Rakshak by KalpitLabs

What it does

Most LLM-based products ship with no input security layer. We know because we found and responsibly disclosed vulnerabilities in Le Chat (Mistral) and Sarvam AI's Indus model — system prompt extraction, guardrail bypass, phishing content generation. Rakshak sits between your users and your model. Blocks on the way in, redacts on the way out. Built for Indian AI teams but works with any LLM API. Self-serve API key, integrates in under an hour.

Adversarial red teaming for production LLMs. We break your AI before attackers do.

Sits between your users and your model. Blocks what goes in. Sanitizes what comes out. LLMs in production are vulnerable. A single prompt can extract your system instructions, leak API keys, expose internal URLs, or override your model's behavior entirely. Most teams discover this during an incident — a user screenshots your system prompt, a researcher publishes your internals, or an attacker exfiltrates data through the chat window. By then it's too late. Intercepts every prompt before it reaches your model. Runs through three stages: pattern detection for known attack signatures, semantic similarity against a threat dataset, and an LLM classifier for novel attacks. If flagged — blocked.…from kalpitlabs.com

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