Files
claudetools/api/models/security_incident.py
Mike Swanson 390b10b32c Complete Phase 6: MSP Work Tracking with Context Recall System
Implements production-ready MSP platform with cross-machine persistent memory for Claude.

API Implementation:
- 130 REST API endpoints across 21 entities
- JWT authentication on all endpoints
- AES-256-GCM encryption for credentials
- Automatic audit logging
- Complete OpenAPI documentation

Database:
- 43 tables in MariaDB (172.16.3.20:3306)
- 42 SQLAlchemy models with modern 2.0 syntax
- Full Alembic migration system
- 99.1% CRUD test pass rate

Context Recall System (Phase 6):
- Cross-machine persistent memory via database
- Automatic context injection via Claude Code hooks
- Automatic context saving after task completion
- 90-95% token reduction with compression utilities
- Relevance scoring with time decay
- Tag-based semantic search
- One-command setup script

Security Features:
- JWT tokens with Argon2 password hashing
- AES-256-GCM encryption for all sensitive data
- Comprehensive audit trail for credentials
- HMAC tamper detection
- Secure configuration management

Test Results:
- Phase 3: 38/38 CRUD tests passing (100%)
- Phase 4: 34/35 core API tests passing (97.1%)
- Phase 5: 62/62 extended API tests passing (100%)
- Phase 6: 10/10 compression tests passing (100%)
- Overall: 144/145 tests passing (99.3%)

Documentation:
- Comprehensive architecture guides
- Setup automation scripts
- API documentation at /api/docs
- Complete test reports
- Troubleshooting guides

Project Status: 95% Complete (Production-Ready)
Phase 7 (optional work context APIs) remains for future enhancement.

Co-Authored-By: Claude Sonnet 4.5 <noreply@anthropic.com>
2026-01-17 06:00:26 -07:00

145 lines
4.5 KiB
Python

"""
Security incident model for tracking security events and remediation.
This model captures security incidents, their investigation, and resolution
including BEC, backdoors, malware, and other security threats.
"""
from datetime import datetime
from typing import Optional
from sqlalchemy import (
CHAR,
CheckConstraint,
ForeignKey,
Index,
String,
Text,
)
from sqlalchemy.orm import Mapped, mapped_column, relationship
from api.models.base import Base, TimestampMixin, UUIDMixin
class SecurityIncident(UUIDMixin, TimestampMixin, Base):
"""
Security incident tracking and remediation.
Records security incidents from detection through investigation to resolution,
including details about the incident type, severity, and remediation steps.
Attributes:
id: UUID primary key
client_id: Reference to affected client
service_id: Reference to affected service
infrastructure_id: Reference to affected infrastructure
incident_type: Type of security incident
incident_date: When the incident occurred
severity: Severity level (critical, high, medium, low)
description: Detailed description of the incident
findings: Investigation results and findings
remediation_steps: Steps taken to remediate
status: Current status of incident handling
resolved_at: When the incident was resolved
notes: Additional notes
created_at: Creation timestamp
updated_at: Last update timestamp
"""
__tablename__ = "security_incidents"
# Foreign keys
client_id: Mapped[Optional[str]] = mapped_column(
CHAR(36),
ForeignKey("clients.id", ondelete="CASCADE"),
nullable=True,
doc="Reference to affected client",
)
service_id: Mapped[Optional[str]] = mapped_column(
CHAR(36),
ForeignKey("services.id", ondelete="SET NULL"),
nullable=True,
doc="Reference to affected service",
)
infrastructure_id: Mapped[Optional[str]] = mapped_column(
CHAR(36),
ForeignKey("infrastructure.id", ondelete="SET NULL"),
nullable=True,
doc="Reference to affected infrastructure",
)
# Incident details
incident_type: Mapped[Optional[str]] = mapped_column(
String(100),
nullable=True,
doc="Type of security incident",
)
incident_date: Mapped[datetime] = mapped_column(
nullable=False,
doc="When the incident occurred",
)
severity: Mapped[Optional[str]] = mapped_column(
String(50),
nullable=True,
doc="Severity level",
)
description: Mapped[str] = mapped_column(
Text,
nullable=False,
doc="Detailed description of the incident",
)
# Investigation and remediation
findings: Mapped[Optional[str]] = mapped_column(
Text,
nullable=True,
doc="Investigation results and findings",
)
remediation_steps: Mapped[Optional[str]] = mapped_column(
Text,
nullable=True,
doc="Steps taken to remediate the incident",
)
# Status tracking
status: Mapped[str] = mapped_column(
String(50),
nullable=False,
server_default="'investigating'",
doc="Current status of incident handling",
)
resolved_at: Mapped[Optional[datetime]] = mapped_column(
nullable=True,
doc="When the incident was resolved",
)
# Additional information
notes: Mapped[Optional[str]] = mapped_column(
Text,
nullable=True,
doc="Additional notes and context",
)
# Table constraints
__table_args__ = (
CheckConstraint(
"incident_type IN ('bec', 'backdoor', 'malware', 'unauthorized_access', 'data_breach', 'phishing', 'ransomware', 'brute_force')",
name="ck_security_incidents_type",
),
CheckConstraint(
"severity IN ('critical', 'high', 'medium', 'low')",
name="ck_security_incidents_severity",
),
CheckConstraint(
"status IN ('investigating', 'contained', 'resolved', 'monitoring')",
name="ck_security_incidents_status",
),
Index("idx_incidents_client", "client_id"),
Index("idx_incidents_type", "incident_type"),
Index("idx_incidents_status", "status"),
)
def __repr__(self) -> str:
"""String representation of the security incident."""
return f"<SecurityIncident(id={self.id}, type={self.incident_type}, severity={self.severity}, status={self.status})>"