Cybersecurity51 mins ago

ShinyHunters Claims Zara Breach, Exposing 197,400 Customer Records

ShinyHunters says it stole 140 GB from Zara, exposing 197,400 customer emails, locations and support tickets. No payment data taken.

Peter Olaleru/3 min/US

Cybersecurity Editor

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ShinyHunters Claims Zara Breach, Exposing 197,400 Customer Records
Source: BleepingcomputerOriginal source

ShinyHunters asserted responsibility for a Zara data leak that exposed 197,400 records, including emails, locations, order IDs and support tickets. The attackers did not obtain names, phone numbers, addresses, login credentials or payment information.

Context

Zara, the flagship brand of Inditex, operates over 1,500 stores worldwide. The compromised data resided in databases hosted by a former technology provider and was accessed via stolen Anodot authentication tokens. Have I Been Pwned confirmed the breach after analyzing the leaked archive.

Key Facts

- 197,400 unique email addresses were exposed, alongside geographic locations, product SKUs, order IDs and support‑ticket metadata. - ShinyHunters released a 140 GB archive allegedly taken from BigQuery instances using the compromised tokens. - The attackers did not acquire names, phone numbers, physical addresses, credentials or payment data, per Inditex and Have I Been Pwned. - ShinyHunters has previously claimed breaches at Google, Cisco, Match Group, Medtronic and others, often leveraging vishing to steal SSO tokens.

What It Means

The incident shows how token‑based abuse can bypass traditional perimeter defenses, allowing threat actors to query cloud data stores without triggering credential‑based alerts. While no financial or identity data was taken, the exposed purchase and support information could enable targeted phishing or social‑engineering campaigns.

Mitigations

- Rotate and invalidate all Anodot (or similar monitoring) API tokens immediately; enforce short‑lived tokens and mandatory re‑authentication. - Detect anomalous token usage with MITRE ATT&CK technique T1078 (Valid Accounts) monitoring: flag token use from unfamiliar IPs or at unusual times. - Apply the principle of least privilege to BigQuery service accounts; restrict access to only required datasets. - Enable data‑exfiltration detection rules for large query result downloads (e.g., >100 MB) and correlate with token‑access logs. - Review and patch any known vulnerabilities in token‑management platforms; consult vendor advisories for CVE‑2023‑XXXX‑style issues if applicable.

Watch for follow‑up claims from ShinyHunters or similar groups attempting to monetize the leaked support‑ticket data through targeted phishing or credential‑stuffing attempts.

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