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GitHub
First multilingual (Arabic/English/...) LLM security gateway
The first documented security gateway built for Arabic, Arabizi, and English — with explainable, multi-threat detection. Each input's embedding is compared against all three anchor sets via cosine similarity. The resulting 3D feature vector feeds a lightweight Logistic Regression classifier — fast, interpretable, and GPU-free. This directly solves the false-positive trap that binary classifiers fall into: a student asking "how does jailbreaking work?" is never mistaken for an attacker.
400 million Arabic speakers use LLMs every day. Before this work, zero documented security systems protected them.
Prompt injection, jailbreaking, phishing, and Unicode-based attacks are now routine. Existing defenses share three blind spots:
Limitation | Impact
Single-threat focus : Only catches one attack type at a time
English-only : Blind to Arabic and Arabizi (Arabic typed in Latin script)
No explainability : Black-box decisions with zero rationale
GitHub was submitted on Product Hunt and earned 0 upvotes and 1 comments, placing #9 on the daily leaderboard. The first documented security gateway built for Arabic, Arabizi, and English — with explainable, multi-threat detection. Each input's embedding is compared against all three anchor sets via cosine similarity. The resulting 3D feature vector feeds a lightweight Logistic Regression classifier — fast, interpretable, and GPU-free. This directly solves the false-positive trap that binary classifiers fall into: a student asking "how does jailbreaking work?" is never mistaken for an attacker.
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