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Marius CiepluchandClaude Opus 5
241af31a9a
Task 2.3. A pair is scored once per family. Detection means a finding whose family tag relates to the labeled family and whose line sits inside the labeled function; the words in a finding are never read, because a text token is exactly the proxy that made the old hunter number meaningless. Silence means no such finding on the fixed side, and findings of other families or outside the labeled function are counted separately and never called leaks. A fabricated family id counts as neither, and is recorded as noise worth naming. Every evaluation runs a pair several times, because a single run misses most real changes. The recorded outcome is the majority of the runs and the runs that disagree with it are the pair's own flakiness, which is what the regression budget will be built from. A pair that cannot be scored keeps its reason and is never run, and a labeled function no parsed range names is unscorable rather than a silent miss. Co-Authored-By: Claude Opus 5 (1M context) <[email protected]> Claude-Session: https://claude.ai/code/session_01T7XD7x5KonMdmGRkp63EQG
153 lines
6.9 KiB
Python
153 lines
6.9 KiB
Python
"""learning-harness task 2.3: per-pair family scoring (offline)."""
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from __future__ import annotations
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from pathlib import Path
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from openultrasast.benchmark import ExpectedFinding
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from openultrasast.findings import StaticFinding
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from openultrasast.learning.families import load_families
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from openultrasast.pairs import PairCase
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RANGES = {"app.py": (("leaky", 10, 13), ("guarded", 4, 7))}
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def _finding(family: str, line: int, path: str = "app.py") -> StaticFinding:
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return StaticFinding(
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finding_id=f"detector:{path}:{line}",
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path=path,
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title="t",
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severity="medium",
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confidence="low",
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evidence_level="suspicion",
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rationale="r",
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line=line,
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function_name=None,
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reachability_status="unknown",
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reachability_evidence=[],
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reachability_conditions=[],
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tags=[f"family:{family}", "detector:x@1"],
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ranking_priority=0.0,
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)
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def _case(tmp_path: Path, *, family: str = "access_control", unscorable: str | None = None) -> PairCase:
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(tmp_path / "v.py").write_text("x = 1\n")
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(tmp_path / "f.py").write_text("x = 2\n")
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return PairCase(
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name="p",
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slice="vibe-py",
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language="python",
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origin="test",
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vuln_file=tmp_path / "v.py",
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fixed_file=tmp_path / "f.py",
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relpath="app.py",
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expected=(
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ExpectedFinding(
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cwe="CWE-639", vulnerability_class="x", path="app.py", evidence="", function="leaky", mechanism="other", family=family
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),
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),
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min_recall=1.0,
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fix_policy="silent",
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unscorable=unscorable,
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)
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def test_detection_needs_the_labeled_family_inside_the_labeled_function(tmp_path: Path) -> None:
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from openultrasast.learning.scoring import score_pair_family
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taxonomy = load_families()
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case = _case(tmp_path)
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hit = score_pair_family(case, "access_control", [[_finding("access_control", 12)]], [[]], ranges=RANGES, taxonomy=taxonomy)
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assert hit.outcome == "pair_correct" and hit.runs == ("pair_correct",)
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outside = score_pair_family(case, "access_control", [[_finding("access_control", 5)]], [[]], ranges=RANGES, taxonomy=taxonomy)
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assert outside.outcome == "both_silent" # the right family in the wrong function is not a detection
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other_file = score_pair_family(
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case, "access_control", [[_finding("access_control", 12, "other.py")]], [[]], ranges=RANGES, taxonomy=taxonomy
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)
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assert other_file.outcome == "both_silent"
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wrong_family = score_pair_family(case, "access_control", [[_finding("injection", 12)]], [[]], ranges=RANGES, taxonomy=taxonomy)
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assert wrong_family.outcome == "both_silent" and wrong_family.other_findings_vuln == 1
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def test_a_fabricated_family_never_counts_and_is_recorded(tmp_path: Path) -> None:
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from openultrasast.learning.scoring import score_pair_family
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taxonomy = load_families()
