How It Works: The 5-Node Anomaly Detection Flow This workflow efficiently processes logs to detect anomalies. Scheduled Check (Cron Node): This is the primary trigger. It schedules the workflow to run at a defined interval (e.g., every 15 minutes), ensuring logs are routinely scanned for suspicious activity. Fetch Logs (HTTP Request Node): This node is responsible for retrieving logs from an external source. It sends a request to your log API endpoint to get a batch of the most recent logs. Count Failed Logins (Code Node): This is the core of the detection logic. The JavaScript code filters the logs for a specific event ("login_failure"), counts the total, and identifies unique IPs involved. This information is then passed to the next node. Failed Logins > Threshold? (If Node): This node serves as the final filter. It checks if the number of failed logins exceeds a threshold you set (e.g., more than 5 attempts). If it does, the workflow is routed to the notification node; if not, the workflow ends safely. Send Anomaly Alert (Slack Node): This node sends an alert to your team if an anomaly is detected.
Tags
Related workflows
See all Slack→Send Slack notifications when a new release is published for public Github repos
This workflow checks a configured list of Github repositories daily to see if a new release has been published. How it works: Workflow has a daily trigger RepoConfig node is a JSON array that defines a list of repositories to check releases for For each of the configured repos it fetches the latest release If the release was published within the last 24 hours it is output The release is sent as a Slack message showing the repo name, release name and link Setup Update the JSON in the RepoConfig node to the Github repos you wish to get notifications for Setup your Slack connection (or replace with your choice of notification)
Automated Real Estate Property Lead Scoring with BatchData
How It Works This workflow automates the real estate lead qualification process by leveraging property data from BatchData. The automation follows these steps: When a new lead is received through your CRM webhook, the workflow captures their address information It then makes an API call to BatchData to retrieve comprehensive property details A sophisticated scoring algorithm evaluates the lead based on property characteristics like: Property value (higher values earn more points) Square footage (larger properties score higher) Property age (newer constructions score higher) Investment status (non-owner occupied properties earn bonus points) Lot size (larger lots receive additional score) Leads are automatically classified into categories (high-value, qualified, potential, or unqualified) The workflow updates your CRM with enriched property data and qualification scores High-value leads trigger immediate follow-up tasks for your team Notifications are sent to your preferred channel (Slack in this example) The entire process happens within seconds of receiving a new lead, ensuring your sales team can prioritize the most valuable opportunities immediately.. Who It's For This workflow
Manage Slack channel and users automatically
Explore this workflow on its official n8n template page.