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Codeql

Trail of BitsOfficialPublished by Trail of Bits

  • Skill
  • Workflow
  • Security
  • CC-BY-SA-4.0
  • Low risk
  • Has scripts

From the author

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.
— the description by Trail of Bits

AutoGineer summary

Written by AutoGineer from the skill’s own files, not by the author

This skill provides a structured, multi-phase workflow for performing static application security testing (SAST) using CodeQL. It manages the entire lifecycle of a security scan, including database construction, data extension modeling for custom project APIs, and execution of high-precision or comprehensive query suites. The skill enforces rigorous quality gates, such as database validation and explicit suite verification, to ensure that findings are accurate and that the absence of findings is a result of secure code rather than extraction or configuration errors.

What it does

  • Builds CodeQL databases for multiple languages including Python, JS/TS, Go, Java, C/C++, C#, Ruby, and Swift.
  • Automates the creation and application of data extension models to cover project-specific sources and sinks.
  • Executes security scans using either high-precision or comprehensive query suites.
  • Validates database quality and query suite resolution to prevent silent analysis failures.
  • Generates and manages SARIF-formatted security reports within a structured output directory.
  • Provides a robust fallback mechanism for build failures, including dependency installation and environment-specific workarounds.

When to use it

  • When you need to perform deep, interprocedural security analysis on a codebase.
  • When you want to identify vulnerabilities that require taint tracking across complex application logic.
  • When you need to audit custom frameworks or APIs that standard scanners might miss.
  • When you require a repeatable, documented security scan process with verified results.

Advantages

  • Reduces false negatives by enforcing data extension modeling for custom code.
  • Ensures analysis reliability through mandatory database quality checks.
  • Prevents configuration drift by using explicit query suite references.
  • Provides clear audit trails for security findings and scan configurations.

Usage examples

“run codeql scan on this repository”
The agent will discover the codebase language, build a CodeQL database, apply necessary data extensions, run the security analysis, and output a SARIF report.
“find vulnerabilities in this repo”
The agent will initiate the full CodeQL pipeline, including database discovery, quality assessment, and vulnerability analysis.

Install

  1. Download the skill as a ZIP:

    https://mp-staging.autogineer.com/agent-skills/trailofbits/codeql/download
  2. Unzip it into the cross-client skills folder of your project:

    mkdir -p .agents/skills && unzip codeql.zip -d .agents/skills

Documentation by Trail of Bits

CodeQL Analysis

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/.

Essential Principles

  1. Database quality is non-negotiable. A database that builds is not automatically good — a cached build extracts nothing while reporting success.

  2. 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.

  3. 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.

  4. 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.

  5. 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.

  6. Follow workflows step by step. Each phase gates the next; skipping quality assessment or data extensions leaves the gap invisible in the results.

Each Bash call is a fresh shell

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:

  • a lost function makes run_logged exit 127, which the build ladder reads as a failed method and walks down to --build-mode=none, never having invoked CodeQL

  • a lost array expands to nothing, so every --threat-model and --model-packs the user chose is dropped while the final report still lists them as used

  • a lost scalar under set -u aborts the block with unbound variable

Output Directory

All generated files (database, build logs, diagnostics, extensions, results) are stored in a single output directory.

  • If the user specifies an output directory in their prompt, use it as OUTPUT_DIR.

  • If not specified, default to ./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}_${N}" ]; do
    N=$((N + 1))
  done
  OUTPUT_DIR="${BASE}_${N}"
fi
mkdir -p "$OUTPUT_DIR"

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
Database Discovery

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
  exit 1
fi

FOUND_DBS=()
while IFS= read -r db; do
  [ -n "$db" ] || continue
  FOUND_DBS+=("$db")
done <<<"$DB_LIST"

echo "Found ${#FOUND_DBS[@]} existing database(s)"

# The metadata the selection prompt needs, collected here rather than in a block of its
# own: FOUND_DBS is gone by the next Bash call, and a loop over an array that no longer
# exists prints nothing and reports success.
for db in "${FOUND_DBS[@]}"; do
  CODEQL_LANG=$(codeql resolve database --format=json -- "$db" 2>/dev/null | jq -r '.languages[0]')
  CREATED=$(grep '^creationMetadata:' -A5 "$db/codeql-database.yml" 2>/dev/null | grep 'creationTime' | awk '{print $2}')
  echo "$db — language: $CODEQL_LANG, created: $CREATED"
done

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.

