Monitor failed logins in your Python application

LogSnag makes it easy to track your Python application and monitor failed logins.

Most Python applications require some form of authentication for users to access the application. This is a common practice to ensure that only authorized users can access the application and prevent security issues such as API abuse. These authentication methods can be implemented in various ways, but the most common are basic authentication, Social logins (Google, Facebook, etc.), and more.

With either method, we commonly have to deal with failed logins, be it due to incorrect credentials or other reasons, such as someone trying to brute-force the login. In such cases, monitoring failed logins and taking action depending on the situation is crucial. For example, suppose we notice a user repeatedly falling to login. In that case, we can take action to reach out to them and offer help, or in cases of brute-force attacks, we can take immediate action to block the user's IP address, notify the targeted user, and more.

Here at LogSnag, we have worked on a powerful solution for monitoring and tracking problems. We have created LogSnag, a powerful, real-time event tracking tool that works seamlessly with Python. We have made it trivial to set up real-time event tracking for anything important within our applications. In addition, we provide powerful features that let us take event tracking to the next level and do things like creating user journeys, analytics, insights, and more.

For example, in the case of failed logins, we can set up LogSnag to track failed attempts and notify our team when we observe unusual behavior. This way, we can always be aware of the security of our application and take immediate action if needed.


Setting up LogSnag

  1. Sign up for a free LogSnag account.
  2. Create your first project from the dashboard.
  3. Head to settings and copy your API token.

Python code snippets

To track failed logins, you can use the following code snippet Please ensure to replace YOUR_API_TOKEN with your API token and update the project and channel names.

Using Python with http.client
import http.client
import json

conn = http.client.HTTPSConnection("api.logsnag.com")
payload = json.dumps({
  "project": "my-saas",
  "channel": "status",
  "event": "Failed Login Attempt",
  "description": "Detected 3 failed login attempts in the last 5 minutes",
  "icon": None,
  "notify": True
})
headers = {
  'Content-Type': 'application/json',
  'Authorization': 'Bearer YOUR_API_TOKEN'
}
conn.request("POST", "/v1/log", payload, headers)
res = conn.getresponse()
data = res.read()
print(data.decode("utf-8"))
Using Python with Requests
import requests
import json

url = "https://api.logsnag.com/v1/log"

payload = json.dumps({
  "project": "my-saas",
  "channel": "status",
  "event": "Failed Login Attempt",
  "description": "Detected 3 failed login attempts in the last 5 minutes",
  "icon": None,
  "notify": True
})
headers = {
  'Content-Type': 'application/json',
  'Authorization': 'Bearer YOUR_API_TOKEN'
}

response = requests.request("POST", url, headers=headers, data=payload)

print(response.text)

Python integration details

We believe that event tracking should be simple and accessible to every developer and team. Therefore, we have worked hard to create the next generation of event-tracking tools. As a result, LogSnag is flexible and easy to use, making it a great companion for your Python applications.

We would love to see you use LogSnag to track every aspect of your Python application. So please give us a try and let us know what you think!

Other use-cases for LogSnag

  1. Track payment events via Python

  2. Track user signup events via Python

  3. Track your Python cron jobs

  4. Track waitlist signup events via Python

  5. Track user sign in events in Python

  6. Get a notification when your Python code is done executing

  7. Monitor when a user exceeds the usage limit for your Python service

  8. Monitor when a new feature is used in your Python application

  9. Monitor suspicious activity in your Python application

  10. Monitor when a user is being rate limited in your Python application

  11. Monitor when database goes down in your Python application

  12. Monitor your CPU usage in your Python application

  13. Monitor memory usage in your Python application

  14. Monitor high disk usage in your Python application

  15. Track when a file is uploaded to your Python application

  16. Track when a form is submitted to your Python application

  17. Track canceled subscriptions in your Python application

  18. Monitor failed payments for your Python application

  19. Monitor your CI/CD build status for your Python application

  20. Monitor when a user changes their email address in your Python application

  21. Monitor Redis downtime in your Python application

  22. Monitor your Postgres downtime in your Python application

  23. Monitor MySQL downtime in your Python application

    View all common use-cases with Python