CVE-2025-59422
Langgenius Dify 1.8.1
Raw vector
CVSS:4.0/AV:N/AC:H/AT:N/PR:L/UI:N/VC:H/VI:N/VA:N/SC:N/SI:N/SA:N/E:X/CR:X/IR:X/AR:X/MAV:X/MAC:X/MAT:X/MPR:X/MUI:X/MVC:X/MVI:X/MVA:X/MSC:X/MSI:X/MSA:X/S:X/AU:X/R:X/V:X/RE:X/U:XSummary
CVE-2025-59422 is a medium-severity Improper Access Control (CWE-284) vulnerability in Langgenius Dify. Its CVSS base score is 6.0 (Medium).
Operationally, exploitation aligns with the MITRE ATT&CK technique Messaging Applications (T1213.005); ranked at the 14th percentile by exploit likelihood (below the median); it is not currently listed in the CISA KEV catalog; a public proof-of-concept is referenced.
This vulnerability is AI-related — categorised as LLM Application Platforms; in the Privacy and Disclosure risk domain.
The strongest mitigations our analysis identified map to AC-3 (Access Enforcement) and AC-4 (Information Flow Enforcement) — see the control section below for these in your framework.
OWASP Top 10 for Web (2025)
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2025-31091
Vulnerability Data
Dify is an open-source LLM app development platform. In version 1.8.1, a broken access control vulnerability on the /console/api/apps/<APP_ID>chat-messages?conversation_id=<CONVERSATION_ID>&limit=10 endpoint allows users in the same workspace to read chat messages of other users. A regular user is able to read…
more
the query data and the filename of the admins and probably other users chats, if they know the conversation_id. This impacts the confidentiality of chats. This issue has been patched in version 1.9.0.
- CWE(s)
AI Security AnalysisAI
- AI Category
- LLM Application Platforms
- Risk Domain
- Privacy and Disclosure
- OWASP Top 10 for LLMs 2025
- None mapped
- Classification Reason
- Matched keywords: dify, llm
Related Threats
MITRE ATT&CK Enterprise TechniquesAI
Why these techniques?
Broken access control enables unauthorized access to other users' chat messages via API, facilitating collection from messaging applications (T1213.005) and discovery of unsecured credentials in chat messages (T1552.008).
CVEs Like This One
Affected Assets
Mitigating Controls
Control response
Mitigating Controls (NIST 800-53 r5) AI
Directly enforces authorization checks on the /console/api/apps/<APP_ID>/chat-messages endpoint so that only the conversation owner (or explicitly authorized users) can retrieve messages, blocking the cross-user read that defines CVE-2025-59422.
Limits each workspace account to the minimum privileges required to access only its own conversation resources, reducing the blast radius when conversation_id values are known or guessed.
Enforces information-flow rules that prevent chat-message data belonging to one user from flowing to another user in the same workspace unless an explicit policy permits it.
Mitigating Controls (NIST CSF 2.0) AI
Derived directly from the weakness types (CWEs) cited in the NVD entry via our AI-authored CWE→CSF cross-walk (authority under review) — links open the control.
PR.AA-05 directly enforces policy-based access management and least privilege, eliminating most improper-access-control defects, yet CWE-284 also covers implementation flaws and design gaps outside a single management control.
Hardened baselines and deviation monitoring directly eliminate most configuration-induced access-control defects, yet CWE-284 also encompasses code-level and design flaws outside the scope of configuration management alone.
Secure SDLC practices catch most access-control defects during design/coding/testing (mostly), yet leave residual risk from runtime configuration, architecture, and operational controls (partial).
PR.AA-01 supplies managed identities/credentials that support but do not implement access-control decisions, so it only partially prevents CWE-284 in either direction.
Authentication directly blocks unauthenticated actors (partial prevention of CWE-284) but leaves authorization logic, policy enforcement, and role checks untouched, so the control neither eliminates nor fully mitigates the broader weakness.
PR.DS-01 encryption mitigates impact of failed access checks on stored data but neither implements nor constrains access-control logic itself.
Mitigating Controls (ISO/IEC 27001:2022 Annex A) AI
Derived directly from the weakness types (CWEs) cited in the NVD entry via our AI-authored CWE→ISO cross-walk (authority under review) — links open the control.
Defining and enforcing explicit access rights and restrictions for each entity directly stops the assignment of permissions that exceed what is required, eliminating the root condition that allows improper access control.
Formal authorization, role-based provisioning, and timely revocation of access rights directly stop the creation of accounts or permissions that exceed what the business actually needs.
By enforcing explicit rules on which identities or groups may perform read, write, delete or execute operations and by denying anonymous access to sensitive data, the control directly stops the creation of overly permissive or missing access-control checks.
Requiring one-to-one mapping of identities to entities and timely removal of unused identities directly stops attackers from leveraging stale or shared accounts to bypass access restrictions.
By explicitly transferring security roles and responsibilities when personnel change jobs or leave, the control reduces the chance that former employees retain access rights they no longer need, thereby limiting improper access control.
Physical entry controls enforce explicit authorization and authentication at every access point, directly stopping unauthorized actors from reaching information-processing assets.