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Python is loved for its simplicity and flexibility, but let’s be honest—security can’t be an afterthought when building applications. Whether you’re writing a quick script or deploying a large-scale service, vulnerabilities in Python apps can creep in quietly and cause real damage if not addressed early.

One of the most common issues is dependency management. With Python, we often install third-party libraries without thinking twice. If you’re not checking for known vulnerabilities in your dependencies, you’re potentially opening the door to exploits. Tools like pip-audit or integrating security scans into CI/CD pipelines can help catch these risks before deployment.

Another challenge is input validation. Think about a simple feature like python find in list. On its own, it seems harmless. But if the data being searched comes directly from untrusted sources (like user input), it could lead to unexpected crashes or even injection-style attacks if poorly handled. Sanitizing and validating data before processing it is always a must.

Hardcoding credentials is another security pitfall. Storing API keys or passwords directly in code is a recipe for leaks. Using environment variables or vault services like HashiCorp Vault is a safer alternative.

Finally, logging and error handling often get ignored. Exposing stack traces or sensitive data in logs is dangerous. Always ensure logs are scrubbed of sensitive details and follow least-privilege principles in your code.

This is where tools like Keploy can add value. By automatically generating test cases and mocks from real API traffic, Keploy ensures your app is tested under realistic scenarios—including edge cases you might not anticipate manually. That means fewer blind spots, and by extension, fewer security surprises.