Codeql
Trail of BitsOfficialPublished by Trail of Bits
- Skill
- Workflow
- Security
- CC-BY-SA-4.0
- Low risk
- Has scripts
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
Download the skill as a ZIP:
https://autogineer.com/agent-skills/trailofbits/codeql/downloadUnzip 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
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'sdefaultSuiteFileapplies 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.pyafter the build, confirm{baseDir}/scripts/verify_query_suite.pyexited 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/arm64mismatch, not a build failure. Try Homebrew arm64 tools or Rosetta before falling back tobuild-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.
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_loggedexit 127, which the build ladder reads as a failed method and walks down to--build-mode=none, never having invoked CodeQLa lost array expands to nothing, so every
--threat-modeland--model-packsthe user chose is dropped while the final report still lists them as useda lost scalar under
set -uaborts the block withunbound 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:
$OUTPUT_DIR/
├── rulesets.txt # Selected query packs (logged after Step 3)
├── codeql.db/ # CodeQL database (dir containing codeql-database.yml)
├── build.log # Build log
├── codeql-config.yml # Exclusion config (interpreted languages)
├── diagnostics/ # Diagnostic queries and CSVs
├── extensions/ # Data extension YAMLs
├── raw/ # Unfiltered analysis output
│ ├── results.sarif
│ └── run-all.qls | important-only.qls
└── results/ # Final results (filtered for important-only, copied for run-all)
└── results.sarifDatabase Discovery
A CodeQL database is identified by the presence of a codeql-database.yml marker file inside its directory. When searching for existing databases, always collect all matches — there may be multiple databases from previous runs or for different languages.
Discovery command. find_databases.sh prints one database path per line, filtering
out the marker files a failed build leaves behind. Build the array in the same block
that selects from it — each Bash call is a fresh shell, so an array built here is empty
by the next call, and the run concludes there is no database:
# Command substitution, not `done < <(...)`: a process substitution discards the script's
# exit status, so "codeql is not on this shell's PATH" (exit 2) would arrive as an empty
# list and route to "build a new database" with three good ones sitting on disk.
if ! DB_LIST=$("{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"
doneNever 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 --versionThen 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-extendedmisses entirely."security-and-quality is the broadest suite" -
security-and-qualityexcludes allexperimental/query paths. For run-all mode, import bothsecurity-and-qualityandsecurity-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/arm64mismatch, not a fundamental build failure. See macos-arm64e-workaround.md."No findings means the code is secure" - Run
check_db_quality.pyandverify_query_suite.pyand 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
defaultSuiteFileapplies 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.
| 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 |
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.
| 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 |
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
$OUTPUT_DIRto its parent directory (or the directory containing it), set$DB_NAMEto 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
| 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 |
| 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 |
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.ymlmarker) and{baseDir}/scripts/check_db_quality.pyexited 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.pyexited 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.logwith all commands, fixes, and quality assessments
Files
- ATTRIBUTION.mdAdded by AutoGineer921 B
- LICENSELicence file added by AutoGineer19.7 KiB
- SKILL.md18.2 KiB
- agents/openai.yaml239 B
- assets/trail-of-bits-mark.svg3.0 KiB
- references/build-fixes.md3.2 KiB
- references/diagnostic-query-templates.md9.5 KiB
- references/extension-yaml-format.md7.4 KiB
- references/important-only-suite.md5.1 KiB
- references/language-details.md5.7 KiB
- references/macos-arm64e-workaround.md7.3 KiB
- references/performance-tuning.md2.8 KiB
- references/quality-assessment.md7.8 KiB
- references/ruleset-catalog.md2.1 KiB
- references/run-all-suite.md5.4 KiB
- references/sarif-processing.md3.0 KiB
- references/threat-models.md2.7 KiB
- scripts/build_log.shScript2.1 KiB
- scripts/check_db_quality.pyScript14.7 KiB
- scripts/find_databases.shScript2.5 KiB
- scripts/generate_suite.shScript3.3 KiB
- scripts/pyproject.toml585 B
- scripts/test_build_log.pyScript3.2 KiB
- scripts/test_build_mode_claims.pyScript3.6 KiB
- scripts/test_check_db_quality.pyScript19.8 KiB
- scripts/test_find_databases.pyScript6.0 KiB
- scripts/test_generation_scripts.pyScript11.6 KiB
- scripts/test_script_flags.pyScript6.3 KiB
- scripts/test_section_pointers.pyScript7.9 KiB
- scripts/test_shell_blocks.pyScript29.1 KiB
- scripts/test_suite_templates.pyScript5.0 KiB
- scripts/test_verify_query_suite.pyScript1.9 KiB
- scripts/verify_query_suite.pyScript2.7 KiB
- workflows/build-database.md13.0 KiB
- workflows/create-data-extensions.md10.3 KiB
- workflows/run-analysis.md13.3 KiB
scripts/test_check_db_quality.py
"""Regression tests for the database quality gate.
