# tmylla/Awesome-LLM4Cybersecurity

An overview of LLMs for cybersecurity.

Repository: https://github.com/tmylla/Awesome-LLM4Cybersecurity
Canonical: https://ross.abutalabs.com/products/awesome-llm4cybersecurity
Homepage: https://tmylla.github.io/Awesome-LLM4Cybersecurity/
Language: JavaScript
License Family: other
Last push: 2026-08-20T13:20:10+00:00

## Health v2 (maintenance only)
Score: 70/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 98, release rhythm 35, longevity 68
- inputs: {"age_days": 954, "days_push": 13, "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 1761, forks 189 (observed 2026-08-28T04:05:32.557903+00:00)

## What it is
A curated awesome-list and systematic literature review tracking 861+ papers on large language models applied to cybersecurity, organized into 11 categories such as LLM-assisted defense, vulnerability detection, and agentic cyber systems. It accompanies an arXiv survey paper and includes a web-based paper explorer for searching and filtering the corpus.

## Use cases
- find research papers on LLMs for cybersecurity
- survey the state of LLM-based vulnerability detection
- research LLM-assisted attack and defense techniques
- find fine-tuned security domain LLMs
- track recent papers on AI agents for cybersecurity
- find evaluation benchmarks for security LLMs

## When to choose
- you need a comprehensive, regularly updated bibliography of LLM-for-security research
- you are writing a survey or literature review on LLMs in cybersecurity
- you want to discover benchmarks, domain LLMs, or agentic security research directions

## When to avoid
- you need runnable software or tools rather than paper references
- you need production security tooling for defending systems
- you require a formally licensed dataset (the repo has no license)

## Facets
- artifact type: learning-resource
- maturity: active
- function: documentation, security, llm-inference
- domain: security, large-language-models, artificial-intelligence, awesome-lists, developer-tools
- platform: -
- tags: awesome-list, cybersecurity, systematic-literature-review, research-papers, llm4security, vulnerability-detection, threat-intelligence, web-server

## Member repositories
- tmylla/Awesome-LLM4Cybersecurity (main) score 70

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:05:32.557903+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 2026-08-30T03:27:13.033956+00:00, confidence not recorded.
  - readme: https://github.com/tmylla/Awesome-LLM4Cybersecurity (fetched 2026-08-28T04:05:32.557903+00:00, sha 35e9f3093b94)
  - homepage: https://tmylla.github.io/Awesome-LLM4Cybersecurity/ (fetched 2026-08-29T11:05:49.060778+00:00, sha c83206b3fba9)
- Data as of 2026-08-30T08:39:29.467469+00:00.