Crypto Gone Wrong - Why secure algorithms still gets exploited?

So people think crypto fails because of math. What actually breaks is what we build around it like implementation details, key handling, assumptions in application code, etc. And now it's getting even worse as AI generated code enters production, a scan of 4 million code samples found AI-generated code has a 45% security flaw rate.

In this talk, I will unpack five real-world failures that show how cryptographic systems actually get attacked like a bit flipping exploit that drained $12M in Bitcoin, AES-GCM nonce reuse, padding oracle attacks that recover plaintext, timing leaks that reveal bytes one by one, and weak password hashing that can be cracked offline in minutes. Each case will be explained through the lens of "what went wrong in the design" and "how the attack becomes possible in practice."

More importantly, the talk will explain what these failures mean for real systems. We will look at how attackers exploit implementation gaps, why these bugs keep recurring, and how to prevent them by design instead of by patching after the fact.

You will leave with a practical checklist for building safer systems: correct use of authenticated encryption, safe nonce and key handling, constant-time operations, secure password storage, and review habits that catch crypto mistakes before they ship.

1. Crypto rarely fails in the algorithm, it fails in the way it is implemented in real systems.
2. Even a secure scheme like AES-GCM can become dangerous when tags, nonces, or verification are handled badly.
3. The real fix is engineering discipline using the right API, enforcing the right checks, and designing for misuse before the attackers do.