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Governance · Service

Patch Management Service

The exposure window is the business risk. Shrink it.

Structured patch lifecycle management — vulnerability tracking, testing, deployment, and verification.

< 7 days
Target critical-patch SLA
> 97%
Deployment success rate
4 tiers
Risk-based ring deployment
Zero-day
24/7 on-call response
Overview

Ensures timely remediation of security updates while minimizing operational disruption. We design a risk-based patch cadence, instrument it, and run the weekly ops so your exposure window shrinks quarter over quarter.

What you receive
  • Risk-based patch model
  • Weekly ops review
  • Deployment and verification records
  • Executive scorecard
  • Zero-day response runbook
Cadence
7-day onboarding · managed monthly
Compliance mapping
ISO 27001 A.12.6.1PCI DSS 6.3HIPAA §164.308(a)(5)NIST SP 800-40r4CIS Control 7
Outcomes
  • Measurably smaller exposure window quarter-over-quarter
  • Zero-day response with 24-hour compensating controls
  • Executive-ready patch compliance scorecard
  • Auditor evidence for patch-management controls
Methodology

How the engagement runs. Phase by phase.

PHASE 01

Inventory reconciliation

CMDB + endpoint agent + network scan; reconcile to ground truth.

1–2 weeks
PHASE 02

Risk model + SLAs

Asset-criticality tiering, patch-SLA policy by severity × tier.

1 week
PHASE 03

Ring architecture + pipeline

Canary/early/broad/full rings, test-suite definition, rollback playbook.

2 weeks
PHASE 04

First managed cycle

Run full monthly cycle with handholding: scan → score → deploy → verify.

4 weeks
PHASE 05

Steady-state ops

Monthly cycle + zero-day response + quarterly tuning review.

Ongoing
PHASE 06

Executive scorecard

Monthly metrics: exposure window, SLA adherence, exception count.

Monthly
Tools & stack

What we actually use. No secrets.

Every tool earns its place. We publish our stack so your team can audit, review, and integrate with what we bring.

MI Microsoft SCCM / Intune
Microsoft SCCM
RE Red Hat Satellite / SUSE Manager
Red Hat Satellite
AN Ansible / Chef / Puppet
Ansible
TA Tanium / BigFix / Automox
Tanium
QU Qualys / Rapid7 / Tenable
Qualys
JA Jamf / Intune for macOS
Jamf
CU Custom Python dashboards
Custom Python dashboards
SE ServiceNow / Jira CMDB integration
ServiceNow
MI Microsoft SCCM / Intune
Microsoft SCCM
RE Red Hat Satellite / SUSE Manager
Red Hat Satellite
AN Ansible / Chef / Puppet
Ansible
TA Tanium / BigFix / Automox
Tanium
QU Qualys / Rapid7 / Tenable
Qualys
JA Jamf / Intune for macOS
Jamf
CU Custom Python dashboards
Custom Python dashboards
SE ServiceNow / Jira CMDB integration
ServiceNow
Windows
  • MI Microsoft SCCM / Intune
    Microsoft SCCM / Intune
    Enterprise Windows patch orchestration and reporting
Linux
  • RE Red Hat Satellite / SUSE Manager
    Red Hat Satellite / SUSE Manager
    Enterprise Linux patch management with errata sync
Cross-platform
  • AN Ansible / Chef / Puppet
    Ansible / Chef / Puppet
    Config-as-code patch automation for mixed environments
Endpoint
  • TA Tanium / BigFix / Automox
    Tanium / BigFix / Automox
    Real-time endpoint state and patch enforcement
Verification
  • QU Qualys / Rapid7 / Tenable
    Qualys / Rapid7 / Tenable
    Pre/post-patch vulnerability scanning for closure proof
macOS
  • JA Jamf / Intune for macOS
    Jamf / Intune for macOS
    Apple fleet management and OS upgrade orchestration
Reporting
  • CU Custom Python dashboards
    Custom Python dashboards
    Exposure-window metrics, SLA compliance, exec scorecards
ITSM
  • SE ServiceNow / Jira CMDB integration
    ServiceNow / Jira CMDB integration
    Change-management workflow integration for audit trail
Techniques

How we do the work. Not just what.

