Modern applications process and store a large amount of information every day.
This information can include passwords, files, user data, messages, and other digital content. In many situations, applications need a way to verify data without storing or exposing the original information.
This is where hashing becomes important.
Hashing is the process of converting data into a fixed-length value using a mathematical function called a hash function.
The generated value is called a hash or hash value.
For example, an application may take some data:
Hello World
and pass it through a hash function:
Hello World
↓
Hash Function
↓
Hash Value
The resulting hash looks like a random sequence of characters.
Unlike encryption, hashing is generally designed to be a one-way process. You can generate a hash from data, but you should not be able to recover the original data from the hash.
As a result, hashing is widely used for password storage, data integrity checks, digital signatures, file verification, and many other security-related tasks.
In this article, we’ll explain what hashing is, how it works, why it is important, and where it is used in modern applications.
What Is Hashing?
Hashing is the process of converting input data into a fixed-size output using a hash function.
The input can be almost any type of data, including:
- Text
- Passwords
- Files
- Images
- Documents
- Messages
The output is called a hash value.
The basic process looks like this:
Input Data → Hash Function → Hash Value
For example:
Hello
↓
Hash Function
↓
2cf24dba...
The exact hash value depends on the algorithm being used.
A key feature of cryptographic hashing is that the original input is not intended to be recovered from the generated hash.
How Does Hashing Work?
Hashing follows a relatively simple concept.
The process can be understood in several steps.
Original Data → Hash Function → Fixed-Length Hash
Let’s look at each step.
Step 1: Data Is Provided as Input
First, an application provides data to a hash function.
For example:
Hello World
The input is processed by the hashing algorithm.
Step 2: The Hash Function Processes the Data
A hash function performs mathematical operations on the input.
The function can process data of different lengths.
For example:
Hi
or:
This is a much longer message containing many words.
Even though the input sizes are different, a particular hash algorithm produces output with a fixed length.
Step 3: A Hash Value Is Generated
After processing the input, the hash function produces a hash value.
Conceptually:
Input Data
↓
Hash Function
↓
Hash Value
For example:
Hello World
↓
SHA-256
↓
a generated hash value
The output appears random.
However, it is generated deterministically.
That means the same input passed to the same hash function produces the same output, assuming the same relevant parameters.
Hashing Is a One-Way Process
One of the most important characteristics of cryptographic hashing is that it is designed to be one-way.
For example:
Password
↓
Hash Function
↓
Hash Value
An application can generate the hash from the password.
However, the hash function is not designed to provide a normal reverse operation:
Hash Value
↓
???
↓
Original Password
This is why hashing is useful for certain security tasks.
A Simple Hashing Example
Suppose a user enters:
MyPassword123
The application processes the password through an appropriate password hashing function:
MyPassword123
↓
Password Hashing Function
↓
Stored Password Hash
Instead of storing the original password directly, a secure system stores a derived password hash.
Later, when the user logs in, the system verifies the entered password against the stored hash using the appropriate password hashing process.
Important Properties of a Good Cryptographic Hash Function
Cryptographic hash functions are designed to have several important properties.
1. Deterministic
The same input produces the same hash output.
For example:
Hello
↓
Hash Function
↓
Hash A
If the same data is hashed again using the same algorithm and parameters:
Hello
↓
Hash Function
↓
Hash A
The output remains consistent.
This makes hashing useful for data verification.
2. Fixed-Length Output
A hash function produces an output of a specific length.
The input might be:
Hi
or a very large file.
However, a given hash algorithm produces output with its defined length.
For example, SHA-256 produces a 256-bit hash value.
3. Small Changes Produce Very Different Hashes
A small change to the input can produce a very different output.
For example:
Hello
and:
hello
are different inputs.
Therefore, their hash values will be completely different.
This behavior is often called the avalanche effect.
Conceptually:
Hello
↓
Hash A
hello
↓
Hash B
Even a small input change can result in a significantly different hash.
4. Designed to Be One-Way
Cryptographic hash functions are designed so that recovering the original input from the hash is computationally infeasible.
This property makes them useful for password verification and other security applications.
What Is a Hash Collision?
A hash collision occurs when two different inputs produce the same hash value.
Because a hash function maps a potentially unlimited number of possible inputs into a fixed-size output, collisions are theoretically unavoidable.
However, a strong cryptographic hash function is designed to make finding a collision computationally infeasible.
For example:
Input A
↓
Hash Function
↓
Hash X
Input B
↓
Hash Function
↓
Hash X
For modern cryptographic uses, developers should choose algorithms that remain appropriate and avoid known broken collision-resistant hashes.
Hashing vs Encryption
Hashing and encryption are often confused.
However, they serve different purposes.
Encryption
Encryption is designed to protect data that may need to be recovered later.