Quick Start

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
  echo "  brew install --cask codeql" >&2
  echo "  https://github.com/github/codeql-action/releases  (codeql-bundle)" >&2
  exit 1
fi

# jq parses `codeql resolve database --format=json` in the very next step. Without it
# CODEQL_LANG comes back empty and the run continues against the wrong language.
if ! command -v jq >/dev/null 2>&1; then
  echo "ERROR: jq not found on PATH (brew install jq / apt install jq)" >&2
  exit 1
fi

# uv runs both guard scripts and both suite generators. Check it here rather than at
# suite generation, which is after the build — otherwise a machine without uv spends
# the whole build before failing.
if ! command -v uv >/dev/null 2>&1; then
  echo "ERROR: uv not found on PATH (https://docs.astral.sh/uv/getting-started/)" >&2
  exit 1
fi

codeql --version

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.

Rationalizations to Reject

These shortcuts lead to missed findings. Do not accept them:

  • "security-extended is enough" - It is the baseline. Always check if Trail of Bits packs and Community Packs are available for the language. They catch categories security-extended misses entirely.

  • "security-and-quality is the broadest suite" - 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.

  • "The database built, so it's good" - A database that builds does not mean it extracted well. Always run quality assessment and check file counts against expected source files.

  • "Data extensions aren't needed for standard frameworks" - Even Django/Spring apps have custom wrappers that CodeQL does not model. Skipping extensions means missing vulnerabilities.

  • "build-mode=none is fine for compiled languages" - It produces severely incomplete analysis. Only use as an absolute last resort. On macOS, try the arm64 toolchain workaround or Rosetta first.

  • "The build fails on macOS, just use build-mode=none" - Exit code 137 is caused by arm64e/arm64 mismatch, not a fundamental build failure. See macos-arm64e-workaround.md.

  • "No findings means the code is secure" - Run 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.

  • "I'll just run the default suite" / "I'll just pass the pack names directly" - Each pack's defaultSuiteFile applies hidden filters and can produce zero results. Always use an explicit suite reference.

  • "I'll put files in the current directory" - All generated files must go in $OUTPUT_DIR. Scattering files in the working directory makes cleanup impossible and risks overwriting previous runs.

  • "Just use the first database I find" - Multiple databases may exist for different languages or from previous runs. When more than one is found, present all options to the user. Only skip the prompt when the user already specified which database to use.

  • "The user said 'scan', that means they want me to pick a database" - "Scan" is not database selection. If multiple databases exist and the user didn't name one, ask.


Workflow Selection

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.

WorkflowPurpose
build-databaseCreate CodeQL database using build methods in sequence
create-data-extensionsDetect or generate data extension models for project APIs
run-analysisSelect rulesets, execute queries, process results
Building unattended

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.

Auto-Detection Logic

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.

ConditionAction
No databases foundResolve new $OUTPUT_DIR, execute build → extensions → analysis (full pipeline)
One database foundUse AskUserQuestion: reuse it or build new?
Multiple databases foundUse AskUserQuestion, capped at four options — see Database Discovery
User explicitly stated intentSkip AskUserQuestion, act on their instructions directly
Database Selection Prompt

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:

  • If user picks an existing database: Set $OUTPUT_DIR to its parent directory (or the directory containing it), set $DB_NAME to the selected path, then proceed to extensions → analysis.

  • If user picks "Build new": Resolve a new $OUTPUT_DIR, execute build → extensions → analysis.

General Decision Prompt

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.


