AI & LLM Security in India

AI & LLM security in India protects AI and Large Language Model applications from prompt injection, data leakage, model poisoning and excessive agency. India is investing heavily through the IndiaAI Mission (a multi-thousand-crore national programme), passed the Digital Personal Data Protection (DPDP) Act 2023, and CERT-In requires reporting of cyber incidents within six hours. CyberSigma delivers LLM red-teaming and AI governance mapped to MeitY and CERT-In and the global frameworks (OWASP LLM Top 10, NIST AI RMF, ISO/IEC 42001, MITRE ATLAS). We are CERT-In empanelled and PCI QSA (CEMEA) authorised.

Secure AI adoption for India organisations

India is investing heavily through the IndiaAI Mission (a multi-thousand-crore national programme), passed the Digital Personal Data Protection (DPDP) Act 2023, and CERT-In requires reporting of cyber incidents within six hours. That momentum means India organisations must now show their AI is secure, governed and compliant — not just functional.

AI introduces failure modes traditional testing misses: chatbots manipulated into leaking data, AI agents coaxed into unauthorised actions, and poisoned models or datasets from public hubs. CyberSigma secures the full AI lifecycle — model, data, application, prompts, plugins and agents — and maps every finding to MeitY and CERT-In and recognised global frameworks.

• LLM & GenAI application penetration testing and red-teaming (OWASP LLM Top 10).
• AI/ML model, pipeline and MLOps security assessment (MITRE ATLAS, Google SAIF).
• AI governance — ISO/IEC 42001 AI Management System and NIST AI RMF.
• Local alignment with MeitY and CERT-In.
• Secure AI adoption — GenAI usage policy, shadow-AI and data-leak controls.

The IndiaAI Mission, DPDP Act and CERT-In

Indian organisations across BFSI, IT/ITeS and government are scaling AI as the IndiaAI Mission accelerates adoption. The DPDP Act 2023 governs personal data used by AI, MeitY has issued advisories on AI and deepfakes, and CERT-In's six-hour incident-reporting rule applies to AI systems too.

What we test (OWASP Top 10 for LLMs + MITRE ATLAS)

We adversarially test your LLM and GenAI applications the way a real attacker targeting a India organisation would:

• Prompt injection — direct and indirect (documents, web pages, tools).
• Sensitive information disclosure — PII, secrets and system-prompt leakage.
• Insecure output handling — XSS, SSRF and code execution from model output.
• Excessive agency — agents/plugins taking unauthorised or destructive actions.
• Training-data poisoning and model/data supply-chain risks.
• Jailbreaks, guardrail bypass, model extraction and denial-of-wallet.

AI governance & compliance in India

We turn the applicable frameworks into a prioritised, evidenced programme:

• Digital Personal Data Protection (DPDP) Act 2023 for AI and training data.
• MeitY AI advisories (incl. deepfakes / due diligence).
• CERT-In directions, including six-hour incident reporting.
• ISO/IEC 42001 + NIST AI RMF.

How does the DPDP Act 2023 affect AI in India?

The DPDP Act governs processing of personal data, including data used to train or run AI — covering consent, purpose limitation and security. We assess your AI systems against it.

Do CERT-In rules apply to AI systems?

Yes. CERT-In directions, including the six-hour incident-reporting requirement and logging obligations, apply to the infrastructure running your AI. We help you meet them.

How does AI red-teaming differ from normal penetration testing?

Traditional pen testing targets code and infrastructure; AI red-teaming additionally targets the model's behaviour via prompts, poisoned context and connected tools to make it leak data or act without authorisation. Mature programmes use both — we provide each and can combine them.