RCR v0.3 — RuleFlow Chain Runner
A GUI front-end for the RuleFlow pipeline: rulest + concentrator + ranker, all wired together to get the most out of the extracted Hashcat rules.
What it actually does
You feed it three files—a base wordlist, a target wordlist, and cracked passwords. You select an OpenCL device, choose a preset, and you can adjust the expected runtime (higher values result in more chains generated), click Run, and the program runs through the entire chain: informed extraction, genetic rule extraction, rule cleaning/optimization, and then scoring and ranking the survivors from the larger results. Finally, you get a structured CSV file.
The presets
Mode Generations Populations Best for
Fast 150 300 Quick tests, medium dictionaries
Balanced 300 600 Daily driver, good default
Maximum 500 1000 Deep runs, large or stubborn sets
Why I built this
The backend tools are solid, but running them one-by-one with long command lines gets old fast. This wraps the whole flow in a single window with:
Live log with ANSI colors, horizontal scrolling for long lines, and auto-trim so it doesn't choke on verbosity
Memory watchdog — monitors RAM/VRAM usage and auto-suggests switching to Low-Memory preset if a stage gets killed by OOM
OpenCL device scanner — detects your GPU or falls back to CPU without manual --device flags
MAB vs Legacy ranker — pick adaptive bandit sampling for huge skewed rule sets, or exhaustive scoring when you want full statistical accuracy
Quick start
git clone https://github.com/A113L/ruleflow.git
cd ruleflow
python rcr
[image: 1783156184940-rcr-midrun.jpg]
Requires Python 3 + tkinter. The backend scripts (rulest_v2.py, concentrator.py, ranker.py) should be in the same directory.
Feedback or bug reports welcome — this is a personal tools that grew a UI, so rough edges are expected.
