The 6-Month AI Security Playbook for Startups

The talk frames security as a bottleneck for early-stage companies and argues that a lean startup can build a usable baseline within six months. The speaker uses a role-play in which a founding team must pass an investor's security due diligence, and suggests starting with vendor questions about data training, audits and AI guardrails, plus a simple tabletop exercise for an AI tool outage.

The middle covers a month-by-month plan. It starts with asset inventory using discovery tools such as Open-AudIT and Snipe-IT, then vulnerability scanning with OpenVAS, where an LLM condenses long reports into action steps. Detection follows, with Wazuh agents, dashboards, and n8n workflows that enrich indicators before alerting analysts. Incident response uses Shuffle playbooks alongside TheHive and Cortex for case handling. Compliance is handled with an open-source GRC suite that gathers evidence and flags gaps, and vendor risk is reviewed through document analysis and breach-data checks.

The closing advice is to track results such as mean time to respond, cases per analyst, and the share of vulnerabilities auto-remediated, so leadership can see the impact. The speaker stresses keeping human review on automated fixes and not sending confidential data to external AI services.