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Open_Ultra_SAST/benchmarks/ranking/position.py
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Marius CiepluchandClaude Fable 5.1 60d13d7b6e feat(model): phase 2 of flow-aware-ranking -- spend the region budget by evidence, weights published
`Evidence.score` orders pairs within a tier by one table of weights (open sinks, cleansed sinks, local /
carried / near sources, entry, declared public), capped so volume stops counting, and zero for tier 0 so
the weights can rank but never manufacture. `ScanBudget.order_by_evidence` runs the evidence pass over
every region and cuts `max_regions` from each region's best (tier, score); `order_by_evidence()` is the
one ordering function, used by the scan and by `benchmarks/ranking/position.py --evidence`. Off by
default until the position benchmark says where the pinned CVEs land under it.

Co-Authored-By: Claude Fable 5.1 <[email protected]>
Claude-Session: https://claude.ai/code/session_01T7XD7x5KonMdmGRkp63EQG
2026-09-11 10:47:47 +02:00

161 lines
7.7 KiB
Python

"""Phase 0 of flow-aware-ranking: where does each pinned CVE sit in the order the scan actually examines?
The ranker's success metric is not "is the CVE in the budget" -- on Paid Memberships Pro it already is, at
position 390 of 4,463 -- but **how small the budget can be while every CVE stays in it**. That number is
`budget_at_recall`, and until it is written down nothing later can claim to have improved it.
This is the baseline. It runs no engine and asks no model: it is the region pipeline exactly as the scan
uses it, sorted exactly as the scan sorts it, with each known vulnerability's position read off. Offline,
against pinned checkouts, so two runs of one repository agree.
ousast-venv/bin/python benchmarks/ranking/position.py # every pinned recipe with a checkout
ousast-venv/bin/python benchmarks/ranking/position.py --json # the same, as an artifact
"""
from __future__ import annotations
import argparse
import json
import sys
from collections import Counter
from pathlib import Path
sys.path.insert(0, str(Path(__file__).resolve().parents[2] / "src"))
from openultrasast.mapping import analyze_entry_points # noqa: E402
from openultrasast.model.regions import ScanRegion, regions_for # noqa: E402
from openultrasast.model.shipped import declared_sources # noqa: E402
from openultrasast.preprocess import preprocess_repository # noqa: E402
from openultrasast.repos import checkout_path, load_repo_recipes # noqa: E402
def ordered_regions(root: Path) -> list[ScanRegion]:
"""The regions in the order `scan_repository` examines them. One definition, imported, never copied."""
_, targets = preprocess_repository(root)
regions = regions_for(analyze_entry_points(root, targets), targets, shipped=declared_sources(root))
# The scan's own total order. If this drifts from scan.py the baseline measures the wrong thing, which
# is why the sort key is the one thing here worth a test against the driver.
return sorted(regions, key=lambda r: (not r.shipped, -r.rank, r.path, r.function or ""))
def evidence_ordered_regions(root: Path, regions: list[ScanRegion]) -> tuple[list[ScanRegion], dict[str, object]]:
"""The regions in the order phase 2 spends the budget: by each region's best (tier, score), from a real
evidence pass over EVERY region. Needs Joern. The ordering function is the scan's own, imported."""
import time
from openultrasast.cpg.backend import resolve_cpg_backend
from openultrasast.model.scan import _collect, _evidence_pass, _hook_callbacks, order_by_evidence
backend = resolve_cpg_backend()
started = time.monotonic()
cpg = backend.build(root, language=regions[0].language if regions else "")
build_seconds = round(time.monotonic() - started, 1)
if cpg is None:
raise SystemExit(f"no graph for {root}: {getattr(backend, 'last_failure', '')}")
try:
started = time.monotonic()
evidence, failed = _evidence_pass(cpg, _collect(regions), _hook_callbacks(root, regions))
evidence_seconds = round(time.monotonic() - started, 1)
