Sesame IT HOSHI vs Sigma Query: Side-by-Side Comparison (2026)
Features, pricing, ratings, and pros and cons, compared head to head.
Sesame IT HOSHI is a commercial detection engineering tool by Jizô AI. Sigma Query is a free detection engineering tool. Compare features, ratings, integrations, and community reviews side by side to find the best detection engineering fit for your security stack. Independent and vendor-neutral: our scores and rankings are earned, never bought — sponsored placement is always labeled.
CST VerdictShort answer
Mid-market and enterprise security teams that struggle converting threat intelligence into actionable detection rules will benefit most from Sesame IT HOSHI, which automates that translation and feeds industry-specific attack scenarios directly into Jizô AI's detection engine. The daily-updated use case library means your detection coverage stays current without forcing analysts to manually build rules from intelligence reports. Not ideal for organizations seeking a standalone threat intelligence platform; HOSHI is purpose-built as a detection rule factory for teams already committed to the Jizô AI ecosystem. Startups and mid-market SOCs building detection programs from scratch should use Sigma Query to avoid reinventing rules; 3,000+ community-maintained detections mapped to 385+ MITRE ATT&CK techniques means you start with mature baselines instead of blank templates. The free model and cloud deployment eliminate procurement friction, and multi-platform coverage across Windows, Linux, cloud providers, and network appliances lets you apply the same rule set across your entire stack without rewriting. Skip this if your team lacks SIEM experience or needs rules packaged inside a commercial product with vendor support; Sigma Query requires you to understand your detection logic well enough to integrate and tune community rules yourself.
