Istiaque Ahmed

The work introduces Reflex-Guard, a lightweight locally running guardrail for LLM prompt safety that combines jailbreak-aware preprocessing, compact sentence-transformer embeddings, and seven fast binary classifiers, achieving 95.9% recall on harmful prompts at 37.6 ms end-to-end latency on a balanced dataset of 30,568 samples drawn from five complementary sources, faster than Llama Guard 2 (255 ms) and SafeDecoding (723 ms), detecting 100% of GCG suffix attacks and Base64-encoded prompts at the default threshold, while DrAttack structured prompts required lowering the threshold to 0.03 for optimal detection.

The work introduces Reflex-Guard, a lightweight locally running guardrail for LLM prompt safety that combines jailbreak-aware preprocessing, compact sentence-transformer embeddings, and seven fast binary classifiers, achieving 95.9% recall on harmful prompts at 37.6 ms end-to-end latency on a balanced dataset of 30,568 samples drawn from five complementary sources, faster than Llama Guard 2 (255 ms) and SafeDecoding (723 ms), detecting 100% of GCG suffix attacks and Base64-encoded prompts at the default threshold, while DrAttack structured prompts required lowering the threshold to 0.03 for optimal detection.

The work introduces Reflex-Guard, a lightweight locally running guardrail for LLM prompt safety that combines jailbreak-aware preprocessing, compact sentence-transformer embeddings, and seven fast binary classifiers, achieving 95.9% recall on harmful prompts at 37.6 ms end-to-end latency on a strategically balanced dataset of 30,568 samples drawn from five complementary sources, faster than Llama Guard 2 (255 ms) and SafeDecoding (723 ms), detecting 100% of GCG suffix attacks and Base64-encoded prompts at the default threshold, while DrAttack structured prompts required lowering the threshold to 0.03 for optimal detection.

The work introduces Reflex-Guard, a lightweight locally running guardrail for LLM prompt safety that combines jailbreak-aware preprocessing, compact sentence-transformer embeddings, and seven fast binary classifiers, achieving 95.9% recall on harmful prompts at 37.6 ms end-to-end latency on a strategically balanced dataset of 30,568 samples drawn from five complementary sources, faster than Llama Guard 2 (255 ms) and SafeDecoding (723 ms), detecting 100% of GCG suffix attacks and Base64-encoded prompts at the default threshold, while DrAttack structured prompts required lowering the threshold to 0.03 for optimal detection.