Scans a codebase for security vulnerabilities using CodeQL's interprocedural data flow and taint tracking analysis. Triggers on "run codeql", "codeql scan", "build codeql database", "SAST scan", "taint analysis", "dataflow analysis", or "find vulnerabilities in this repo". Covers Python, JavaScript/TypeScript, Go, Java/Kotlin, C/C++, C#, Ruby, and Swift. Supports "run all" (security-and-quality + security-experimental) and "important only" (high-precision) scan modes, and creates data extension models for project-specific sources and sinks. For fast single-file pattern matching, or when no build is available for a compiled language, use the semgrep skill; to parse SARIF that already exists rather than produce it, use the sarif-parsing skill.
Use the skills CLI to install this skill with one command. Auto-detects all installed AI assistants.
Method 1 - skills CLI
npx skills i trailofbits/skills/plugins/static-analysis/skills/codeqlMethod 2 - openskills (supports sync & update)
npx openskills install trailofbits/skillsAuto-detects Claude Code, Cursor, Codex CLI, Gemini CLI, and more. One install, works everywhere.
Installation Path
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Supported languages: Python, JavaScript/TypeScript, Go, Java/Kotlin, C/C++, C#, Ruby, Swift.
Skill resources: Reference files and templates are located at {baseDir}/references/ and {baseDir}/workflows/.
Database quality is non-negotiable. A database that builds is not automatically good — a cached build extracts nothing while reporting success.
Data extensions catch what CodeQL misses. Django, Spring, and Express projects still wrap database calls, request parsing, and shell execution in project-specific APIs that no shipped model covers.
Explicit suite references prevent silent query dropping. Never pass pack names to codeql database analyze — each pack's defaultSuiteFile applies hidden filters that can produce zero results. Always generate a .qls.
Zero findings needs investigation, not celebration. It can mean poor extraction, missing models, the wrong packs, or suite filtering. Run {baseDir}/scripts/check_db_quality.py after the build, confirm {baseDir}/scripts/verify_query_suite.py exited zero for the suite in use — the generation scripts run it, so invoke it by hand only for a reused or hand-edited suite — and say in the report that both passed.
macOS Apple Silicon requires workarounds for compiled languages. Exit code 137 is an arm64e/arm64 mismatch, not a build failure. Try Homebrew arm64 tools or Rosetta before falling back to build-mode=none.
Follow workflows step by step. Each phase gates the next; skipping quality assessment or data extensions leaves the gap invisible in the results.
Nothing carries across a Bash call: not variables, not arrays, not functions sourced from
build_log.sh. Every block below that uses a value must re-establish it in the same block.
The workflows point back here rather than repeating it; what they do state is the specific
damage at that site, because each one fails differently and silently:
run_logged exit 127, which the build ladder reads as a failed
method and walks down to --build-mode=none, never having invoked CodeQL--threat-model and --model-packs the user
chose is dropped while the final report still lists them as usedset -u aborts the block with unbound variableAll generated files (database, build logs, diagnostics, extensions, results) are stored in a single output directory.
OUTPUT_DIR../static_analysis_codeql_1. If that already exists, increment to _2, _3, etc.In both cases, always create the directory with mkdir -p before writing any files.
Set USER_SPECIFIED_DIR to the literal path from the user's prompt before running this,
or leave it unset to auto-increment. Nothing else assigns it.
# Resolve output directory
USER_SPECIFIED_DIR="${USER_SPECIFIED_DIR:-}" # substitute the user's path here, if any
if [ -n "$USER_SPECIFIED_DIR" ]; then
OUTPUT_DIR="$USER_SPECIFIED_DIR"
else
BASE="static_analysis_codeql"
N=1
while [ -e "${BASE
The output directory is resolved once at the start before any workflow executes. All workflows receive $OUTPUT_DIR and store their artifacts there:
$OUTPUT_DIR/
├── rulesets.txt # Selected query packs (logged after Step 3)
├── codeql.db/ # CodeQL database (dir containing codeql-database.yml)
├── build.log # Build log
├── codeql-config.yml # Exclusion config (interpreted languages)
├── diagnostics/ # Diagnostic queries and CSVs
├── extensions/ # Data extension YAMLs
├── raw/ # Unfiltered analysis output
│ ├── results.sarif
│ └── run-all.qls | important-only.qls
└── results/ # Final results (filtered for important-only, copied for run-all)
└── results.sarif
A CodeQL database is identified by the presence of a codeql-database.yml marker file inside its directory. When searching for existing databases, always collect all matches — there may be multiple databases from previous runs or for different languages.
Discovery command. find_databases.sh prints one database path per line, filtering
out the marker files a failed build leaves behind. Build the array in the same block
that selects from it — each Bash call is a fresh shell, so an array built here is empty
by the next call, and the run concludes there is no database:
# Command substitution, not `done < <(...)`: a process substitution discards the script's
# exit status, so "codeql is not on this shell's PATH" (exit 2) would arrive as an empty
# list and route to "build a new database" with three good ones sitting on disk.
if ! DB_LIST=$("{baseDir}/scripts/find_databases.sh" "${OUTPUT_DIR:-.}" .); then
echo "ERROR: database discovery failed — see the message above" >&2
Never assume a database is named codeql.db — discover it by its marker file.
When multiple databases are found: use AskUserQuestion to let the user select which database to use, or to build a new one, from the language and creation time printed above. AskUserQuestion takes at most four options, so with more databases than that, offer the three most recent plus "Build a new database" and list the rest in the prompt text. Skip AskUserQuestion if the user explicitly stated which database to use or to build a new one in their prompt.
