mirror of
https://github.com/norandom/OpenUltraSAST.git
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Rebuild the quick-scan detection engine and ground-truth benchmarks to hit >=90% recall / <10% false positives for C/C++, Python, JavaScript, and Java. Engine (findings.py, preprocess.py): - Scope each PatternRule by language (fixes cross-language false positives such as the Python eval/exec rule firing on JS .exec()). - Add JavaScript/TypeScript rules (command exec, eval/Function, reflected XSS, SQLi, path traversal, SSRF, weak hash, deserialization); execFile/spawn-argv excluded as safe alternatives. - Add Java rules (Runtime exec, SQL string concatenation, weak hash, readObject) and a Groovy server-side template rule (yieldUnescaped of a bound variable). - Broaden C/C++ and Python coverage; precision guards for format strings and parameterised vs concatenated SQL; #-comment skipping; CWE in rationale. - Register .java/.groovy/.tpl source extensions. Benchmarks: - Add realistic corpora modeled on Damn Vulnerable C/C++, PyGoat/DVPWA, and NodeGoat, plus the real kiview/damn-vulnerable-spring-boot-app vendored verbatim (MIT, attribution in LICENSE/NOTICE.md). Each manifest carries complete, independently-labeled ground truth including genuinely hard-to-detect vulns (integer overflow, second-order SQLi, prototype pollution) so recall is measured honestly, plus safe-API files for precision. - Fix pre-existing smoke-manifest ground-truth errors (Python/JS line offsets, missing C/C++ strcpy entry, Java SQLi line). benchmark.py: - Fix sink matching to normalise the expected sink consistently so sinks with underscores (e.g. render_template_string) can match. Tests: - Add tests/test_detection_benchmarks.py enforcing the >=90% recall / <10% FP goal per language and overall. Measured: C/C++ 93.3%, Python 93.3%, JavaScript 92.3%, Java 100%; overall 93.6% recall, 0.0% false-positive rate. Co-Authored-By: Claude Opus 4.8 <[email protected]>
233 lines
9.7 KiB
Python
233 lines
9.7 KiB
Python
from __future__ import annotations
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import argparse
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import json
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from dataclasses import dataclass
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from pathlib import Path
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from time import perf_counter
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from .benchmark import (
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create_benchmark_run,
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evaluate_benchmark,
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load_baseline_findings,
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load_benchmark_manifest,
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load_findings,
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resolve_benchmark_source,
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write_benchmark_artifacts,
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)
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from .config import load_config
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from .findings import StaticFinding, quick_scan_findings, write_findings
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from .harness import HarnessRuntime, HarnessTraceWriter, write_harness_config
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from .hunter import run_hunter_pool, write_hunter_trajectories
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from .index import build_code_chunks
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from .mapping import analyze_entry_points, attach_reachability_hints, ingest_sarif, write_entry_points, write_static_hints
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from .preprocess import preprocess_repository, write_preprocess_artifact
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from .rank import rank_targets, write_rankings
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from .reports import scan_exit_code, write_manifest, write_markdown_report, write_sarif_report
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from .run import create_scan_run
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from .verification import verify_findings, write_verification_results
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@dataclass(frozen=True)
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class ScanOutcome:
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scan_id: str
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run_dir: Path
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file_target_count: int
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ranked_target_count: int
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finding_count: int
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exit_code: int
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def main(argv: list[str] | None = None) -> int:
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parser = argparse.ArgumentParser(prog="ousast")
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subparsers = parser.add_subparsers(dest="command", required=True)
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scan = subparsers.add_parser("scan", help="scan a local repository")
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scan.add_argument("path", type=Path)
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scan.add_argument("--mode", choices=("quick", "standard", "deep"), default="quick")
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scan.add_argument("--config", type=Path, default=Path("openultrasast.toml"))
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scan.add_argument("--fail-on", choices=("never", "findings", "verified"), default="never")
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index = subparsers.add_parser("index", help="chunk a local repository for embedding index construction")
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index.add_argument("path", type=Path)
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index.add_argument("--config", type=Path, default=Path("openultrasast.toml"))
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index.add_argument("--chunk-lines", type=int, default=80)
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benchmark = subparsers.add_parser("benchmark", help="run a benchmark manifest and write scoreboard artifacts")
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benchmark.add_argument("manifest", type=Path)
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benchmark.add_argument("--mode", choices=("quick", "standard", "deep"), default="quick")
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benchmark.add_argument("--config", type=Path, default=Path("openultrasast.toml"))
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args = parser.parse_args(argv)
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if args.command == "scan":
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return _scan(args.path, args.config, args.mode, args.fail_on)