Reference Index

FileContent
Scripts
scripts/verify_query_suite.pyFails 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.pyFails a database with no analysable source. Run after every build
scripts/build_log.shlog_step/run_logged helpers; source before any build step
scripts/find_databases.shPrints every database that codeql resolve database accepts, one per line. Build your array from it in the block that reads it
scripts/generate_suite.shWrites 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.mdApple Silicon build tracing workarounds
references/build-fixes.mdBuild failure fix catalog
references/quality-assessment.mdDatabase quality metrics and improvements
references/extension-yaml-format.mdData extension YAML column definitions and examples
references/sarif-processing.mdjq commands for SARIF output processing
references/diagnostic-query-templates.mdQL queries for source/sink enumeration
references/important-only-suite.mdImportant-only suite template and generation
references/run-all-suite.mdRun-all suite template
references/ruleset-catalog.mdAvailable query packs by language
references/threat-models.mdThreat model configuration
references/language-details.mdLanguage-specific build and extraction details
references/performance-tuning.mdMemory, threading, and timeout configuration

Success Criteria

A complete CodeQL analysis run should satisfy:

  • [ ] Output directory resolved (user-specified or auto-incremented default)

  • [ ] All generated files stored inside $OUTPUT_DIR

  • [ ] Database built (discovered via codeql-database.yml marker) and {baseDir}/scripts/check_db_quality.py exited zero

  • [ ] Data extensions evaluated — either created in $OUTPUT_DIR/extensions/ or explicitly skipped with justification

  • [ ] Analysis run with explicit suite reference (not default pack suite), and {baseDir}/scripts/verify_query_suite.py exited zero for it

  • [ ] All installed query packs (official + Trail of Bits + Community) used or explicitly excluded

  • [ ] Selected query packs logged to $OUTPUT_DIR/rulesets.txt

  • [ ] Unfiltered results preserved in $OUTPUT_DIR/raw/results.sarif

  • [ ] Final results in $OUTPUT_DIR/results/results.sarif (filtered for important-only, copied for run-all)

  • [ ] Zero-finding results investigated (database quality, model coverage, suite selection)

  • [ ] Build log preserved at $OUTPUT_DIR/build.log with all commands, fixes, and quality assessments

Files

scripts/test_generation_scripts.py

"""Run generate_suite.sh for real, in both modes.

It writes the `.qls` that decides which queries run. Both modes previously lived as
copy-pasted bash inside two reference docs, and both ended with
`if ! codeql resolve queries "$SUITE_FILE" | wc -l; then` — a condition that can never
be true, since `wc` succeeding masks any CodeQL failure.

Runs against a fake `codeql` on PATH, so no CodeQL install is needed and the real
control flow is still exercised.
"""

from __future__ import annotations

import os
import re
import stat
import subprocess
from pathlib import Path

import pytest

SKILL_ROOT = Path(__file__).resolve().parent.parent
BASH_BLOCK = re.compile(r"^```bash\n(.*?)^```", re.MULTILINE | re.DOTALL)

GENERATE_SUITE = SKILL_ROOT / "scripts" / "generate_suite.sh"
YAML_BLOCK = re.compile(r"^```yaml\n(.*?)^```", re.MULTILINE | re.DOTALL)


def _significant(text: str) -> list[str]:
    """Suite lines that carry meaning — comments and blanks are presentation."""
    return [
        ln.rstrip() for ln in text.splitlines() if ln.strip() and not ln.lstrip().startswith("#")
    ]


def _invocation_block(doc: Path) -> str:
    """The bash block that calls generate_suite.sh."""
    blocks = [
        b for b in BASH_BLOCK.findall(doc.read_text(encoding="utf-8")) if "generate_suite.sh" in b
    ]
    if len(blocks) != 1:
        pytest.fail(f"expected one invocation block in {doc.name}, found {len(blocks)}")
    return blocks[0]


# The doc that documents each mode. Both must invoke the script rather than inlining it
# again, or the duplication this script replaced grows back unnoticed.
SUITES = {
    "important-only": SKILL_ROOT / "references" / "important-only-suite.md",
    "run-all": SKILL_ROOT / "references" / "run-all-suite.md",
}


def test_the_docs_invoke_the_script_rather_than_inlining_it() -> None:
    """Guard the guard: these tests exercise the script, not what the docs tell an agent.

