Attack ChainAIDerived
Hypothetical attack flow derived from CVE metadata – not a confirmed exploit chain
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AccessAuthenticate as regular user
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ExploitEnumerate file UUIDs via knowledge base API
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ExecutionSend batch file overwrite request
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ImpactPoison RAG content served to LLM
Vulnerability Assessment
| Weakness |
CWE
OWASP Top 10:2025
A01:2025 - Broken Access Control
ASVS 5.0
V8 - Authorization Object-level authorization, IDOR prevention
|
| Exploitation Conditions | Requires authenticated user account on Open WebUI versions prior to 0.8.6. Attacker must have read access to a shared knowledge base to enumerate file UUIDs via GET endpoint, then exploits missing ownership validation in POST /api/v1/retrieval/process/files/batch to overwrite file content. No victim interaction needed. |
| Impact | Real-world risk is moderate-to-high despite the 7.1 CVSS score. The CVSS vector (AV:N/AC:L/PR:L/UI:N) indicates network-accessible exploitation with low complexity, but requires authenticated access and targets integrity rather than confidentiality (C:N/I:H/A:L). The attack is highly automatable once valid credentials are obtained, making it suitable for insider threats or compromised accounts in multi-tenant environments. The integrity impact is severe because attackers control AI-generated outputs, enabling misinformation campaigns, social engineering, or business logic manipulation through poisoned RAG responses. No EPSS score or KEV listing is provided in the input data, and no public exploit identified at time of analysis, suggesting limited observed exploitation. However, the trivial technical complexity (simple API calls with known UUIDs) and the security-critical nature of LLM trust boundaries elevate this beyond typical authorization flaws. Organizations using Open WebUI for shared knowledge bases with multiple authenticated users should prioritize remediation. |
| Exploit ScenarioDerived | An authenticated attacker with read-only access to a corporate knowledge base queries GET /api/v1/knowledge/{id}/files to enumerate file UUIDs associated with technical documentation or policy content. The attacker then sends POST requests to /api/v1/retrieval/process/files/batch with those UUIDs and malicious payloads replacing legitimate content. When other users query the LLM for information, the RAG system retrieves the poisoned files, causing the AI to deliver fabricated technical instructions, altered compliance guidance, or social engineering prompts designed to extract credentials or authorize fraudulent transactions. |
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Alert meAnalysisAIv1 – Mar 27, 2026
Open WebUI versions prior to 0.8.6 permit authenticated users to overwrite arbitrary file contents through an insecure batch processing endpoint, escalating read-only knowledge base access to write permissions without ownership validation. Attackers with low-level privileges can manipulate RAG (Retrieval-Augmented Generation) content served to language models, poisoning AI responses delivered to other users. CVSS 7.1 (High) reflects network-accessible exploitation with low complexity requiring only standard user authentication; no public exploit identified at time of analysis.
RemediationAI
Upgrade Open WebUI to version 0.8.6 or later, which includes authorization checks on the file batch processing endpoint (see GitHub Security Advisory https://github.com/open-webui/open-webui/security/advisories/GHSA-jjp7-g2jw-wh3j). Until patching is completed, implement compensating controls by restricting access to shared knowledge bases, limiting the number of authenticated users with read access to sensitive RAG content, and monitoring API calls to /api/v1/retrieval/process/files/batch for anomalous activity patterns such as users modifying files outside their owned collections. Consider deploying network segmentation to isolate Open WebUI instances from untrusted networks and enforce multi-factor authentication to reduce credential compromise risks.
Affected VersionsENISA
Affected Packages
Source: OSV (Open Source Vulnerabilities)
Affects your stack
Affects 1 package in pypi
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Technical ContextAI · show details
Open WebUI is a self-hosted LLM platform implementing Retrieval-Augmented Generation (RAG) for knowledge management. The vulnerability stems from CWE-639 (Authorization Bypass Through User-Controlled Key), where the POST /api/v1/retrieval/process/files/batch endpoint accepts file UUIDs without verifying ownership or write permissions. Users with read access to shared knowledge bases can enumerate file identifiers via GET /api/v1/knowledge/{id}/files, then submit those UUIDs to the batch processing endpoint to inject malicious content. The compromised files are subsequently retrieved by the RAG pipeline and served to the LLM as authoritative context, enabling prompt injection attacks targeting other platform users. The affected software operates as cpe:2.3:a:open-webui:open-webui (inferred from GitHub advisory scope).
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Severity by source
AV:N/AC:L/PR:L/UI:N/S:U/C:N/I:H/A:L
Primary rating from GitHub Advisory · only source for this CVE.
CVSS VectorGitHub Advisory
Lifecycle Timeline
2DescriptionGitHub Advisory
Open WebUI is a self-hosted artificial intelligence platform designed to operate entirely offline. Prior to version 0.8.6, any authenticated user can overwrite any file's content by ID through the POST /api/v1/retrieval/process/files/batch endpoint. The endpoint performs no ownership check, so a regular user with read access to a shared knowledge base can obtain file UUIDs via GET /api/v1/knowledge/{id}/files and then overwrite those files, escalating from read to write. The overwritten content is served to the LLM via RAG, meaning the attacker controls what the model tells other users. Version 0.8.6 patches the issue.
Executive ViewAI
Open WebUI versions before 0.8.6 contain a file-write vulnerability that allows authenticated users to bypass access controls and modify knowledge base content, enabling poisoning of AI-generated responses served to other users. Organizations deploying Open WebUI in production risk compromised AI output integrity and potential reputational harm if malicious actors inject false or misleading information into retrieval systems that influence downstream decision-making.
Until patched version 0.8.6 is released and deployed: (1) Disable or restrict network access to the batch processing endpoint via WAF or firewall rules; (2) Implement strict role-based access control (RBAC) limiting write permissions on knowledge base resources to administrator accounts only; (3) Segment Open WebUI deployment from production AI inference endpoints; (4) Enable comprehensive audit logging of all file operations and access attempts to detect unauthorized modifications; (5) Establish process for periodic integrity validation of knowledge base content against baseline snapshots.
Threat Intelligence Overview
How this decision was reached
The engine reads each signal below and applies a fixed list of rules from top to bottom. The first rule that matches sets the recommended action – like a statement, every line is shown.
What every action level means
SSVC AssessmentENISA
Priority Score
Attack Technique
Authentication bypass attacks exploit flaws in the verification mechanisms that control access to systems and applications.
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EUVD-2026-16482
GHSA-jjp7-g2jw-wh3j
NVD
CVE.org
EPSS
Vulnrichment
Exploit-DB