ProjectDiscovery Brings Open Source AI Testing to Vulnerability Discovery

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ProjectDiscovery has made available an autonomous security testing platform that leverages an open source artificial intelligence (AI) testing framework to detect and validate vulnerabilities at a lower total cost. Company CEO Rishi Sharma said version 1.0 of the Neo platform is also available via a cloud service that makes it possible for DevSecOps teams to run tests and conduct investigations using a consumption-based pricing model. Additionally, Neo 1.0 adds integrations with DevOps tools and platforms such as GitHub, Jira, Confluence, Slack, Linear, application programming interfaces (APIs), webhooks, and the Model Context Protocol (MCP). Based on an open source project, ProjectDiscovery, in addition to using Neo to detect, validate and route vulnerabilities to the responsible developer, also provides access to Nuclei, an open-source vulnerability scanner driven by customizable YAML templates to detect misconfigurations and exploits. Also included are tools such as Subfinder for discovering subdomains, an httpx tool to probe HTTP, a web crawling tool dubbed Katana, and a port scanning tool known as Naabu. Collectively these components provide the foundation for an open source ProjectDiscovery ecosystem that already includes more than 100,000 practitioners, making it less costly to discover and remediate vulnerabilities using an autonomous security testing and penetration platform that continuously generates alerts in real time or can be used to run tests at scheduled intervals, said Sharma. Relying on code scanning tools is no longer enough, he added. Instead, there …

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