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Open_Ultra_SAST/src/openultrasast/ruleset/store.py
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from __future__ import annotations
import json
import tomllib
from collections.abc import Iterable
from dataclasses import dataclass, replace
from pathlib import Path
DEFAULT_RULESET_DIR = Path(__file__).parent
VALID_STATUS = ("enabled", "shadow", "disabled")
class RulesetError(ValueError):
"""Raised when a ruleset data file is malformed."""
@dataclass(frozen=True)
class PatternRule:
"""A detection rule expressed as governed data (no rule-local severity).
``pattern`` is human-PR-only; the self-improvement loop may only change
``status``/``min_evidence_level``/``precision_estimate`` via the ledger.
"""
rule_id: str
title: str
languages: tuple[str, ...]
cwe: str
tags: tuple[str, ...]
pattern: str
status: str = "enabled"
min_evidence_level: str = "static_corroboration"
precision_estimate: float = 0.0
version: str = "1"
def load_ruleset(directory: Path = DEFAULT_RULESET_DIR, ledger: Path | None = None) -> tuple[PatternRule, ...]:
"""Load every ``*.toml`` rule file under ``directory`` and apply the loop ledger.
Rules are returned sorted by ``rule_id`` for determinism. The optional ledger
(``rule_policy.json``) overlays loop-owned ``status``/``min_evidence_level``/
``precision_estimate`` per ``rule_id``.
"""
rules: dict[str, PatternRule] = {}
for path in sorted(directory.rglob("*.toml")):
payload = tomllib.loads(path.read_text())
for item in payload.get("rule", []):
rule = _rule_from_dict(item, path)
if rule.rule_id in rules:
raise RulesetError(f"duplicate rule_id {rule.rule_id!r} in {path}")
rules[rule.rule_id] = rule
overlay = _load_ledger(ledger)
resolved = [_apply_overlay(rule, overlay.get(rule.rule_id)) for rule in rules.values()]
return tuple(sorted(resolved, key=lambda rule: rule.rule_id))
def write_ruleset(path: Path, rules: Iterable[PatternRule]) -> None:
"""Write rules as TOML. Patterns use literal multi-line strings (no escaping)."""
path.parent.mkdir(parents=True, exist_ok=True)
blocks: list[str] = []
for rule in rules:
if "'''" in rule.pattern:
raise RulesetError(f"rule {rule.rule_id} pattern cannot contain a triple single-quote")
blocks.append(
"\n".join(
[
"[[rule]]",
f"rule_id = {_s(rule.rule_id)}",
f"title = {_s(rule.title)}",
f"languages = {_arr(rule.languages)}",
f"cwe = {_s(rule.cwe)}",
f"tags = {_arr(rule.tags)}",
f"status = {_s(rule.status)}",
f"min_evidence_level = {_s(rule.min_evidence_level)}",
f"precision_estimate = {float(rule.precision_estimate)}",
f"version = {_s(rule.version)}",
f"pattern = '''{rule.pattern}'''",
]
)
)
path.write_text("\n\n".join(blocks) + "\n")
def _rule_from_dict(item: dict[str, object], path: Path) -> PatternRule:
try:
rule_id = str(item["rule_id"])
cwe = str(item["cwe"])
pattern = str(item["pattern"])
except KeyError as exc:
raise RulesetError(f"rule in {path} missing required field {exc}") from exc
status = str(item.get("status", "enabled"))
if status not in VALID_STATUS:
raise RulesetError(f"rule {rule_id} has invalid status {status!r}")
if not pattern:
raise RulesetError(f"rule {rule_id} has an empty pattern")
return PatternRule(
rule_id=rule_id,
title=str(item.get("title", rule_id)),
languages=_str_tuple(item.get("languages")),
cwe=cwe,
tags=_str_tuple(item.get("tags")),
pattern=pattern,
status=status,
min_evidence_level=str(item.get("min_evidence_level", "static_corroboration")),
precision_estimate=float(item.get("precision_estimate", 0.0)), # type: ignore[arg-type]
version=str(item.get("version", "1")),
)
def _load_ledger(ledger: Path | None) -> dict[str, dict[str, object]]:
if ledger is None or not ledger.exists():
return {}
payload = json.loads(ledger.read_text())
return {str(key): value for key, value in payload.items() if isinstance(value, dict)}
def _apply_overlay(rule: PatternRule, overlay: dict[str, object] | None) -> PatternRule:
if not overlay:
return rule
status = str(overlay.get("status", rule.status))
if status not in VALID_STATUS:
status = rule.status
return replace(
rule,
status=status,
min_evidence_level=str(overlay.get("min_evidence_level", rule.min_evidence_level)),
precision_estimate=float(overlay.get("precision_estimate", rule.precision_estimate)), # type: ignore[arg-type]
)
def _str_tuple(value: object) -> tuple[str, ...]:
if isinstance(value, list):
return tuple(str(item) for item in value)
return ()
def _s(value: str) -> str:
return '"' + value.replace("\\", "\\\\").replace('"', '\\"') + '"'
def _arr(values: tuple[str, ...]) -> str:
return "[" + ", ".join(_s(value) for value in values) + "]"