ProjectDiscovery's Solutions Engineer Davis Franklin explains the gap between building a DIY LLM-based security tool and running a mature security program. While spinning up a proof-of-concept with Claude Code is achievable in 30 minutes, DIY solutions break on model updates and lack the orchestration needed for enterprise scale. Neo is positioned as a purpose-built AI-native security platform with pre-triaged findings, persistent memory across multi-week pentests, 50+ integrated tools, support for business logic and IDOR vulnerability detection, and the ability to pentest LLMs and AI chatbots. The post is structured as a Q&A from a webinar, covering topics like Opus 4.7 support, pricing, tool customization, and current limitations.

6m read timeFrom projectdiscovery.io
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Any data yet on Opus 4.7?What kinds of vulnerabilities are easier to find with Neo?Any plans for Neo to do AI red teaming of LLMs, chatbots, and agents?How much would an end-to-end test of an app cost?Can you customize the tools Neo has access to?How does Neo manage context and memory across multi-day or multi-week penetration tests?What challenges does Neo still have to solve in its current state?