The workflow used to compute these metrics and print them, special-casing zero files to
"N/A (no files)" — so a database that extracted nothing still got analysed. These pin
the thresholds that now stop it.
"""
from __future__ import annotations
import json
import zipfile
from pathlib import Path
import pytest
from check_db_quality import (
DIAGNOSTICS_FORMAT_CHANGED,
ERROR_RATIO_EXCEEDED,
QualityFailure,
assess,
is_finalised,
main,
)
PROJECT_FILES = ["src/app.c", "src/util.c", "include/app.h"]
TOOLCHAIN_FILES = ["usr/include/stdio.h", "Library/Developer/SDK/string.h", "System/x.h"]
def _database(
tmp_path: Path,
*,
loc: int = 1200,
project_files: list[str] | None = None,
toolchain_files: list[str] | None = None,
source_prefix: str | None = None,
extractor_errors: int = 0,
baseline: bool = True,
archive: bool = True,
) -> Path:
"""Build a directory shaped like a finalized CodeQL database.
With `source_prefix`, the yml records a source root and the archive stores project
files beneath it, as CodeQL does. Without one, it falls back to the toolchain
blocklist — which is what a database from a CLI old enough to omit the key gets.
"""
database = tmp_path / "codeql.db"
database.mkdir(parents=True, exist_ok=True)
marker = "primaryLanguage: cpp\nfinalised: true\n"
if source_prefix:
marker += f"sourceLocationPrefix: {source_prefix}\n"
(database / "codeql-database.yml").write_text(marker)
if baseline:
files = project_files if project_files is not None else PROJECT_FILES
(database / "baseline-info.json").write_text(
json.dumps({"languages": {"cpp": {"linesOfCode": loc, "files": files}}})
)
if archive:
root = (source_prefix or "").replace("\\", "/").strip("/")
sources = project_files if project_files is not None else PROJECT_FILES
names = [f"{root}/{name}" if root else name for name in sources]
names += toolchain_files if toolchain_files is not None else TOOLCHAIN_FILES
with zipfile.ZipFile(database / "src.zip", "w") as handle:
for name in names:
handle.writestr(name, "// source\n")
if extractor_errors:
diagnostics = database / "diagnostic" / "extractors" / "cpp"
diagnostics.mkdir(parents=True)
(diagnostics / "errors.jsonl").write_text(
"".join(f'{{"severity":"error","n":{i}}}\n' for i in range(extractor_errors))
)
return database
def _diag(database: Path, name: str, payload: str) -> Path:
directory = database / "diagnostic" / "extractors" / "cpp"
directory.mkdir(parents=True, exist_ok=True)
path = directory / name
path.write_text(payload)
return path
# --- the thresholds that did not previously exist ---------------------------------
def test_zero_baseline_loc_fails(tmp_path: Path) -> None:
"""No analysable source must halt the run, not produce a clean report."""
with pytest.raises(QualityFailure, match="Baseline lines of code is 0"):
assess(_database(tmp_path, loc=0))
def test_zero_project_files_fails(tmp_path: Path) -> None:
"""Only toolchain paths in src.zip means build tracing captured nothing.
