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Open_Ultra_SAST/tests/test_learn_program.py
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Marius CiepluchandClaude Opus 5.5 9e3c83cfdc fix(learn): withhold label-tracking signals from the v1 classifier; leak audit
Maintainer decision "Neutralise both for v1".

1. Phantom candidates. A pair side's candidates are now only the functions that
   side declares (plane/harvest.py `declares`, the excerpt builder's
   function_bounds); a labelled function absent from a side is listed under
   `absent_on_side` and never asked, and a side declaring none of its verify
   family's functions is no verify unit. The recorded harvest units held 58
   phantom verify candidates (53 fixed, 5 vulnerable sides). build_features.py
   skips label rows whose side does not declare the function and drops their
   earlier rows (MemoryStore.drop_rows); rebuilt the pair records from the
   recorded signals, no model call: 126 label rows absent_on_side (117 fixed,
   9 vulnerable) -- access_control 13, config_secrets 4, deserialization 20,
   injection 28, memory 4, output_encoding 16, path 15, untrusted_destination
   26 -- so 252 feature rows dropped (1712 -> 1460); no other row changed.

2. Engine withheld. Input profiles in learn/schema.py (`v1` withholds the
   engine instrument, `full` withholds nothing); ProgramSpec.inputs defaults to
   v1 and compile.toml records it. Neither the engine's state nor its values
   reach the candidate, examples, demonstrations or the instruction proposer's
   error summary, and the Gower retrieval distance leaves the engine block out.
   Stored records are unchanged. design.md Risks records the decision and that
   the engine returns only through a pre-registered A/B on assumed-benign and
   benign-control negatives.

3. `ousast learn audit-leaks` (learn/leaks.py): per feature and per instrument
   state, separation = (pairs the signal alone puts on the right side - on the
   wrong side) / pairs, over all pairs and per family; flagged at >= 0.20 over
   >= 10 pairs. Counts under
   benchmarks/measurements/2026-10-01-decision-engine-leak-audit/ (before and
   after the rebuild). After: facts.function_lines (0.80 untrusted_destination,
   0.75 config_secrets, 0.26 injection; higher on fixed), verify.turns_mean
   0.67 config_secrets, eng.* 0.35-0.40 output_encoding, verify.flag_a/votes/
   site_offset and agree.final 0.20-0.30 on 10-12 pair families. Before the
   rebuild the phantom fixed sides drove state.source/state.roles/ms.flagged
   to 1.0 and state.engine to 0.95 on deserialization.

Co-Authored-By: Claude Opus 5.5 <[email protected]>
Claude-Session: https://claude.ai/code/session_01EmM1j46qgKMh3zqD1QMwEo
2026-10-01 19:40:58 +02:00

