub Enterprise Server. If your enterprise uses a more recent version of the CodeQL action, see the GitHub Enterprise Cloud article for information on the latest features. For information on using the latest version, see "Configuring code scanning for your appliance."
Producing detailed logs for debugging
To produce more detailed logging output, you can enable step debug logging. For more information, see "Enabling debug logging."
Automatic build for a compiled language fails
If an automatic build of code for a compiled language within your project fails, try the following troubleshooting steps.
-
Remove the
autobuild
step from your code scanning workflow and add specific build steps. For information about editing the workflow, see "Configuring code scanning." For more information about replacing theautobuild
step, see "Configuring the CodeQL workflow for compiled languages." -
If your workflow doesn't explicitly specify the languages to analyze, CodeQL implicitly detects the supported languages in your code base. In this configuration, out of the compiled languages C/C++, C#, and Java, CodeQL only analyzes the language with the most source files. Edit the workflow and add a matrix specifying the languages you want to analyze. The default CodeQL analysis workflow uses such a matrix.
The following extracts from a workflow show how you can use a matrix within the job strategy to specify languages, and then reference each language within the "Initialize CodeQL" step:
jobs: analyze: permissions: security-events: write actions: read ... strategy: fail-fast: false matrix: language: ['csharp', 'cpp', 'javascript'] steps: ... - name: Initialize CodeQL uses: github/codeql-action/init@v1 with: languages: ${{ matrix.language }}
For more information about editing the workflow, see "Configuring code scanning."
No code found during the build
If your workflow fails with an error No source code was seen during the build
or The process '/opt/hostedtoolcache/CodeQL/0.0.0-20200630/x64/codeql/codeql' failed with exit code 32
, this indicates that CodeQL was unable to monitor your code. Several reasons can explain such a failure:
-
The repository may not contain source code that is written in languages supported by CodeQL. Check the list of supported languages and, if this is the case, remove the CodeQL workflow. For more information, see "About code scanning with CodeQL
-
Automatic language detection identified a supported language, but there is no analyzable code of that language in the repository. A typical example is when our language detection service finds a file associated with a particular programming language like a
.h
, or.gyp
file, but no corresponding executable code is present in the repository. To solve the problem, you can manually define the languages you want to analyze by updating the list of languages in thelanguage
matrix. For example, the following configuration will analyze only Go, and JavaScript.strategy: fail-fast: false matrix: # Override automatic language detection by changing the list below. # Supported options are listed in a comment in the default workflow. language: ['go', 'javascript']
For more information, see the workflow extract in "Automatic build for a compiled language fails" above.
-
Your code scanning workflow is analyzing a compiled language (C, C++, C#, or Java), but the code was not compiled. By default, the CodeQL analysis workflow contains an
autobuild
step, however, this step represents a best effort process, and may not succeed in building your code, depending on your specific build environment. Compilation may also fail if you have removed theautobuild
step and did not include build steps manually. For more information about specifying build steps, see "Configuring the CodeQL workflow for compiled languages." -
Your workflow is analyzing a compiled language (C, C++, C#, or Java), but portions of your build are cached to improve performance (most likely to occur with build systems like Gradle or Bazel). Since CodeQL observes the activity of the compiler to understand the data flows in a repository, CodeQL requires a complete build to take place in order to perform analysis.
-
Your workflow is analyzing a compiled language (C, C++, C#, or Java), but compilation does not occur between the
init
andanalyze
steps in the workflow. CodeQL requires that your build happens in between these two steps in order to observe the activity of the compiler and perform analysis. -
Your compiled code (in C, C++, C#, or Java) was compiled successfully, but CodeQL was unable to detect the compiler invocations. The most common causes are:
- Running your build process in a separate container to CodeQL. For more information, see "Running CodeQL code scanning in a container."
- Building using a distributed build system external to GitHub Actions, using a daemon process.
- CodeQL isn't aware of the specific compiler you are using.