The case the old shell forgave with "N/A (no files)".
"""
with pytest.raises(QualityFailure, match="Zero project files"):
assess(_database(tmp_path, project_files=[]))
def test_error_ratio_over_threshold_fails(tmp_path: Path) -> None:
with pytest.raises(QualityFailure, match="error ratio"):
assess(_database(tmp_path, extractor_errors=3)) # 3/3 files = 100%
def test_error_ratio_under_threshold_passes(tmp_path: Path) -> None:
many = [f"src/f{i}.c" for i in range(100)]
metrics = assess(_database(tmp_path, project_files=many, extractor_errors=2))
assert metrics["error_ratio"] == 2.0
def test_threshold_is_configurable(tmp_path: Path) -> None:
database = _database(tmp_path, extractor_errors=3)
with pytest.raises(QualityFailure):
assess(database, max_error_ratio=5.0)
assert assess(database, max_error_ratio=100.0)["extractor_errors"] == 3
# --- toolchain files must not be mistaken for project source ----------------------
def test_toolchain_files_do_not_count_as_project_source(tmp_path: Path) -> None:
"""Counting SDK headers would let an extraction that captured only headers pass."""
database = _database(
tmp_path,
project_files=[],
toolchain_files=[f"usr/include/h{i}.h" for i in range(200)],
)
with pytest.raises(QualityFailure, match="Zero project files"):
assess(database)
def test_the_source_root_beats_the_toolchain_blocklist(tmp_path: Path) -> None:
"""A Linux toolchain under `nix/store/` is not project source, and no list knows that.
The blocklist was macOS-shaped, so these 200 headers counted as project files: the
error-ratio denominator inflated and the gate softened. The recorded source root
settles it without the list having to name every platform's toolchain location.
"""
database = _database(
tmp_path,
source_prefix="/srv/build/proj",
project_files=["src/app.c", "src/util.c"],
toolchain_files=[f"nix/store/x-gcc-13/include/h{i}.h" for i in range(200)],
)
assert assess(database)["project_files"] == 2
def test_real_archive_layout_from_codeql_2_25_6(tmp_path: Path) -> None:
"""Pin the contract, copied from a cpp database this skill's own workflow built.
src.zip stores each file at its absolute path minus the leading slash, so the source
root from the yml is a literal prefix of the project's entries and of nothing else.
"""
database = _database(
tmp_path,
source_prefix="/private/tmp/scan/proj",
project_files=["src/main.c"],
toolchain_files=[
"Applications/Xcode.app/Contents/Developer/Platforms/MacOSX.platform/"
"Developer/SDKs/MacOSX.sdk/usr/include/stdio.h"
],
)
with zipfile.ZipFile(database / "src.zip") as handle:
assert "private/tmp/scan/proj/src/main.c" in handle.namelist()
assert assess(database)["project_files"] == 1
def test_toolchain_only_archive_fails_even_with_a_source_root(tmp_path: Path) -> None:
"""Nothing under the root is the signal the gate exists for, not a layout problem."""
database = _database(
tmp_path,
source_prefix="/srv/build/proj",
project_files=[],
toolchain_files=[f"usr/include/h{i}.h" for i in range(50)],
)
with pytest.raises(QualityFailure, match="Zero project files"):
assess(database)
def test_archive_that_ignores_the_source_root_fails_loudly(tmp_path: Path) -> None:
"""Files outside the root that are not toolchain paths mean an unmodelled layout.
Counting them as project source, or as zero, would both report a number nobody can
check. Windows drive letters are the case most likely to land here.