    If a doc grows its own `cat > "$SUITE_FILE" << HEADER` again, everything below still
    passes while the skill runs unverified bash.
    """
    for name, doc in sorted(SUITES.items()):
        text = doc.read_text(encoding="utf-8")
        assert f"generate_suite.sh {name}" in text, f"{doc.name} no longer calls the script"
        inlined = [b for b in BASH_BLOCK.findall(text) if "<< HEADER" in b or "<<HEADER" in b]
        assert not inlined, f"{doc.name} inlines suite generation again: {inlined[0][:80]}"


@pytest.mark.parametrize("name", sorted(SUITES))
def test_the_invocation_block_propagates_failure(name: str) -> None:
    """A failed generation must fail the block an agent runs, not just the script.

    `generate_suite.sh` exits non-zero on an unset language and on a suite that resolves
    to nothing. Written with the `SUITE_FILE=` assignment last, the block discards that
    status and returns 0, and the run proceeds to analysis with no suite — or with a
    stale one from an earlier run. Rediscovered here after exactly that shipped.
    """
    block = _invocation_block(SUITES[name])
    assert "set -e" in block, f"{SUITES[name].name}: invocation block does not set -e"
    last = [
        ln.strip() for ln in block.splitlines() if ln.strip() and not ln.strip().startswith("#")
    ][-1]
    assert not re.match(r"[A-Z_]+=", last), (
        f"{SUITES[name].name}: the block ends with the assignment `{last}`, which "
        f"overwrites the script's exit status. Put the script call last."
    )


@pytest.mark.parametrize("name", sorted(SUITES))
def test_the_documented_template_matches_what_the_script_writes(name: str, tmp_path: Path) -> None:
    """The yaml template is a copy of logic that now lives in the script.

    Nothing else compares them: test_suite_templates.py checks the template's shape, so a
    filter changed in one place leaves every test green while the doc documents filters
    nobody runs. Neither resolves against the real CLI — that is a manual check now.
    """
    result = _run(name, tmp_path, env_extra={"CODEQL_LANG": "cpp"})
    assert result.returncode == 0, result.stderr

    blocks = YAML_BLOCK.findall(SUITES[name].read_text(encoding="utf-8"))
    assert len(blocks) == 1, f"expected one yaml template in {SUITES[name].name}"
    documented = _significant(blocks[0].replace("<CODEQL_LANG>", "cpp"))
    written = _significant(_suite_text(tmp_path, name))
    assert documented == written, (
        f"{SUITES[name].name}'s template no longer matches generate_suite.sh.\n"
        f"documented: {documented}\nwritten:    {written}"
    )


@pytest.mark.parametrize("name", sorted(SUITES))
def test_the_doc_names_the_path_the_script_writes(name: str, tmp_path: Path) -> None:
    """The doc assigns SUITE_FILE literally; the script derives it. Two definitions."""
    _run(name, tmp_path, env_extra={"CODEQL_LANG": "cpp"})
    written = next((tmp_path / "out" / "raw").glob("*.qls"))
    documented = f'SUITE_FILE="$OUTPUT_DIR/raw/{name}.qls"'
    assert documented in SUITES[name].read_text(encoding="utf-8"), (
        f"{SUITES[name].name} does not assign {documented}"
    )
    assert written.name == f"{name}.qls", (
        f"script wrote {written.name}, but the doc points at {name}.qls"
    )


def _fake_codeql(directory: Path, *, queries: int = 3, exit_code: int = 0) -> Path:
    """A stand-in for the CodeQL CLI that reports a controlled query count.

