LinkedIn Inbound Scanner
Overview
Analyze LinkedIn messages for potential job scams using AI
LinkedIn Inbound Scanner helps you quickly identify potential job scams and suspicious outreach messages on LinkedIn using AI-powered analysis. The tool reviews inbound messages for common scam signals such as impersonation, unrealistic job offers, pressure tactics, off-platform communication requests, and other deceptive patterns commonly used in employment fraud. Each message is analyzed in seconds and assigned a risk score from 1 to 10, making it easy to understand how likely a message is to be a scam at a glance. In addition to the numeric score, the scanner provides a brief explanation of the factors that influenced the rating, helping you decide whether to respond, ignore, or report the message. Designed for job seekers, freelancers, and professionals who receive high volumes of LinkedIn messages, LinkedIn Inbound Scanner adds an extra layer of protection—helping you avoid wasting time, sharing sensitive information, or falling victim to scams. Key features: - AI-driven analysis of LinkedIn messages - Clear scam risk score (1–10) for each message - Detection of common job scam patterns and red flags - Simple explanations to support informed decisions - Fast, private, and easy to use LinkedIn Inbound Scanner does not send messages or act on your behalf—it simply helps you make safer, more informed decisions when reviewing inbound LinkedIn outreach.
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Details
- Version1.0.0
- UpdatedJanuary 15, 2026
- Size32.82KiB
- LanguagesEnglish
- Developer
Email
faisal.of.usmani@gmail.com - Non-traderThis developer has not identified itself as a trader. For consumers in the European Union, please note that consumer rights do not apply to contracts between you and this developer.
Privacy
This developer declares that your data is
- Not being sold to third parties, outside of the approved use cases
- Not being used or transferred for purposes that are unrelated to the item's core functionality
- Not being used or transferred to determine creditworthiness or for lending purposes