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‎LICENSE‎

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MIT License
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Copyright (c) 2026 Georg Wallisch
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Permission is hereby granted, free of charge, to any person obtaining a copy
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of this software and associated documentation files (the "Software"), to deal
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in the Software without restriction, including without limitation the rights
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to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
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copies of the Software, and to permit persons to whom the Software is
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furnished to do so, subject to the following conditions:
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The above copyright notice and this permission notice shall be included in all
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copies or substantial portions of the Software.
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THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
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IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
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FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
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AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
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LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
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OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
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SOFTWARE.

‎README.md‎

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# gwtools
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Small security-focused command-line utilities.
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Currently included:
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- `gwpgen.py` – entropy-driven, cryptographically sound password generator
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---
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## gwpgen – Entropy-Driven Password Generator
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`gwpgen` is a cryptographically clean password generator designed with
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a strict focus on:
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- measurable entropy instead of arbitrary complexity rules
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- unbiased random selection (rejection sampling)
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- bias-free Fisher–Yates shuffle
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- explicit character class enforcement
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- reproducible entropy targets (e.g. 100-bit, 256-bit)
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The design goal is not “memorable passwords” but mathematically
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well-defined randomness suitable for:
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- WPA/WPA3 PSKs
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- API keys
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- device provisioning
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- offline secrets
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- infrastructure credentials
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---
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## Design Principles
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### 1. Entropy-Based Length Calculation
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Password length is derived from the requested entropy:
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length = ceil(target_entropy / log2(alphabet_size))
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No arbitrary length defaults.
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---
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### 2. Uniform Randomness
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Character selection uses rejection sampling to avoid modulo bias.
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---
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### 3. Bias-Free Shuffle
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Class-enforced characters are shuffled using a cryptographically correct
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Fisher–Yates algorithm without modulo bias.
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---
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### 4. No Policy Theater
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No artificial "must contain symbol" rules unless explicitly requested.
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Character classes are enforced only if selected.
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---
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## Examples
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Generate 100-bit alphanumeric password:
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python3 gwpgen.py --strong --alphanum
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MIT License – see LICENSE file.

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