Bots in translation: Can AI really fix SIEM rule sprawl across vendors?

Enterprises migrating between different SIEM platforms (security information and event management systems, which collect and analyze security data) struggle because each vendor uses different query languages and data models, requiring manual rule rewrites. Researchers developed ARuleCon, an AI system that can automatically translate detection rules across platforms while preserving their detection logic, improving accuracy by 10-15% over standard AI approaches. However, security experts debate whether the problem truly needs AI, since manual translation is slow but some argue deterministic engineering (rule-based programming without AI) could solve it.