Attack ChainAIDerived
Hypothetical attack flow derived from CVE metadata – not a confirmed exploit chain
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AccessAuthenticate to Kibana with low-privilege credentials
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DeliveryObtain target user's AI Assistant conversation identifier
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ExploitCraft API request referencing foreign conversation ID
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ExecutionBypass conversation ownership check
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ImpactRead or overwrite victim's AI conversation data
Vulnerability Assessment
| Weakness |
CWE
OWASP Top 10:2025
A01:2025 - Broken Access Control
ASVS 5.0
V8 - Authorization Object-level authorization, IDOR prevention
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| Exploitation Conditions | Exploitation requires an authenticated Kibana session with at least low-privilege access (PR:L per CVSS vector). The attacker must additionally obtain a specific AI Assistant conversation identifier belonging to another user; this identifier is described as hard-to-guess, which is reflected in AC:H. The AI Assistant feature must be enabled and in active use by the victim user, generating conversation records with identifiers. Exploitation is limited to reading or modifying AI conversation content - it does not affect underlying Elasticsearch indices, Kibana dashboards, or authentication mechanisms. Unauthenticated external attackers are categorically excluded by the PR:L requirement. |
| Impact | The CVSS 3.1 base score of 4.2 (Medium) is consistent with the available signals and reflects a genuinely limited-impact vulnerability. AV:N confirms network-accessible exploitation, but AC:H reflects the requirement to know a hard-to-guess conversation identifier - a meaningful practical barrier that reduces opportunistic exploitation. PR:L requires a valid authenticated session, ruling out unauthenticated external attackers. Scope is Unchanged (S:U), impact is limited to Low confidentiality and Low integrity - an attacker can read or alter another user's AI conversation content but cannot escalate privileges, exfiltrate credentials, or affect availability. No EPSS score was provided in the input data; it is INFERRED to be low given the AC:H constraint, authentication requirement, and niche feature scope. No CISA KEV listing and no public POC exist, making real-world exploitation unlikely outside targeted insider scenarios. This is a genuine IDOR that warrants patching but should not be prioritized above critical or actively exploited vulnerabilities in the same environment. |
| Exploit ScenarioDerived | An authenticated Kibana user with low-level privileges who has obtained another user's AI Assistant conversation identifier - through log exposure, API response enumeration, or social engineering - crafts a direct API request referencing that foreign conversation ID. The server processes the request without validating ownership, returning or accepting modifications to conversation content belonging to the victim user. No public proof-of-concept code exists at time of analysis. |
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Alert meAnalysisAIv1 – Aug 25, 2026
Insecure direct object reference in Kibana's AI Assistant feature allows an authenticated low-privileged user to access or modify another user's AI conversation by supplying that conversation's identifier in API requests. Affected versions are addressed in the Elastic security update ESA-2026-51, covering Kibana 8.16.3 and 8.17.2. No public exploit code or active exploitation has been identified at time of analysis; the AC:H rating reflects the hard-to-guess nature of the conversation identifier as a meaningful practical barrier.
RemediationAI
Upgrade Kibana to version 8.16.3 (for 8.16.x deployments) or 8.17.2 (for 8.17.x deployments) as detailed in Elastic security advisory ESA-2026-51 at https://discuss.elastic.co/t/kibana-8-16-3-8-17-2-security-update-esa-2026-51/387446. If immediate upgrade is not feasible, a targeted compensating control is to disable the AI Assistant feature entirely for untrusted or low-privileged user roles via Kibana's feature privilege controls - this eliminates the attack surface at the cost of losing AI Assistant functionality for those users. Restricting the Kibana instance to trusted internal networks reduces the network-accessible attack surface but does not mitigate insider-threat scenarios where a legitimate authenticated user attempts cross-user access. No side effects are associated with upgrading to the patched versions beyond standard upgrade procedures.
Affected VersionsENISA
Affected Packages
Source: OSV (Open Source Vulnerabilities)
Affects your stack
Affects 1 package in euvd
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Technical ContextAI · show details
CWE-639 (Authorization Bypass Through User-Controlled Key) describes a classic Insecure Direct Object Reference (IDOR) pattern: the server accepts a user-supplied resource identifier and acts on it without confirming that the requesting user is the authorized owner of that resource. In Kibana's AI Assistant feature, conversations are stored under unique identifiers, but the backend access control logic does not enforce that the authenticated requester matches the conversation owner. The CAPEC-1 pattern (Accessing Functionality Not Properly Constrained by ACLs) maps to this precisely - the ACL check for conversation ownership is either absent or bypassable. The Elastic Stack's Kibana component is the web interface for Elasticsearch, and its AI Assistant stores conversational context server-side, meaning multiple users' conversation data coexists in the same backend data store with identifier-based segregation that this flaw undermines.
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Severity by source
AV:N/AC:H/PR:L/UI:N/S:U/C:L/I:L/A:N
Network-accessible via web UI; AC:H for hard-to-guess ID; PR:L for authenticated session; no availability or scope impact.
Primary rating from Vendor (elastic).
CVSS VectorVendor: elastic
DescriptionCVE.org
Authorization Bypass Through User-Controlled Key (CWE-639) in Kibana can lead to unauthorized data modification via Accessing Functionality Not Properly Constrained by ACLs (CAPEC-1). Under certain conditions, an authenticated user could reference another user's AI Assistant conversation identifier to access or modify a conversation they do not own. Successful exploitation requires knowledge of a hard-to-guess identifier.
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-2026-65489
GHSA-623v-mjrc-8wr7
NVD
CVE.org
EPSS
Vulnrichment
Exploit-DB