Hashcat Rule Performance Benchmark

Aether

GPU-accelerated rule performance testing with radar charts, heatmaps, statistical analysis, and configuration confirmation. 50 built-in test words.

OpenCL GPU Radar Charts Heatmaps Config Confirmation 50 Test Words

Overview

Aether benchmarks the performance of individual Hashcat rules using GPU acceleration, generating detailed statistics and visualizations to help you understand which rules perform best and why.

Unlike Ranker (which ranks rules by hit rate on real hashes), Aether measures raw performance characteristics — execution speed, transformation diversity, and edge case behavior — useful for profiling and optimizing new rules before deployment.

Core Features

⚡

OpenCL GPU acceleration

Massively parallel rule testing using the shared OpenCL kernel. Multi-iteration averaging for statistical robustness.

◈

Radar charts & heatmaps

Visualize rule performance across multiple metrics simultaneously. Export charts as PNG or SVG.

✓

Config confirmation UX

Interactive summary displayed before execution. Prevents accidental long benchmark runs.

⌥

50 built-in test words

Carefully curated word set covering all rule categories. No external dictionary required.

∑

Statistical summaries

Mean, median, stddev, and percentile metrics per rule. CSV and JSON export.

Benchmarking Workflow

Step 1

Load & configure

Load rule files and display config summary for user confirmation.

Step 2

Initialize OpenCL

Compile kernel and allocate device memory for rules and test words.

Step 3

Multi-iteration testing

Each rule tested with multiple iterations for statistical accuracy.

Step 4

Calculate metrics

Compute performance statistics across all dimensions.

Step 5

Generate visualizations

Produce radar charts, heatmaps, and distribution plots.

Step 6

Export results

Save sorted rules and full performance report (CSV/JSON).

Visualization Types

◈

Radar chart

Multi-axis performance plot — speed, diversity, coverage, and consistency per rule.

⊞

Heatmap

Rule × word matrix showing transformation output diversity.

∫

Distribution plot

Histogram of output length changes and character modification patterns.

Integration

Aether is most useful after Ranker has identified your top rules. Use Aether to deeply profile the top-k rules and understand their characteristics before deploying in a real session.

Ranker docs OpenCL kernel