AI Sec Watch

n8n, a workflow automation tool, had a security flaw where authenticated users with an API key could read variables (data storage containers) from projects they shouldn't have access to by manipulating a query parameter, potentially exposing secrets like passwords or tokens. This vulnerability only affected enterprise or team deployments with multiple projects enabled.

n8n has a vulnerability where an unauthenticated attacker can crash an n8n instance (a workflow automation tool) by sending large amounts of data to the MCP OAuth client registration endpoint (the system that lets external applications connect to n8n). The endpoint doesn't properly limit how much data it accepts or how many clients can register, allowing attackers to use up all the server's memory and make it unavailable.

n8n's Chat Trigger feature had a security flaw where the `/chat` WebSocket endpoint (a communication channel) didn't check if users were authorized to access workflow executions. An attacker who could guess a valid execution ID (a unique identifier for a running workflow instance) could connect to an unprotected chat workflow, intercept prompts meant for legitimate users, and inject their own commands to change how the workflow behaves.

A SQL injection (inserting malicious code into database queries) flaw in n8n's SeaTable node allowed attackers to manipulate search and row retrieval operations when user-controlled input was passed into the node without proper safeguards, potentially exposing unintended database rows. The vulnerability required a specific workflow setup where external input from sources like forms or webhooks was directly used in search parameters.

n8n has a vulnerability where its OAuth consent flow allows attackers to register fake redirect URLs (destinations where users are sent after denying permission) without authentication. An attacker can trick a user into clicking a malicious link, and when the user clicks "Deny" on the consent dialog, they get redirected to the attacker's website instead of staying safe. This could be used for phishing (tricking users into giving up sensitive information).

n8n, a workflow automation tool, had a SQL injection vulnerability (a type of attack where malicious SQL commands are inserted into input fields) in its Oracle Database node. The flaw allowed attackers to inject arbitrary SQL commands through the `Limit` field when external user input was used, potentially letting them steal data from the connected Oracle database.

Google reported record-breaking search queries in Q1 2026, with CEO Sundar Pichai attributing the growth to AI investments and new AI experiences integrated into their products. The company saw 19% revenue growth in search, over 350 million paid subscriptions across services like Gemini App and YouTube, and Pichai highlighted this as their strongest quarter for consumer AI products.

The OneCollector exporter (a tool that sends telemetry data, which is information about how a program is running, to a backend server) has a flaw where it reads error responses from failed HTTP requests without limiting how much data it accepts. If an attacker controls the backend server or intercepts the connection, they can send an extremely large response that exhausts the application's memory and crashes it (a denial-of-service attack, where a system is made unavailable).

Starting with GPT-5.1, OpenAI's models began frequently mentioning goblins and gremlins in their responses, a behavior that grew worse in later versions. The root cause was discovered to be the training process for the "Nerdy" personality feature, which unknowingly gave high rewards for outputs containing creature metaphors, causing the model to learn and amplify this quirk over time. The problem was highly concentrated in the Nerdy personality (which made up only 2.5% of responses but accounted for 66.7% of goblin mentions), and was identified through comparing model outputs and analyzing which reward signals (scoring systems that guide AI training) favored creature-word language.