T.01

Risk-based patch scoring

Priority = CVSS × exploitability (EPSS) × asset-criticality. A 9.8 on a dev laptop is not a 9.8 on your payment processor.

T.02

Ring deployment

4-tier rings: canary (IT) → early (volunteer dept) → broad → full. Bad patches caught by ring 1, never reach production.

T.03

Maintenance windows that work

We find your actual-safe windows from historical uptime data, not the one on the whiteboard.

T.04

Zero-day response playbook

When a KEV-listed vuln drops: 1) inventory exposure, 2) compensating control, 3) emergency patch, 4) verification scan. Each step has an owner and SLA.

T.05

Exception governance

Every can't-patch asset has an exception record with compensating control, expiry date, and executive owner. No silent exceptions.

T.06

Patch-testing pipeline

Critical patches run through a smoke-test suite before ring 1 — captures 80% of patch regressions pre-deploy.

From the field

Real problems. Real fixes.

Anonymized incidents from actual engagements: what broke, why it mattered, and how we fixed it.

01
Problem

Client's patch SLA was 30 days — in practice averaging 78 days, with no visibility why.

Impact

Cyber-insurance renewal flagged the exposure window as material risk.

Resolution

Ring deployment + pipeline automation collapsed average critical to 5 days and everything-else to 21. Visibility dashboard showed each delay root cause (CAB, test fail, window miss) so managers could fix systemic issues, not chase tickets.

02
Problem

Log4Shell dropped on a Friday afternoon — client had no inventory of Java apps.

Impact

60 hours of engineering triage to find where log4j lived.

Resolution

Post-incident we built an ongoing software-inventory pipeline (JAR/NPM/PyPI fingerprints pushed to a central store). For the next zero-day (spring4shell), inventory took 20 minutes. 90% time reduction per event.

03
Problem

Monthly Windows patch broke a legacy LOB app — IT rolled back, patch cycle stalled for 3 months.

Impact

SMB-v1 and other deprecated protocols remained exposed.

Resolution

Added LOB-app smoke test to ring 0 and compatibility shim for KB3033929-style issues. Re-enabled monthly cycle within 2 weeks. LOB app scheduled for modernization with a dated retirement SLA.

Data model

Patch lifecycle

Scan → score → deploy in rings → verify → report.

input
process
store
output
pass Asset inventory CVE / EPSS / KEV Risk-scored queue Patch-test pipeline Ring deployment Post-scan verification Exec scorecard
Metrics we ship against

Targets, not promises.

Metric
Our target
Baseline (industry avg)
Critical patch SLA
≤ 7 days at P95
Industry avg: 49 days
Patch deployment success rate
> 97%
Industry avg: 84%
Zero-day response time
< 24 hours to compensating control
Industry avg: 5 days
Unmanaged asset count
< 1% of fleet
Industry avg: 8–15%
Questions we hear

Answered plainly.

Have something we didn't cover? Ask us directly →

Will patches break our critical apps?
The ring model catches regressions in the IT canary before they reach production. Smoke tests catch another 80% pre-ring. Zero production-outage patches in our last 3 client-years.
Can you handle zero-days?
Yes — 24/7 on-call response with a KEV-aligned playbook: inventory, compensating control, emergency patch, verification scan, executive update.
What about servers we can't reboot easily?
We plan around maintenance windows discovered from historical uptime data, use live-kernel patching where supported (Ksplice, Livepatch), and track pending-reboot exposure separately.
Who owns what — you or us?
We run the process; your team owns the assets. Our role is the pipeline, SLAs, metrics, and zero-day response. Your team retains final approve on CAB decisions.
Next step

Scope a patch management service engagement.

30-minute scoping call. You'll talk to an operator, not a BDR.