The Catalyst: One Language, Many Attack Surfaces The comfortable fiction is: “We wrote English rules, so the model is safe.” The truth: LLMs are multilingual. A user can request the same jailbreak in another script, mix Latin keywords into CJK text, or hide instructions behind homoglyphs. If your policy lives only in English sentences, you have not policed the channel. Phase 2 of the Practical Guide series is the Voice layer: how to handle multiple languages and cultural nuance without giving attackers a free pass. The implementation detail is Silas Shield ( silas-shield ); the narrative is Language Sentry . The same rules apply to every language. Overview Skill Shield (Silas) in my setup is a drop-in OpenClaw skill: SKILL.md enforces vision rules, PII hashing, image-gen lockdown, cross-session isolation, and multilingual injection defence. The Python entry points ( shield.py , script_detector.py , pre_screener.py , hash.py ) run locally for message checks.…