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.
ShinyHunters operates as a data extortion group, focusing on theft and monetization rather than operational disruption via encryption. Their modus operandi involves:
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.
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.
T1190 - Exploit Public-Facing Application and T1078 - Valid Accounts.T1530 - Data from Cloud Storage Object and T1213 - Data from Information Repositories.T1041 - Exfiltration Over C2 Channel.T1657 - Financial Extortion, where the threat of public data release is used to compel payment.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.
No specific Indicators of Compromise were provided in the source articles.
To detect activity similar to ShinyHunters' TTPs, security teams should hunt for:
s3:GetObject, blob:GetBlobFile Encryption)User Account Permissions)Outbound Traffic Filtering)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.
ShinyHunters lists Kodak on its dark web leak site (approximate date).
Deadline set by ShinyHunters for Kodak to make a payment.

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.
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Every tactic, technique, and sub-technique used in this threat has been identified and mapped to the MITRE ATT&CK framework for consistent, actionable threat language.
Observables and indicators of compromise (IOCs) have been extracted and cataloged. Risk has been assessed and correlated with known threat actors and historical campaigns.
Detection rules, incident response steps, and D3FEND-aligned mitigation strategies are included so your team can act on this intelligence immediately.
Structured threat data is packaged as a STIX 2.1 bundle and can be visualized as an interactive graph — relationships between actors, malware, techniques, and indicators.
Sigma detection rules are derived from the threat techniques in this article and can be converted for deployment across any major SIEM or EDR platform.