finally:
if callable(getattr(cpg, "cleanup", None)):
cpg.cleanup()
tiers = Counter(e.tier for e in evidence.values())
facts = {
"build_seconds": build_seconds,
"evidence_seconds": evidence_seconds,
"pairs": len(evidence),
"pairs_unanswered": failed,
"tier_counts": {str(k): v for k, v in sorted(tiers.items())},
}
return order_by_evidence(regions, evidence), facts
def measure(name: str, root: Path, known: list[dict[str, object]], *, by_evidence: bool = False) -> dict[str, object]:
regions = ordered_regions(root)
facts: dict[str, object] = {}
if by_evidence:
regions, facts = evidence_ordered_regions(root, regions)
tiers = Counter(r.rank for r in regions)
largest = max(tiers.values()) if tiers else 0
rows: list[dict[str, object]] = []
for item in known:
# A known vulnerability names a file and a function. Match on both, path by suffix because a recipe
# writes it relative to the repository and a region may carry it the same way or deeper.
hit = next(
(i for i, r in enumerate(regions) if r.path.endswith(str(item["file"])) and r.function == item["function"]),
None,
)
rows.append(
{
"id": item["id"],
"family": item["family"],
"site": f"{item['file']}:{item['line']}:{item['function']}",
# Zero-based. None means no region is named after this function: the site is a SINK that an
# entry-point region elsewhere reaches through `callDepth` -- VAmPI's SQL injection lives in
# `models/user_model.py:get_user` and is found from the handler that calls it. Its true
# position is that handler's, which only the flow can say, so it is reported and left out of
# `budget_at_recall` rather than counted as a miss it is not.
"position": hit,
"rank": regions[hit].rank if hit is not None else None,
"in_scope": item["in_scope"],
"reached_transitively": hit is None,
}
)
positioned = [r["position"] for r in rows if r["position"] is not None and r["in_scope"]]
return {
"repo": name,
"regions": len(regions),
"distinct_ranks": len(tiers),
"largest_tier_share": round(largest / len(regions), 3) if regions else 0.0,
"largest_tier_rank": max(tiers, key=lambda k: tiers[k]) if tiers else None,
# The smallest examined-region budget that still holds every in-scope known vulnerability.
"budget_at_recall": (max(positioned) + 1) if positioned else None,
"known": rows,
**facts,
}
def main() -> int:
parser = argparse.ArgumentParser(description=__doc__, formatter_class=argparse.RawDescriptionHelpFormatter)
parser.add_argument("--json", action="store_true", help="emit one JSON object per repository")
parser.add_argument("--repo", help="only this recipe")
parser.add_argument("--evidence", action="store_true", help="phase 2: order by a real evidence pass over every region (needs Joern)")
args = parser.parse_args()
results: list[dict[str, object]] = []
for recipe in load_repo_recipes():
if args.repo and recipe.name != args.repo:
continue
if "detection" not in recipe.measures:
continue
root = checkout_path(recipe)
if not root.is_dir():
print(f"{recipe.name}: not checked out, skipping", file=sys.stderr)
continue
known = [
{"id": k.id, "family": k.family, "file": k.file, "function": k.function, "line": k.line, "in_scope": k.in_scope}
for k in recipe.known
]
results.append(measure(recipe.name, root, known, by_evidence=args.evidence))
if args.json:
print(json.dumps(results, indent=2))
return 0
for r in results:
print(
f"{r['repo']}: {r['regions']} regions, {r['distinct_ranks']} distinct ranks, "
f"{100 * float(r['largest_tier_share']):.1f}% share rank {r['largest_tier_rank']}"
)
for k in r["known"]:
where = "reached via another region" if k["position"] is None else f"position {k['position']} (rank {k['rank']})"
scope = "" if k["in_scope"] else " [out of scope]"
print(f" {k['id']:16} {where:28} {k['site']}{scope}")
print(f" budget_at_recall = {r['budget_at_recall']}")
if "tier_counts" in r:
print(f" build {r['build_seconds']}s, evidence {r['evidence_seconds']}s over {r['pairs']} pairs, tiers {r['tier_counts']}")
return 0
if __name__ == "__main__":
raise SystemExit(main())