"""
database = _database(tmp_path, project_files=["src/app.c"], toolchain_files=[])
(database / "codeql-database.yml").write_text(
"primaryLanguage: cpp\nfinalised: true\nsourceLocationPrefix: /srv/build/proj\n"
)
with pytest.raises(QualityFailure, match="layout does not match"):
assess(database)
def test_healthy_database_passes(tmp_path: Path) -> None:
metrics = assess(_database(tmp_path))
assert metrics["baseline_loc"] == 1200
assert metrics["project_files"] == len(PROJECT_FILES)
assert metrics["extractor_errors"] == 0
# --- malformed inputs are failures, not zeros -------------------------------------
def test_missing_marker_fails(tmp_path: Path) -> None:
plain = tmp_path / "not-a-db"
plain.mkdir()
with pytest.raises(QualityFailure, match="not a CodeQL database"):
assess(plain)
def test_missing_baseline_info_fails(tmp_path: Path) -> None:
with pytest.raises(QualityFailure, match="baseline-info.json"):
assess(_database(tmp_path, baseline=False))
def test_missing_source_archive_fails(tmp_path: Path) -> None:
with pytest.raises(QualityFailure, match="src.zip"):
assess(_database(tmp_path, archive=False))
def test_empty_language_map_fails(tmp_path: Path) -> None:
database = _database(tmp_path)
(database / "baseline-info.json").write_text(json.dumps({"languages": {}}))
with pytest.raises(QualityFailure, match="no languages"):
assess(database)
def test_parses_baseline_info_as_codeql_actually_writes_it(tmp_path: Path) -> None:
"""Pin the real contract, copied verbatim from a database built by CodeQL 2.25.6.
`codeql database create` writes baseline-info.json when it finalizes. `print-baseline`
prints a count to stdout and creates nothing, so the file is the only machine-readable
source. Extra keys (displayName, name) must not break parsing.
"""
database = _database(tmp_path, baseline=False)
(database / "baseline-info.json").write_text(
json.dumps(
{
"languages": {
"python": {
"displayName": "Python",
"files": ["app.py"],
"linesOfCode": 5,
"name": "python",
}
}
}
)
)
assert assess(database)["baseline_loc"] == 5
def test_sums_lines_of_code_across_languages(tmp_path: Path) -> None:
"""`languages` is a map, so a multi-language database has more than one entry."""
database = _database(tmp_path, baseline=False)
(database / "baseline-info.json").write_text(
json.dumps(
{
"languages": {
"python": {"linesOfCode": 5, "files": ["a.py"]},
"cpp": {"linesOfCode": 7, "files": ["b.c"]},
}
}
)
)
assert assess(database)["baseline_loc"] == 12
# --- diagnostics: severity, not brace count ---------------------------------------
def test_pretty_printed_notes_are_not_errors(tmp_path: Path) -> None:
"""The regression. Verbatim from a healthy database built by CodeQL 2.25.6.
Despite the `.jsonl` name this is one pretty-printed object. Counting lines starting
with `{` scored its nested braces as records and failed the database at a 500% error
ratio, while CodeQL reported extractor-failures: 0.
"""
database = _database(tmp_path)
_diag(
database,
"autobuilder-41150.jsonl",
json.dumps(
{
"timestamp": "2026-07-30T23:47:17Z",
"source": {
"id": "cpp/autobuilder/buildless/mode-active",
"name": "C/C++ was extracted with build-mode set to 'none'",
"extractorName": "cpp",
},
"severity": "note",
"visibility": {"statusPage": False, "telemetry": True},
"attributes": {"tried": []},
},
indent=2,
),
)
assert assess(database)["extractor_errors"] == 0
def test_codeql_own_failure_count_wins(tmp_path: Path) -> None:
"""summary.jsonl carries `extractor-failures`, which is authoritative."""
database = _database(tmp_path, project_files=[f"src/f{i}.c" for i in range(100)])
_diag(
database,
"summary.jsonl",
json.dumps({"attributes": {"extractor-failures": 3, "extractor-successes": 97}}, indent=4),
)
assert assess(database)["extractor_errors"] == 3
def test_failure_counts_sum_across_extractors(tmp_path: Path) -> None:
database = _database(tmp_path, project_files=[f"src/f{i}.c" for i in range(100)])
for lang, failures in (("cpp", 2), ("python", 1)):
directory = database / "diagnostic" / "extractors" / lang
directory.mkdir(parents=True, exist_ok=True)
(directory / "summary.jsonl").write_text(
json.dumps({"attributes": {"extractor-failures": failures}})
)
assert assess(database)["extractor_errors"] == 3
def test_a_summary_from_one_extractor_does_not_mask_another(tmp_path: Path) -> None:
"""The summary-vs-severity preference is per extractor, not per database.
