Listen to this Post
Introduction
Madison Square Garden Entertainment Corp. has spent years building one of the most aggressive private surveillance networks in the United States, using facial recognition technology to scan, track, and categorize every visitor who walks through its doors. That same surveillance apparatus is now at the center of a catastrophic data breach after the cybercriminal group ShinyHunters published 45 gigabytes of stolen data—including biometric facial recognition records, internal threat assessments, and personal identifiable information (PII) on up to 26 million individuals. The breach, which occurred on June 5, 2026, and was made public after MSG missed a June 15 ransom deadline, has triggered a federal class action lawsuit and raises urgent questions about the fiduciary responsibility organizations bear when collecting and storing the most sensitive data imaginable: biometric identifiers that cannot be changed like a password.
Learning Objectives
- Understand the technical scope and security failures behind the Madison Square Garden facial recognition data breach
- Learn how ShinyHunters and similar threat actors exploit unpatched vulnerabilities and weak access controls
- Master practical commands and configurations for auditing biometric/PII data storage, securing APIs, and hardening cloud environments
- Develop incident response and breach notification strategies for organizations handling biometric data
- Identify regulatory compliance requirements (BIPA, GDPR, CCPA) and fiduciary obligations for PII custodians
1. The ShinyHunters Playbook: How the Breach Unfolded
ShinyHunters, the extortion gang behind the MSG breach, has been on a sustained campaign in 2026, exploiting an unpatched Oracle PeopleSoft zero-day to breach more than 100 organizations. The group’s typical approach involves stealing sensitive data and using “pay-or-leak” extortion tactics to pressure victims into paying ransoms. In MSG’s case, the intrusion occurred on June 5, 2026. When the company failed to reach an agreement by the June 15 deadline, ShinyHunters published more than 42 gigabytes of data on its leak site.
What was exposed:
- Facial recognition surveillance logs and biometric tracking records
- Internal threat assessments and risk profiles classifying celebrities (Ben Stiller as “low risk,” rapper A Boogie wit da Hoodie as “high risk”)
- Customer emails expressing concern about being misidentified by MSG’s facial recognition cameras
- Background check information, credit scores, and Social Security numbers
- Ticketing operations, customer account details, and internal corporate documents
For security professionals, this breach serves as a case study in several critical failures:
Step-by-Step: Auditing Your Biometric Data Storage
- Identify all biometric data repositories: Use data discovery tools to locate where facial recognition templates, hashes, and raw images are stored.
Linux: Find files containing biometric-related patterns sudo grep -rli "facial|biometric|faceprint|template" /data/ --include=.{db,json,xml,csv,log} 2>/dev/null Windows PowerShell: Search for biometric data indicators Get-ChildItem -Path D:\ -Recurse -Include .db,.json,.xml | Select-String -Pattern "facial|biometric|faceprint" -
Classify data sensitivity: Tag all biometric data as “Critical” and apply the strictest access controls.
Linux: Set restrictive permissions on biometric data directories sudo chmod 600 /data/biometric/.db sudo chown securityadmin:securitygroup /data/biometric/ Windows: Set NTFS permissions via icacls icacls "D:\BiometricData" /grant "SYSTEM:(F)" /grant "SecurityAdmins:(F)" /inheritance:r
3. Implement encryption at rest and in transit:
Linux: Encrypt a directory with LUKS sudo cryptsetup luksFormat /dev/sdb1 sudo cryptsetup open /dev/sdb1 biometric_encrypted sudo mkfs.ext4 /dev/mapper/biometric_encrypted Windows: Enable BitLocker for the drive hosting biometric data Manage-bde -on D: -RecoveryPassword -EncryptionMethod XtsAes256
4. Monitor access logs continuously:
Linux: Monitor file access in real-time with auditd sudo auditctl -w /data/biometric/ -p rwxa -k biometric_access sudo ausearch -k biometric_access --start today Windows: Enable advanced audit policies auditpol /set /subcategory:"File System" /success:enable /failure:enable
- The Fiduciary Duty Problem: Why Collecting PII Creates Legal Liability
Andy Jenkinson’s post cuts to the heart of the matter: “Any organisation collecting, harvesting, storing and potentially commercialising PII data, has a fiduciary responsibility to ensure that PII data is secure. When a cyber incident occurs, as in this case, and Madison Square Garden Entertainment Corp. are found to have neglected basic security measures, that makes them complicit and liable for unlawful access, cyber crime, and fraud.”
