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Built for the real threat.
Kalpit Labs builds the guardrails, runs the red team, and puts a firewall in front of your LLMs — so you can ship AI without shipping the risk.
Security Disclosures Reported To
// What we do
Security built
for AI systems.
Kalpit Labs is an AI-native security company. We don't adapt old tools — we build from the ground up for the specific threat surface that LLMs, agents, and AI-powered products create.
AI Red Teaming
We attack your AI systems the way real adversaries do — using novel prompt techniques, multi-language vectors, and model-specific exploits. Not a checkbox exercise.
Runtime Guardrails
Rakshak sits between your users and your LLM. Every prompt screened. Every response checked. Threats blocked before they reach your model or your users.
AI Traffic Firewall
Kavach inspects all LLM API traffic in real-time — rate limiting, anomaly detection, threat logging. Like a WAF, built exclusively for AI endpoints.
// The threat surface
Attacks your existing
security won't catch.
Traditional red teams test infrastructure. Firewalls protect networks. Pentests find code vulnerabilities. None of them test what happens when someone talks to your AI in the wrong way.
Prompt Injection
Malicious instructions embedded in user input override your system prompt, hijacking your model's behaviour entirely.
Jailbreaking
Adversarial phrasing bypasses safety guidelines, making your model produce harmful, off-policy, or confidential content.
System Prompt Extraction
Attackers trick your LLM into revealing its system prompt — exposing your business logic, tone, and guardrails.
PII Exfiltration
Users craft prompts that cause your model to leak other users' data, internal documents, or Aadhaar/PAN details from context.
Multilingual Bypass
Attacks written in Hindi, Tamil, or Urdu slip through English-only guardrails undetected — a gap unique to Indian AI products.
Indirect Prompt Injection
Hostile content in documents, web pages, or tool outputs hijacks your agent mid-task — without the user doing anything.
Every AI product is exposed to these vectors — from day one. Most teams discover them after an incident, not before.
Get assessed →// How we secure it
Find. Guard. Enforce.
A three-layer security approach — from adversarial discovery to runtime protection to traffic-layer enforcement. Each layer works standalone or together as a full security stack.
AI Red Team
— NirikshaAvailableWe attack your AI product the way a real adversary would — structured adversarial testing across all known AI attack vectors, tailored to your stack and language mix.
Guardrail Layer
— RakshakLiveRakshak deploys a real-time guardrail between your users and your LLM. Every prompt screened, every response checked. Blocks threats before they reach your model or your users.
AI Traffic Firewall
— KavachComing soonKavach sits in front of any LLM API and inspects all traffic in real-time. Rate limiting, anomaly detection, threat logging. Like Cloudflare WAF — but purpose-built for AI endpoints.
// Rakshak — deep dive
A firewall for your LLM.
Not your network.
Rakshak sits between your users and your AI — screening every prompt going in and every response coming out. It doesn't change how your model works. It just makes sure nothing dangerous gets through in either direction.
Stops bad inputs
Every user message is screened before it touches your LLM. Prompt injections, jailbreaks, and persona override attacks are caught at the door.
Guards your outputs
Rakshak checks what your model sends back too. PII, confidential data, and off-policy content are detected and redacted before they reach your users.
Protects your system prompt
Your business logic, tone rules, and guardrails are your IP. Rakshak blocks any attempt to extract or reveal your system prompt.
Custom rules on request
Every business is different. Tell us what your product can and can't do — we build custom guardrail rules that match your specific policy.
// How it works — live pipeline
User
Rakshak · Input Guard
LLM
// Why Kalpit Labs
The difference is
specificity.
Generic security tools give you generic coverage. AI threats require tools and expertise built specifically for them.
Built for AI. Not adapted from it.
We didn't take a network scanner and add LLM support. Rakshak and Niriksha are purpose-designed for the specific threat surface that AI systems create — from day one.
India-first, truly.
Our threat models include Hindi, Tamil, Telugu, Urdu and 8 more Indian languages. We detect Aadhaar, PAN, and UPI exfiltration natively. No other vendor in this space does.
Real red teamers, not just a product.
Niriksha is a hands-on adversarial engagement run by security researchers who specialise in AI systems — not a SaaS scan button with a PDF report.
Zero performance impact.
Rakshak adds single-digit milliseconds to your inference latency. Multi-stage screening designed to be fast enough for real-time production use.
Deploy your way.
Self-host Rakshak in your own infrastructure or use our managed cloud. Your traffic never leaves your environment if you don't want it to.
Compliance-ready.
DPDP-aligned audit logging out of the box. Every blocked prompt logged with reason, timestamp, and risk level — ready for compliance review.
// Kalpit Labs vs traditional security
| Capability | Kalpit Labs | Traditional Pentest | Firewalls / WAF |
|---|---|---|---|
| Prompt injection detection | ✓ | — | — |
| Jailbreak & persona override | ✓ | — | — |
| PII exfiltration (Aadhaar, PAN) | ✓ | — | — |
| Multilingual attack detection | ✓ | — | — |
| System prompt protection | ✓ | — | — |
| Real-time runtime guardrails | ✓ | — | — |
| AI red team engagement | ✓ | ✓ | — |
| Network layer protection | — | — | ✓ |
// Field dispatches
From the field.
Research, walkthroughs, and findings from real AI red team engagements. No fluff. No vendor marketing. Just what we found.
// Get started
Secure your AI before
someone else tests it.
Whether you need a guardrail layer for your LLM product or a full adversarial red team engagement — we have both. Start with the API today or talk to us about a custom engagement.