Why Cursor Keeps Hashing Passwords With MD5 (And How to Fix It)

A developer discovered that AI coding assistants like Cursor, Claude Code, and Copilot frequently generate password hashing code using weak algorithms such as MD5 or SHA-1, which are fast and lack salting. The root cause is that training data includes outdated examples from StackOverflow and old tutorials. The developer recommends using slow, password-specific hashes like bcrypt, scrypt, or argon2id, and suggests tools like SafeWeave or pre-commit hooks to catch insecure crypto before deployment.

I asked Cursor to add a signup endpoint to a side project last week. Clean code, worked first try. Then I read the part where it stored the password: one line, hashlib.md5 . No salt. No work factor. Just a raw MD5 digest sitting in my users table. I have seen this enough times now that I stopped being surprised. Claude Code does it. Copilot does it. Ask any AI editor to "hash the password before saving" and there is a real chance you get MD5 or SHA-1 back. python import hashlib CWE-916: fast hash, no salt, no work factor def store password password : return hashlib.md5 password.encode .hexdigest Sometimes it is SHA-1 instead. Sometimes SHA-256. It does not matter. They are all built to be fast, and speed is exactly what you do not want here. The training data. MD5 password hashing was standard advice on StackOverflow and in PHP tutorials for the better part of a decade. Millions of examples. The models learned the pattern because the pattern was everywhere. They do not know that in 2012 LinkedIn leaked 6.5 million unsalted SHA-1 passwords and most were cracked within days. They just know that "hash a password" and "md5" show up together a lot. The math is the real problem. A modern GPU rig computes billions of MD5 hashes per second. If your user database leaks, and databases leak, every common password falls almost instantly. No salt means identical passwords produce identical hashes, so one rainbow table cracks your whole table at once. Use a slow hash built for passwords: bcrypt, scrypt, or argon2id. They are deliberately expensive to compute, which barely matters for a single login but wrecks an attacker running billions of guesses. python import bcrypt salted, slow by design, tuneable work factor def store password password : return bcrypt.hashpw password.encode , bcrypt.gensalt rounds=12 def verify password password, stored : return bcrypt.checkpw password.encode , stored bcrypt salts automatically, so you never manage it yourself. rounds=12 is a sane default in 2026. If you want the current best practice, argon2id via the argon2-cffi library is the OWASP-recommended choice. Install and you are done: pip install bcrypt The catch: your AI editor will not flag the MD5 version. It is valid Python. It runs. It passes your tests. Nothing tells you it is wrong until the breach. I have been running SafeWeave https://safeweave.dev for exactly this. It hooks into Cursor and Claude Code as an MCP server and flags weak crypto like md5/sha1 password hashing before I move on to the next file. That said, even a basic pre-commit hook with semgrep will catch most of it. The important thing is catching it while you still have the context, whatever tool you use.