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    <title>DEV Community: Chickadee</title>
    <description>The latest articles on DEV Community by Chickadee (@_f2020edd5eb067ec5dac6).</description>
    <link>https://dev.to/_f2020edd5eb067ec5dac6</link>
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      <title>DEV Community: Chickadee</title>
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      <title>I built my first open-source project: Chickadee Studio — a desktop tool for detecting hidden and disguised advertising on websites</title>
      <dc:creator>Chickadee</dc:creator>
      <pubDate>Tue, 27 Oct 2026 08:06:51 +0000</pubDate>
      <link>https://dev.to/_f2020edd5eb067ec5dac6/i-built-my-first-open-source-project-chickadee-studio-a-desktop-tool-for-detecting-hidden-and-4dbb</link>
      <guid>https://dev.to/_f2020edd5eb067ec5dac6/i-built-my-first-open-source-project-chickadee-studio-a-desktop-tool-for-detecting-hidden-and-4dbb</guid>
      <description>&lt;p&gt;Hey everyone!&lt;/p&gt;

&lt;p&gt;I wanted to share my first open-source project,*Chickadee Studio.&lt;/p&gt;

&lt;p&gt;It's a desktop application I built to help identify potentially hidden or disguised advertising in website content, including posts, comments, and images.&lt;/p&gt;

&lt;p&gt;The idea came from a problem I found interesting: not all advertising is immediately visible or easy to identify with simple keyword matching.&lt;/p&gt;

&lt;p&gt;Some content uses look-alike characters, unusual Unicode combinations, text embedded in images, or even hidden HTML elements.&lt;/p&gt;

&lt;p&gt;So I wanted to experiment with combining several techniques to analyze this kind of content.&lt;/p&gt;

&lt;p&gt;What it does:&lt;/p&gt;

&lt;ul&gt;
&lt;li&gt;Scans webpages, posts, comments, and images&lt;/li&gt;
&lt;li&gt;Uses OCR (PaddleOCR) to extract text from images&lt;/li&gt;
&lt;li&gt;Analyzes DOM elements and CSS for potentially hidden content&lt;/li&gt;
&lt;li&gt;Detects text obfuscation techniques&lt;/li&gt;
&lt;li&gt;Uses local ML models to help identify advertising context&lt;/li&gt;
&lt;li&gt;Provides screenshots and evidence for manual review&lt;/li&gt;
&lt;li&gt;Supports optional AI-assisted analysis&lt;/li&gt;
&lt;/ul&gt;

&lt;p&gt;&lt;strong&gt;Tech stack:&lt;/strong&gt; Python, Electron, React, Playwright, PaddleOCR, and scikit-learn.&lt;/p&gt;

&lt;p&gt;The core analysis runs locally, and the project is available under the Apache 2.0 license.&lt;/p&gt;

&lt;p&gt;It's still an early project, and I'm sure there are plenty of things that could be improved.&lt;/p&gt;

&lt;p&gt;Since this is my first open-source release, I'd especially appreciate feedback on the architecture, detection approach, usability, or anything else that stands out.&lt;/p&gt;

&lt;p&gt;GitHub: &lt;a href="https://github.com/chickadee-project/chickadee_studio" rel="noopener noreferrer"&gt;https://github.com/chickadee-project/chickadee_studio&lt;/a&gt;&lt;/p&gt;

&lt;p&gt;Thanks for checking it out!&lt;/p&gt;

&lt;p&gt;&lt;a href="https://media2.dev.to/dynamic/image/width=800%2Cheight=%2Cfit=scale-down%2Cgravity=auto%2Cformat=auto/https%3A%2F%2Fdev-to-uploads.s3.us-east-2.amazonaws.com%2Fuploads%2Farticles%2Fk6vu65f9rni2rt8dhlwm.png" class="article-body-image-wrapper"&gt;&lt;img src="https://media2.dev.to/dynamic/image/width=800%2Cheight=%2Cfit=scale-down%2Cgravity=auto%2Cformat=auto/https%3A%2F%2Fdev-to-uploads.s3.us-east-2.amazonaws.com%2Fuploads%2Farticles%2Fk6vu65f9rni2rt8dhlwm.png" alt=" " width="800" height="511"&gt;&lt;/a&gt;&lt;/p&gt;

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      <category>security</category>
      <category>opensource</category>
      <category>machinelearning</category>
      <category>ocr</category>
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