Why Password Salts Must Be Cryptographically Random

Securing user accounts requires state-of-the-art hashing algorithms and entropy measures. Here is how passwords are secured.

A cryptographic password is a secure key verified using hashing algorithms (like bcrypt) and unique random salt values. Checking password complexity entropy ensures the credentials resist modern high-speed brute-force attacks.

Using cryptographic salts is essential to protect password hashes from pre-computed rainbow table attacks. However, simply adding a salt is not enough. If the salt values are generated using a standard pseudorandom number generator (PRNG)—such as JavaScript's Math.random() or Python's random module—the security of the entire database is compromised. Salts must be generated using Cryptographically Secure Pseudorandom Number Generators (CSPRNGs).

In this guide, we'll explain PRNG predictability, detail CSPRNG entropy sources, and analyze security rules.

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⚙️ The Vulnerability of Standard PRNGs

Standard programming language random functions (like Math.random()) are designed for speed and statistical uniformity, not security. They use algorithms (like LCG or Mersenne Twister) that rely on a internal state:

1. State Reconstruction: If an attacker can observe a sequence of generated salts, they can reverse-engineer the PRNG's internal state.
2. Predicting Future Salts: Once the state is reconstructed, the attacker can predict all future salts that will be generated by the server.
3. Pre-computing Rainbow Tables: By predicting the salts, the attacker can pre-compute rainbow tables for future user registrations before the database is even breached.

📊 Password Length and Entropy Reference

In addition to using secure salts on the server, passwords must have high entropy. Refer to the logarithmic scale chart below to see how length scales cracking difficulty:

🛡️ CSPRNGs: Cryptographically Secure Randomness

CSPRNGs (such as JavaScript's crypto.getRandomValues() or Python's secrets module) prevent prediction by incorporating high-entropy system noise into their state calculations:

• Entropy Sources: They gather noise from hardware interrupts, mouse movements, disk seek times, and thermal sensors.
• Forward Secrecy: If an attacker manages to compromise the current state of a CSPRNG, they still cannot calculate past or future generated values.
• (Read our Rainbow Table Salting Defenses Guide to review database protections).
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