    It reads the suite it is handed and rejects one that is missing or empty, the way
    the real CLI would. An earlier version ignored its arguments entirely, so these
    tests would have passed even if the generator had written nothing at all.
    """
    directory.mkdir(parents=True, exist_ok=True)
    script = directory / "codeql"
    payload = "[" + ", ".join(f'"q{i}.ql"' for i in range(queries)) + "]"
    script.write_text(
        "#!/bin/sh\n"
        "# Last argument is the suite path, as `codeql resolve queries ... -- FILE`.\n"
        'for arg in "$@"; do suite="$arg"; done\n'
        'if [ ! -s "$suite" ]; then\n'
        '  echo "fake codeql: no such suite or empty: $suite" >&2\n'
        "  exit 2\n"
        "fi\n"
        'if ! grep -q "^- " "$suite"; then\n'
        '  echo "fake codeql: $suite has no suite entries" >&2\n'
        "  exit 2\n"
        "fi\n"
        f"if [ {exit_code} -ne 0 ]; then\n"
        '  echo "fake codeql failure" >&2\n'
        f"  exit {exit_code}\n"
        "fi\n"
        f"echo '{payload}'\n"
    )
    script.chmod(script.stat().st_mode | stat.S_IEXEC | stat.S_IXGRP | stat.S_IXOTH)
    return script


def _fake_uv(directory: Path) -> Path:
    """`uv run SCRIPT ARGS...` -> `python3 SCRIPT ARGS...`.

    The generation scripts invoke the guard via `uv run`. Relying on the real uv would
    make these tests depend on the ambient environment: CI runs pytest inside `uv run`,
    where uv is not on the child's PATH, so the suite passed locally and failed there.
    """
    directory.mkdir(parents=True, exist_ok=True)
    script = directory / "uv"
    # allow-legacy-python: a test stub standing in for uv itself, run with a controlled PATH.
    script.write_text(
        "#!/bin/sh\n"
        '[ "$1" = "run" ] && shift\n'
        "# Drop uv-only flags so the remaining argv is the script and its arguments.\n"
        "while [ $# -gt 0 ]; do\n"
        '  case "$1" in --no-project|--quiet|-q) shift ;; --with) shift 2 ;; *) break ;; esac\n'
        "done\n"
        'exec python3 "$@"\n'
    )
    script.chmod(script.stat().st_mode | stat.S_IEXEC | stat.S_IXGRP | stat.S_IXOTH)
    return script


def _run(
    mode: str, tmp_path: Path, *, env_extra: dict[str, str], **fake
) -> subprocess.CompletedProcess[str]:
    bin_dir = tmp_path / "bin"
    _fake_codeql(bin_dir, **fake)
    _fake_uv(bin_dir)
    output_dir = tmp_path / "out"
    (output_dir / "raw").mkdir(parents=True, exist_ok=True)

    env = {
        "PATH": f"{bin_dir}{os.pathsep}{os.environ['PATH']}",
        "HOME": str(tmp_path),
        "OUTPUT_DIR": str(output_dir),
        **env_extra,
    }
    return subprocess.run(
        [str(GENERATE_SUITE), mode], capture_output=True, text=True, env=env, cwd=tmp_path
    )


def _suite_text(tmp_path: Path, name: str) -> str:
    matches = list((tmp_path / "out" / "raw").glob("*.qls"))
    assert matches, f"{name}: no .qls was written"
    return matches[0].read_text()


@pytest.mark.parametrize("name", sorted(SUITES))
def test_generates_a_suite_naming_the_language(name: str, tmp_path: Path) -> None:
    result = _run(name, tmp_path, env_extra={"CODEQL_LANG": "cpp"})
    assert result.returncode == 0, f"{name} generation failed:\n{result.stderr}"

    text = _suite_text(tmp_path, name)
    assert "codeql/cpp-queries" in text, f"{name}: CODEQL_LANG did not expand"
    assert "${CODEQL_LANG}" not in text, f"{name}: placeholder left unexpanded"