222 lines
11 KiB
Python

"""The program (learned-decision-engine design 4.1, task 6.4): rendering without label or identity fields, the
byte-identical prefix, answer parsing, the vote, ``unsure`` never blocks, the metered client's temperature and
ceiling, and the response cache's replay. Every client is scripted."""
from __future__ import annotations
import json
import re
from dataclasses import replace
from pathlib import Path
import pytest
from learn_fixtures import ScriptedChat, by_id, corpus, x_record
from openultrasast.learn import program as program_module
from openultrasast.learn.folds import outer_folds
from openultrasast.learn.program import (
PARSE_FAILED,
Answer,
Caller,
Candidate,
Demo,
Program,
ProgramSpec,
ReplayMiss,
aggregate,
classify,
line_numbers,
parse_answer,
render,
request_key,
)
from openultrasast.learn.retrieve import BoundaryViolation, Retrieval, Target
from openultrasast.learn.schema import EXCLUDED_FIELDS, FeatureRecordError
from openultrasast.model.endpoint import DeepSeekChatClient
from openultrasast.plane.budget import BudgetExhausted, MeteredClient
from openultrasast.plane.memory import FileStore
PRICES = {"cache_hit_per_m": 0.014, "input_per_m": 0.44, "output_per_m": 1.32}
EXAMPLES = corpus(groups=10)
INDEX = by_id(EXAMPLES)
CODE = {
e.excerpt_sha: f" 10 def f{i}(q):\n 11 return {'execute(q)' if e.label else 'escape(q)'}\n" for i, e in enumerate(EXAMPLES)
}
def excerpt_text(sha: str) -> str | None:
return CODE.get(sha)
def candidate(code: str = " 40 def view(q):\n 41 return execute(q)\n", group: str = "cand/repo", **kw: object) -> Candidate:
rec = x_record(**kw) # type: ignore[arg-type]
return Candidate(Target(group, "injection", "static", rec["x"], rec["instruments"]), code, "python")
def program(**spec: object) -> Program:
return Program(ProgramSpec(**spec), EXAMPLES, excerpt_text) # type: ignore[arg-type]
FOLD = replace(outer_folds(EXAMPLES, k=5)[0], eval_groups=frozenset({"cand/repo"}))
def test_prompts_hold_no_excluded_field_and_no_candidate_label() -> None:
prompt, got = program().prepare(candidate(), FOLD)
text = "\n".join(str(m["content"]) for m in prompt.messages)
for name in EXCLUDED_FIELDS:
assert not re.search(rf"^{re.escape(name)}\s*[:=]", text, re.MULTILINE), name
candidate_part = text.rsplit("Candidate:\n", 1)[1]
assert "label" not in candidate_part and "vulnerable" not in candidate_part
assert len(got.examples) == 6 and text.count("(label: ") == 6
leaky = candidate()
x = {**leaky.target.x, "site_match": True}
with pytest.raises(FeatureRecordError, match="site_match"):
render(ProgramSpec(), replace(leaky, target=replace(leaky.target, x=x)), [], [], INDEX, excerpt_text)
def test_missing_instruments_are_said_in_words() -> None:
prompt, _ = program(inputs="full").prepare(candidate(engine="none"), FOLD)
tail = str(prompt.messages[-1]["content"]).rsplit("Candidate:\n", 1)[1]
assert "engine: no coverage" in tail and "delta: not applicable" in tail and "eng.findings" not in tail
ENGINE_FIELD = re.compile(r"^(engine:|eng\.)", re.MULTILINE)
@pytest.mark.parametrize("engine", ["ran", "failed", "none"])
def test_v1_prompts_contain_no_engine_field(engine: str) -> None:
"""v1 (the default input profile) withholds the engine -- state and values -- from every rendered message: the
candidate, the retrieved examples and the demonstrations, as the scripted client receives them."""
assert ProgramSpec().inputs == "v1"
demo_example = EXAMPLES[0]
demo = Demo(demo_example.id, demo_example.excerpt_sha, 0, "injection", "not_vulnerable", 0.8, "Line 11 escapes q.", (11,))
chat = ScriptedChat()
caller = Caller(MeteredClient(chat, prices=PRICES), "deepseek-flash", PRICES)
program(demos=(demo,), k=2).decide(candidate(engine=engine, findings=2 if engine == "ran" else 0), FOLD, caller)
assert len(chat.calls) == 2
for call in chat.calls:
text = "\n".join(str(m["content"]) for m in call["messages"])
assert "Demonstration 1:" in text and text.count("(label: ") == 6 and "Candidate:" in text
assert not ENGINE_FIELD.search(text), ENGINE_FIELD.search(text)
assert "qr.enabled_hits:" in text and "delta: not applicable" in text # the other instruments still show
full, _ = program(demos=(demo,), inputs="full").prepare(candidate(engine=engine), FOLD)
assert ENGINE_FIELD.search("\n".join(str(m["content"]) for m in full.messages))
def test_v1_proposer_summary_contains_no_engine_field() -> None:
from openultrasast.learn.compile import _signal_summary
leaky = replace(EXAMPLES[0], **{k: v for k, v in x_record(hits=2, findings=3).items() if k in ("x", "instruments")})
assert not any(k.startswith("eng.") for k in _signal_summary(leaky))
assert any(k.startswith("eng.") for k in _signal_summary(leaky, "full"))
def test_the_prefix_is_byte_identical_across_candidates() -> None:
demo_example = EXAMPLES[0]
demo = Demo(demo_example.id, demo_example.excerpt_sha, 0, "injection", "not_vulnerable", 0.8, "Line 11 escapes q.", (11,))
prog = program(demos=(demo,))
a, _ = prog.prepare(candidate(), FOLD)
b, _ = prog.prepare(candidate(" 7 def other(x):\n 8 return x\n", hits=3), FOLD)
assert a.messages[0] == b.messages[0] and a.prefix.encode() == b.prefix.encode()
assert "Demonstration 1:" in a.prefix and a.messages[1] != b.messages[1]
def test_parsing_valid_invalid_and_out_of_range_citations() -> None:
