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Sentinel — Credibility Engine

ExtensionPrivacy & Security
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Overview

Silent background protection. Detects deception, brand impersonation, and scam narratives before you become a victim.

Sentinel doesn’t wait for malware — it detects the deception that leads you there. Sentinel is a deception detection engine designed to identify scam patterns, brand impersonation, and manipulative narratives before you interact with a site. Unlike traditional security tools that respond after a threat is triggered, Sentinel works earlier in the chain — analysing structure, behaviour, and intent to flag risk before credentials are entered, downloads begin, or decisions are made. This means avoiding the threat entirely, rather than reacting after exposure. The engine evaluates websites using three layers of analysis: structural signals from the domain, narrative patterns found in page content, and behavioural conflict patterns commonly used in fraudulent campaigns. Sentinel runs silently in the background and performs all analysis locally inside your browser. No browsing data is collected, transmitted, or stored externally. This project is currently in active development and is being released free to use while the detection engine continues to improve. Users are encouraged to submit feedback and help refine detection accuracy and reduce false positives.

Details

  • Version
    1.4.5
  • Updated
    April 22, 2026
  • Offered by
    andrewpriest09
  • Size
    32.6KiB
  • Languages
    English
  • Developer
    Andrew Priest
    70 Lonsdale Street Nelson BB9 9HG GB
    Email
    andrewpriest09@gmail.com
  • Non-trader
    This 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

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The developer has disclosed that it will not collect or use your data. To learn more, see the developer’s privacy policy.

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
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