Files
Open_Ultra_SAST/tests/test_learning_proposer.py
T

140 lines
6.3 KiB
Python
Raw Normal View History

"""learning-harness task 3.5: failure facts, the scripted proposer and the HarnessX proposer (offline)."""
from __future__ import annotations
import json
from pathlib import Path
import pytest
from openultrasast.learning.detectors import FamilyConfig
from openultrasast.learning.journal import LearningJournal, RoundRecord
from openultrasast.learning.scoring import PairFamilyScore
def _config(family: str = "access_control") -> FamilyConfig:
return FamilyConfig(
family=family,
version="0",
prompt="You hunt access control.",
checklist="- did the handler check ownership?",
tools=("read_definition", "obligations"),
max_steps=3,
max_cost_usd=0.5,
max_chars=4000,
)
def _score(pair: str, outcome: str, *, family: str = "access_control") -> PairFamilyScore:
return PairFamilyScore(pair=pair, family=family, runs=(outcome,), outcome=outcome, slice="vibe-py") # type: ignore[arg-type]
def test_failure_facts_carry_the_misses_the_leaks_and_the_rejected_buffer(tmp_path: Path) -> None:
from openultrasast.learning.proposer import build_failure_facts
journal = LearningJournal(tmp_path / "journal.jsonl")
journal.append(
RoundRecord(
round=1,
family="access_control",
hypothesis="ask about ownership",
levers=("checklist",),
predicted_affected=("access_control",),
predicted_at_risk=(),
outcome="rejected",
reason="tie",
)
)
scores = [_score("miss-one", "both_silent"), _score("leak-one", "both_flagged"), _score("good", "pair_correct")]
facts = build_failure_facts(
scores, family="access_control", config=_config(), journal=journal, train_pairs={"miss-one", "leak-one", "good"}
)
assert [item.pair for item in facts.misses] == ["miss-one"]
assert [item.pair for item in facts.leaks] == ["leak-one"]
assert facts.rejected == ("ask about ownership",)
assert facts.config.family == "access_control" and facts.family == "access_control"
def test_the_proposer_is_never_handed_a_holdout_pair(tmp_path: Path) -> None:
from openultrasast.learning.proposer import build_failure_facts
journal = LearningJournal(tmp_path / "journal.jsonl")
scores = [_score("train-miss", "both_silent"), _score("holdout-miss", "both_silent")]
facts = build_failure_facts(scores, family="access_control", config=_config(), journal=journal, train_pairs={"train-miss"})
assert [item.pair for item in facts.misses] == ["train-miss"]
assert "holdout-miss" not in json.dumps(facts.to_dict())
def test_the_scripted_proposer_returns_one_change_for_one_family(tmp_path: Path) -> None:
from openultrasast.learning.proposer import Proposal, ScriptedProposer, build_failure_facts
journal = LearningJournal(tmp_path / "journal.jsonl")
facts = build_failure_facts([_score("a", "both_silent")], family="access_control", config=_config(), journal=journal, train_pairs={"a"})
scripted = ScriptedProposer(
[
Proposal(
hypothesis="h",
lever="checklist",
change={"checklist.md": "- ask about ownership\n"},
predicted_affected=("access_control",),
)
]
)
proposal = scripted.propose(facts)
assert proposal is not None and proposal.lever == "checklist" and set(proposal.change) == {"checklist.md"}
assert scripted.propose(facts) is None # a scripted proposer runs out rather than repeating itself
@pytest.mark.parametrize(
("change", "lever", "needle"),
[
({"../../etc/passwd": "x"}, "checklist", "outside"),
({"family.toml": "x", "prompt.md": "y"}, "prompt", "one file"),
({"secrets.md": "x"}, "checklist", "secrets.md"),
({"prompt.md": "x" * 9000}, "prompt", "cap"),
],
ids=["escapes_the_family_directory", "two_files", "unknown_file", "over_the_cap"],
)
def test_a_proposal_that_reaches_beyond_its_family_is_refused_by_name(change: dict[str, str], lever: str, needle: str) -> None:
from openultrasast.learning.proposer import Proposal, refuse_proposal
refusal = refuse_proposal(Proposal(hypothesis="h", lever=lever, change=change), _config()) # type: ignore[arg-type]
assert refusal is not None and needle in refusal
def test_a_well_formed_proposal_is_accepted_and_applies_inside_its_own_directory(tmp_path: Path) -> None:
from openultrasast.learning.proposer import Proposal, apply_proposal, refuse_proposal
directory = tmp_path / "access_control"
directory.mkdir()
(directory / "checklist.md").write_text("- old\n")
proposal = Proposal(hypothesis="h", lever="checklist", change={"checklist.md": "- new\n"}, predicted_affected=("access_control",))
assert refuse_proposal(proposal, _config()) is None
apply_proposal(proposal, directory)
assert (directory / "checklist.md").read_text() == "- new\n"
def test_the_write_roots_are_one_family_directory_and_exclude_the_checker_and_the_corpus(tmp_path: Path) -> None:
from openultrasast.learning import canaries
from openultrasast.learning.proposer import write_roots
roots = write_roots(tmp_path / "configs", "access_control")
assert roots == (tmp_path / "configs" / "access_control",)
verifier_module = Path(canaries.__file__).resolve()
assert not any(verifier_module.is_relative_to(root.resolve()) for root in roots)
corpus = Path("benchmarks").resolve()
assert not any(str(corpus).startswith(str(root.resolve())) for root in roots)
def test_the_harnessx_proposer_degrades_with_a_reason_when_the_extra_is_absent(tmp_path: Path, monkeypatch: pytest.MonkeyPatch) -> None:
from openultrasast.learning import proposer as proposer_module
from openultrasast.learning.proposer import HarnessXProposer, build_failure_facts
journal = LearningJournal(tmp_path / "journal.jsonl")
facts = build_failure_facts([_score("a", "both_silent")], family="access_control", config=_config(), journal=journal, train_pairs={"a"})
monkeypatch.setattr(proposer_module, "has_harnessx", lambda: False)
agent = HarnessXProposer(configs_dir=tmp_path / "configs", model="m")
assert agent.propose(facts) is None
assert agent.reason == "harnessx_unavailable"
assert agent.write_roots("access_control") == (tmp_path / "configs" / "access_control",)