n8n versions before 1.123.64, 2.29.8, and 2.30.1 contain a privilege escalation vulnerability in Enterprise SSO instance-role provisioning. The provisioning path maps an IdP-asserted role claim to an n8n global role but does not prevent assignment of the global:owner role (unlike the token-exchange identity path, which rejects it). An SSO-authenticated user whose instance-role claim resolves to global:owner is provisioned as instance owner, gaining full administrative control over workflows, credentials, users, and instance configuration. Exploitation requires that Enterprise SSO is configured, instance-role provisioning is enabled via N8N_SSO_SCOPES_PROVISION_INSTANCE_ROLE (disabled by default), and the attacker controls the instance-role claim value issued by the IdP.
n8n versions before 1.123.64 fail to properly mask custom HTTP header credentials in LLM sub-node execution data, writing plaintext API keys and secrets to workflow execution records. Authenticated users with access to execution data can read exposed header values and credentials that persist in the database and can be exported.
n8n before 2.29.8 and 2.30.x before 2.30.1 does not enforce shell sandbox restrictions on Linux and Windows in the @n8n/computer-use package (sandboxing was applied only on macOS). Shell commands executed by the tool run without any filesystem or network restrictions, allowing unrestricted access to the host filesystem and network from within the computer-use agent process. This issue only affects deployments where the @n8n/computer-use package is explicitly installed and running; standard n8n installations are not affected.
Missing Authorization (CWE-862) in Kibana can lead to unauthorized cross-space information disclosure via user-supplied input that circumvents space-level access control.
Uncontrolled Resource Consumption (CWE-400) in Elasticsearch can lead to denial of service via Exponential Data Expansion (CAPEC-197). An authenticated user may submit a specially crafted query to the ES|QL engine that causes exponential CPU consumption during query evaluation. Because the resource exhaustion persists beyond query completion, repeated requests can fully exhaust the available query worker resources, rendering ES|QL queries unavailable until the node is restarted.
Incomplete List of Disallowed Inputs (CWE-184) in Kibana can allow an authenticated attacker with access to the Reporting feature to bypass outbound request restrictions configured by an administrator, causing the reporting service to send requests to network destinations that should be denied by the configured security policy.
Missing Authorization (CWE-862) in Kibana can lead to unauthorized information disclosure via Privilege Abuse (CAPEC-122). A user with limited feature privileges can access workflow execution outputs in their Kibana space without the authorization required to do so through the documented API. The accessible data may include sensitive information returned by workflow steps, such as results from connected data sources that the caller would not otherwise be authorized to access.
Uncontrolled Recursion (CWE-674) in Elasticsearch can lead to denial of service via a specially crafted search request submitted by a low-privileged authenticated user. A user with read-level index access can submit a request that triggers unbounded recursive processing within the Elasticsearch query evaluation component, causing a fatal error that terminates the affected node. In single-node deployments, this results in complete service outage; in multi-node clusters, it causes repeated node restarts and sustained availability degradation.
Incorrect Authorization (CWE-863) in Kibana can lead to integrity compromise of Machine Learning audit and notification records via Accessing Functionality Not Properly Constrained by ACLs (CAPEC-1).
A vulnerability exists in Kibana's Machine Learning functionality where a Machine Learning management endpoint performs an insufficient authorization check. The endpoint validates only a coarse privilege level but does not verify that the requesting user has access to the specific Machine Learning job or notification resources provided in the request. As a result, a low-privileged user with Machine Learning access in any Kibana space can manipulate Machine Learning audit and notification records for arbitrary jobs—including jobs in other spaces or belonging to other users—by leveraging Kibana's internally elevated credentials to write to restricted Machine Learning system indices that the user cannot access directly.
Authorization Bypass Through User-Controlled Key (CWE-639) in Kibana can lead to information disclosure via user-supplied identifiers that reference scheduled query result data from Kibana Spaces the requester is not authorized to access.