DifyTap Flaws Expose AI Data Across Tenants on Platform Powering 1M+ Apps

Gbhackers •Divya • June 23, 2026

A series of critical vulnerabilities in the widely used open-source LLMOps platform Dify, which powers over one million AI applications. These vulnerabilities, collectively referred to as “DifyTap,” include four flaws, two rated as critical and two that require no authentication. They expose cross-tenant data leakage risks, allowing attackers to access private AI conversations, preview sensitive […]

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This article is one source in a clustered incident — the cluster page carries the summary, timeline and every other outlet covering it.

Critical DifyTap Vulnerabilities Expose AI Data Across 1M+ Apps Zafran Labs identified four vulnerabilities in Dify, an open-source AI platform used by over one million applications, including critical flaws allowing cross-tenant data leakage. Two vulnerabilities, CVE-2026-41947 and CVE-2026-41948, are rated critical, enabling attackers to access private conversations and documents without authentication. The flaws stem from inadequate tenant isolation and API trust boundaries, allowing one customer's data to be accessed by another. Additionally, CVE-2024-5846, a known use-after-free vulnerability in PDFium, remained unpatched for over 18 months. The vulnerabilities were disclosed responsibly, and patches have been released in version 1.14.2 of Dify. The findings highlight significant security gaps in AI systems, particularly in multi-tenant architectures. Zafran's ongoing Project DarkSide aims to expose such weaknesses in AI applications. 8 sources 71

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DifyTap Flaws Expose AI Data Across Tenants on Platform Powering 1M+ Apps

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Attack Types (1)

CWE Weaknesses (2)

MITRE ATT&CK (1)

Platforms (1)

Vulnerabilities (1)