For the common case ("scan this codebase for vulnerabilities"):
# Verify CodeQL is installed. Stop here if it is not — every later command fails with
# a less informative error, and the run wastes a build cycle before saying why.
if ! command -v codeql >/dev/null 2>&1; then
echo "ERROR: codeql not found on PATH. Install it with one of:" >&2
echo " gh extension install github/gh-codeql # then: gh codeql install-stub" >&2
Then resolve OUTPUT_DIR using the block in Output Directory above —
it honours a user-specified directory, which a bare auto-increment does not.
Then execute the full pipeline: build database → create data extensions → run analysis using the workflows below.
These shortcuts lead to missed findings. Do not accept them:
security-extended misses entirely.security-and-quality excludes all experimental/ query paths. For run-all mode, import both security-and-quality and security-experimental. The delta is 1–52 queries depending on the language.arm64e/arm64 mismatch, not a fundamental build failure. See macos-arm64e-workaround.md.check_db_quality.py and verify_query_suite.py and report that they passed. Without them, zero findings and a database that extracted nothing are the same output.This skill has three workflows. Once a workflow is selected, execute it step by step without skipping phases.
These runs are long. A database build has four fallback methods, so use the task tools to track progress. Decide which steps are worth tracking based on the run.
| Workflow | Purpose |
|---|---|
| build-database | Create CodeQL database using build methods in sequence |
| create-data-extensions | Detect or generate data extension models for project APIs |
| run-analysis | Select rulesets, execute queries, process results |
This plugin ships /static-analysis:codeql-build, which runs the build-database steps
end to end: detect the language and toolchain, walk the method ladder applying fixes from
build-fixes.md between rungs, and enforce the quality gate.
/static-analysis:codeql-build {"target": "/abs/path", "lang": "cpp"}
It asks nothing. Every method failing, and a database that built but sits below the quality
threshold, come back as statuses — no-method-succeeded and built-below-threshold — for you
to act on here, because whether the remaining extractor errors are confined to code nobody
needs analysed is a judgement call the run cannot make.
Use it when the build is the long, uncertain part and you want it driven to a conclusion. Work build-database.md by hand when you want a say in which method is tried, or when a build failure needs interpreting as it happens.
If user explicitly specifies what to do (e.g., "build a database", "run analysis on ./my-db"), execute that workflow directly. Do NOT call AskUserQuestion for database selection if the user's prompt already makes their intent clear — e.g., "build a new database", "analyze the codeql database in static_analysis_codeql_2", "run a full scan from scratch".
Default pipeline for "test", "scan", "analyze", or similar: Discover existing databases using the command in Database Discovery above, then decide.
| Condition | Action |
|---|---|
| No databases found | Resolve new $OUTPUT_DIR, execute build → extensions → analysis (full pipeline) |
| One database found | Use AskUserQuestion: reuse it or build new? |
| Multiple databases found | Use AskUserQuestion, capped at four options — see Database Discovery |
| User explicitly stated intent | Skip AskUserQuestion, act on their instructions directly |
When existing databases are found and the user did not explicitly specify which to use,
present them via AskUserQuestion under the header "Existing CodeQL Databases". Label each
option with the path, language, and creation time collected above — ./static_analysis_codeql_1/codeql.db (language: python, created: 2026-02-24) — and make the last option "Build a new database".
After selection:
$OUTPUT_DIR to its parent directory (or the directory containing it), set $DB_NAME to the selected path, then proceed to extensions → analysis.$OUTPUT_DIR, execute build → extensions → analysis.If neither the database nor the workflow is clear from the prompt, offer the four
workflows via AskUserQuestion — full scan (recommended), build database, create data
extensions, run analysis — naming any databases found and the resolved $OUTPUT_DIR.
| File | Content |
|---|---|
| Scripts | |
| scripts/verify_query_suite.py | Fails a suite that resolves to zero queries. The generation scripts run it; invoke by hand only for a reused or hand-edited suite |
| scripts/check_db_quality.py | Fails a database with no analysable source. Run after every build |
| scripts/build_log.sh | log_step/run_logged helpers; source before any build step |
| scripts/find_databases.sh | Prints every database that codeql resolve database accepts, one per line. Build your array from it in the block that reads it |
A complete CodeQL analysis run should satisfy:
$OUTPUT_DIRcodeql-database.yml marker) and {baseDir}/scripts/check_db_quality.py exited zero$OUTPUT_DIR/extensions/ or explicitly skipped with justification{baseDir}/scripts/verify_query_suite.py exited zero for it$OUTPUT_DIR/rulesets.txt$OUTPUT_DIR/raw/results.sarif$OUTPUT_DIR/results/results.sarif (filtered for important-only, copied for run-all)$OUTPUT_DIR/build.log with all commands, fixes, and quality assessmentsdefaultSuiteFile applies hidden filters and can produce zero results. Always use an explicit suite reference.$OUTPUT_DIR. Scattering files in the working directory makes cleanup impossible and risks overwriting previous runs.| scripts/generate_suite.sh | Writes the run-all or important-only .qls and verifies it resolves to a non-zero query count |
| References — the three workflows are listed under Workflow Selection |
| references/macos-arm64e-workaround.md | Apple Silicon build tracing workarounds |
| references/build-fixes.md | Build failure fix catalog |
| references/quality-assessment.md | Database quality metrics and improvements |
| references/extension-yaml-format.md | Data extension YAML column definitions and examples |
| references/sarif-processing.md | jq commands for SARIF output processing |
| references/diagnostic-query-templates.md | QL queries for source/sink enumeration |
| references/important-only-suite.md | Important-only suite template and generation |
| references/run-all-suite.md | Run-all suite template |
| references/ruleset-catalog.md | Available query packs by language |
| references/threat-models.md | Threat model configuration |
| references/language-details.md | Language-specific build and extraction details |
| references/performance-tuning.md | Memory, threading, and timeout configuration |