A local-first CLI recon triage assistant for authorised bug bounty workflows.
Project description
BugSlyce
BugSlyce is a local-first, evidence-led recon triage tool for authorised labs, CTFs and scoped assessments. It runs bounded project workflows, preserves local artefacts, builds operator reports and helps prioritise manual review.
BugSlyce is not an exploitation framework, vulnerability scanner or automated pentesting platform. Its reports describe observed evidence and review leads; BugSlyce does not claim confirmed vulnerabilities.
Current package version: 1.0.0. BugSlyce v1.0.0 is the current stable
release.
Authorised Use
Use BugSlyce only against systems you own or are explicitly authorised to
assess. The generated scope.md template is a local safety aid, not proof of
authorisation. Always review scope and programme rules before running recon.
Supported Host Expectations
BugSlyce is intended for Linux operator workstations. It has been developed and validated on Kali Linux and Linux Mint. Other Debian-derived Linux systems, including Ubuntu, are expected to work when the required Python version and external tools are available, but they are not currently part of the directly validated host set. Native Windows and macOS operation is not currently claimed.
What BugSlyce Provides
- Local project scaffolding and scope templates.
- Passive doctor/readiness checks.
- Bounded Quick, Standard and Deep Recon project workflows.
- Deterministic reports, runbooks, status files and pipeline metadata.
- Local evidence-pack ZIP export.
- Conservative resume behaviour for completed or clearly reusable work.
- Offline interpretation that keeps raw evidence separate from conclusions.
Operator Modes
| Mode | Profile | Purpose |
|---|---|---|
| Manual Setup Only | none | Create project metadata and scope.md without running recon. |
| Quick Recon | lab-safe-tiny |
Fast first-pass bounded collection using the bundled lab-root-tiny wordlist. |
| Standard Recon | standard-bounded |
Bounded collection plus offline interpretation using standard-bounded-core. |
| Deep Recon | deep-bounded |
Bounded same-origin Deep collection and offline review orchestration using deep-bounded-core. |
Install from PyPI
Install BugSlyce as an isolated command-line application with pipx:
sudo apt update
sudo apt install pipx nmap curl gobuster
pipx ensurepath
pipx install bugslyce
Open a new terminal if pipx ensurepath asks you to refresh your shell, then
run the doctor before recon:
bugslyce doctor
Source Install
For a source install on a Debian-derived workstation:
sudo apt update
sudo apt install git python3 python3-venv nmap curl gobuster
git clone https://github.com/Rayza-Slyce/bugslyce.git
cd bugslyce
python3 -m venv .venv
source .venv/bin/activate
python -m pip install --upgrade pip
python -m pip install .
bugslyce doctor
If the virtual environment is not active, use:
./.venv/bin/bugslyce doctor
Detailed setup instructions are in docs/INSTALLATION.md.
First Launch
Most operators should start with the guided launcher:
bugslyce
The launcher can create a project, ask for engagement context, choose a mode,
show the exact command that will run and require an exact YES confirmation
before live recon starts.
Output Overview
A completed project commonly contains:
bugslyce_project.json: project metadata.scope.md: operator-reviewed scope template.recon_manifest.json: collected evidence manifest.report.md: evidence-led report and review leads.recon_status.mdandrecon_status.json: current progress and next-step context.runbook.md: operator guide for the local project.project_pipeline.mdandproject_pipeline.json: pipeline step history.- an adjacent evidence-pack ZIP.
Deep Recon additionally retains:
deep_source_route_collection.mddeep_source_route_collection.jsondeep_recon_review.mddeep_recon_runbook.mddeep_recon_orchestration.json
The evidence pack may contain target identifiers, service banners, headers, HTML and discovered paths. Store and share it carefully. It is not proof that a vulnerability exists.
Resume Summary
Completed Quick, Standard and Deep projects may be resumed as verified reuse. A completed Deep resume is a no-op apart from local validation and leaves canonical artefacts unchanged. Partial Deep network state fails closed because the complete in-memory response bodies required for offline Deep analysis are not persisted. Use a clean project for an explicit Deep rerun after an unsafe partial state.
Interactive resume preview is read-only. Declining resume changes no canonical project files.
More Documentation
Development and Testing Status
The package version is 1.0.0. The deterministic test suite mocks live
execution and should not contact targets. Local development checks include:
python -m pytest
bugslyce doctor
bugslyce --help
Licence
BugSlyce is released under the MIT Licence. See LICENSE.
Project details
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