SCAMSTER DETECTION FILTER
SCAMSTER DETECTION FILTER
Stop Repeat Scam Profiles, Stolen Photos & Fraud Tactics with Real-Time AI
Mediafirewall AI’s Scamster Detection Filter flags known scamsters and image-pattern matches before profiles go live. We detect stolen or re-used photos, deceptive thumbnails, and fraud bait that pushes off-platform payments. Profiles are checked against a Scamster Database plus face-match and text/image signals.Protect users, prevent romance scams, and enforce policy with audit-ready, pre-visibility decisions.
Supported Moderation
Every image, video, or text is checked instantly no risks slip through.
What Is a Scamster Detection Filter?
Impersonation Flagging
Identifies uploaded photos that mimic celebrities, influencers, or known personas common in romance scams and social engineering a... Read more
Fraud Pose Detection
Flags overly staged portraits, stock-model aesthetics, exaggerated professionalism, or fake uniforms, that scammers often use to f... Read more
Image Source Screening
Verifies if the image appears in scam-heavy domains, reverse image trails, or public web results—filtering content scraped for dec... Read more
Synthetic Visual Artifact Detection
Surfaces telltale signs of altered or AI-synthesized imagery: unnatural skin tones, inconsistent shadows, or blurred contours that... Read more
Built-In Policy Matching
Aligns with your platform’s custom image rules to auto-enforce takedowns, blocks, or escalation, no manual review needed.
How our Moderation Works
Mediafirewall’s Scamster Detection Filter integrates directly into your image moderation pipeline. The moment a photo is uploaded, the system evaluates it against a curated visual intelligence graph, spotting red flags linked to impersonation, visual fraud tactics, and reused scam assets. Every image is scored, flagged, or cleared in milliseconds, with no manual triage, ensuring uninterrupted user onboarding and platform safety.
Why Mediafirewall’s Scamster Detection Filter?
When deception looks real and intentions are hidden, trust can be exploited. This filter goes beyond detection—it empowers enterprises to identify scamsters and safeguard digital integrity across all formats.
Pre-Onboarding Fraud Prevention
Screen out scam profiles before they're live. Block scam attempts at the upload ... Read more
Confidence for High-Risk Categories
Whether it’s dating platforms, peer-to-peer marketplaces, or education portals—u... Read more
Lower Cost of Trust & Safety Ops
Minimize the burden on moderation teams. Automate visual screening to prevent es... Read more
Configurable by Risk Level
Deploy custom thresholds per region, product, or demographic. Adapt precision wi... Read more
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Scamster Detection Filter FAQ
It combines Scamster Database lookups with face match, web-image checks, and OCR to flag re-used photos, stolen assets, and fraud cues before profiles go live.
Romance scams exploit trust with polished photos and quick off-platform moves; pre-visibility checks reduce financial loss and abuse.
At account creation, on profile/photo edits, and during re-verification, with continuous checks on reported accounts.
In profile headshots, gallery images, bios, and text-on-image overlays (QR codes, coupon codes, payment handles.
Users avoid fraud and catfishing; platforms reduce chargebacks, support load, and brand-trust erosion.
Yes robust face match and visual similarity cues tolerate crops, filters, lighting changes, and minor retouches.
Policy-aware outcomes allow routing to review, age-gating, or limited visibility, with evidence snapshots to decide quickly.
Decisions include timestamps, policy references, and evidence in audit-ready logs aligned with platform rules and regional digital-safety standards.