# admintony/Prepare-for-AWD

AWD攻防赛脚本集合

Repository: https://github.com/admintony/Prepare-for-AWD
Canonical: https://ross.abutalabs.com/products/prepare-for-awd
Language: Python
License Family: other
Last push: 2019-10-17T01:09:45+00:00

## Health v2 (maintenance only)
Score: 32/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 0, release rhythm 35, longevity 100
- inputs: {"age_days": 3218, "days_push": 2513, "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 1075, forks 217 (observed 2026-08-28T04:03:29.233188+00:00)

## What it is
A collection of Python and PHP scripts for AWD (Attack with Defense) CTF competitions, including batch attack scripts for planting and triggering webshells to grab flags, plus defense scripts for file monitoring, WAF logging, and countering persistent shells. It is a toolkit aimed at offline capture-the-flag attack/defense matches.

## Use cases
- batch getflag from webshells during AWD CTF
- deploy persistent PHP webshells across opponent hosts
- monitor and auto-delete modified PHP files to defend a server
- analyze Apache access logs for attack traffic
- counter immortal webshells on a compromised box

## When to choose
- preparing for an AWD-style attack-defense CTF
- you need ready-made batch attack and defense scripts for offline CTF matches

## When to avoid
- production security operations - scripts are competition-grade and unvetted
- you need a maintained tool with a license or active releases

## Facets
- artifact type: cli-tool
- maturity: maintenance
- function: security, penetration-testing, web-scraping, developer-tools
- domain: security, penetration-testing, developer-tools
- platform: python, cli
- tags: awd, ctf, capture-the-flag, webshell, attack-defense, offensive-security, waf, log-analysis, linux

## Member repositories
- admintony/Prepare-for-AWD (main) score 32

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:03:29.233188+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 2026-08-30T06:53:25.377952+00:00, confidence not recorded.
  - readme: https://github.com/admintony/Prepare-for-AWD (fetched 2026-08-28T04:03:29.233188+00:00, sha 4d977741ca37)
- Data as of 2026-08-30T08:39:29.467469+00:00.