Enterprise - Zero Trust Security & Identity Analytics

Overview

A global enterprise with 45,000 employees and extensive third-party vendor access struggled with legacy perimeter-based security insufficient for cloud-first infrastructure and remote workforce, experiencing frequent compromised account incidents, insider threats, and inability to enforce least-privilege access principles across hybrid environment.

Key Challenges

• Legacy castle-and-moat security model with implicit trust inside perimeter failing in cloud and remote work era

• Frequent compromised account incidents: credential stuffing, phishing, and password reuse causing 120+ security events annually

• Insider threat blind spots: unable to detect malicious insiders or negligent employee behavior patterns

• Overprivileged user accounts and service accounts violating least-privilege principles creating excessive blast radius

• Static authentication insufficient to detect account compromise when legitimate credentials used

• Fragmented identity systems: Active Directory, Azure AD, Okta, AWS IAM with inconsistent access policies

• Privileged access management gaps with shared admin credentials and insufficient session monitoring

• Third-party vendor and contractor access lacking visibility and granular controls

• Manual access reviews taking months with stale permissions accumulating over time

• No contextual awareness: unable to adapt security controls based on user behavior, device posture, or risk signals

Our Approach

• 1

  Designed and implemented comprehensive zero trust security architecture with 'never trust, always verify' principles

• 2

  Built Databricks-powered UEBA (User and Entity Behavior Analytics) platform analyzing all identity and access events

• 3

  Deployed machine learning models establishing baseline behavioral profiles for all users detecting anomalous activity

• 4

  Implemented real-time identity risk scoring combining authentication signals, behavioral analytics, and threat intelligence

• 5

  Created adaptive authentication engine dynamically adjusting MFA requirements based on contextual risk factors

• 6

  Established micro-segmentation with identity-based access controls replacing network perimeter security

• 7

  Unified identity governance across all IAM systems with centralized policy management and enforcement

• 8

  Built privileged access management (PAM) solution with just-in-time access provisioning and session recording

• 9

  Implemented continuous access evaluation terminating sessions when risk thresholds exceeded

• 10

  Created automated access certification workflows with machine learning-powered recommendations

• 11

  Integrated endpoint detection, CASB, and SIEM data for comprehensive identity threat detection

Key Outcomes

• Reduced compromised account incidents by 89% (from 120 to 13 annually) through behavioral detection and adaptive authentication

• Achieved 100% zero trust architecture implementation across all cloud and on-premises infrastructure

• Accelerated insider threat detection by 76% (from average 85 days to 20 days) with UEBA behavioral analytics

• Implemented real-time identity risk scoring for all 45,000 employees and 8,000 third-party accounts

• Reduced overprivileged accounts by 67% through automated least-privilege access enforcement

• Decreased privileged account compromises by 94% with just-in-time access and session monitoring

• Blocked 847 account compromise attempts through adaptive authentication challenge-up during suspicious login patterns

• Accelerated access review cycles by 89% (from 4 months to 2 weeks) with ML-powered automated recommendations

• Prevented data exfiltration from 12 compromised accounts through continuous access evaluation and automatic session termination

• Reduced help desk password reset tickets by 42% through risk-based authentication reducing friction for legitimate users

• Achieved audit compliance with comprehensive identity activity logging and tamper-proof audit trails

• Identified and remediated 23,000+ stale permissions and orphaned accounts reducing attack surface