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Geoffrey Kim
Geoffrey Kim

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Finding the Optimal Bcrypt Rounds for Your Machine

When it comes to securely storing user passwords, using a strong hashing algorithm like bcrypt is essential. Bcrypt is designed to be slow and computationally expensive, making it resistant to brute-force attacks. One of the key parameters in bcrypt is the number of rounds, which determines the computational cost and time required to compute the hash.

Choosing the right number of rounds is crucial for balancing security and performance. A higher number of rounds increases the security by making it harder for attackers to crack passwords, but it also increases the time it takes to compute the hash. On the other hand, a lower number of rounds might be faster but compromises security.

So, how do you find the optimal number of rounds for your specific hardware? In this blog post, we'll walk through the process of testing and determining the right number of rounds for your machine, whether it's a desktop, laptop, or server.

Step 1: Set Up the Environment

To get started, make sure you have Node.js installed on your machine. Create a new directory for your project and initialize a new Node.js project by running npm init -y in the terminal.

Next, install the bcrypt library by running npm install bcrypt. This library provides an implementation of the bcrypt hashing algorithm for Node.js.

Step 2: Create a Benchmarking Script

Create a new file named bcrypt-benchmark.js and add the following code:

const bcrypt = require('bcrypt');

const testRounds = async (rounds) => {
  const startTime =;
  const hash = await bcrypt.hash('password123', rounds);
  const endTime =;
  const duration = endTime - startTime;
  console.log(`Rounds: ${rounds}, Duration: ${duration}ms`);

const findOptimalRounds = async () => {
  for (let rounds = 8; rounds <= 16; rounds++) {
    await testRounds(rounds);

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This script does the following:

  1. It imports the bcrypt library.
  2. The testRounds function takes a number of rounds as input, hashes a sample password using bcrypt with the specified rounds, and measures the duration it takes to compute the hash.
  3. The findOptimalRounds function iterates over a range of rounds (in this example, from 8 to 16) and calls the testRounds function for each round.
  4. The script then executes the findOptimalRounds function.

Step 3: Run the Benchmarking Script

Execute the benchmarking script by running node bcrypt-benchmark.js in the terminal. The script will output the duration (in milliseconds) for each number of rounds.

Look for the number of rounds that falls within the desired range of 250ms to 500ms on your machine. This range is considered a good balance between security and performance.

For example, the output might look something like this:

Rounds: 8, Duration: 123ms
Rounds: 9, Duration: 251ms
Rounds: 10, Duration: 489ms
Rounds: 11, Duration: 972ms
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In this case, 9 or 10 rounds would be suitable for your machine, as they fall within the desired range.

Step 4: Verify and Adjust

It's recommended to run the benchmarking script a few times to get an average duration for each number of rounds. Keep in mind that the optimal number of rounds may vary depending on your machine's hardware specifications and system load.

If the durations are consistently too fast or too slow, you can adjust the range of rounds being tested in the findOptimalRounds function accordingly.


Finding the optimal number of bcrypt rounds for your machine is an important step in ensuring the security and performance of your application. By using a benchmarking script, you can determine the number of rounds that provides a good balance between security and acceptable hashing time.

Remember to periodically review and update the number of rounds as hardware and computational power evolve over time. This will help maintain the desired level of security for your application.

By following the steps outlined in this blog post, you can confidently configure bcrypt with the appropriate number of rounds for your machine, whether it's a desktop, laptop, or server, ensuring the protection of user passwords while maintaining optimal performance.

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