Decoding Automating Authentication Flows on Linux Without Documentation

In the realm of security research and automation, one recurrent challenge is understanding and replicating authentication workflows, especially when official documentation is lacking or incomplete. This post documents a systematic approach to reverse-engineering and automating auth flows on Linux systems, emphasizing practical techniques, code snippets, and best practices.

The Challenge

A security researcher encountering proprietary or undocumented auth flows typically faces hurdles such as obscured API endpoints, complex client-side logic, and unpredictable system behaviors. Without proper documentation, the key is to analyze system interactions, network traffic, and system logs meticulously.

Initial Approach: Monitoring Network Traffic

The first step involves capturing network communication between the client and server during the authentication process. Tools like Wireshark or tcpdump prove invaluable.

sudo tcpdump -i eth0 port 443 -w auth_flow.pcap

Load the target application and perform the login flow. Afterwards, analyze the .pcap file with Wireshark, focusing on HTTP or HTTPS traffic, extracting API calls, tokens, and headers.

Decrypting HTTPS Traffic

When dealing with HTTPS, decrypting traffic becomes essential. Since we lack documentation, intercepting TLS sessions via the SSLKEYLOGFILE environment variable is effective:

export SSLKEYLOGFILE=~/ssl.log
firefox -new-window

Configure the browser to use the log file, then load the client app or website to capture decrypted traffic, revealing request payloads and responses.

Reverse Engineering the Client-side Logic

Analyzing the client code (often JavaScript in web apps) helps understand the flow. Use browser dev tools or decompile binaries if necessary.

Look for:

• API endpoints
• Authentication tokens
• Redirects
• Important headers

JavaScript snippets like:

fetch('/api/auth', {
  method: 'POST',
  headers: { 'Content-Type': 'application/json' },
  body: JSON.stringify({ username, password })
})

indicate critical steps.

Automating the Flow

With insights gained, scripting the flow is next. Using Python with requests simplifies automating API calls.

import requests

session = requests.Session()

# Step 1: Initiate login
login_response = session.post('https://target.com/api/auth', json={'username': 'user', 'password': 'pass'})

# Extract tokens or session info from response
token = login_response.json().get('access_token')

# Step 2: Use token in subsequent requests
headers = {'Authorization': f'Bearer {token}'}
profile_response = session.get('https://target.com/api/profile', headers=headers)
print(profile_response.json())

Handling MFA and Additional Security Measures

Many flows include Multi-Factor Authentication (MFA). To automate or simulate MFA, observe how MFA tokens are generated or sent—via code, email, or app—and incorporate similar steps into your scripts.

Security and Ethical Considerations

Always conduct such experiments in controlled environments with explicit permission. Automating auth flows on production systems without consent is unethical and potentially illegal.

Conclusion

Reversing and automating undocumented auth flows on Linux demands a layered approach: network analysis, client-side review, and scripting based on observed behaviors. Mastering these techniques enhances security research capabilities and fosters a deeper understanding of system interactions, ultimately contributing to more secure and resilient systems.

Adaptability and meticulous analysis are key to success when documentation falls short. Employing these practices enables security professionals to systematically unravel complex login mechanisms and develop robust automation solutions.

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References:

• "Practical Packet Analysis" by Chris Sanders
• Wireshark User Guide
• Requests documentation on GitHub

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