CVE Database

IBM i 7.6, 7.5, 7.4, and 7.3 could allow a remote attacker to execute arbitrary code or obtain sensitive information due to improper authentication.

IBM i 7.6, 7.5, 7.4, and 7.3 could allow a remote attacker to obtain sensitive information due to improper authentication.

Trigger.dev is a platform for building and deploying fully managed AI agents and workflows. Prior to 4.5.2, addGoogleStrategy() in apps/webapp/app/services/googleAuth.server.ts passes a Google profile email to findOrCreateGoogleUser() in apps/webapp/app/models/user.server.ts without requiring Google's email_verified assertion. When existingEmailUser && !existingUser is true, the flow writes the new Google authIdentifier into the existing email-matched account and returns that user object, allowing an attacker-controlled Google profile with an unverified matching email to take over the account. This issue is fixed in version 4.5.2.

Trigger.dev is a platform for building and deploying fully managed AI agents and workflows. From 3.3.8 until 4.5.6, the PUT /api/v1/runs/:runId/metadata endpoint passes attacker-controlled operation.key values to new JSONHeroPath(operation.key).set(newMetadata, value) in packages/core/src/v3/runMetadata/operations.ts without rejecting dangerous constructor and prototype path segments. A caller with a normal environment API key can pollute Object.prototype in the shared webapp process, corrupting Prisma queries and Prometheus labels, breaking other tenants' worker authentication, and causing a process-wide denial of service. This issue is fixed in version 4.5.6.

Flyto2 Core before 2.28.0 contains a server-side request forgery guard bypass vulnerability that allows attackers to reach internal services by supplying URLs using the unblocked IPv6 address `::` which the kernel routes to loopback identically to `0.0.0.0`. Attackers can submit requests or trigger 302 redirects to ` to bypass the private IP range and blocked hostname checks in `is_private_ip()`, reaching services bound to IPv6 loopback across the `http.get`, `http.request`, and `http.batch` modules.

Relative Path Traversal (CWE-23) in Kibana can lead to the unauthorized deletion of Kibana resources via Relative Path Traversal (CAPEC-139). Kibana Fleet accepted a user-supplied identifier for a Fleet Server host configuration without rejecting relative traversal sequences. The identifier is stored as provided and is later incorporated into the request that Kibana issues when that configuration is removed.

Missing Authorization (CWE-862) in Kibana can lead to cross-space information disclosure and unauthorized data modification via Privilege Abuse (CAPEC-122). Kibana Machine Learning carries out its Elasticsearch operations with elevated internal permissions and relies on a per-request space filter to keep the machine learning data of one space separated from another. Part of the Machine Learning functionality did not apply that filter, so operations issued from one space were carried out against the machine learning data of every space in the deployment.

The Elastic Security capability that suggests existing field values while a user authors endpoint policy artifacts queries Elastic Defend event data with Kibana's internal Elasticsearch account instead of the account of the requesting user. Only Kibana feature privileges are verified, and the caller's Elasticsearch index privileges are not. An authenticated user who holds Elastic Security feature privileges but no read access to the Elastic Defend event indices can therefore retrieve field values from that data, including process command line arguments, which commonly contain tokens, credentials, connection strings, and other sensitive operational detail from protected hosts.

A lower privileged user who holds only the privilege to read agent policies can read the entire configuration of a configured Fleet proxy. This would normally require the Fleet privilege to read settings.The proxy configuration possibly contains proxy authentication credentials and private key material that they should not be authorized to view.

The state that Kibana stores for an Observability Onboarding flow is not bound to the user who created the flow, and the routes that read and update that state do not verify ownership. An authenticated user who holds only generic read access to the space can therefore discover the onboarding flows of other users, read their onboarding state, and write arbitrary progress data into them. A tampered flow can also cause the owner's onboarding view to fail with a server error.

Missing Authorization (CWE-862) in Kibana can lead to unauthorized execution of Osquery and Elastic Defend response actions on managed hosts via Accessing Functionality Not Properly Constrained by ACLs (CAPEC-1). A Kibana user who is able to author and evaluate Elastic Security detection rules can cause response actions to be carried out against enrolled agents without holding the Osquery live query privileges or the Elastic Defend response action privileges that normally govern those capabilities. Depending on the response action involved, this can result in disclosure of information from the affected hosts or in unauthorized changes to their state.

Cross-Site Request Forgery (CWE-352) in Kibana can lead to privilege escalation via Cross Site Request Forgery (CAPEC-62). A user who is permitted to create visualizations can save a specially crafted Vega visualization that, when it is opened by another user, causes authenticated requests to be issued to Kibana in the context of the viewing user's session.

Kibana Agent Builder determines whether a caller owns a private agent by comparing a stable user identifier when one is recorded, and falling back to a comparison of the username when it is not. A username is not unique across Elasticsearch authentication realms, so two distinct principals that share a username in different realms are treated as the same owner. This discloses the configuration and instructions of an agent the caller does not own, and allows that agent to be altered or removed.

