Vulnerabilities-Unmasked  by devanshbatham

Educational resource explaining security vulnerabilities

created 2 years ago
369 stars

Top 77.7% on sourcepulse

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Project Summary

This repository provides simplified, "explain like I'm five" analogies for common cybersecurity vulnerabilities. It targets developers, security enthusiasts, and educators seeking accessible explanations of complex topics like XSS, SQL Injection, and CSRF. The benefit is a more intuitive understanding of security risks through relatable, everyday scenarios.

How It Works

The project leverages a Language Model (LLM) with prompt engineering to generate analogies for various vulnerabilities. Each vulnerability is explained using a narrative that maps internet concepts to tangible, child-friendly examples (e.g., toy boxes for websites, sneaky kids for hackers). This approach aims to demystify technical jargon and make security concepts broadly understandable.

Quick Start & Requirements

  • Install: No installation required; content is directly available in the README.
  • Requirements: None beyond a web browser to view the README.

Highlighted Details

  • Covers 13 common vulnerabilities including XSS, CSRF, SQL Injection, ClickJacking, Subdomain Takeover, Privilege Escalation, RBAC Vulnerabilities, SSRF, Vulnerable Components, LFI, DoS, Authentication Bypass, IDOR, 2FA Bypass, and Race Conditions.
  • Analogies are explicitly stated as LLM-generated and not technical definitions, serving as illustrative examples.
  • Content is presented directly within the README for immediate access.

Maintenance & Community

  • Maintained by devanshbatham.
  • No community links (Discord, Slack) or roadmap are provided in the README.

Licensing & Compatibility

  • The README does not specify a license.
  • Compatibility for commercial use or closed-source linking is undetermined due to the lack of licensing information.

Limitations & Caveats

The analogies, while helpful for conceptual understanding, are not precise technical definitions and may oversimplify or misrepresent the nuances of each vulnerability. The project's reliance on LLM-generated content means accuracy is dependent on the underlying model and prompt quality.

Health Check
Last commit

1 year ago

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Inactive

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