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score = score_pair_family(_case(tmp_path), "access_control", [[_finding("sql_injection", 12)]], [[]], ranges=RANGES, taxonomy=taxonomy)
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assert score.outcome == "both_silent" and score.fabricated_vuln == 1
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assert score.other_findings_vuln == 0 # a fabricated id is not another family, it is noise
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def test_silence_ignores_findings_of_other_families_and_never_calls_them_leaks(tmp_path: Path) -> None:
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from openultrasast.learning.scoring import score_pair_family
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taxonomy = load_families()
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case = _case(tmp_path)
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quiet = score_pair_family(
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case,
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"access_control",
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[[_finding("access_control", 12)]],
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[[_finding("injection", 12), _finding("access_control", 5)]],
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ranges=RANGES,
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taxonomy=taxonomy,
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)
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assert quiet.outcome == "pair_correct" and quiet.other_findings_fixed == 2
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leaked = score_pair_family(
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case, "access_control", [[_finding("access_control", 12)]], [[_finding("access_control", 13)]], ranges=RANGES, taxonomy=taxonomy
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)
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assert leaked.outcome == "both_flagged"
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reversed_pair = score_pair_family(case, "access_control", [[]], [[_finding("access_control", 12)]], ranges=RANGES, taxonomy=taxonomy)
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assert reversed_pair.outcome == "reversed"
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def test_the_outcome_of_several_runs_is_their_majority(tmp_path: Path) -> None:
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from openultrasast.learning.scoring import score_pair_family
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taxonomy = load_families()
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case = _case(tmp_path)
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hit = [_finding("access_control", 12)]
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score = score_pair_family(case, "access_control", [hit, [], hit], [[], [], []], ranges=RANGES, taxonomy=taxonomy)
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assert score.runs == ("pair_correct", "both_silent", "pair_correct") and score.outcome == "pair_correct"
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flaky = score_pair_family(case, "access_control", [hit, [], []], [[], [], []], ranges=RANGES, taxonomy=taxonomy)
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assert flaky.outcome == "both_silent" and flaky.flips == 1 # a run that disagrees with the majority is a flip
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def test_an_unscorable_pair_is_never_run_and_keeps_its_reason(tmp_path: Path) -> None:
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from openultrasast.learning.scoring import score_pair_family
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taxonomy = load_families()
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case = _case(tmp_path, unscorable="identical_twin")
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score = score_pair_family(case, "access_control", [[_finding("access_control", 12)]], [[]], ranges=RANGES, taxonomy=taxonomy)
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assert score.outcome == "unscorable" and score.unscorable_reason == "identical_twin" and score.runs == ()
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def test_a_pair_with_no_parsed_function_range_is_unscorable_not_a_miss(tmp_path: Path) -> None:
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from openultrasast.learning.scoring import score_pair_family
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taxonomy = load_families()
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score = score_pair_family(_case(tmp_path), "access_control", [[]], [[]], ranges={}, taxonomy=taxonomy)
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assert score.outcome == "unscorable" and score.unscorable_reason == "unresolved_label"
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def test_scoring_never_reads_the_text_of_a_finding(tmp_path: Path) -> None:
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from openultrasast.learning.scoring import score_pair_family
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taxonomy = load_families()
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shouting = _finding("injection", 12)
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loud = StaticFinding(**{**shouting.__dict__, "title": "CWE-639 broken object level authorization", "rationale": "IDOR in leaky"})
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score = score_pair_family(_case(tmp_path), "access_control", [[loud]], [[]], ranges=RANGES, taxonomy=taxonomy)
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assert score.outcome == "both_silent" # the words say access control; the family tag says injection, and only that counts
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def test_the_rung_is_the_best_verifier_outcome_among_the_detections(tmp_path: Path) -> None:
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from openultrasast.learning.scoring import score_pair_family
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taxonomy = load_families()
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corroborated = _finding("access_control", 12)
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corroborated.tags.append("verifier:static_corroboration")
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score = score_pair_family(_case(tmp_path), "access_control", [[corroborated]], [[]], ranges=RANGES, taxonomy=taxonomy)
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assert score.outcome == "pair_correct" and score.rung == "static_corroboration"
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plain = score_pair_family(_case(tmp_path), "access_control", [[_finding("access_control", 12)]], [[]], ranges=RANGES, taxonomy=taxonomy)
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assert plain.rung == "suspicion"
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