Attack ChainAIDerived
Hypothetical attack flow derived from CVE metadata – not a confirmed exploit chain
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AccessReach Autotune REST API on adjacent network
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ExploitSend unauthenticated GET to /datasources
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ExecutionReceive cleartext datasource authentication secrets
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ImpactReuse credentials against backing monitoring stack
Vulnerability Assessment
| Weakness |
CWE
OWASP Top 10:2025
A06:2025 - Insecure Design
ASVS 5.0
V6 - Authentication Credential storage protection
|
| Exploitation Conditions | Exploitation requires network reachability to the Autotune service and that at least one monitoring datasource has been configured with authentication secrets (basic-auth password, bearer token, API key, or OAuth2 client secret) - if no secured datasources are configured there are no credentials to harvest. No authentication is needed because the REST API ships without any authentication layer (PR:N), and no user interaction is required. The principal limiting factor is the Adjacent attack vector (AV:A): the attacker must be able to reach the Autotune endpoints, which in typical deployments means positioning inside the same cluster or network segment rather than across the open internet. The vulnerable endpoints are specifically GET /datasources (list-datasources) and the datasource-metadata endpoint. |
| Impact | This is a credible, confirmed credential-exposure flaw rather than a hypothetical high-CVSS issue, but its reach is constrained. The CVSS 3.1 vector (AV:A/AC:L/PR:N/UI:N/S:C/C:H/I:N/A:N, 7.4) shows a low-complexity, unauthenticated path - PR:N confirms no authentication is required because the REST API ships with no authentication layer - with a scope change (S:C) justified by the fact that the leaked secrets grant access to a separate security authority (the backing monitoring stack). Impact is confidentiality-only (C:H, I:N, A:N): the flaw discloses stored credentials but does not itself modify or deny service. The attack vector is Adjacent (AV:A), not full Network (AV:N), which materially limits exposure - an attacker needs reachability to the Autotune service (typically cluster-internal), not arbitrary internet access. No EPSS score, no CISA KEV listing, and no public exploit were provided in the input, so there is no signal of active or probable exploitation; the GitHub reference is the vendor fix (PR 2038), not exploit code. The vuln.today priority is 'this_week' and the SSVC-style decision label aligns with a notable-but-not-emergency posture. Net: real and worth remediating promptly because exploitation is trivial once an attacker is adjacent and secrets are exposed in cleartext, but the adjacent-only vector and absence of exploitation evidence keep it below drop-everything urgency. |
| Exploit ScenarioDerived | An attacker who has gained a foothold on the network adjacent to a Kruize Autotune deployment (for example a compromised pod or host in the same cluster segment) sends an unauthenticated GET request to the /datasources endpoint or the datasource-metadata endpoint. Because the datasource objects are serialized with a default Gson configuration and no field-exclusion strategy, the response returns the stored authentication secrets (basic-auth passwords, bearer tokens, API keys, OAuth2 client secrets) in cleartext, which the attacker then reuses to authenticate to the backing monitoring stack. No public exploit code was identified at time of analysis; exploitation requires only a standard HTTP client. |
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Alert meAnalysisAIv1 – Oct 23, 2026
Kruize Autotune's unauthenticated REST API returns configured monitoring-datasource credentials-basic-auth passwords, bearer tokens, API keys, and OAuth2 client secrets-in cleartext through GET /datasources and the datasource-metadata endpoint. The flaw affects Autotune deployments where at least one monitoring datasource has authentication secrets configured; no specific version range is stated in the provided data. Attackers who can reach the service from an adjacent network can harvest those credentials and reuse them against the backing monitoring stack; no public exploit was identified at time of analysis, and the CVSS score is 7.4 with an adjacent attack vector.
RemediationAI
Apply the upstream fix in kruize/autotune PR 2038 (https://github.com/kruize/autotune/pull/2038), which adds a Gson serialization exclusion strategy so DataSourceInfo.authenticationConfig and AuthenticationConfig objects are not returned by ListDatasources and DSMetadataService; no released patched version is confirmed in the provided data. Until the fix is deployed, restrict network reachability to the Autotune service, especially GET /datasources and the datasource-metadata endpoint, to trusted clients inside the same cluster or network segment, because exploitation requires reachability and the API has no authentication layer. If secured datasources are configured, treat any basic-auth passwords, bearer tokens, API keys, or OAuth2 client secrets returned by these endpoints as exposed and rotate them; deployments with no secured datasources have no such credentials to harvest. Vendor advisory: https://access.redhat.com/security/cve/CVE-2026-110975.
Affected ProductsAI
Kruize Autotune is the affected product; the provided data does not include a version range or CPE string. The vulnerable functionality is the Autotune REST API, specifically GET /datasources (list-datasources) and the datasource-metadata endpoint, in deployments where monitoring datasources are configured with authentication secrets. Vendor references are https://access.redhat.com/security/cve/CVE-2026-110975 and https://bugzilla.redhat.com/show_bug.cgi?id=2512012, and the upstream fix is at https://github.com/kruize/autotune/pull/2038.
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Technical ContextAI · show details
Kruize Autotune is a Java-based REST service, and the exposed endpoints build responses with Gson. In the affected code, the Gson configuration used by ListDatasources and DSMetadataService did not define a field-exclusion strategy, so the DataSourceInfo.authenticationConfig field and related AuthenticationConfig objects were serialized with the rest of the datasource object. Because the API also ships without an authentication layer, any client that can reach the service can request datasource configuration and receive the stored secrets. This maps to CWE-256 (Plaintext Storage of a Password): secrets are persisted for datasource authentication and then disclosed without protection. The upstream PR 2038 addresses the serialization defect by adding a Gson ExclusionStrategy that skips DataSourceInfo.authenticationConfig and AuthenticationConfig during serialization; it does not add an API authentication layer.
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Severity by source
AV:A/AC:L/PR:N/UI:N/S:C/C:H/I:N/A:N
Unauthenticated (PR:N) low-complexity read of an unauthenticated API over an adjacent/cluster network (AV:A); scope changes (S:C) because leaked secrets grant access to the separate monitoring stack; confidentiality-only impact (C:H, I:N, A:N).
Primary rating from Vendor (redhat).
CVSS VectorVendor: redhat
DescriptionCVE.org
A flaw was found in Kruize Autotune. Its REST API ships without an authentication layer, and the endpoints that return datasource configuration - the list-datasources endpoint (GET /datasources) and the datasource-metadata endpoint - serialized datasource objects using a default Gson configuration with no field-exclusion strategy. As a result, the authentication secrets stored for each configured monitoring datasource (basic-auth passwords, bearer tokens, API keys, and OAuth2 client secrets) were returned in cleartext to any client able to reach the service. An attacker with network access to Autotune could harvest these credentials and reuse them to authenticate to the backing monitoring stack.
Executive ViewAI
The unauthenticated Kruize Autotune REST API exposes cleartext credentials for connected monitoring datasources, potentially allowing attackers with adjacent network access to hijack the monitoring stack. This compromises the confidentiality and integrity of performance data and could lead to broader system compromise, affecting security and operations teams relying on these tools.
Restrict network access to Autotune, rotate exposed credentials, enforce authentication and TLS, and monitor for unauthorized access.
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
Information disclosure occurs when an application unintentionally exposes sensitive data that aids attackers in reconnaissance or directly compromises security.
EUVD-2026-109109
GHSA-f9cv-pr2f-46v2
NVD
CVE.org
EPSS
Vulnrichment
Exploit-DB