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Frontend
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correlation analysis
Inspiration
Designed this app specifically for those who might not be the most tech-savvy, creating an intuitive and friendly tool that empowers a company's support team and SDR's to act quickly, patch issues and submit and manage reports.
We knew that in the modern security environment, especially with the advent of AI agents in the wild, vulnerabilities arise more often in ambiguous terms, and correlating common zero days and emerging vulnerabilities with a company's internal systems effectively without human oversight will be a bottleneck for large organizations to secure their data.
The goal is to give maximum leverage to the user while offloading all repetitive work to the agents. One major benefit is correlating existing vulnerabilities with a company's known internal vulnerabilities and support tickets, allowing better clarity to the agent in authoring and running tests and submitting patches
What it does
Scrapes vulnerabilities commonly known and arising on the web, correlating them with internal support tickets related to potential vulnerabilities, uses an agent to fashion unique pentesting criteria, then runs a pentest via NodeZero to ascertain these vulnerabilities, in your projects and fixes them, and creates a report
How we built it
We used Redis to query and create a vector db for support tickets, NodeZero for pentesting and Apify for web scraping vulnerabilities
Challenges we ran into
We ran into some problems setting up API’s, some SSL errors and setting up the MCP server.
Accomplishments that we're proud of
Managed to create a small demo that worked with Redis, Apify and NodeZero MCP server
What we learned
We learned more about the Api’s, MCPs and some of the benefits of natural-language based interaction between agents and sourcing semantic data as context for the agents.
What's next for PatchPilot
We seek to use it in a real world setting for existing systems that may have vulnerabilities.
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