What SC&MS is

The Scam Classification & Mapping System (SC&MS) is a research framework built around a structured taxonomy for classifying scam techniques from first contact to financial extraction. It provides a common language for describing how scams work, breaking them into reusable components across a six-stage lifecycle.

SC&MS organizes scam behavior into the ABCDEF lifecycle:

  • Access: vectors used to initiate first contact with a potential victim
  • Bait: lures, offers, and alerts used to entice a victim's engagement
  • Coercion: pressure and control tactics used to compel action or maintain compliance
  • Deception: fabricated or manipulated artifacts used to mislead victims and make the scam believable
  • Exploiting Trust: borrowed or cultivated trust used to lower a victim's skepticism
  • Financial Gain: methods used to extract money, assets, or other value from victims

Version 0.3 includes 156 techniques and subtechniques across these six stages, each documented with descriptions and tags for filtering.

Why it exists

Scam losses dwarf most other categories of cybercrime, yet reporting and classification remain inconsistent across sectors and jurisdictions. Defenders describe the same scam behavior in different terms, which makes it harder to share intelligence or coordinate a response.

SC&MS exists to give researchers and fraud teams a common, lifecycle-based vocabulary for classifying scam behavior consistently.

What makes it different

Most scam classification treats scams as categories: romance scam, tech support scam, investment scam. SC&MS treats them as combinations of reusable techniques. A romance scam and an investment scam may share the same access vector, the same coercion tactics, and the same extraction method. The taxonomy captures those shared components.

The ABCDEF lifecycle is victim-centric. It tracks what happens to the person being scammed, from the moment of first contact through financial extraction. This makes it useful for analyzing scam operations and communicating across teams that use different terminology.

Who it is for

  • Security and fraud teams mapping detection capabilities against scam techniques
  • Researchers analyzing scam campaigns with consistent terminology
  • Threat intelligence teams structuring scam-related reporting
  • Law enforcement categorizing and tracking scam operations across jurisdictions
  • Financial institutions classifying fraud incidents for internal and cross-industry use
  • Educators building scam awareness and prevention curricula

Current status

SC&MS is currently at version 0.3, published under CC BY-ND 4.0. The license transitions to CC BY 4.0 on December 31, 2027. The taxonomy source is available on GitHub and can be explored interactively in the Explorer.

Permanence

SC&MS makes two promises that are really one. Technique IDs are frozen and never renumbered: once assigned, an ID points to the same technique for the life of the framework. Technique URLs carry that same guarantee. Every technique has a permanent, citable page at https://scams.dev/techniques/<ID>/. SC&MS will not intentionally reassign or break these URLs, and its continuity policy preserves the underlying ID-to-technique mapping in the public taxonomy repository, independently of this website.

How to cite

If you use SC&MS in research or operational work, please cite the framework or an individual technique by its permanent URL. To cite the framework as a whole: 

Narang, S. S. (2026). SC&MS: Scam Classification & Mapping System (Version 0.3) [Data set]. https://scams.dev/

For example, to cite technique B003: 

Narang, S. S. (2026). B003, in SC&MS: Scam Classification & Mapping System (Version 0.3) [Data set]. https://scams.dev/techniques/B003/

A BibTeX entry is available in the taxonomy README, and each technique page carries its own cite block.

Maintainer

SC&MS is created and maintained by Satnam Singh Narang.

Independence

SC&MS is an independent research project. It is not affiliated with, sponsored by, or endorsed by any employer, vendor, or organization. The taxonomy reflects independent analysis built on nearly two decades of research.