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Open_Ultra_SAST/src/openultrasast/regress/candidate.py
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"""Candidate selection and safety-gated regression execution."""
from __future__ import annotations
import json
from collections.abc import Callable, Mapping, Sequence
from dataclasses import asdict, dataclass, replace
from pathlib import Path
from ..complexity.ledger import hotspot_key, select_forced_candidates
from ..complexity.map import Hotspot
from ..config import SandboxConfig
from ..findings import StaticFinding
from ..preprocess import LANGUAGE_BY_EXTENSION
from ..sandbox import SandboxJob, SandboxResult, SandboxRunner
from ..sandbox.runner import WORKSPACE_MOUNT
from .recipes import recipe_for
from .safety import UnsafeSnippetError, check_snippet_safety
from .verdict import (
INCONCLUSIVE,
MISSING_RECIPE,
NOT_TRIGGERABLE,
SAFETY_REJECTED,
TRIGGERABLE,
RegressionVerdict,
is_worth_fixing,
verdict_from_result,
)
DEFAULT_IMAGES = {
"python": "python:3.12-alpine",
"javascript": "node:22-alpine",
"c": "gcc:13",
}
__all__ = [
"INCONCLUSIVE",
"MISSING_RECIPE",
"NOT_TRIGGERABLE",
"SAFETY_REJECTED",
"TRIGGERABLE",
"CandidateVerdict",
"RegressionRunner",
"RegressionVerdict",
"run_regression",
"select_candidates",
"snippet_for",
"write_verdicts",
]
@dataclass(frozen=True)
class CandidateVerdict:
path: str
function_name: str | None
language: str
verdict: str
reason: str
inventory_finding_ids: tuple[str, ...]
worth_fixing: bool = False
def select_candidates(
hotspots: Sequence[Hotspot],
findings: Sequence[StaticFinding],
*,
max_candidates: int,
policy_severity_by_id: Mapping[str, object] | None = None,
rule_cwe: Mapping[str, str] | None = None,
) -> tuple[Hotspot, ...]:
"""Select min(max_candidates, ranked hotspots) ∪ sev-5 reachable inventory.
The cap applies to the ranked hotspot slice. Forced policy-severity-5
reachable (or inferred-file-surface) inventory stays in the set even when a
ledger overlay demoted its hotspot out of that slice.
"""
ranked = tuple(sorted(hotspots, key=lambda item: (-item.score, item.path, item.function_name or "")))
selected = list(ranked[: max(max_candidates, 0)])
seen = {hotspot_key(item.path, item.function_name) for item in selected}
extras: list[Hotspot] = []
for finding in select_forced_candidates(findings, policy_severity_by_id or {}, rule_cwe=rule_cwe):
hotspot = _hotspot_for_finding(finding, ranked) or _hotspot_from_forced_finding(finding)
key = hotspot_key(hotspot.path, hotspot.function_name)
if key in seen:
continue
seen.add(key)
extras.append(hotspot)
return tuple(selected + extras)
def _hotspot_for_finding(finding: StaticFinding, hotspots: Sequence[Hotspot]) -> Hotspot | None:
for hotspot in hotspots:
if finding.finding_id in hotspot.inventory_finding_ids:
return hotspot
key = hotspot_key(finding.path, finding.function_name)
for hotspot in hotspots:
if hotspot_key(hotspot.path, hotspot.function_name) == key:
return hotspot
return None
def hotspot_from_finding(finding: StaticFinding, *, rationale: str) -> Hotspot:
"""A zero-score hotspot wrapping one finding: forced sev-5 inventory or a variant of a known mechanism."""
return Hotspot(
path=finding.path,
function_name=finding.function_name,
score=0.0,
band="low",
signals={},
rationale=rationale,
test_hint=None,
inventory_finding_ids=(finding.finding_id,),
)
def _hotspot_from_forced_finding(finding: StaticFinding) -> Hotspot:
return hotspot_from_finding(finding, rationale="forced reachable severity-5 inventory")
class RegressionRunner:
"""Run a snippet in the sandbox only after the structural safety check passes."""