This is not hyperbole. The class action lawsuit, Avalo v. MSG Entertainment, filed June 16, 2026, in New York federal court, seeks at least $5 million in initial damages. The complaint accuses MSG of “corporate negligence in failing to secure the data it aggressively collects, despite clear warnings from privacy advocates and a previous breach”. This is MSG’s second major breach in under a year—in February 2026, the Cl0p ransomware group exploited a vulnerability in a vendor-hosted Oracle eBusiness Suite application, exposing names, addresses, and Social Security numbers of roughly 131,070 individuals.
Step-by-Step: Building a Fiduciary-Grade Security Program
- Conduct a privacy impact assessment (PIA) for all biometric data collection:
Linux: Use OpenSCAP to scan for compliance gaps sudo oscap xccdf eval --profile (biometric-security-profile) --results results.xml /usr/share/xml/scap/ssg/content/ssg-ubuntu2004-ds.xml
-
Implement data minimization: Delete biometric data that is no longer necessary.
Linux: Find and archive/delete files older than 30 days find /data/biometric/ -type f -mtime +30 -exec gzip {} \; -exec mv {}.gz /archive/ \; Windows PowerShell: Archive old biometric files Get-ChildItem -Path D:\BiometricData -Recurse | Where-Object {$<em>.LastWriteTime -lt (Get-Date).AddDays(-30)} | Compress-Archive -DestinationPath "E:\Archive\biometric</em>$(Get-Date -Format 'yyyyMMdd').zip" -
Implement biometric-specific security controls (NIST SP 800-63B guidelines):
– Biometric templates must be stored as irreversible cryptographic hashes
– Salting and pepper must be applied per template
– Template storage must be separated from personally identifiable information
3. API Security: The Overlooked Attack Surface
The MSG breach highlights how interconnected systems—ticketing APIs, facial recognition endpoints, and customer databases—create expanded attack surfaces. ShinyHunters’ use of an Oracle PeopleSoft zero-day demonstrates that third-party vendor integrations are often the weakest link.
Step-by-Step: Securing Biometric APIs
- Audit all API endpoints handling biometric or PII data:
Use OWASP ZAP for API security scanning zap-cli quick-scan --self-contained --start-options "-config api.disablekey=true" https://api.yourdomain.com/v1/biometric Test for common API vulnerabilities curl -X GET "https://api.yourdomain.com/v1/biometric/templates?user_id=1" -H "Authorization: Bearer {token}"
2. Implement rate limiting and brute-force protection:
Nginx configuration for API rate limiting
limit_req_zone $binary_remote_addr zone=biometric_api:10m rate=5r/s;
location /api/v1/biometric/ {
limit_req zone=biometric_api burst=10 nodelay;
proxy_pass http://biometric_backend;
}
- Enforce strong authentication for all biometric data access:
Implement mutual TLS (mTLS) for service-to-service communication openssl req -1ew -1ewkey rsa:4096 -days 365 -1odes -x509 -keyout server.key -out server.crt Configure API gateway to require client certificates (AWS API Gateway, Kong, or NGINX with ssl_verify_client on)
4. Implement comprehensive API logging and monitoring:
Linux: Monitor API access logs for anomalies
sudo tail -f /var/log/nginx/access.log | grep -E "(/biometric|/facial|/template)"
Set up real-time alerting for unusual access patterns
sudo awk '{print $1, $7, $9}' /var/log/nginx/access.log | sort | uniq -c | sort -1r | head -20
4. Cloud Hardening for Biometric Data
Organizations storing biometric data in the cloud must implement defense-in-depth strategies. MSG’s breach demonstrates that perimeter security alone is insufficient when attackers can exploit zero-day vulnerabilities in vendor applications.
