Inspiration
As cybersecurity majors, my team and I specialize in different areas—offensive security, defensive strategy, security auditing, and networking. We’ve always been passionate about using AI to simplify complex security operations. VenomAI was born out of a shared vision to merge our technical strengths with modern AI capabilities to build a smart, unified cybersecurity tool that empowers both red and blue teams. We wanted to create something practical, educational, and scalable VenomAI is that vision in action
What it does
VenomAI is an AI-powered cybersecurity agent that assists users with both offensive and defensive security tasks. It offers real-time threat intelligence, automated reconnaissance, and vulnerability analysis through a simple chat-based interface. Users can perform tasks like port scanning, subdomain discovery, virus detection, SSL configuration checks, and security header analysis while also getting AI-assisted explanations and recommendations
How we built it
We built VenomAI using Flask for the web backend, integrated PhiData for AI response generation, and leveraged APIs such as VirusTotal, SSL Labs, HackerTarget, crt.sh, and IPinfo. We designed plugin-based support for key features so that each functionality (like DNS lookup or virus scanning) is modular and extendable. Our frontend is clean, intuitive, and built to handle real-time interaction between the user and the backend services.
Challenges we ran into
Integrating multiple APIs while ensuring consistent output formatting was challenging. We also faced difficulties with timeout handling, parsing HTML from some non-API sources, and ensuring a smooth response flow between the AI and the plugin modules.
Accomplishments that we're proud of
We’re proud of how VenomAI brings together automation and AI into one cohesive cybersecurity tool. The tool not only performs technical tasks but also explains them in human-friendly language using GPT-4. Building a multi-plugin, AI-integrated web application from scratch was a major milestone for us.
What we learned
We learned how to build secure plugin-based tools, parse and structure output from various cybersecurity APIs, and integrate conversational AI in a way that genuinely improves user experience. We also improved our team collaboration and debugging skills across different modules.
What's next for Venomai
We plan to add log analysis, exploit identification, and incident response simulations. We’ll also be expanding our AI knowledge base with real-time CVE feeds and legal/regulatory standards. Ultimately, we want VenomAI to serve as a full-suite assistant for both red and blue teams.
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