ShinyHunters Breaches Kodak Amid Shift to "Pay-or-Leak" Extortion

ShinyHunters Claims Kodak Breach, Highlighting Data-Theft Extortion Trend

HIGH
July 25, 2026
6m read
Data BreachThreat ActorCloud Security

Impact Scope

Affected Companies

Eastman KodakOne MedicalMadison Square Garden Entertainment

Industries Affected

TechnologyManufacturingHealthcareMedia and EntertainmentOther

Related Entities

Threat Actors

ShinyHunters

Products & Tech

Snowflake Salesforce Oracle PeopleSoft

Other

Eastman KodakOne MedicalNational Association of Insurance Commissioners (NAIC)Madison Square Garden EntertainmentAmazon

Full Report

Executive Summary

The notorious data extortion group ShinyHunters has added Eastman Kodak to its list of victims, claiming in mid-June 2026 to have stolen 2.2 million customer and corporate records. This incident is a prime example of a growing trend in cybercrime: a strategic shift away from data encryption (traditional ransomware) towards a pure data-theft extortion model. In this "pay-or-leak" scenario, attackers exfiltrate sensitive data and demand payment to prevent its public release. ShinyHunters has pioneered this approach by targeting widely used enterprise platforms like Snowflake, Salesforce, and Oracle PeopleSoft, allowing them to compromise hundreds of downstream organizations through a single upstream vulnerability. The Kodak breach underscores that data backups are no longer a sufficient defense, as the compromise occurs the moment data is exfiltrated.


Threat Overview

ShinyHunters operates as a data extortion group, focusing on theft and monetization rather than operational disruption via encryption. Their modus operandi involves:

  1. Targeting Enterprise Platforms: Instead of attacking individual companies one by one, they target large, multi-tenant SaaS and cloud platforms. A compromise of one of these platforms can yield data from hundreds or thousands of its customers.
  2. Data Exfiltration: The primary goal is to steal large volumes of sensitive data. This can include customer PII, corporate records, intellectual property, and financial information.
  3. Public Extortion: After exfiltrating the data, ShinyHunters lists the victim on its dark web leak site, setting a deadline for a ransom payment. If the victim doesn't pay, the group releases the stolen data publicly or sells it to other criminals.

In the case of Kodak, the company acknowledged that an unauthorized party had "temporarily accessed a limited amount of company data" and that the threat was contained. This incident is part of an 18-month campaign by ShinyHunters that has also impacted major organizations like One Medical (owned by Amazon), the National Association of Insurance Commissioners (NAIC), and Madison Square Garden Entertainment.


Technical Analysis

The group's success relies on exploiting vulnerabilities in third-party platforms that organizations trust with their data. This represents a form of supply chain attack.


Impact Assessment

The shift to a pay-or-leak model has significant implications for enterprise defense. Traditional ransomware defenses focused on business continuity and data recovery (i.e., good backups) are insufficient. Once the data is stolen, the damage is done, and the organization faces a difficult choice between paying the extortion fee or dealing with the consequences of a public data leak. These consequences can include regulatory fines (e.g., under GDPR or CCPA), reputational damage, customer lawsuits, and the weaponization of the leaked data by other threat actors. For Kodak, even a "limited" breach can have an outsized impact if the stolen data is sensitive. The incident also highlights the risk of forgotten data in legacy systems and archives, which are often less secure but still contain valuable information.


IOCs — Directly from Articles

No specific Indicators of Compromise were provided in the source articles.


Cyber Observables — Hunting Hints

To detect activity similar to ShinyHunters' TTPs, security teams should hunt for:

Type
log_source
Value
Cloud audit logs (CloudTrail, Azure Monitor)
Description
Look for anomalous data access patterns, such as a single user account accessing an unusually large number of files or records in a short period.
Type
network_traffic_pattern
Value
Large, sustained egress traffic from production databases or cloud storage to unknown IP addresses.
Description
This is a primary indicator of bulk data exfiltration.
Type
api_endpoint
Value
s3:GetObject, blob:GetBlob
Description
Monitor for high volumes of API calls related to data retrieval from cloud storage, especially from unexpected source IPs or user agents.
Type
user_account_pattern
Value
Dormant accounts suddenly becoming active and accessing data.
Description
Compromised legacy accounts are often used for data theft.

Detection & Response

  • Data Loss Prevention (DLP): Deploy DLP solutions that can monitor and block the exfiltration of sensitive data based on classification and policies.
  • Cloud Security Posture Management (CSPM): Use CSPM tools to continuously scan for and remediate misconfigurations in cloud environments (e.g., public S3 buckets, weak IAM policies).
  • User and Entity Behavior Analytics (UEBA): Implement UEBA to baseline normal data access patterns and detect deviations that could indicate a breach, such as an employee account suddenly downloading millions of customer records.

Mitigation

  • Data Governance and Minimization (M1041): Know where your sensitive data is, classify it, and encrypt it at rest and in transit. More importantly, dispose of data that is no longer needed for business or regulatory reasons to reduce the attack surface. (D3FEND: File Encryption)
  • Third-Party Risk Management: Rigorously vet the security practices of your SaaS and cloud providers. Understand their security model and your responsibilities within it.
  • Strong Access Controls (M1035): Implement strict access controls for all enterprise and cloud platforms. Enforce the principle of least privilege and use MFA for all user accounts. (D3FEND: User Account Permissions)
  • Egress Traffic Filtering (M1037): Monitor and filter outbound network traffic to detect and block large-scale data transfers to untrusted destinations. (D3FEND: Outbound Traffic Filtering)

Timeline of Events

1
June 15, 2026
ShinyHunters lists Kodak on its dark web leak site (approximate date).
2
June 18, 2026
Deadline set by ShinyHunters for Kodak to make a payment.
3
July 25, 2026
This article was published

MITRE ATT&CK Mitigations

Encrypt sensitive data at rest to make it unusable to an attacker even if exfiltrated.

Implement strict, least-privilege access controls for cloud and SaaS platforms.

Use egress filtering and DLP solutions to monitor and block unauthorized data transfers.

Audit

M1047enterprise

Continuously audit cloud configurations and data access logs to detect anomalous behavior.

Timeline of Events

1
June 15, 2026

ShinyHunters lists Kodak on its dark web leak site (approximate date).

2
June 18, 2026

Deadline set by ShinyHunters for Kodak to make a payment.

Sources & References

Article Author

Jason Gomes

Jason Gomes

• Cybersecurity Practitioner

Cybersecurity professional with over 10 years of specialized experience in security operations, threat intelligence, incident response, and security automation. Expertise spans SOAR/XSOAR orchestration, threat intelligence platforms, SIEM/UEBA analytics, and building cyber fusion centers. Background includes technical enablement, solution architecture for enterprise and government clients, and implementing security automation workflows across IR, TIP, and SOC use cases.

Threat Intelligence & AnalysisSecurity Orchestration (SOAR/XSOAR)Incident Response & Digital ForensicsSecurity Operations Center (SOC)SIEM & Security AnalyticsCyber Fusion & Threat SharingSecurity Automation & IntegrationManaged Detection & Response (MDR)

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Tags

ShinyHuntersData ExtortionKodakSnowflakePay-or-LeakData Breach

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