# nixawk/labs

Vulnerability Labs for security analysis

Repository: https://github.com/nixawk/labs
Canonical: https://ross.abutalabs.com/products/nixawk-labs
Language: Python
License Family: other
Topics: cve, vulnerability, security, exploit
Last push: 2021-03-10T10:52:05+00:00

## Health v2 (maintenance only)
Score: 32/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 0, release rhythm 35, longevity 100
- inputs: {"age_days": 3548, "days_push": 2002, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases, no_license
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1162, forks 437 (observed 2026-08-28T04:03:49.472160+00:00)

## What it is
A collection of vulnerability labs and proof-of-concept exploits for known CVEs, written primarily in Python. It serves as a security analysis resource for studying and reproducing real-world vulnerabilities.

## Use cases
- study known cve exploits
- reproduce vulnerabilities in a lab environment
- learn exploit development techniques
- security research reference for cve analysis
- practice penetration testing on known flaws

## When to choose
- you need working PoC code for specific CVEs like Dirty COW or Struts RCE
- you are building a security training or vulnerability analysis lab
- you want to study how real-world exploits are implemented in Python

## When to avoid
- you need a maintained vulnerability scanner or production security tool
- you require a licensed, supported project - it has no license file
- you need up-to-date CVE coverage - the last release was in 2021

## Facets
- artifact type: dataset
- maturity: maintenance
- function: security, penetration-testing, vulnerability-scanning
- domain: security, penetration-testing, developer-tools
- platform: python, cli
- tags: cve, exploit, vulnerability-analysis, security-research, proof-of-concept, linux

## Member repositories
- nixawk/labs (main) score 32

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:03:49.472160+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 2026-08-30T06:31:39.068006+00:00, confidence not recorded.
  - readme: https://github.com/nixawk/labs (fetched 2026-08-28T04:03:49.472160+00:00, sha e71583d34b76)
- Data as of 2026-08-30T08:39:29.467469+00:00.