Step-by-Step: Hardening Cloud Biometric Storage
1. Implement strict IAM policies (AWS example):
{
"Version": "2012-10-17",
"Statement": [
{
"Effect": "Deny",
"Action": "s3:GetObject",
"Resource": "arn:aws:s3:::biometric-data/",
"Condition": {
"BoolIfExists": {
"aws:MultiFactorAuthPresent": "false"
}
}
}
]
}
- Enable S3 Object Lock for immutability (prevents deletion/alteration):
aws s3api put-object-lock-configuration --bucket biometric-data --object-lock-configuration '{"ObjectLockEnabled":"Enabled"}'
3. Configure VPC endpoints and block public access:
AWS: Block all public access to S3 bucket aws s3api put-public-access-block --bucket biometric-data --public-access-block-configuration "BlockPublicAcls=true,IgnorePublicAcls=true,BlockPublicPolicy=true,RestrictPublicBuckets=true"
- Enable detailed CloudTrail logging for all biometric data access:
aws cloudtrail create-trail --1ame biometric-audit-trail --s3-bucket-1ame cloudtrail-logs --is-multi-region-trail aws cloudtrail start-logging --1ame biometric-audit-trail
5. Regular vulnerability scanning of cloud infrastructure:
AWS Inspector scan
aws inspector2 start-findings-report --filter-criteria '{"severity":["CRITICAL","HIGH"]}'
Third-party: Run Trivy on container images
trivy image --severity HIGH,CRITICAL your-biometric-app:latest
5. Breach Notification and Incident Response
MSG’s response to the breach has been described in the class action lawsuit as “woefully insufficient”. As of days after the leak, no statement had been issued by the company. This failure to notify affected individuals compounds the legal liability.
Step-by-Step: Building a Biometric Breach Response Plan
- Prepare breach notification templates in advance (compliant with BIPA, GDPR 33-34, CCPA):
Create encrypted breach notification templates openssl enc -aes-256-cbc -salt -in breach_notification_template.txt -out breach_notification_template.enc
-
Establish a breach response team with defined roles:
Linux: Create an encrypted contact list for the response team gpg --symmetric --cipher-algo AES256 response_team_contacts.csv
3. Implement automated breach detection:
Linux: Monitor for unusual data exfiltration patterns sudo iptables -A OUTPUT -m state --state NEW -m recent --set sudo iptables -A OUTPUT -m state --state NEW -m recent --update --seconds 60 --hitcount 10 -j DROP Windows: Monitor outbound connections for data exfiltration New-1etFirewallRule -DisplayName "Block Data Exfiltration" -Direction Outbound -Action Block -RemoteAddress 0.0.0.0/0 -Protocol TCP
- Conduct regular tabletop exercises simulating biometric data breaches:
– Test communication channels
– Practice forensic data collection
– Validate breach notification procedures
- The Immutable Nature of Biometric Data: Why This Breach Is Different
Unlike passwords or credit card numbers, biometric identifiers—facial recognition templates, fingerprints, iris scans—cannot be changed. Once compromised, they are compromised forever. This makes biometric data breaches uniquely catastrophic.
Step-by-Step: Mitigating Biometric Data Breach Impact
1. Implement biometric template protection techniques:
- Use fuzzy extractors to generate cryptographic keys from biometrics
- Apply irreversible transformations (non-invertible cryptographic hashing)
- Implement cancelable biometrics (intentional distortion of biometric data)
- Example: Implementing a cancelable biometric template (Python pseudocode):
import hashlib import numpy as np</li> </ol> def generate_cancelable_template(biometric_vector, user_salt, transformation_key): Apply user-specific salt salted = biometric_vector + user_salt Apply irreversible transformation transformed = np.dot(salted, transformation_key) Generate final hash return hashlib.sha256(transformed.tobytes()).hexdigest() Store only the cancelable template, never the raw biometric
3. Implement a biometric revocation and re-issuance process:
- When a breach occurs, revoke all affected templates
- Issue new templates with new salts and transformation keys
- This effectively “changes” the biometric without changing the user’s face
- Regulatory Compliance: BIPA, GDPR, and the Fiduciary Standard
MSG’s surveillance practices have long drawn scrutiny. The company controversially used facial recognition to detect and deny entry to lawyers from firms in litigation against MSG. A former vice president sued the company, alleging improper use of facial recognition technology to target perceived enemies. The class action lawsuit notes MSG’s “tempestuous history with respect to data privacy” and that “despite a slew of lawsuits regarding this conduct, as well as consternation from privacy advocates and legislators in New York, the Arena—at the direction of its owner James Dolan—continues to collect biometric information from each visitor”.