@pytest.mark.parametrize("name", sorted(SUITES))
def test_third_party_packs_are_included(name: str, tmp_path: Path) -> None:
    result = _run(
        name,
        tmp_path,
        env_extra={
            "CODEQL_LANG": "cpp",
            "INSTALLED_THIRD_PARTY_PACKS": "trailofbits/cpp-queries acme/cpp-queries",
        },
    )
    assert result.returncode == 0, result.stderr

    text = _suite_text(tmp_path, name)
    assert "trailofbits/cpp-queries" in text
    assert "acme/cpp-queries" in text, "second pack dropped — the loop only handled one"


@pytest.mark.parametrize("name", sorted(SUITES))
def test_generation_aborts_when_codeql_fails(name: str, tmp_path: Path) -> None:
    """The regression guard. This failed before the `| wc -l` pipeline was replaced."""
    result = _run(
        name,
        tmp_path,
        env_extra={"CODEQL_LANG": "cpp"},
        exit_code=2,
    )
    assert result.returncode != 0, (
        f"{name}: CodeQL failed but the script exited 0. A suite that cannot be resolved "
        f"will produce an empty SARIF that reads as a clean scan."
    )


@pytest.mark.parametrize("name", sorted(SUITES))
def test_generation_aborts_when_suite_resolves_to_zero_queries(name: str, tmp_path: Path) -> None:
    """Zero queries is the failure Essential Principle #3 exists to prevent."""
    result = _run(
        name,
        tmp_path,
        env_extra={"CODEQL_LANG": "cpp"},
        queries=0,
    )
    assert result.returncode != 0, (
        f"{name}: suite resolved to zero queries and the script exited 0 — analysis would "
        f"run and report no findings for a codebase it never examined."
    )


@pytest.mark.parametrize("name", sorted(SUITES))
def test_a_suite_that_fails_verification_is_deleted(name: str, tmp_path: Path) -> None:
    """Left on disk it is indistinguishable from a verified one.

    run-analysis Step 4 derives the same path, and the docs tell the model the generator
    already verified the suite — so the file that just failed gets analysed with, and the
    empty SARIF reads as a clean codebase.
    """
    result = _run(name, tmp_path, env_extra={"CODEQL_LANG": "cpp"}, queries=0)
    assert result.returncode != 0

    left = list((tmp_path / "out" / "raw").glob("*.qls"))
    assert not left, f"{name}: unverifiable suite left behind at {left}"


@pytest.mark.parametrize("name", sorted(SUITES))
def test_unset_language_aborts_before_writing_a_suite(name: str, tmp_path: Path) -> None:
    """The guard must precede the heredoc.

    Checked afterwards, an unset CODEQL_LANG leaves a suite naming `codeql/-queries` on
    disk for a later step to pick up.
    """
    result = _run(name, tmp_path, env_extra={})
    assert result.returncode != 0, f"{name}: unset CODEQL_LANG did not abort"

    for written in (tmp_path / "out" / "raw").glob("*.qls"):
        assert "codeql/-queries" not in written.read_text(), (
            f"{name}: wrote a suite naming the empty pack `codeql/-queries` before the "
            f"guard fired — the guard is still after the heredoc"
        )

Requirements and compatibility

Written for: Claude Code

Works with: Claude Code, Claude apps, OpenAI Codex, GitHub Copilot, Cursor, Gemini CLI, Kiro, OpenCode, Goose, Amp, Roo Code, JetBrains Junie, Factory Droid, Devin (ex-Windsurf), Mistral Vibe, OpenHands, Letta

“Works with” means the tool reads the open Agent Skills format; a skill written for one tool may use features others lack.

Needs: Declares allowed tools, Names Claude Code tools, Needs Python

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Attribution and licence

Published by
Trail of Bits
Publisher
Trail of Bits (Official)
Source
trailofbits/skills · plugins/static-analysis/skills/codeql · commit e4dd0bb
Licence
Creative Commons Attribution-ShareAlike 4.0 International (redistribution allowed)
  • LICENSE (added by AutoGineer from LICENSE)
  • ATTRIBUTION.md (written by AutoGineer)
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