Shannon Information TheoryZero-Log Client-Side

Password Entropy Calculator

Calculate information entropy bits using the Shannon equation E = L * log2(R). Analyze character pool dynamics and theoretical security margins.

16
Included Character Pools (R)
Combined Pool Size (R):95 characters
Calculated Shannon Entropy
105.1bits
Military-Grade Defense
Shannon Entropy Equation
E = L × log2(R)

E = 16 × log2(95) = 16 × 6.5698 = 105.1 bits

Total Possible Combinations:9516 ≈ 4.4 × 1031

The Mathematics of Shannon Password Entropy

In 1948, Claude Shannon published his seminal paper A Mathematical Theory of Communication, introducing "entropy" as a metric for the information content or unpredictability in a message. In cybersecurity, this exact formula measures the resistance of a secret string to brute-force discovery:

E = L × log2(R)

Where:

  • L: Length of the password (number of characters).
  • R: Size of the character pool from which each character is uniformly chosen.
  • E: Total bits of information entropy.

Why Bits of Entropy Matter More Than Length Alone

Every single bit added to a password's entropy doubles the total number of guesses an attacker must compute. A password with 80 bits of entropy is not twice as strong as a 40-bit password—it is 240 (over 1 trillion) times stronger.

Frequently Asked Questions

What is password entropy?

Password entropy is a mathematical measure of unpredictability and randomness, expressed in 'bits'. It quantifies how many binary guesses an attacker would have to make in the worst-case exhaustive search.

How many bits of entropy do I need for high security?

For online accounts with rate limiting, 40 to 60 bits is moderate. For true protection against offline GPU cracking of stolen database hashes, security experts recommend at least 80 to 100+ bits of entropy.