Resolved globally, cpp's `extractor-failures: 0` returned 0 for the whole tree and
python's four error records vanished — a database whose python extraction largely
failed passed the ratio gate at 0.0%.
"""
database = _database(tmp_path, project_files=[f"src/f{i}.c" for i in range(100)])
extractors = database / "diagnostic" / "extractors"
(extractors / "cpp").mkdir(parents=True)
(extractors / "cpp" / "summary.jsonl").write_text(
json.dumps({"attributes": {"extractor-failures": 0, "extractor-successes": 40}})
)
(extractors / "python").mkdir(parents=True)
(extractors / "python" / "errors.jsonl").write_text(
"\n".join(json.dumps({"severity": "error", "n": i}) for i in range(4))
)
assert assess(database)["extractor_errors"] == 4
def test_summary_and_severity_extractors_are_both_counted(tmp_path: Path) -> None:
"""Each extractor contributes by whichever measure it recorded."""
database = _database(tmp_path, project_files=[f"src/f{i}.c" for i in range(100)])
extractors = database / "diagnostic" / "extractors"
(extractors / "cpp").mkdir(parents=True)
(extractors / "cpp" / "summary.jsonl").write_text(
json.dumps({"attributes": {"extractor-failures": 2}})
)
(extractors / "python").mkdir(parents=True)
(extractors / "python" / "errors.jsonl").write_text(
"\n".join(json.dumps({"severity": s}) for s in ("error", "note", "error", "error"))
)
assert assess(database)["extractor_errors"] == 5
def test_severity_fallback_counts_only_errors(tmp_path: Path) -> None:
"""With no summary present, count severity `error` and ignore note/warning."""
database = _database(tmp_path, project_files=[f"src/f{i}.c" for i in range(100)])
_diag(
database,
"records.jsonl",
"\n".join(
json.dumps({"severity": s}) for s in ("note", "error", "warning", "error", "note")
),
)
assert assess(database)["extractor_errors"] == 2
def test_plain_json_diagnostics_are_read_too(tmp_path: Path) -> None:
"""The directory holds `.json` files as well; globbing `*.jsonl` skipped them."""
database = _database(tmp_path, project_files=[f"src/f{i}.c" for i in range(100)])
_diag(database, "standalone-extraction.0.json", json.dumps({"severity": "error"}))
assert assess(database)["extractor_errors"] == 1
def test_unparseable_diagnostics_fail_rather_than_count_zero(tmp_path: Path) -> None:
"""A format change must be visible, not silently reported as a healthy database."""
database = _database(tmp_path)
_diag(database, "weird.jsonl", "not json at all\nnor this")
with pytest.raises(QualityFailure, match="format has changed"):
assess(database)
def test_absent_extractor_diagnostics_mean_zero_errors(tmp_path: Path) -> None:
"""Absent is genuinely zero here, unlike the cases above where absent data fails.
Pinned so nobody "fixes" it into a spurious error.
"""
database = _database(tmp_path)
assert not (database / "diagnostic").exists()
assert assess(database)["extractor_errors"] == 0
# --- CLI ---------------------------------------------------------------------------
def test_cli_exits_nonzero_on_bad_database(tmp_path: Path) -> None:
assert main([str(_database(tmp_path, loc=0))]) == 1
def test_nothing_to_analyse_and_ratio_exceeded_get_different_exits(tmp_path: Path) -> None:
"""The build workflow branches on these, so they must not collapse to "non-zero".
Exit 1 is unarguable — there is no source to analyse. Exit 2 is a threshold a
legitimate partial extraction can exceed, and the workflow is allowed to override it
with --max-error-ratio. Reporting both as 1 would make that override look like the
same decision as ignoring an empty database.
