Cole Blahut Cybersecurity Analytics & Operations
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Security Operations Assessment and Risk Reduction Plan

Independent simulationPython & data analysisIdentity securityRisk advisory

I analyzed a synthetic authentication dataset for a fictional mid-sized organization, applied transparent triage rules to identify high-priority patterns, and translated the findings into a risk register and phased remediation plan.

Scope and integrity note. This is a portfolio simulation using fabricated data, not a real client engagement, production security assessment, or evidence of an actual compromise. Scenario labels are included in the data so reviewers can reproduce the exercise. In a real engagement, conclusions would require validation against identity-provider records, user context, and organizational baselines.

Executive Summary

600
synthetic authentication events reviewed
30 days
simulated observation period
4
scenario categories examined
90 days
proposed remediation horizon

The exercise focuses on four identity-security scenarios: repeated authentication failures across multiple accounts, successful sign-ins tagged as unusual-location activity, legacy-style authentication without an MFA challenge, and privileged sign-ins without an MFA challenge. These are deliberately constructed test cases, not independently confirmed malicious activity.

Business Question

How should a 250-person professional-services company prioritize identity and authentication improvements when security staff have limited time and need to explain technical findings to leadership?

The assessment emphasizes controls with direct relevance to account compromise risk, clear ownership, practical implementation sequencing, and measurable outcomes.

Methodology

  1. Defined the scope. Used a fabricated 30-day authentication dataset with timestamps, user IDs, source IPs, application names, authentication outcomes, MFA results, and device-management status.
  2. Applied transparent triage rules. Flagged repeated failures from a single source across multiple accounts, unusual-location scenario events, legacy-style authentication without an MFA challenge, and privileged successful sign-ins without an MFA challenge.
  3. Documented limitations. Treated each match as a lead for validation, not proof of compromise. Location anomalies alone are especially prone to false positives.
  4. Prioritized treatment. Ranked recommendations by potential business impact and urgency, then mapped them to a 30/60/90-day sequence.
  5. Defined success measures. Proposed control-coverage and operational metrics that a real organization could track over time.

Key Findings

PriorityFindingSimulated evidenceRecommended response
CriticalPrivileged successful sign-ins without MFA challenge10 constructed eventsValidate sessions and policies; require MFA for privileged accounts; document exceptions.
HighRepeated failures across multiple accounts60 failed attempts across 8 accounts from one sourceReview targeted accounts and source; tune alerts; validate smart-lockout controls.
HighLegacy-style authentication without MFA challenge15 constructed eventsInventory dependencies and disable legacy protocols where feasible.
Medium pending validationSuccessful sign-ins tagged as unusual-location activity15 constructed eventsCorrelate location with VPN, device, travel, and sign-in history before escalation.

Interpretation: The counts describe how the synthetic test data were constructed. They are not estimates of attack frequency or evidence that an actual organization experienced these events.

Recommended 30/60/90-Day Roadmap

TimingActionsOutcome to measure
Days 0–30Require MFA for privileged accounts; review privileged sessions and policy exceptions; validate lockout settings; assign finding owners.All privileged accounts covered or documented as approved exceptions; actions have accountable owners.
Days 31–60Inventory legacy authentication; remove it where feasible; create an identity-alert triage playbook.Legacy authentication disabled or exception-approved; playbook tested on representative events.
Days 61–90Expand managed-device controls for sensitive apps; run an incident-response tabletop; establish monthly reporting.Coverage, triage time, validation rate, overdue actions, and exceptions reported to leadership.

Risk Register

The downloadable register includes risk domain, observation, estimated likelihood and impact, priority, treatment, success measure, and target window. Ratings are preliminary planning judgments for this fictional scenario, not calibrated risk estimates.

Deliverables and Reproducibility

The analysis script uses pandas and writes a summary JSON and triage findings CSV. See the README for the run command and the exact rules used.

Framework References

These sources inform the framing; this project does not claim certification, formal compliance, or complete control-framework coverage.

What This Project Demonstrates