About Shannon Information Entropy Calculator
Analyze the Shannon Information Entropy ($H = -\sum p_i \log_2 p_i$) of passwords, encrypted payloads, and random strings. Measures bit density per character, total entropy bits, and unique symbol frequencies.
Key Capabilities & Features
- Exact Shannon entropy calculation: Bits per character ($0$ to $8$ bits)
- Total information entropy calculation across entire string
- Unique character pool analysis and frequency breakdown
- Security rating: Very Low, Low, Moderate, High, Maximum
- Real-time live updates as you modify text
How to Use Shannon Information Entropy Calculator
Input Text
Paste or type any string, password, or encrypted cipher.
Analyze Entropy
Review the bits-per-character score and total entropy metric.
Check Frequency
Inspect the character frequency table for repetitive patterns.
Privacy & In-Browser Execution Guarantee
Text is evaluated purely in client memory using mathematical frequency distributions. Zero network calls.
Frequently Asked Questions
What is Shannon entropy in cryptography?
Shannon entropy measures the average amount of unexpected information or randomness in a text. High entropy indicates random, uncompressed data; low entropy indicates predictable, repetitive patterns.
What is a good Shannon entropy score for a password?
A Shannon entropy score above 3.5 to 4.0 bits per character indicates excellent character pool diversity and strong resistance to dictionary attacks.
How is total entropy calculated from bits per character?
Total entropy is calculated by multiplying the information density (bits/char) by the total character length of the input string.