For .NET Framework projects, and for C# projects using either
dotnet build
ormsbuild
, you should specify/p:UseSharedCompilation=false
in your workflow'srun
step, when you build your code.For example, the following configuration for C# will pass the flag during the first build step.
- run: | dotnet build /p:UseSharedCompilation=false
If you encounter another problem with your specific compiler or configuration, contact � 的网站管理员.
For more information about specifying build steps, see "Configuring the CodeQL workflow for compiled languages."
Lines of code scanned are lower than expected
For compiled languages like C/C++, C#, Go, and Java, CodeQL only scans files that are built during the analysis. Therefore the number of lines of code scanned will be lower than expected if some of the source code isn't compiled correctly. This can happen for several reasons:
- The CodeQL
autobuild
feature uses heuristics to build the code in a repository. However, sometimes this approach results in an incomplete analysis of a repository. For example, when multiplebuild.sh
commands exist in a single repository, the analysis may not be complete since theautobuild
step will only execute one of the commands, and therefore some source files may not be compiled. - Some compilers do not work with CodeQL and can cause issues while analyzing the code. For example, Project Lombok uses non-public compiler APIs to modify compiler behavior. The assumptions used in these compiler modifications are not valid for CodeQL's Java extractor, so the code cannot be analyzed.
If your CodeQL analysis scans fewer lines of code than expected, there are several approaches you can try to make sure all the necessary source files are compiled.
Replace the autobuild
step
Replace the autobuild
step with the same build commands you would use in production. This makes sure that CodeQL knows exactly how to compile all of the source files you want to scan.
For more information, see "Configuring the CodeQL workflow for compiled languages."
Inspect the copy of the source files in the CodeQL database
You may be able to understand why some source files haven't been analyzed by inspecting the copy of the source code included with the CodeQL database. To obtain the database from your Actions workflow, modify the init
step of your CodeQL workflow file and set debug: true
.
- name: Initialize CodeQL
uses: github/codeql-action/init@v1
with:
debug: true
This uploads the database as an actions artifact that you can download to your local machine. For more information, see "Storing workflow artifacts."
The artifact will contain an archived copy of the source files scanned by CodeQL called src.zip. If you compare the source code files in the repository and the files in src.zip, you can see which types of file are missing. Once you know what types of file are not being analyzed, it is easier to understand how you may need to change the workflow for CodeQL analysis.
Alerts found in generated code
对于 Java、C、C++ 和 C# 等编译语言,CodeQL 分析在工作流程运行过程中构建的所有代� �。 要限制要分析的代� �量,请通过在 run
块中指定自己的生成步骤,仅生成要分析的代� �。 可以将指定自己的生成步骤与对 pull_request
和 push
事件使用 paths
或 paths-ignore
筛选器相结合,以确保工作流仅在特定代� �更改时运行。 有关详细信息,请参阅 GitHub Actions 的工作流语法。
对于 Go、JavaScript、Python 和 TypeScript 等语言, CodeQL 分析而不编译源代� �,您可以指定其他配置选项来限制要分析的代� �量。 有关详细信息,请参阅“指定要扫描的目录”。
Extraction errors in the database
The CodeQL team constantly works on critical extraction errors to make sure that all source files can be scanned. However, the CodeQL extractors do occasionally generate errors during database creation. CodeQL provides information about extraction errors and warnings generated during database creation in a log file. The extraction diagnostics information gives an indication of overall database health. Most extractor errors do not significantly impact the analysis. A small number of extractor errors is healthy and typically indicates a good state of analysis.
However, if you see extractor errors in the overwhelming majority of files that were compiled during database creation, you should look into the errors in more detail to try to understand why some source files weren't extracted properly.
The build takes too long
If your build with CodeQL analysis takes too long to run, there are several approaches you can try to reduce the build time.
Increase the memory or cores
If you use self-hosted runners to run CodeQL analysis, you can increase the memory or the number of cores on those runners.
Use matrix builds to parallelize the analysis
The default CodeQL analysis workflow uses a matrix of languages, which causes the analysis of each language to run in parallel. If you have specified the languages you want to analyze directly in the "Initialize CodeQL" step, analysis of each language will happen sequentially. To speed up analysis of multiple languages, modify your workflow to use a matrix. For more information, see the workflow extract in "Automatic build for a compiled language fails" above.