Plaintext
↓
Encryption
↓
Ciphertext
↓
Decryption
↓
Plaintext
With the appropriate key, authorized systems can decrypt the information.
Hashing
Hashing is designed to create a fixed-size representation of data.
Original Data
↓
Hash Function
↓
Hash Value
The original data is not normally recovered from the hash.
Therefore:
Encryption is used when data needs to be protected and later recovered.
Hashing is used when data needs to be verified or compared without storing the original value.
Hashing vs Encoding
Hashing is also different from encoding.
Encoding changes data into another format for compatibility or transmission.
For example:
Original Data
↓
Encoding
↓
Encoded Data
Encoding can normally be reversed by decoding.
Hashing is not intended to work that way.
Therefore:
Encoding is not a security mechanism.
Hashing can provide security-related properties when an appropriate cryptographic hash function is used.
Where Is Hashing Used?
Hashing is used in many technologies and applications.
1. Password Storage
Password storage is one of the most common uses of hashing.
A secure application should not store passwords as plain text.
Instead, it uses a password hashing function to derive a password hash.
The process looks like this:
User Password
↓
Password Hashing Function
↓
Password Hash
↓
Database
When the user logs in:
Entered Password
↓
Password Verification
↓
Compare With Stored Hash
↓
Allow or Reject Login
For password storage, developers should use purpose-built password hashing algorithms such as Argon2, bcrypt, or scrypt, rather than using a general-purpose fast hash function alone.
What Is Salt in Password Hashing?
A salt is additional random data used during password hashing.
Conceptually:
Password
+
Random Salt
↓
Password Hashing Function
↓
Password Hash
Salting helps ensure that identical passwords do not automatically produce identical stored password hashes when unique salts are used.
It also makes certain large-scale precomputation attacks less effective.
A secure password hashing library generally provides appropriate salt handling.
2. File Integrity Checking
Hashing can help verify whether a file has changed.
Suppose you download a file.
The original source provides a hash:
Expected Hash:
ABC123...
You can calculate the hash of the downloaded file:
Downloaded File
↓
Hash Function
↓
Calculated Hash
Then compare:
Expected Hash
↓
Compare
↓
Calculated Hash
If the hashes match, it provides evidence that the file matches the data associated with that hash.
If they differ, the file content has changed or does not match the expected data.
3. Data Integrity Verification
Applications can use hashes to detect changes in data.
For example:
Original Data
↓
Hash
↓
Store Hash
Later:
Current Data
↓
Hash Again
↓
Compare Hashes
If the values differ, the data is different.
This is useful in many systems where detecting unexpected changes is important.
4. Digital Signatures
Hashing is also commonly used as part of digital signature systems.
Conceptually:
Document
↓
Hash
↓
Digital Signature Process
↓
Signature
The recipient can verify the signature and integrity using the appropriate cryptographic process.
Digital signatures provide more than simple hashing because they use cryptographic keys and signature algorithms.
5. Blockchain Technology
Hashing is used extensively in blockchain systems.
Blocks can contain cryptographic hashes that connect data structures and help detect changes.
If data in a protected structure changes, the related hash values can also change.
Therefore, hashing can help support tamper-evident data structures.
However, hashing alone does not automatically make a system secure or decentralized.
6. Caching
Hashing can also be used to generate identifiers for data.
For example, an application may use a hash of content as part of a cache key.
Conceptually:
Content
↓
Hash
↓
Cache Identifier
This can help systems identify specific versions of content.
Common Hashing Algorithms
Several hash algorithms exist.
Examples include:
- SHA-256
- SHA-384
- SHA-512
- SHA-3
For password storage, specialized password hashing algorithms are generally more appropriate, including:
- Argon2
- bcrypt
- scrypt
Different algorithms are designed for different purposes.
Therefore, developers should choose the right tool for the specific use case.
Why SHA-256 Should Not Be Used Alone for Password Storage
SHA-256 is a fast general-purpose cryptographic hash function.
However, password hashing has different requirements.
Attackers can potentially test large numbers of password guesses quickly against fast hash functions.
Purpose-built password hashing algorithms are intentionally designed to make password guessing more expensive.
Therefore, developers should generally use algorithms such as:
- Argon2
- bcrypt
- scrypt
for password storage.
A Simple Password Hashing Flow
The process can be simplified like this.
Step 1: User Creates a Password
MyPassword123
Step 2: Password Is Processed
Password
+
Salt
↓
Password Hashing Function
Step 3: Hash Is Stored
Database
↓
Password Hash
The original password should not be stored directly.
Login Verification Flow
When the user logs in:
Step 1: User Enters Password
MyPassword123
Step 2: Application Uses the Password Hashing Algorithm
The application verifies the entered password against the stored password hash.
Step 3: Verification Result
Password Matches
↓
Login Allowed
or:
Password Does Not Match
↓
Login Rejected
A password verification library typically performs this comparison using the stored hash and its associated parameters.
