# safe-graph/graph-fraud-detection-papers

A curated list of Graph/Transformer-based fraud, anomaly, and outlier detection papers & resources

Repository: https://github.com/safe-graph/graph-fraud-detection-papers
Canonical: https://ross.abutalabs.com/products/graph-fraud-detection-papers
Homepage: https://safe-graph.github.io/paper_dashboard/
License Family: other
Topics: fraud-detection, security, awsome-list, papers, machine-learning, data-science, deep-learning, graph-algorithms, graph-neural-networks, graph-convolutional-networks, academic-publications, spam-detection, data-mining, anomaly-detection, dataset, outlier-detection, survey, llm, transformer, foundation-models
Last push: 2026-06-29T04:42:42+00:00

## Health v2 (maintenance only)
Score: 73/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 90, release rhythm 35, longevity 100
- inputs: {"age_days": 2477, "days_push": 65, "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 1889, forks 298 (observed 2026-08-28T04:05:49.375005+00:00)

## What it is
A curated awesome-list of academic papers and resources on graph- and transformer-based fraud, anomaly, and outlier detection, organized by year and topic. It includes an interactive paper dashboard and a companion RAG-based LLM chatbot for querying the collected literature.

## Use cases
- find papers on graph neural network fraud detection
- survey transformer-based anomaly detection research
- find datasets for fraud detection research
- keep up with latest LLM fraud detection papers
- research resources for building a fraud detection system
- find outlier detection papers with code

## When to choose
- you need a curated reading list of fraud/anomaly detection literature
- you want paper links with venues and code in one place
- you want to explore graph neural network applications in fraud detection

## When to avoid
- you need production-ready fraud detection software
- you want a runnable library rather than a paper collection

## Facets
- artifact type: learning-resource
- maturity: active
- function: machine-learning, nlp, search-engine, rag
- domain: machine-learning, security, data-science, awesome-lists, tutorials
- platform: python
- tags: awesome-list, fraud-detection, anomaly-detection, graph-neural-networks, transformers, academic-papers, survey, outlier-detection, spam-detection, foundation-models, web

## Member repositories
- safe-graph/graph-fraud-detection-papers (main) score 73

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:05:49.375005+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 2026-08-30T03:13:10.304730+00:00, confidence not recorded.
  - readme: https://github.com/safe-graph/graph-fraud-detection-papers (fetched 2026-08-28T04:05:49.375005+00:00, sha 5eb75d27665e)
  - homepage: https://safe-graph.github.io/paper_dashboard/ (fetched 2026-08-29T10:52:38.062468+00:00, sha cdded6a22fe5)
- Data as of 2026-08-30T08:39:29.467469+00:00.