What is Senthex and how does it detect multi-turn prompt injections?

Senthex is a low-latency reverse proxy that tracks cumulative injection scores across conversation turns using decay, patterns like crescendo/splitting/poisoning, and adaptive thresholds—no ML required.

How do multi-turn prompt injections bypass traditional LLM firewalls?

They split attacks across messages (crescendo escalation, payload chunks, or poisoning acknowledgments), evading per-message scorers that flag only overt dangers.

Can I implement multi-turn detection without ML in my app?

Yes—use a session store like Redis, decay cumulative scores (e.g., 0.9 factor), detect patterns on last 3 turns, and add noise/dynamic thresholds to thwart fuzzing.

🤖 AI Dev Tools

Senthex: The Lightning-Fast Firewall Crushing Multi-Turn Prompt Injections Sans ML

Picture this: an attacker whispers a codeword, then unleashes hell—your LLM firewall yawns. Senthex doesn't. It tracks conversations like a hawk, stacking suspicions without breaking a sweat.

theAIcatchup Apr 07, 2026 4 min read

Diagram of Senthex proxy blocking a multi-turn prompt injection attack on an LLM API

⚡ Key Takeaways

Senthex detects multi-turn injections via cumulative scoring, pattern matching, and adaptive defenses—all in 16ms with pure heuristics. 𝕏
Patterns caught: crescendo escalations, payload splits across messages, and jailbreak acknowledgments in assistant replies. 𝕏
Dynamic thresholds and noise make bypassing exponentially harder, flipping the attacker advantage. 𝕏

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#Senthex proxy #heuristic detection #heuristics-vs-ml #multi-turn prompt injections #prompt-injection-detection #senthex

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Originally reported by dev.to

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