The native inference process that Elasticsearch uses to evaluate uploaded machine learning models accepts a model operation that computes a memory address from an offset supplied inside the model, without validating that the offset stays within the bounds of the underlying storage. A user with the privileges required to upload and deploy a trained model can craft a model that reads and writes memory outside the intended allocation. The result is heap corruption that crashes the inference process, and, with sufficient control over the heap layout, could allow arbitrary code execution in the context of that process.

Observable Discrepancy (CWE-203) in Kibana Fleet can lead to information disclosure via Excavation (CAPEC-116). Fleet removes the Elasticsearch API key value of an enrolled Elastic Agent from the responses of its agent listing capability, but that capability accepted caller-supplied filter expressions over the stored field that holds the value, and evaluated them with Kibana's own internal Elasticsearch privileges rather than the caller's. Because the number of matching agents is reported back to the caller, the difference between a matching and a non-matching filter formed a side channel from which the full API key value could be reconstructed one character at a time with a short sequence of requests.

Incorrect Authorization (CWE-863) in Kibana Fleet can lead to privilege escalation via Privilege Abuse (CAPEC-122). Fleet restricts some callers to managing integration policies for one specific integration. When an existing integration policy was updated, that restriction was evaluated against the integration recorded on the stored policy rather than against the replacement integration supplied with the update. An authenticated user holding only the Elastic Defend endpoint policy management privilege was therefore able to convert an endpoint policy they administer into a policy for a different integration, and to supply that integration's configuration at the same time.

Authorization Bypass Through User-Controlled Key (CWE-639) in Kibana can lead to unauthorized cross-space access via Accessing Functionality Not Properly Constrained by ACLs (CAPEC-1). The result is disclosure of inference output from a trained model in a different space that the user is not authorized to list, read, or use, which exposes the behavior of a model. The same pattern also reached the deployment stop and deployment update operations, allowing an active trained model deployment in another space to be stopped or to have its allocated resources altered.

Open WebUI is an extensible, feature-rich, and user-friendly self-hosted AI platform. From 0.9.5 before 0.10.0, any authenticated user can overwrite the content of a message in a channel they do not belong to (including private and DM channels) by sending a chat completion request with a channel:-prefixed chat_id and a target message_id. The channel: path routes pipeline output through _make_channel_emitter, which writes to the Messages table using the caller-supplied message_id without binding it to the channel. This issue is fixed in version 0.10.0.

wetty provides terminal access in browser over http/https. Prior to version 3.0.4, the wetty client decodes a base64 filename from the file-download escape sequence and interpolates it raw into a Toastify HTML string (`escapeMarkup: false`). Any output the victim renders - a `cat`'d file, a tailed log, an SSH MOTD, a `curl` response - that contains `\x1b[5i...:...\x1b[4i` runs script in the wetty origin and types attacker-chosen keystrokes into the victim's SSH session. Version 3.0.4 fixes the issue.

WsgiDAV is a generic and extendable WebDAV server based on WSGI. WsgiDAV 4.3.3 and prior can allow a WebDAV request path containing an encoded parent-directory segment to escape the configured filesystem share root in a specific path layout. The issue is fixed with version 4.3.4.

compliance-trestle is a tooling platform for managing compliance as code. Prior to versiions 3.12.2 and 4.0.3, the compliance-trestle library's remote fetching cache mechanism (HTTPSFetcher and SFTPFetcher) constructs the local cache file path from the URL path component without sanitizing path traversal sequences (`../`). When a remote OSCAL profile references a URL with traversal in its path, the HTTP response body is written to a location outside the intended cache directory, enabling arbitrary file write with attacker-controlled content to the filesystem. Versions 3.12.3 and 4.0.3 patch the issue.

IBM i 7.6, 7.5, 7.4, and 7.3 s vulnerable to a buffer overflow from improperly validating client data. By sending malformed requests to one of the host servers, a remote attacker could leverage this vulnerability to cause a denial-of-server (DoS) for that server.

An undocumented hard-coded credential, shared by all device units, is authorized to bypass authentication. This allows an attacker within Bluetooth range to arbitrarily manipulate brain stimulation parameters and state.

IBM i 7.6, 7.5, 7.4, and 7.3 could allow a remote attacker to cause a denial of service due to an infinite loop.

IBM i 7.6, 7.5, 7.4, and 7.3 could allow a remote authenticated attacker to execute arbitrary code due to a buffer overflow.

IBM i 7.6, 7.5, 7.4, and 7.3 could allow a remote attacker to execute arbitrary code due to a buffer overflow.

IBM i 7.6, 7.5, 7.4, and 7.3 could allow a remote attacker to cause a denial of service due to unbounded resource allocation.

IBM i 7.6, 7.5, 7.4, and 7.3 could allow a remote authenticated attacker to bypass security restrictions due to improper validation of anti-CSRF tokens.

IBM i 7.6, 7.5, 7.4, and 7.3 could allow a remote authenticated attacker to perform unauthorized operations and access sensitive information due to improper session management.

IBM i 7.6, 7.5, 7.4, and 7.3 could allow a local attacker to execute arbitrary code due to an out-of-bounds write.