Step-by-Step: Achieving Biometric Compliance
- Map all biometric data collection to regulatory requirements:
| Regulation | Key Requirement | Implementation Step |
||–||
| BIPA (Illinois) | Written consent before collection | Implement consent management system |
| GDPR 9 | Explicit consent for biometric data | Document lawful basis for processing |
| CCPA/CPRA | Right to delete biometric data | Implement data deletion workflows |
| NY SHIELD Act | Reasonable security safeguards | Conduct regular security assessments |2. Implement a consent management system:
Linux: Set up audit logging for consent records sudo auditctl -w /data/consent/ -p rwxa -k consent_audit Create immutable consent records sha256sum consent_record_$(date +%Y%m%d).json > consent_record_$(date +%Y%m%d).json.sha256
3. Conduct regular third-party security assessments:
Run automated compliance scans sudo openscap xccdf eval --profile (gdpr-bipa-profile) --results compliance_results.xml /usr/share/xml/scap/ssg/content/ssg-ubuntu2004-ds.xml
What Undercode Say
- Key Takeaway 1: Organizations that collect biometric data have a fiduciary duty to secure it. Negligence is not just a PR problem—it creates legal liability for unlawful access, cybercrime, and fraud. MSG’s second major breach in under a year demonstrates a pattern of willful disregard for data security.
-
Key Takeaway 2: Biometric data breaches are fundamentally different from credential breaches. You can change a password; you cannot change your face. The immutable nature of biometric identifiers means that once exposed, the damage is permanent. Organizations must treat biometric data with the highest level of security controls, including encryption at rest and in transit, strict access controls, and continuous monitoring.
Analysis: The MSG breach represents a watershed moment for biometric privacy. The exposure of facial recognition records, internal threat assessments, and customer complaints about surveillance practices reveals the dark underbelly of mass biometric collection. ShinyHunters’ exploitation of an Oracle PeopleSoft zero-day underscores that even well-resourced organizations fail to patch critical vulnerabilities in a timely manner. The class action lawsuit will likely set precedents for biometric data breach liability, potentially establishing that the mere act of collecting biometric data creates an elevated duty of care. Organizations currently deploying or considering facial recognition systems should view this breach as a warning: if you collect biometric data, you are a prime target for attackers, and the consequences of a breach are existential.
Prediction
- -1: MSG will face cascading legal consequences, including multiple class action lawsuits, regulatory fines under state biometric privacy laws (potentially exceeding $5 billion under BIPA’s per-violation penalties), and shareholder derivative suits. The company’s market valuation will suffer as investors price in litigation risk and reputational damage.
-
-1: The breach will accelerate legislative action on biometric privacy at the federal level. Congress will likely introduce (and potentially pass) a national biometric privacy law that establishes a federal standard, preempting the current patchwork of state laws but potentially imposing even stricter requirements.
-
-1: ShinyHunters’ success will embolden other threat actors to target organizations with large biometric databases. We will see a surge in attacks against sports venues, entertainment complexes, airports, and any organization deploying facial recognition. The biometric data black market will expand significantly.
-
-P: The breach will force organizations to fundamentally rethink their biometric data collection practices. Privacy-preserving technologies—such as on-device facial recognition, cancelable biometrics, and zero-knowledge proofs—will see accelerated adoption as organizations seek to reduce their attack surface and legal liability.
-
-P: Security vendors will develop new biometric-specific security solutions, including real-time biometric data monitoring, automated template revocation systems, and AI-powered anomaly detection for biometric database access. This will create a new market segment in the cybersecurity industry.
-
-P: Consumer awareness of biometric privacy risks will increase dramatically, leading to greater demand for transparency and opt-out mechanisms. Organizations that proactively adopt privacy-by-design principles for biometric data will gain competitive advantage and consumer trust.
This article is based on reporting from The Next Web, WIRED, 404 Media, Bloomberg Law, Front Office Sports, BankInfoSecurity, and The Verge, as well as expert commentary from Andy Jenkinson – WHITETHORN SHIELD, Fellow at the Cyber Theory Institute and Director of Fintech (FITCA).
▶️ Related Video (80% Match):
🎯Let’s Practice For Free:
🎓 Live Courses & Certifications:
Join Undercode Academy for Verified Certifications
🚀 Request a Custom Project:
Secure, high-velocity infrastructure and disruptive technological engineering. Contact our engineering team for high-tier development and proprietary systems:
[email protected]
💎 Smart Architecture | 🛡️ Secure by Design | ⭐ Trusted by ThousandsIT/Security Reporter URL:
Reported By: Andy Jenkinson – Hackers Feeds
Extra Hub: Undercode MoN
Basic Verification: Pass ✅🔐JOIN OUR CYBER WORLD [ CVE News • HackMonitor • UndercodeNews ]
📢 Follow UndercodeTesting & Stay Tuned:
