About ORTSLAB

Find out if an SMS, email or WhatsApp message is a scam — analysis in seconds

ORTSLAB is a digital message forensic analysis engine built by a court-appointed IT expert. Paste the text of any suspicious SMS, email or WhatsApp message and the engine checks over 40 fraud signals: the sender's real origin, hidden links, domain authenticity and the language patterns scammers use. No registration and nothing to install: we don't store the original text of your message.

Submit evidence
⬇
Drag a .eml, .txt file or image
or paste the text directly
👤
Citizens

Check it in seconds, no registration.

⚖️
Lawyers

Forensic groundwork before going to court.

🏢
Companies

BEC, CEO fraud and brand impersonation.

What the engine detects
Authentication
SPF / DKIM / DMARC
Links and domain
Redirects and shorteners
Domain age (RDAP)
Recently registered domains
No registration · no cost · results in seconds
Analyzing evidence…
01 Diagnosis
02 Indicators
03 Reasoning
04 Data
From: — Subject: — Date: —
🇪🇸 IP: 176.58.9.XXX·EML·120 puntos
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RIESGO DE FRAUDE: ALTO
Suplantación de notaría con adjunto malicioso — múltiples indicadores combinados.
⚠️ Main evidence
📵 Want to dig deeper? Analyze it from a computer to view the full report.
🔬 Score breakdown by axis
🧠 Reasoning — consistency layer
No single signal is conclusive on its own: SPF without DKIM is found in any small business that never configured DKIM, and a different domain in a link is found in any company with an external email provider. But together — identity not fully verified + a destination that doesn't match who it claims to be — they stop being reasonable coincidence.
In addition, the ".iso" attachment evades both antivirus software and Windows' warning when mounted as a virtual drive — combined with the unverifiable identity, the overall set of signals is consistent with a targeted attack, not a configuration mistake.
✉️ Headers and identity
📎 Attachments
🔗 URLs found

Case: — Opened: —
Tools

What can we find out about this?

The Scanner answers one question: is this message a scam? Here we answer another: what public information is there about a stray piece of data — with no message involved at all? Type or paste a domain, an IP, a URL or a phone number, or drag in a file.