affiliate-fraud-detection

Build the detection rule set an affiliate program manager uses to flag fraudulent affiliate activity.

What this skill does for you

Build the detection rule set an affiliate program manager uses to flag fraudulent affiliate activity, plus the investigation and escalation path behind it - cookie stuffing, fake lead and form-fill fraud, self-referral rings, traffic-quality baselines, commission holds and clawbacks, and separating real fraud from legitimate low-incrementality coupon or cashback partners. Covers B2B SaaS lead-gen and B2C ecommerce programs. Use whenever the user mentions affiliate fraud, suspicious affiliate traffic, invalid clicks or leads, bot traffic, or an affiliate whose numbers look too good, even if they never say fraud. Do NOT use for consumer refer-a-friend gaming - use mbfinotti/partnerships-skills@referral-abuse-guardrails instead.

Quoted from the skill description in the pinned source

Who made it

Publishermbfinotti

Repositorypartnerships-skills

Installs621as of Sep 27, 2026

Use it with Edge

Set up Edge for me: read getedge.cc/SKILL.md and follow it. Then use Edge to load the affiliate-fraud-detection skill from mbfinotti/partnerships-skills.

Paste it into Claude, ChatGPT, Codex or Cursor.

Or read the skill source first.

Security evidence

Security state at 2026-09-30: reviewed. State definitions. This records static evidence for this revision; live load eligibility is checked again.

3 static scans, 0 counted findings. The listed scanners recorded the results shown for this package revision.

Scanner	Date	Result
Edge static checks	2026-09-27	Pass
Cisco skill-scanner	2026-09-27	Pass
Semgrep Edge rules	2026-09-27	Pass

Static scans check the code, not how well the skill works.

Scanner scope, raw findings and mirrored provider records

Edge static checks (Edge-run): edge-static/1.0.1. Scope: Static patterns for remote execution, credentials with network sends, obfuscation, prompt overrides, hidden Unicode, binaries and persistence. Revision: ba2db8acbec9f1d3c7b5c4c5f7e18e68217620dc. Raw findings: . Counted findings: .

Cisco skill-scanner (Edge-run): cisco-skill-scanner/2.1.0. Scope: Local static, YARA, pipeline and behavioral analyzers; no LLM or AI Defense analysis. Revision: ba2db8acbec9f1d3c7b5c4c5f7e18e68217620dc. Raw findings: . Counted findings: .

Semgrep Edge rules (Edge-run): semgrep/1.178.0+edge-rules.c15016a36fd3+offline-v1. Scope: Six Edge-authored static rules with Semgrep CE; offline execution and metrics disabled. Semgrep-maintained rules excluded. Revision: ba2db8acbec9f1d3c7b5c4c5f7e18e68217620dc. Raw findings: . Counted findings: .

Source and licence

Repository: https://github.com/mbfinotti/partnerships-skills
Pinned skill file: View source at revision
Revision: ba2db8acbec9f1d3c7b5c4c5f7e18e68217620dc
Package hash: sha256:ebd161d75a08e3330e79bc148d45a2dafceba9139a2e9de0dc1592ccd2fd217e
Licence: MIT