"""
assert main([str(_database(tmp_path, project_files=[]))]) == 1
assert main([str(_database(tmp_path, extractor_errors=3))]) == ERROR_RATIO_EXCEEDED
def test_raising_the_threshold_clears_only_the_ratio_failure(tmp_path: Path) -> None:
"""The escape hatch must not also wave through a database with nothing in it."""
assert main([str(_database(tmp_path, extractor_errors=3)), "--max-error-ratio", "100"]) == 0
assert main([str(_database(tmp_path, loc=0)), "--max-error-ratio", "100"]) == 1
def test_json_output_carries_the_metrics_the_docs_read(tmp_path: Path, capsys) -> None:
"""quality-assessment.md reads these keys with jq instead of recomputing them.
A second hand-written pipeline is how the doc came to log 202 project files while the
script reported 2 — it filtered a macOS-shaped prefix list rather than the source root.
"""
assert main([str(_database(tmp_path)), "--format=json"]) == 0
metrics = json.loads(capsys.readouterr().out)
assert set(metrics) == {
"baseline_loc",
"project_files",
"archive_files",
"extractor_errors",
"error_ratio",
"finalised",
}
assert metrics["project_files"] == len(PROJECT_FILES)
# archive_files counts the toolchain too, so it is the larger of the two. The doc used
# to get this from its own `unzip -Z1 | wc -l`.
assert metrics["archive_files"] > metrics["project_files"]
assert metrics["finalised"] is True
def test_cli_exits_zero_on_healthy_database(tmp_path: Path) -> None:
assert main([str(_database(tmp_path))]) == 0
def test_cli_accepts_max_error_ratio(tmp_path: Path) -> None:
database = _database(tmp_path, extractor_errors=3)
assert main([str(database)]) == ERROR_RATIO_EXCEEDED
assert main([str(database), "--max-error-ratio", "100"]) == 0
def test_exit_codes_avoid_argparses_usage_status(tmp_path: Path) -> None:
"""argparse exits 2 on a bad command line, so no verdict of ours may use 2.
build-database.md tells the reader that the ratio exit means "re-run with a raised
--max-error-ratio". Sharing 2 with argparse made `--max-error-ratio abc` — which
inspects nothing — indistinguishable from that verdict.
"""
assert 2 not in {ERROR_RATIO_EXCEEDED, DIAGNOSTICS_FORMAT_CHANGED}
with pytest.raises(SystemExit) as usage_error:
main([str(_database(tmp_path)), "--max-error-ratio", "not-a-number"])
assert usage_error.value.code == 2
def test_a_non_json_file_in_the_diagnostics_tree_is_ignored(tmp_path: Path) -> None:
"""A future release dropping a .log there must not fail an otherwise good database.
Every file under diagnostic/extractors used to be handed to the JSON parser, and the
resulting failure carried the non-overridable "nothing to analyse" code.
"""
database = _database(tmp_path, project_files=[f"src/f{i}.c" for i in range(100)])
_diag(database, "records.jsonl", json.dumps({"severity": "error"}))
(database / "diagnostic" / "extractors" / "cpp" / "extractor.log").write_text(
"2026-07-31 building ...\nnot json at all\n"
)
assert assess(database)["extractor_errors"] == 1
def test_a_malformed_json_diagnostic_still_fails_with_its_own_code(tmp_path: Path) -> None:
"""Narrowing the glob must not silence the format-change signal it was added for."""
database = _database(tmp_path)
_diag(database, "weird.jsonl", "not json at all\nnor this")
assert main([str(database)]) == DIAGNOSTICS_FORMAT_CHANGED
def test_an_unfinalised_database_is_reported_as_such(tmp_path: Path) -> None:
"""An interrupted build leaves the key absent, not false.
`codeql database finalize` after a failed trace-command is the case: the database
resolves, analyses, and reports nothing.
"""
database = _database(tmp_path)
marker = database / "codeql-database.yml"
marker.write_text(marker.read_text().replace("finalised: true\n", ""))
assert is_finalised(database) is False
assert assess(database)["finalised"] is False
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)
- Synced
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