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if args.command == "index":
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return _index(args.path, args.config, args.chunk_lines)
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if args.command == "benchmark":
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return _benchmark(args.manifest, args.config, args.mode)
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return 2
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def _scan(path: Path, config_path: Path, mode: str, fail_on: str) -> int:
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outcome = _run_scan(path, config_path, mode, fail_on)
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_print_scan_outcome(outcome)
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return outcome.exit_code
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def _run_scan(path: Path, config_path: Path, mode: str, fail_on: str) -> ScanOutcome:
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if mode == "deep":
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raise SystemExit("mode 'deep' is specified but sandboxed dynamic analysis is not implemented")
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if not path.exists() or not path.is_dir():
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raise SystemExit(f"scan path is not a directory: {path}")
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config = load_config(config_path if config_path.exists() else None)
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run = create_scan_run(path, config)
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runtime = HarnessRuntime(
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scan_id=run.scan_id,
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config=config,
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trace_writer=HarnessTraceWriter(run.root / "trace" / "events.jsonl"),
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)
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write_harness_config(config=config, processors=[], contract_mode="strict", path=run.root / "harness.json")
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runtime.start(mode=mode, target=run.target)
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static_hints = runtime.run_stage("static_mapping", lambda: _load_static_hints(config.static_analysis.sarif_paths))
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write_static_hints(static_hints, run.root / "mapping" / "static_hints.json")
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snapshot, targets = runtime.run_stage(
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"preprocess",
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lambda: preprocess_repository(run.target, run.root / "preprocess" / "file_targets.json", static_hints),
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)
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entry_points = runtime.run_stage("entry_point_mapping", lambda: analyze_entry_points(run.target, targets))
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write_entry_points(entry_points, run.root / "mapping" / "entry_points.json")
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targets = attach_reachability_hints(targets, entry_points)
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write_preprocess_artifact(snapshot, targets, run.root / "preprocess" / "file_targets.json")
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rankings = runtime.run_stage("rank", lambda: rank_targets(targets))
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write_rankings(rankings, run.root / "rank" / "ranking.json")
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if mode == "standard":
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hunter_result = runtime.run_stage("hunter_pool", lambda: run_hunter_pool(run.target, targets, rankings, scan_id=run.scan_id))
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findings = hunter_result.findings
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trajectories = hunter_result.trajectories
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else:
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findings = runtime.run_stage("quick_findings", lambda: quick_scan_findings(run.target, targets, rankings))
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trajectories = []
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findings_path = run.root / "findings.json"
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verification_path = run.root / "verification.json"
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markdown_path = run.root / "report.md"
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sarif_path = run.root / "report.sarif"
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manifest_path = run.root / "manifest.json"
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trajectories_path = run.root / "traces" / "hunter_trajectories.jsonl"
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write_findings(findings, findings_path)
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if trajectories:
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write_hunter_trajectories(trajectories, trajectories_path)
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verifications = runtime.run_stage("verify", lambda: verify_findings(findings))
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write_verification_results(verifications, verification_path)
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runtime.run_stage("report", lambda: write_markdown_report(findings, markdown_path, verifications))
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runtime.run_stage("sarif", lambda: write_sarif_report(findings, verifications, sarif_path))
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runtime.run_stage(
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"manifest",
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lambda: write_manifest(
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run=run,
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findings=findings,
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verifications=verifications,
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artifact_paths=_artifact_paths(
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findings=findings_path,
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verification=verification_path,
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markdown=markdown_path,
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sarif=sarif_path,
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trajectories=trajectories_path if trajectories else None,
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),
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path=manifest_path,
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),
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)
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runtime.finish(status="succeeded")
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return ScanOutcome(
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scan_id=run.scan_id,
