AI & LLM Vulnerabilities

Parse Dashboard versions 7.3.0-alpha.42 through 9.0.0-alpha.7 have a CSRF vulnerability (cross-site request forgery, where an attacker tricks a logged-in user into unknowingly sending requests to a website). An attacker can create a malicious webpage that, when visited by someone authenticated to Parse Dashboard, forces their browser to send unwanted requests to the AI Agent API endpoint without their knowledge. This vulnerability is fixed in version 9.0.0-alpha.8 and later.

Parse Dashboard versions 7.3.0-alpha.42 through 9.0.0-alpha.7 have a security flaw in the AI Agent API endpoint (a feature for managing Parse Server apps) where authorization checks are missing, allowing authenticated users to access other apps' data and read-only users to perform write and delete operations they shouldn't be allowed to do. Only dashboards with the agent feature enabled are vulnerable to this issue.

A security vulnerability exists in the `MarkdownRenderer.jsx` component where it uses `dangerouslySetInnerHTML` (a React feature that directly inserts HTML code without filtering) to display content generated by the AI model, allowing XSS (cross-site scripting, where attackers inject malicious code that runs in a user's browser). This means if the model outputs code containing `<script>` tags, those scripts will execute automatically, potentially redirecting users or performing other harmful actions, and the problem persists even after closing the chat because the malicious script gets saved in the chat history.

OpenClaw, a personal AI assistant, had a security flaw in versions 2026.2.13 and below on macOS where OAuth tokens (authentication credentials that prove you're logged in) could be used to inject malicious OS commands (commands that run at the operating system level) into the credential refresh process. An attacker could exploit this by crafting a specially designed token to execute arbitrary commands on the affected system.

OpenSift, an AI study tool that searches through large datasets using semantic search (finding similar content based on meaning) and generative AI, has a vulnerability in versions 1.1.2-alpha and below where it can be tricked into requesting unsafe internet addresses through its URL ingest feature (the part that accepts web links as input). An attacker could exploit this to access private or local network resources from the computer running OpenSift.

OpenSift, an AI study tool that uses semantic search (finding information by meaning rather than exact keywords) and generative AI to analyze large datasets, has a vulnerability in versions 1.1.2-alpha and below where untrusted content is rendered unsafely in the chat interface, allowing XSS (cross-site scripting, where attackers inject malicious code that runs in a user's browser). An attacker who can modify stored study materials could execute JavaScript code when a legitimate user views that content, potentially letting the attacker perform actions as that user within the application.

MLflow contains a vulnerability (CVE-2026-2635) where hard-coded default credentials are stored in the basic_auth.ini file, allowing remote attackers to bypass authentication without needing valid login information and potentially execute code with administrator privileges. This flaw exploits the use of default passwords, a common security mistake where systems ship with unchangeable built-in login credentials.

TensorFlow has a vulnerability where it loads plugins from an unsafe location, allowing attackers who already have low-level access to a system to gain higher privileges (privilege escalation, where an attacker gains elevated permissions to do things they normally couldn't). An attacker exploiting this flaw could run arbitrary code (any commands they choose) with the same permissions as the target user.

This advisory describes a vulnerability in Google Cloud Vertex AI related to predictable bucket naming (a bucket is a container for storing data in cloud storage). The content provided explains the framework used to assess vulnerability severity through metrics like attack vector, complexity, and required privileges, but does not describe the actual vulnerability details, its impact, or how it affects users.

This advisory describes a stored XSS (cross-site scripting, where malicious code is saved and executed when users view a webpage) vulnerability in Google Cloud Vertex AI SDK. The text provided explains the CVSS scoring framework (a 0-10 rating system for vulnerability severity) used to evaluate this vulnerability, covering factors like how an attacker could exploit it, what privileges they need, and what systems could be impacted.