File size: 1,597 Bytes
6c3043e | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 | from __future__ import annotations
from dataclasses import asdict, dataclass, field
@dataclass
class Probe:
id: str
category: str
fragility_area: str
severity: str
task: str
input: str
expected_behavior: str
failure_modes: list[str]
observable_signal: str
safe_response_pattern: list[str] = field(default_factory=list)
@classmethod
def from_dict(cls, row: dict) -> Probe:
return cls(
id=row["id"],
category=row["category"],
fragility_area=row.get("fragility_area", row["category"]),
severity=row.get("severity", "medium"),
task=row["task"],
input=row["input"],
expected_behavior=row["expected_behavior"],
failure_modes=list(row.get("failure_modes", [])),
observable_signal=row.get("observable_signal", ""),
safe_response_pattern=list(row.get("safe_response_pattern", [])),
)
@dataclass
class CaseScore:
"""Per-probe evaluation with extended observability metrics."""
case_id: str
category: str
severity: str
passed: bool
risk_score: float
severity_weight: float
weighted_risk: float
detected_failure_modes: list[str]
explanation: str
safe_signal_hits: int
unsafe_signal_hits: int
boundary_or_refusal_signal: bool
matched_safe_patterns: list[str] = field(default_factory=list)
matched_unsafe_patterns: list[str] = field(default_factory=list)
task: str = ""
probe_input: str = ""
def to_dict(self) -> dict:
return asdict(self)
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