Argon2 Hash Generator

Generates Argon2 hashes from a password and salt for developers, security engineers, and researchers needing configurable, memory-hard password hashing.

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1,548+
Total Calculations Run
< 15ms
Browser Execution Speed
100%
Client-Side Privacy
4.9 / 5.0
User Satisfaction

Worked Example & Common Values

Below is a sample worked calculation demonstrating how Argon2 Hash Generator processes input data instantly inside your browser.

Sample Input Length: 16, Uppercase, Numbers, Symbols
Computed Result k9#vP2$mQ8!xZ5@y (Strong, high-entropy password)
Execution Mode Client-Side In-Browser JS
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About This Tool

The Argon2 Hash Generator computes an Argon2 hash from a plaintext password and a salt, using user-specified parameters. It supports Argon2id, Argon2i, and Argon2d variants, with options for version, hash length, memory_cost, time_cost, and parallelism. The tool outputs an encoding suitable for storage (PHC string) and can emit raw hash bytes if requested. It is designed for developers, security teams, and researchers who need reproducible hash outputs for authentication tests, benchmarks, and threat modeling.

Conceptually, Argon2 is a memory-hard key derivation function. The tool performs input validation, converts numeric parameters to internal units (memory_cost in KiB, time_cost in iterations), and executes the selected variant with the supplied salt and password. The result is a single hash value plus a standard header containing the type, version, and parameters. For interoperability, the tool can provide the PHC-compatible string or the raw hash, depending on workflow needs.

Who benefits: software engineers integrating password storage, security architects evaluating parameter trade-offs, auditors validating configurations, and educators building labs. Use cases include hashing sample credentials for test environments, teaching Argon2 behavior, or comparing performance across configurations. The tool helps ensure consistent results across languages and libraries by exposing explicit parameters and a stable salt, enabling reproducible security experiments.

Unique value: explicit control over Argon2 variant, version, and encoded output; built-in validation to prevent weak configurations; clear sample PHC output format; and the ability to export the encoded string for integration into codebases or configuration files. The tool emphasizes risk-aware defaults while allowing advanced tuning for performance benchmarks and compliance reporting.

How to Use

Provide inputs: password, salt, type, hash_len, memory_cost, time_cost, parallelism.
Choose variant and version: select Argon2id by default for general use; adjust version if needed.
Run calculation: execute the hash with the given parameters to obtain a PHC string or raw hash.
Review outputs: verify the encoded string contains type, v, m, t, p, salt, and hash; copy for storage or integration.
Export as needed: use the result in code, configuration, or test data.

How to use argon2 password generator

Frequently Asked Questions

Find Quick Answers

What is Argon2 used for?
Argon2 is a memory-hard password hashing function designed to resist GPU cracking and side-channel attacks. It produces a secure, salted hash suitable for password storage and verification, with tunable memory, time, and parallelism parameters to balance security and performance.
Which Argon2 variant should I choose?
Argon2id is generally recommended for production use as it blends memory-hardness with resistance to side-channel and precomputation attacks. Argon2i emphasizes side-channel resistance, while Argon2d favors fast hashing and may be more vulnerable to GPU-based attacks.
What is PHC string and why use it?
PHC (Password Hashing Competition) string encodes the variant, version, parameters, salt, and hash in a single portable format. It enables straightforward storage, interoperability across languages, and easy parameter auditing without requiring separate fields.
How should I choose memory and time costs?
Higher memory_cost increases resistance to GPU cracking but lowers performance. Time_cost controls iterations, affecting latency. Start with moderate values (e.g., memory_cost in tens to hundreds of KiB and time_cost of 2–4), then benchmark in your environment to meet security and performance targets.

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