def __init__(self, sandbox: SandboxRunner) -> None:
self._sandbox = sandbox
def run_recipe(
self,
language: str,
snippet: str,
image: str,
sandbox_limits: SandboxConfig,
*,
repo_root: Path,
oracle: Callable[[SandboxResult], bool] | None = None,
) -> RegressionVerdict:
job = recipe_for(language, snippet, image, sandbox_limits, repo_root=repo_root)
if job is None:
return verdict_from_result(recipe_missing=True)
return self.run_snippet(snippet, job, oracle=oracle)
def run_snippet(
self, snippet: str, job: SandboxJob | None, *, oracle: Callable[[SandboxResult], bool] | None = None
) -> RegressionVerdict:
if job is None:
return verdict_from_result(recipe_missing=True)
try:
check_snippet_safety(snippet)
except UnsafeSnippetError:
return verdict_from_result(safety_rejected=True)
return verdict_from_result(self._sandbox.run(job), oracle=oracle)
def snippet_for(language: str, path: str, function_name: str | None) -> str:
"""Render a scratch snippet that loads the candidate source inside the sandbox."""
relative = path.replace("\\", "/")
workspace_path = f"{WORKSPACE_MOUNT}/{relative}"
identity = function_name or relative
if language == "python":
return (
f"# candidate {identity}\n"
"from pathlib import Path\n"
f"source = Path({workspace_path!r}).read_text()\n"
f"compile(source, {relative!r}, 'exec')\n"
)
if language == "javascript":
return (
f"// candidate {identity}\n"
"const fs = require('fs');\n"
f"const source = fs.readFileSync({workspace_path!r}, 'utf8');\n"
"if (!source.length) { process.exit(1); }\n"
)
if language == "c":
return f"/* candidate {identity} */\nint main(void) {{ return 0; }}\n"
return ""
def run_regression(
hotspots: Sequence[Hotspot],
findings: Sequence[StaticFinding],
*,
max_candidates: int,
policy: Mapping[str, object],
rule_cwe: Mapping[str, str],
languages_by_path: Mapping[str, str],
repo_root: Path,
sandbox: SandboxRunner,
sandbox_limits: SandboxConfig,
images: Mapping[str, str],
) -> tuple[CandidateVerdict, ...]:
"""Select candidates under the cap, run recipes in the sandbox, and return verdicts."""
selected = select_candidates(
hotspots,
findings,
max_candidates=max_candidates,
policy_severity_by_id=policy,
rule_cwe=rule_cwe,
)
runner = RegressionRunner(sandbox)
findings_by_id = {finding.finding_id: finding for finding in findings}
records: list[CandidateVerdict] = []
for hotspot in selected:
language = _language_for(hotspot.path, languages_by_path)
snippet = _proposed_snippet(hotspot, findings) or snippet_for(language, hotspot.path, hotspot.function_name)
image = images.get(language) or DEFAULT_IMAGES.get(language, "ousast-missing-image")
mapped = runner.run_recipe(language, snippet, image, sandbox_limits, repo_root=repo_root)
reachability = _reachability_for(hotspot, findings_by_id)
mapped = replace(mapped, worth_fixing=is_worth_fixing(mapped.verdict, reachability))
records.append(
CandidateVerdict(
path=hotspot.path,
function_name=hotspot.function_name,
language=language,
verdict=mapped.verdict,
reason=mapped.reason,
inventory_finding_ids=hotspot.inventory_finding_ids,
worth_fixing=mapped.worth_fixing,
)
)
return tuple(records)
def write_verdicts(verdicts: Sequence[CandidateVerdict], path: Path) -> None:
path.parent.mkdir(parents=True, exist_ok=True)
payload = {"verdicts": [asdict(item) for item in verdicts]}
path.write_text(json.dumps(payload, indent=2, sort_keys=True) + "\n")
def _proposed_snippet(hotspot: Hotspot, findings: Sequence[StaticFinding]) -> str | None:
for finding in findings:
snippet = finding.proposed_snippet
if not snippet:
continue
if finding.path == hotspot.path or finding.finding_id in hotspot.inventory_finding_ids:
return snippet
return None
def _language_for(path: str, languages_by_path: Mapping[str, str]) -> str:
if path in languages_by_path:
return languages_by_path[path]
return LANGUAGE_BY_EXTENSION.get(Path(path).suffix.lower(), "unknown")
def _reachability_for(hotspot: Hotspot, findings_by_id: Mapping[str, StaticFinding]) -> str:
statuses = [
findings_by_id[finding_id].reachability_status for finding_id in hotspot.inventory_finding_ids if finding_id in findings_by_id
]
for status in statuses:
if is_worth_fixing(TRIGGERABLE, status):
return status
return statuses[0] if statuses else "unknown"