# Kim-Hammar/awesome-rl-for-cybersecurity

A curated list of resources dedicated to reinforcement learning applied to cyber security.

Repository: https://github.com/Kim-Hammar/awesome-rl-for-cybersecurity
Canonical: https://ross.abutalabs.com/products/awesome-rl-for-cybersecurity
License: NOASSERTION
License Family: other
Last push: 2026-07-21T18:06:50+00:00

## Health v2 (maintenance only)
Score: 74/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 93, release rhythm 35, longevity 100
- inputs: {"age_days": 1723, "days_push": 43, "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 1085, forks 145 (observed 2026-08-28T04:03:31.917764+00:00)

## What it is
A curated awesome-list of resources for applying reinforcement learning to cyber security, including RL environments, papers, books, blog posts, and talks. It focuses exclusively on RL-based work, excluding general machine learning approaches.

## Use cases
- find reinforcement learning papers on cybersecurity
- discover RL environments for security research
- learn about autonomous security management with RL
- find datasets and simulators for RL-based intrusion response
- start researching RL for network defense
- find books and talks on RL for security

## When to choose
- you need a starting point for RL-in-cybersecurity research
- you want curated papers, environments, and talks in one place
- you are looking for RL cyber ranges and simulation platforms

## When to avoid
- you need general machine learning for cybersecurity resources
- you need runnable software rather than a resource list
- you need production security tooling

## Facets
- artifact type: learning-resource
- maturity: active
- function: reinforcement-learning, security, documentation
- domain: security, reinforcement-learning, awesome-lists
- platform: cross-platform
- tags: awesome-list, curated-resources, cyber-range, research-papers, rl-environments

## Member repositories
- Kim-Hammar/awesome-rl-for-cybersecurity (main) score 74

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:03:31.917764+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 2026-08-30T06:49:41.244875+00:00, confidence not recorded.
  - readme: https://github.com/Kim-Hammar/awesome-rl-for-cybersecurity (fetched 2026-08-28T04:03:31.917764+00:00, sha 77d2109154a6)
- Data as of 2026-08-30T08:39:29.467469+00:00.