API key management in Prompt Engineering / GenAI - ML Experiment: Train & Evaluate

Experiment - API key management

Problem:You have built a machine learning model that uses an external API for data enrichment. Currently, the API key is hardcoded in your code, which poses security risks and makes it difficult to rotate keys.

Current Metrics:Model runs successfully but API key exposure risk is high; no automated key rotation; potential downtime if key is compromised.

Issue:Hardcoded API keys increase security risks and reduce maintainability. There is no system to manage or rotate keys safely.

Your Task

Implement a secure API key management system that keeps keys out of source code, supports easy rotation, and prevents unauthorized access.

Do not hardcode API keys in the source code.

Use environment variables or secure vaults for storing keys.

Ensure the model can access the API key at runtime without exposing it.

Hint 1

Hint 2

Hint 3

Hint 4

Solution

Prompt Engineering / GenAI

import os
import requests

# Load API key from environment variable
API_KEY = os.getenv('API_KEY')

if not API_KEY:
    raise ValueError('API_KEY environment variable not set')

# Example function to call external API using the key

def get_enriched_data(data_id):
    url = f'https://api.example.com/data/{data_id}'
    headers = {'Authorization': f'Bearer {API_KEY}'}
    response = requests.get(url, headers=headers)
    response.raise_for_status()
    return response.json()

# Usage example
if __name__ == '__main__':
    sample_id = '12345'
    result = get_enriched_data(sample_id)
    print(f'Enriched data for {sample_id}:', result)

# To run this code, set the API_KEY environment variable in your shell:
# export API_KEY='your_actual_api_key_here'

Removed hardcoded API key from source code.

Added code to load API key from environment variable.

Added error handling if API key is missing.

Demonstrated usage of API key in request headers securely.

Results Interpretation

Before: API key was hardcoded in the code, risking exposure and making rotation difficult.

After: API key is loaded securely from environment variables, reducing exposure risk and enabling easy rotation.

Managing API keys securely by keeping them out of source code and loading them at runtime improves security and maintainability of machine learning projects that rely on external APIs.

Bonus Experiment

Try integrating a secrets manager (like AWS Secrets Manager or HashiCorp Vault) to store and retrieve API keys dynamically instead of environment variables.

💡 Hint

Use the SDK of your chosen secrets manager to fetch the API key at runtime securely, and update your code to handle this retrieval.

Practice

1. What is the main purpose of an API key in AI services?

easy

A. To improve AI model accuracy

B. To speed up the AI model training

C. To store user data securely

D. To control who can access the AI service

Solution

1. Step 1: Understand API key role

   An API key acts like a password to allow access to AI services.

2. Step 2: Identify main purpose

   It controls who can use the service by authenticating requests.

3. Final Answer:

   To control who can access the AI service -> Option D

4. Quick Check:

   API key = Access control [OK]

Hint: API keys are like secret passwords for access [OK]

Common Mistakes:

• Thinking API keys improve model accuracy
• Confusing API keys with data storage
• Believing API keys speed up training

2. Which of the following is the correct way to include an API key in a request header?

easy

A. Authorization: Bearer YOUR_API_KEY

B. API-Key: YOUR_API_KEY

C. Key: YOUR_API_KEY

D. Token: YOUR_API_KEY

Solution

1. Step 1: Recall standard header format

   The common standard is to use 'Authorization' with 'Bearer' followed by the API key.

2. Step 2: Match correct header syntax

   Authorization: Bearer YOUR_API_KEY matches this standard format exactly.

3. Final Answer:

   Authorization: Bearer YOUR_API_KEY -> Option A

4. Quick Check:

   Authorization header uses Bearer token [OK]

Hint: Use 'Authorization: Bearer' for API keys in headers [OK]

Common Mistakes:

• Using incorrect header names like 'Key' or 'Token'
• Omitting 'Bearer' keyword
• Placing API key in URL instead of header

3. Consider this Python code snippet using an API key:

import requests
headers = {"Authorization": "Bearer abc123"}
response = requests.get("https://api.example.com/data", headers=headers)
print(response.status_code)

What will this code print if the API key is valid and the request succeeds?

medium

A. 401

B. 200

C. 404

D. 500

Solution

1. Step 1: Understand HTTP status codes

   200 means success, 401 means unauthorized, 404 means not found, 500 means server error.

2. Step 2: Analyze code behavior with valid key

   With a valid API key, the request should succeed and return status code 200.

3. Final Answer:

   200 -> Option B

4. Quick Check:

   Valid key + successful request = 200 [OK]

Hint: 200 means success, 401 means unauthorized [OK]

Common Mistakes:

• Confusing 401 unauthorized with success
• Assuming 404 means invalid key
• Thinking 500 is related to API key

4. You have this code snippet to send a request with an API key:

headers = {"Authorization": "Bearer " + api_key}
response = requests.get(url, headers=headers)

But you get a 401 Unauthorized error. What is the most likely cause?

medium

A. The requests library is not imported

B. The URL is misspelled

C. The API key variable is empty or incorrect

D. The server is down

Solution

1. Step 1: Understand 401 error meaning

   401 Unauthorized means the server rejected the request due to bad or missing credentials.

2. Step 2: Identify cause related to API key

   If the API key variable is empty or wrong, the Authorization header is invalid, causing 401.

3. Final Answer:

   The API key variable is empty or incorrect -> Option C

4. Quick Check:

   401 error = invalid credentials [OK]

Hint: 401 means check your API key value first [OK]

Common Mistakes:

• Blaming URL spelling for 401 error
• Ignoring missing import errors
• Assuming server down causes 401

5. You want to improve security by rotating your API keys regularly. Which approach is best to avoid service interruption?

hard

A. Create a new key, update your app to use it, then delete the old key

B. Delete the old key first, then create a new key

C. Use the same key forever without changes

D. Share your API key publicly to get feedback

Solution

1. Step 1: Understand key rotation process

   To avoid downtime, keep old key active until new key is working.

2. Step 2: Choose safe rotation order

   Create new key, update app, confirm it works, then delete old key.

3. Final Answer:

   Create a new key, update your app to use it, then delete the old key -> Option A

4. Quick Check:

   Rotate keys safely by overlapping usage [OK]

Hint: Add new key before deleting old one [OK]

Common Mistakes:

• Deleting old key before new key is ready
• Never rotating keys at all
• Sharing keys publicly