AI Security & Compliance India

Indian enterprises are deploying large language models, computer vision systems, and ML-driven decision engines at unprecedented pace — but AI security has not kept up. LLM-powered chatbots can be manipulated through prompt injection to reveal confidential data, bypass content filters, or execute unintended actions. ML models can be poisoned through training data manipulation, stolen through model extraction attacks, or fooled by adversarial inputs crafted to cause misclassification. These are not theoretical risks — they are active exploits being used against production AI systems globally. DPDPA introduces specific obligations for organisations processing personal data through automated systems, and CERT-In's incident reporting requirements now explicitly cover AI-related security incidents. RBI's evolving guidance on AI in financial services demands that banks and NBFCs demonstrate security controls around AI systems making credit decisions, fraud detection, and customer interaction automation. Indian enterprises deploying AI without dedicated security engineering face regulatory penalties, data breach liability, and operational risk from compromised AI systems.

Opsio's AI security practice addresses the complete OWASP Top 10 for LLMs — prompt injection, insecure output handling, training data poisoning, model denial of service, supply chain vulnerabilities, sensitive information disclosure, insecure plugin design, excessive agency, overreliance, and model theft. We implement defence-in-depth strategies combining input validation, output filtering, guardrail systems, monitoring, and access controls to protect your AI deployments within Indian regulatory and threat landscapes.

Our red team engagements simulate real-world attack scenarios against your AI systems — attempting prompt injection, jailbreaking, data extraction, adversarial input crafting, and model manipulation to identify vulnerabilities before malicious actors do. Red team findings are translated into actionable remediation plans with prioritised fixes, architectural recommendations, and guardrail configurations that close identified gaps systematically.

For LLM deployments, we implement production guardrail systems using tools like Guardrails AI, NeMo Guardrails, and custom validation layers that filter prompts and responses in real time. Input validation catches prompt injection attempts, output filtering prevents sensitive data leakage including Aadhaar numbers, PAN details, and financial information, and topic controls keep the LLM within its intended domain. These guardrails operate with minimal latency impact, preserving user experience whilst enforcing security boundaries.

AI security is not a one-time assessment — it is an ongoing discipline requiring continuous monitoring, threat intelligence, and adaptation as attack techniques evolve. Opsio provides managed AI security operations including real-time prompt monitoring, anomaly detection across model inputs and outputs, automated guardrail updates based on emerging threats, and incident response for AI-specific security events aligned with CERT-In reporting timelines. Our IST-based security operations centre ensures rapid response to AI threats targeting your Indian deployments.