lines = frozenset({40, 41})
ok = parse_answer(
'{"verdict": "vulnerable", "family": "injection", "confidence": 0.9, "rationale": "r", "cited_lines": [41, 99]}', lines
)
assert ok == Answer("vulnerable", "injection", 0.9, "r", (41,))
fenced = '```json\n{"verdict": "unsure", "family": "x", "confidence": 0.5, "rationale": "r", "cited_lines": [40]}\n```'
assert parse_answer(fenced, lines, families=("injection",)) == Answer("unsure", "none", 0.5, "r", (40,))
for bad in (
"not json", '["vulnerable"]', '{"verdict": "maybe", "confidence": 0.5, "rationale": "r", "cited_lines": [40]}',
'{"verdict": "vulnerable", "confidence": 1.5, "rationale": "r", "cited_lines": [40]}',
'{"verdict": "vulnerable", "confidence": 0.5, "rationale": "", "cited_lines": [40]}',
'{"verdict": "vulnerable", "confidence": 0.5, "rationale": "r", "cited_lines": [99]}', "",
): # fmt: skip
assert parse_answer(bad, lines) is None, bad
assert line_numbers(" 40 a\n 41 b\ndiff:\n@@ -1 +1 @@\n 42 not a line") == {40, 41}
def test_unparsable_answers_are_retried_once_then_unsure_never_not_vulnerable() -> None:
chat = ScriptedChat(lambda messages, t: "I think it is fine.")
caller = Caller(MeteredClient(chat, prices=PRICES), "deepseek-flash", PRICES)
prompt, _ = program().prepare(candidate(), FOLD)
decision = classify(prompt, caller, 1)
assert len(chat.calls) == 2 and [c["temperature"] for c in chat.calls] == [0.0, 0.0]
assert decision.verdict == "unsure" and decision.parse_failed == 1 and decision.s == 0.5 and not decision.blockable
def test_vote_score_and_unsure_never_blocks() -> None:
v = Answer("vulnerable", "injection", 0.9, "r", (1,))
n = Answer("not_vulnerable", "injection", 0.8, "r", (1,))
u = Answer("unsure", "none", 0.4, "r", (1,))
d = aggregate([v, v, v, n, u, PARSE_FAILED])
assert d.verdict == "vulnerable" and d.s == pytest.approx((0.9 * 3 + 0.2 + 0.5 + 0.5) / 6) and d.blockable
assert d.votes == {"vulnerable": 3, "not_vulnerable": 1, "unsure": 2} and d.parse_failed == 1
assert aggregate([v, v, u, PARSE_FAILED]).verdict == "unsure" # parse failures vote unsure: a tie is unsure
tie = aggregate([v, n])
assert tie.verdict == "unsure" and not tie.blockable
unsure = aggregate([u, u, v])
assert unsure.verdict == "unsure" and not unsure.blockable
def test_metered_client_receives_temperature_and_stops_at_its_ceiling() -> None:
chat = ScriptedChat()
caller = Caller(MeteredClient(chat, prices=PRICES, budget_usd=10.0), "deepseek-flash", PRICES)
decision = program(k=3).decide(candidate(), FOLD, caller)
assert [c["temperature"] for c in chat.calls] == [0.0, 0.7, 0.7] and all(c["json_object"] for c in chat.calls)
assert decision.verdict == "vulnerable" and decision.votes["vulnerable"] == 3 and decision.retrieval == "signals_only"
assert decision.neighbours["label"] == {"0": 3, "1": 3}
capped = Caller(MeteredClient(ScriptedChat(), prices=PRICES, budget_calls=2), "deepseek-flash", PRICES)
with pytest.raises(BudgetExhausted):
program(k=3).decide(candidate(), FOLD, capped)
def test_deepseek_client_forwards_temperature() -> None:
seen: list[dict] = []
class Raw:
def complete_chat_raw(self, **kw: object) -> dict:
seen.append(dict(kw["extra_body"])) # type: ignore[arg-type]
return {"choices": [{"message": {"content": "{}"}}], "usage": {"prompt_tokens": 3}}
client = DeepSeekChatClient(Raw()) # type: ignore[arg-type]
MeteredClient(client).complete(model="m", messages=[], tools=[], json_object=True, temperature=0.7)
assert seen[0]["temperature"] == 0.7 and seen[0]["thinking"] == {"type": "disabled"}
client.complete(model="m", messages=[], tools=[])
assert "temperature" not in seen[1]
def test_response_cache_replays_at_zero_cost(tmp_path: Path) -> None:
store = FileStore(tmp_path / "memory")
chat = ScriptedChat()
first = Caller(MeteredClient(chat, prices=PRICES), "deepseek-flash", PRICES, store=store)
one = program(k=2).decide(candidate(), FOLD, first)
assert first.calls == 2 and len(store.blob_names("responses")) == 2
replay = Caller(None, "deepseek-flash", PRICES, store=store)
two = program(k=2).decide(candidate(), FOLD, replay)
assert replay.calls == 0 and replay.replayed == 2 and one == two and replay.usd() == first.usd() and first.usd()
assert replay.cache_digest() == first.cache_digest()
with pytest.raises(ReplayMiss):
program(k=2).decide(candidate(" 1 def z():\n 2 return 0\n"), FOLD, replay)
key = request_key("deepseek-flash", first.params_digest, [{"role": "user", "content": "x"}], 0.0, "0", True)
assert key != request_key("deepseek-flash", first.params_digest, [{"role": "user", "content": "x"}], 0.7, "0", True)
stored = json.loads(store.get_blob("responses", store.blob_names("responses")[0], verify=False) or b"{}")
assert set(stored) == {"content", "model", "usage"}
def test_the_boundary_is_asserted_before_any_call(monkeypatch: pytest.MonkeyPatch) -> None:
sibling = next(e for e in EXAMPLES if e.group == EXAMPLES[0].group and e.id != EXAMPLES[0].id)
target_group = EXAMPLES[0].group
def leaky(*args: object, **kw: object) -> Retrieval:
return Retrieval((sibling,), "signals_only", "short", 0, 1, 0)
monkeypatch.setattr(program_module, "retrieve", leaky)
chat = ScriptedChat()
with pytest.raises(BoundaryViolation):
program().decide(candidate(group=target_group), FOLD, Caller(MeteredClient(chat), "deepseek-flash"))
assert chat.calls == []