# berylliumsec/nebula

AI-powered penetration testing assistant for automating recon, note-taking, and vulnerability analysis.

Repository: https://github.com/berylliumsec/nebula
Canonical: https://ross.abutalabs.com/products/berylliumsec-nebula
Homepage: https://www.berylliumsec.com
Language: Python
License: BSD-2-Clause
License Family: permissive
Topics: ethical-hacking-tool, penetration-testing-framework, penetration-testing-tool, ai-powered-ethical-hacking-tool, ai-powered-penetration-testing-tool, ai, python, cybersecurity, cybersecurity-tools, ethical-hacking, llm, security-automation, vulnerability-assesment-tools, vulnerability-assessment, vulnerability-scanners
Last push: 2026-09-02T11:01:01+00:00

## Health v2 (maintenance only)
Score: 92/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 100, release rhythm 92, longevity 76
- inputs: {"age_days": 1068, "days_push": 0, "days_rel": 53, "gap_med": 0, "n_releases_24m": 32}
- flags: none
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1097, forks 167 (observed 2026-09-03T02:15:09.579267+00:00)

## What it is
Nebula is an AI-powered penetration testing desktop application that combines a terminal, browser, notes, findings, and reporting into one workbench. It uses LLMs (hosted, local, or OpenAI-compatible) to assist with recon, note-taking, and vulnerability analysis while keeping the operator in control via scope enforcement, approval pauses, and isolated execution.

## Use cases
- automate recon during a pentest
- AI-assisted vulnerability analysis
- take notes and generate pentest reports
- run security engagements from one desktop workbench
- use an LLM assistant for ethical hacking tasks

## When to choose
- you are a pentester wanting AI assistance with built-in scope and approval controls
- you want an integrated terminal, evidence, findings, and reporting workflow
- you need support for local or OpenAI-compatible model runtimes

## When to avoid
- you need a stable production tool - it is an alpha preview release
- you are not authorized to test the target systems
- you only need a simple vulnerability scanner without an AI workflow

## Facets
- artifact type: application
- maturity: experimental
- function: security, penetration-testing, llm-inference, agent-framework, terminal-ui
- domain: security, penetration-testing, artificial-intelligence, developer-tools
- platform: -
- tags: pentesting, ai-assistant, vulnerability-assessment, recon, ethical-hacking, offensive-security, linux, desktop, docker

## Member repositories
- berylliumsec/nebula (main) score 92

## Provenance
- Observed fields: from GitHub, fetched 2026-09-03T02:15:09.579267+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T06:47:41.080580+00:00, confidence not recorded.
  - readme: https://github.com/berylliumsec/nebula (fetched 2026-09-03T02:15:09.579267+00:00, sha 2a07afdd26c5)
- Data as of 2026-08-30T08:39:29.467469+00:00.