Affiliate Fraud Detection
by mbfinottiba2db8acbec9MIT1 starsListed Oct 8, 2026Updated Oct 8, 2026Repository updated 3 weeks ago
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.
Only the file list is public. File contents are available once the skill is installed in a workspace.
| Path | Size | Type |
|---|---|---|
| evals/evals.json | 37.6 KB | application/json |
| references/detection-signals.md | 10 KB | text/markdown |
| references/false-positives-and-incrementality.md | 7.2 KB | text/markdown |
| references/fraud-taxonomy.md | 5.8 KB | text/markdown |
| references/investigation-and-enforcement.md | 5.9 KB | text/markdown |
| references/worked-examples.md | 8 KB | text/markdown |
| SKILL.md | 19.9 KB | text/markdown |
Source and attribution
Source:mbfinotti/partnerships-skillsinskills/affiliate-fraud-detectionat commitba2db8a
License: MIT
Content belongs to its original authors. SourceWeft indexes it from a public repository.
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