Monitor suspicious activity in your Python application

When building a Python application that you plan to release to the public, or even if you're building a private application, as developers, we are always looking for ways to make sure that our application is secure and that it's not being misused.

The misuse of our application can be in the form of a user trying to access data they shouldn't have access to or a user trying to perform an action they shouldn't be able to achieve. This can be a severe problem and can lead to many issues such as data loss, data corruption, or even data theft.

Thus, it's essential to set up a system to monitor suspicious activity in your Python application properly and let you and your team know when something is wrong.

For example, let's say you're building a Python application that allows users to upload files. One of the common concerns with this type of application is that users may try to take advantage of your service and upload files that they shouldn't be able to upload, such as illegal content, huge files, or even malware.

LogSnag is an excellent tool for this problem as it trivializes tracking events in your Python application and suspicious monitoring activity. For example, you can use LogSnag to track an event when a user uploads a file. You can then set up a rule to notify you when a user uploads a file that is larger than 100MB. This way, you will know when a user is trying to upload a too large file, and you can take further 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

Use the following code snippet to connect LogSnag to your Python application. Make sure to replace the YOUR_API_TOKEN with your API token and update the project and channel names.

import http.client
import json

conn = http.client.HTTPSConnection("api.logsnag.com")
payload = json.dumps({
  "project": "my-saas",
  "channel": "monitoring",
  "event": "Suspicious File Detected",
  "description": "User uploaded a suspicious file",
  "icon": "🛸",
  "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"))

import requests
import json

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

payload = json.dumps({
  "project": "my-saas",
  "channel": "monitoring",
  "event": "Suspicious File Detected",
  "description": "User uploaded a suspicious file",
  "icon": "🛸",
  "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

LogSnag is a flexible and easy-to-use event tracking service that can monitor suspicious activity in your Python application. It works excellent with Python and provides powerful features such as real-time event tracking, cross-platform push notifications, event filtering, user and product journeys, charts and analytics, and much more.

For example, LogSnag automatically generates user journeys for your product, and you can use this to see how your users use your application. In addition, in the case of suspicious activity, you can view the user's journey to see if they have performed any other questionable actions that they shouldn't have performed.

Here at LogSnag, we believe 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.

LogSnag provides a generous free plan to get you started with event tracking. You can also check out our pricing page to see our paid plans. So please give us a try and let us know what you think!

Other use-cases for LogSnag

1. Monitor your CI/CD build status for your Python application
2. Monitor your CPU usage in your Python application
3. Monitor when database goes down in your Python application
4. Monitor high disk usage in your Python application
5. Monitor when a user changes their email address in your Python application
6. Monitor failed logins in your Python application
7. Monitor failed payments for your Python application
8. Monitor memory usage in your Python application
9. Monitor MySQL downtime in your Python application
10. Monitor when a new feature is used in your Python application
11. Monitor your Postgres downtime in your Python application
12. Monitor Redis downtime in your Python application
13. Monitor when a user exceeds the usage limit for your Python service
14. Monitor when a user is being rate limited in your Python application
15. Get a notification when your Python code is done executing
16. Send push notifications to your phone or desktop using Python
17. Track canceled subscriptions in your Python application
18. Track your Python cron jobs
19. Track when a file is uploaded to your Python application
20. Track when a form is submitted to your Python application
21. Track payment events via Python
22. Track user sign in events in Python
23. Track user signup events via Python
24. Track waitlist signup events via Python