Case Studies Hub - Part 1 (Hero)

Real-World Cybersecurity Case Studies

Learn from actual attacks, defense strategies, and remediation techniques documented during AIMF Security's research

Attack Analysis Defense Strategies Remediation Guides
Case Studies Hub - Part 2 (Stats)
7
Documented Case Studies
5
Attack Vector Categories
100%
Real-World Incidents
Case Studies Hub - Part 3 (Introduction)

Why These Case Studies Matter

These aren't theoretical scenarios—they're real attacks that happened to real people. Each case study documents the full attack lifecycle: initial compromise, detection methods, forensic analysis, and complete remediation.

By studying these incidents, you'll learn to recognize attack patterns, implement effective detection strategies, and respond decisively when threats emerge.

⚠️ Disclaimer: All case studies are based on actual security incidents. Sensitive information has been redacted or anonymized. These materials are for educational purposes only.

Case Studies Hub - Part 4 (Case Studies Grid)

Featured Case Studies

High Threat

Amazon Mobile Exploitation Campaign

Mobile Security Cross-Device

Mobile application exploitation revealing cross-device attack patterns and mobile-specific vulnerabilities that traditional security tools often miss.

Key Findings

  • Mobile-specific attack vectors
  • Cross-device compromise patterns
  • Application-level exploitation
Read Full Case Study →
Critical

Gmail Cross-Device Exploit

Session Hijacking Account Takeover

Cross-device session hijacking attack demonstrating account-level exploitation and multi-device compromise through sophisticated session manipulation.

Key Findings

  • Session persistence across devices
  • Account-level exploitation techniques
  • Multi-device compromise patterns
Read Full Case Study →
High Threat

Facebook CDN Attack Campaign

CDN Abuse Data Exfiltration

CDN abuse via connect.facebook.net resulting in 289,489 bytes exfiltrated through automated attack waves every 2-4 hours.

Key Findings

  • Automated attack waves (2-4 hour intervals)
  • 289,489 bytes data exfiltration
  • CDN-based attack infrastructure
Read Full Case Study →
Critical

GHOST Network Infrastructure Campaign

APT Infrastructure

Advanced persistent threat demonstrating infrastructure-level compromise and sophisticated network attack patterns.

Key Findings

  • Infrastructure-level compromise
  • Advanced persistent threat tactics
  • Network-wide exploitation
Read Full Case Study →
High Threat

WiFi Pineapple Defense Campaign

Rogue AP MITM

Rogue access point attacks demonstrating WiFi security vulnerabilities and man-in-the-middle defense strategies.

Key Findings

  • Rogue access point detection
  • Man-in-the-middle prevention
  • WiFi security best practices
Read Full Case Study →
Medium

McAfee Security Incident Campaign

Security Software AV Bypass

Security software exploitation revealing antivirus bypass techniques and vulnerabilities in security tools themselves.

Key Findings

  • Antivirus bypass techniques
  • Security software vulnerabilities
  • Defense-in-depth importance
Read Full Case Study →
Case Studies Hub - Part 5 (Themes)

Common Attack Themes

OAuth & Authentication

OAuth & Authentication

OAuth re-attachment attacks, legacy connections, and authentication bypass techniques affecting millions of users.

Mobile Security

Mobile Security

Mobile app vulnerabilities, cross-device attack chains, and platform-specific exploitation methods.

Network Attacks

Network Attacks

CDN abuse, data exfiltration, network-level compromise, and rogue access point attacks.

Case Studies Hub - Part 6 (CTA)

Learn From Real Attacks

Explore detailed case studies with forensic analysis, detection methods, and complete remediation guides

Case Studies Hub - Part 7 (Attribution Disclaimer)
⚠️ Attribution Disclaimer

Indicators and techniques documented in these case studies may suggest risk patterns, but attribution requires independent third-party assertion and is not inferred by this analysis. All reports present IOC-based observations from direct network traffic analysis. Classification of activity as malicious is based on behavioral observation, not third-party reputation services. No actor identity, geographic origin, or organizational affiliation is claimed unless explicitly stated.