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run_dir=run.root,
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file_target_count=len(targets),
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ranked_target_count=len(rankings),
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finding_count=len(findings),
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exit_code=scan_exit_code(findings, verifications, fail_on),
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)
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def _print_scan_outcome(outcome: ScanOutcome) -> None:
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print(f"scan_id={outcome.scan_id}")
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print(f"run_dir={outcome.run_dir}")
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print(f"file_targets={outcome.file_target_count}")
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print(f"ranked_targets={outcome.ranked_target_count}")
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print(f"findings={outcome.finding_count}")
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def _load_static_hints(sarif_paths: tuple[str, ...]) -> list[object]:
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hints: list[object] = []
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for sarif_path in sarif_paths:
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path = Path(sarif_path)
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if path.exists():
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hints.extend(ingest_sarif(path))
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return hints
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def _artifact_paths(**paths: Path | None) -> dict[str, Path]:
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return {name: path for name, path in paths.items() if path is not None}
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def _benchmark(manifest_path: Path, config_path: Path, mode: str) -> int:
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if not manifest_path.exists() or not manifest_path.is_file():
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raise SystemExit(f"benchmark manifest is not a file: {manifest_path}")
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manifest = load_benchmark_manifest(manifest_path)
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target = resolve_benchmark_source(manifest_path, manifest)
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run = create_benchmark_run(target, manifest)
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started_at = perf_counter()
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outcome = _run_scan(target, config_path, mode, "never")
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runtime_seconds = perf_counter() - started_at
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findings = _load_scan_findings(outcome.run_dir)
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baseline_findings = load_baseline_findings(manifest_path, manifest)
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result = evaluate_benchmark(
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run=run,
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mode=mode,
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findings=findings,
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scan_id=outcome.scan_id,
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scan_run_dir=outcome.run_dir,
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runtime_seconds=runtime_seconds,
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baseline_findings=baseline_findings,
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)
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write_benchmark_artifacts(run, manifest_path, result)
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_print_scan_outcome(outcome)
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print(f"benchmark_run_id={run.benchmark_run_id}")
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print(f"benchmark_run_dir={run.root}")
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print(f"benchmark_expected={result.metrics.expected_findings_total}")
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print(f"benchmark_matched={result.metrics.matched_findings_total}")
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print(f"benchmark_missed={result.metrics.missed_findings_total}")
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return 0
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def _load_scan_findings(run_dir: Path) -> list[StaticFinding]:
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return load_findings(run_dir / "findings.json")
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def _index(path: Path, config_path: Path, chunk_lines: int) -> int:
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if not path.exists() or not path.is_dir():
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raise SystemExit(f"index path is not a directory: {path}")
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config = load_config(config_path if config_path.exists() else None)
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run = create_scan_run(path, config)
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snapshot, targets = preprocess_repository(run.target, run.root / "preprocess" / "file_targets.json")
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chunks = build_code_chunks(run.target, targets, max_lines=chunk_lines)
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payload = {
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"store": config.embeddings.store or "json-local",
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"embedding_model": config.embeddings.model,
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"repo_root": snapshot.root,
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"repo_commit": snapshot.commit,
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"chunk_count": len(chunks),
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"chunks": [chunk.__dict__ for chunk in chunks],
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}
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path_out = run.root / "index" / "chunks.json"
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path_out.parent.mkdir(parents=True, exist_ok=True)
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path_out.write_text(json.dumps(payload, indent=2, sort_keys=True) + "\n")
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print(f"scan_id={run.scan_id}")
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print(f"run_dir={run.root}")
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print(f"chunks={len(chunks)}")
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print(f"index_artifact={path_out}")
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return 0
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if __name__ == "__main__":
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raise SystemExit(main())
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