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import logging
from typing import Any
from core.plugin_system import PluginContext, PluginInterface, PluginMetadata
logger = logging.getLogger(__name__)
class EvidenceAnalysisPlugin(PluginInterface):
"""
Analyzes case evidence for suspicious keywords and metadata anomalies.
"""
@property
def metadata(self) -> PluginMetadata:
return PluginMetadata(
name="evidence_analysis",
version="1.0.0",
namespace="zenith/intelligence/evidence_analysis",
author="Zenith Team",
description="Analyzes evidence metadata and content for fraud indicators",
dependencies={},
capabilities=["intelligence", "case_analysis"],
security_level="official",
api_version="v1",
)
async def initialize(self, context: PluginContext) -> bool:
self.context = context
return True
async def execute(self, inputs: dict[str, Any]) -> dict[str, Any]:
"""
Expects {"case_data": {...}}
"""
case_data = inputs.get("case_data")
if not case_data:
return {"error": "No case data provided"}
return await self._analyze_evidence(case_data)
async def _analyze_evidence(self, case_data: dict[str, Any]) -> dict[str, Any]:
"""Analyze evidence for fraud indicators"""
insights = []
recommendations = []
confidence = 0.0
evidence = case_data.get("evidence", [])
for item in evidence:
content = item.get("content", "").lower()
filename = item.get("filename", "").lower()
# Check for suspicious keywords
fraud_keywords = [
"offshore",
"cayman",
"shell company",
"wire transfer",
"cash equivalent",
"round number",
"just below",
]
found_keywords = [kw for kw in fraud_keywords if kw in content]
if found_keywords:
insights.append(
f"Evidence '{filename}' contains suspicious keywords: {', '.join(found_keywords)}"
)
recommendations.append(
f"Review evidence '{filename}' for fraud indicators"
)
confidence += 0.3
# Check file metadata
metadata = item.get("metadata", {})
if metadata.get("modified_date") and metadata.get("created_date"):
# Check for backdating
metadata["created_date"]
metadata["modified_date"]
# Logic simplified for plugin example
return {
"insights": insights,
"recommendations": recommendations,
"confidence": min(confidence, 1.0),
"risk_score": 0, # Evidence alone rarely sets distinct risk score unless critical
}
async def cleanup(self) -> None:
pass
def validate_config(self, config: dict[str, Any]) -> list[str]:
return []