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Patching Strategy

Patching Strategy

Patching Strategy

Patching Strategy

Patching Strategy

Patching Strategy

Patching Strategy

Patching Strategy

Patching Strategy

Introduction

Patching is the most fundamental security practice, yet organizations consistently struggle with timely patch deployment. The challenge is balancing speed against stability — deploying patches too slowly leaves systems vulnerable, while deploying too quickly risks breaking critical applications. A mature patching strategy addresses both sides of this equation.

Vulnerability Prioritization

Not all vulnerabilities are equal. Prioritize based on exploitability, asset criticality, and threat intelligence.

from dataclasses import dataclass

from enum import Enum

class Severity(Enum):

CRITICAL = 1

HIGH = 2

MEDIUM = 3

LOW = 4

@dataclass

class Vulnerability:

cve_id: str

cvss_score: float

asset_criticality: int # 1-5

exploit_available: bool

in_wild: bool

affected_systems: int

def prioritize(vuln: Vulnerability) -> int:

score = vuln.cvss_score

Asset criticality multiplier

score *= (vuln.asset_criticality / 3)

Exploit availability

if vuln.exploit_available:

score *= 1.5

if vuln.in_wild:

score *= 2.0

Reachability

if vuln.affected_systems > 100:

score *= 1.3

return round(score, 1)

Prioritization Matrix

patch_priority:

critical:

\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\- cvss_score: ">= 9.0"

\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\- exploit_in_wild: true

\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\- sla_hours: 24

\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\- process: emergency_change

high:

\\\\\\\\\\\

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