Is Hashing Secure?
Hashing can provide strong security properties when implemented correctly.
However, security depends on several factors.
These include:
- The algorithm used
- The purpose of the hash
- Correct implementation
- Proper salt usage for passwords
- Appropriate work factors or cost parameters
- Protection against application vulnerabilities
For example, storing passwords with an unsalted fast hash is not considered a strong modern password storage approach.
Therefore, developers must choose the right hashing method for the task.
Can Hashes Be Cracked?
A hash is not normally “decrypted” because hashing does not use a normal reverse decryption process.
However, attackers may attempt to guess possible input values and hash those guesses.
For example:
Guess Password
↓
Hash Guess
↓
Compare With Target Hash
If the generated hash matches the target, the guessed input may be correct.
This is one reason strong, unique passwords and purpose-built password hashing algorithms are important.
Common Hash Attacks
Several attack techniques can be used against weakly protected password hashes.
1. Dictionary Attacks
An attacker may hash common passwords and compare the results with a target hash.
Examples of common passwords include predictable or widely used phrases.
Using a strong password and a slow password hashing function helps increase resistance to this type of guessing.
2. Brute-Force Attacks
An attacker may systematically try many possible passwords.
The process looks like this:
Password Guess 1
↓
Hash
↓
Compare
Password Guess 2
↓
Hash
↓
Compare
Strong password hashing algorithms increase the cost of repeated guesses.
3. Rainbow Table Attacks
Rainbow tables are precomputed collections used to speed up some password hash attacks.
Unique salts make large-scale precomputed tables much less useful because each stored password requires different hashing inputs.
Best Practices for Hashing
Developers should follow several important practices.
1. Use Modern Algorithms
Choose algorithms appropriate for the purpose.
Avoid outdated or broken algorithms for security-sensitive uses.
2. Use Specialized Password Hashing Algorithms
For passwords, use:
- Argon2
- bcrypt
- scrypt
Do not rely on plain fast hashing alone.
3. Use Unique Salts for Passwords
Unique random salts help protect against certain attacks and ensure identical passwords do not automatically result in identical hashes.
4. Do Not Create Your Own Cryptographic Algorithm
Use trusted cryptographic libraries and established standards.
5. Keep Security Libraries Updated
Security libraries should be kept current.
6. Understand the Purpose
Not every hashing algorithm is appropriate for every task.
For example:
Password Storage
↓
Argon2, bcrypt, or scrypt
File Integrity
↓
Appropriate cryptographic hash
Digital Signatures
↓
Hash + Signature Algorithm
Choosing the right tool is essential.
Hashing in JavaScript
Modern JavaScript environments provide cryptographic APIs and libraries.
For example, in a server-side Node.js environment, developers can generate a SHA-256 hash using the built-in crypto module:
const crypto = require("crypto");
const hash = crypto
.createHash("sha256")
.update("Hello World")
.digest("hex");
console.log(hash);
This generates a deterministic SHA-256 hash.
However, for password storage, developers should use a dedicated password hashing library or supported implementation rather than simply applying SHA-256.
Hashing in Modern Web Applications
A typical application may use hashing in several areas.
For example:
User Password
↓
Password Hashing
↓
Database
At the same time:
File
↓
Cryptographic Hash
↓
Integrity Check
And:
Document
↓
Hash
↓
Digital Signature
Therefore, hashing can serve different purposes across the same application.
A Simple Hashing Flow
The complete hashing process can be summarized as:
Step 1: Original Data
Hello World
Step 2: Hash Function
Hello World
↓
Hash Function
Step 3: Hash Value
Generated Hash
Step 4: Verification
Later, the system can process the relevant data again and compare the result.
Data
↓
Hash
↓
Compare With Expected Value
The overall flow is:
Input Data → Hash Function → Hash Value → Store or Compare
Final Thoughts: How Does Hashing Work?
Hashing converts data into a fixed-length value using a hash function.
The same input produces the same output under the same hashing conditions.
At the same time, even a small change to the input can produce a significantly different result.
Unlike encryption, hashing is not designed for normal reversal.
This makes it useful for password verification, data integrity checks, file verification, and many other security applications.
The key idea is simple:
Original Data → Hash Function → Hash Value
Conclusion
Hashing is an important concept in cybersecurity and modern software development.
It allows applications to create fixed-size representations of data that can be used for verification and integrity checks.
From password storage to file verification and digital signatures, hashing plays an important role in many technologies.
However, hashing must be used correctly.
Developers should select appropriate algorithms, use specialized password hashing methods for passwords, and avoid outdated cryptographic practices.
The most important difference to remember is simple:
Encryption protects data that may need to be recovered.
Hashing creates a value used to verify or compare data without normally recovering the original input.