Reduce the amount of code being analyzed in a single workflow
Analysis time is typically proportional to the amount of code being analyzed. You can reduce the analysis time by reducing the amount of code being analyzed at once, for example, by excluding test code, or breaking analysis into multiple workflows that analyze only a subset of your code at a time.
对于 Java、C、C++ 和 C# 等编译语言,CodeQL 分析在工作流程运行过程中构建的所有代� �。 要限制要分析的代� �量,请通过在 run
块中指定自己的生成步骤,仅生成要分析的代� �。 可以将指定自己的生成步骤与对 pull_request
和 push
事件使用 paths
或 paths-ignore
筛选器相结合,以确保工作流仅在特定代� �更改时运行。 有关详细信息,请参阅 GitHub Actions 的工作流语法。
对于 Go、JavaScript、Python 和 TypeScript 等语言, CodeQL 分析而不编译源代� �,您可以指定其他配置选项来限制要分析的代� �量。 有关详细信息,请参阅“指定要扫描的目录”。
If you split your analysis into multiple workflows as described above, we still recommend that you have at least one workflow which runs on a schedule
which analyzes all of the code in your repository. Because CodeQL analyzes data flows between components, some complex security behaviors may only be detected on a complete build.
Run only during a schedule
event
If your analysis is still too slow to be run during push
or pull_request
events, then you may want to only trigger analysis on the schedule
event. For more information, see "Events."
Check which query suites the workflow runs
By default, there are three main query suites available for each language. If you have optimized the CodeQL database build and the process is still too long, you could reduce the number of queries you run. The default query suite is run automatically; it contains the fastest security queries with the lowest rates of false positive results.
You may be running extra queries or query suites in addition to the default queries. Check whether the workflow defines an additional query suite or additional queries to run using the queries
element. You can experiment with disabling the additional query suite or queries. For more information, see "Configuring code scanning."
Error: "Server error"
If the run of a workflow for code scanning fails due to a server error, try running the workflow again. If the problem persists, contact � 的网站管理员.
Error: "Out of disk" or "Out of memory"
On very large projects, CodeQL may run out of disk or memory on the runner. If you encounter this issue, try increasing the memory on the runner.
Error: "is not a .ql file, .qls file, a directory, or a query pack specification"
You will see this error if CodeQL is unable to find the named query, query suite, or query pack at the location requested in the workflow. There are two common reasons for this error.
- There is a typo in the workflow.
- A resource the workflow refers to by path was renamed, deleted, or moved to a new location.
After verifying the location of the resource, you can update the workflow to specify the correct location. If you run additional queries in Go analysis, you may have been affected by the relocation of the source files. For more information, see Relocation announcement: github/codeql-go
moving into github/codeql
in the github/codeql-go repository.
Warning: "git checkout HEAD^2 is no longer necessary"
If you're using an old CodeQL workflow you may get the following warning in the output from the "Initialize CodeQL" action:
Warning: 1 issue was detected with this workflow: git checkout HEAD^2 is no longer
necessary. Please remove this step as Code Scanning recommends analyzing the merge
commit for best results.
Fix this by removing the following lines from the CodeQL workflow. These lines were included in the steps
section of the Analyze
job in initial versions of the CodeQL workflow.
with:
# We must fetch at least the immediate parents so that if this is
# a pull request then we can checkout the head.
fetch-depth: 2
# If this run was triggered by a pull request event, then checkout
# the head of the pull request instead of the merge commit.
- run: git checkout HEAD^2
if: ${{ github.event_name == 'pull_request' }}
The revised steps
section of the workflow will look like this:
steps:
- name: Checkout repository
uses: actions/checkout@v2
# Initializes the CodeQL tools for scanning.
- name: Initialize CodeQL
uses: github/codeql-action/init@v1
...
For more information about editing the CodeQL workflow file, see "Configuring code scanning."