neurology Cloud & Modern Architecture

AI Security & Consulting

You're Building with AI. But Is Your AI Building an Attack Surface?

AI and LLM security consulting for Indian businesses. Prompt injection defence, training data security, adversarial AI testing, and AI integration security assessment.

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What Is AI Security & Consulting?

AI Security & Consulting helps organisations safely integrate artificial intelligence — particularly Large Language Models (LLMs) like GPT, Claude, Gemini, and open-source models — into their products and operations without creating new attack vectors.

The rapid adoption of AI across Indian businesses has created an entirely new category of security risks. LLM prompt injection allows attackers to manipulate AI outputs. Training data poisoning can compromise model behaviour. AI-generated content can leak sensitive information from training data. And AI agents with tool access can be tricked into performing unintended actions.

Verentix provides security assessment and consulting for organisations building AI-powered products, integrating LLMs into their workflows, or deploying AI agents that interact with business-critical systems.

Why Your Business Needs This

Indian businesses are rapidly integrating AI — from customer service chatbots and document processing to code generation and decision support systems. But most implementations have zero security review.

Common AI security issues we find include LLM-powered chatbots that can be manipulated to reveal system prompts, internal data, or execute unintended actions through prompt injection. AI systems that process user input without sanitisation, allowing attackers to manipulate outputs. RAG (Retrieval Augmented Generation) systems where the knowledge base contains sensitive documents that can be extracted through carefully crafted queries. AI agents with API access that can be tricked into making unauthorised API calls, modifying data, or accessing restricted resources.

For regulated industries, AI security is particularly critical because AI-generated outputs that are incorrect, biased, or manipulated can create regulatory liability — especially in fintech, healthcare, and legal applications.

What You Get

check_circle LLM prompt injection testing and defence architecture
check_circle Training data security assessment — data leakage and poisoning risk
check_circle AI agent security review — tool access controls and guardrails
check_circle RAG system security — knowledge base access control and data leakage prevention
check_circle Adversarial testing of AI-powered features and chatbots
check_circle AI security architecture design and best practices for your development team

Our Approach

AI System Mapping (Day 1-2): We inventory all AI integrations — LLMs in use, training data sources, RAG knowledge bases, AI agents, tool access, and data flows between AI components and business systems.

Prompt Injection Testing (Day 2-5): Systematic testing of every user-facing AI interaction point for direct and indirect prompt injection vulnerabilities. We attempt to extract system prompts, bypass safety measures, manipulate outputs, and access restricted functionality.

Data Security Assessment (Day 5-7): Review of training data handling, RAG knowledge base security, and data leakage risk from AI-generated outputs. We test whether sensitive information from your data can be extracted through AI interactions.

Architecture Review and Recommendations (Day 7-10): Assessment of your AI security architecture — input sanitisation, output filtering, access controls, monitoring, and guardrails. Recommendations for securing your AI systems based on current best practices and emerging threat models.

Real Results for Indian Businesses

A fintech company in Mumbai had deployed an AI chatbot for customer support that could be manipulated through prompt injection to reveal other customers' account details by embedding specific instructions in the chat message. Our testing identified the vulnerability before public launch, and we helped design input sanitisation and output filtering controls.

An ed-tech startup in Pune had an AI-powered essay grading system where prompt injection in student submissions could manipulate grading outputs — artificially inflating scores. Our adversarial testing identified 12 distinct injection techniques, and we helped implement a secure architecture separating user input from system instructions.

A legal services company in Delhi had built a RAG-based legal research tool. Our assessment found that carefully crafted queries could extract entire documents from the knowledge base — including confidential client information that had been inadvertently included in the training data.

Frequently Asked Questions

What is prompt injection?expand_more
Prompt injection is an attack where a user crafts input that manipulates an LLM to ignore its original instructions and follow attacker-provided instructions instead. It is analogous to SQL injection but for AI systems. It can cause chatbots to reveal system prompts, leak data, bypass safety measures, or perform unintended actions.
Do you test all types of AI systems?expand_more
We focus primarily on LLM-based systems — chatbots, AI agents, RAG systems, AI-powered features, and AI-integrated workflows. We also assess traditional ML models for adversarial robustness, but our primary expertise is in LLM security.
Is AI security really necessary for my business?expand_more
If your AI system processes user input, accesses sensitive data, makes decisions that affect users, or has access to APIs and tools — yes, security testing is essential. The attack surface of AI systems is fundamentally different from traditional applications, and standard penetration testing does not cover AI-specific threats.
Can you help us build secure AI systems from scratch?expand_more
Yes. We provide AI security architecture consulting — helping you design your AI integration with security built in from the start. This includes prompt engineering best practices, input/output filtering, access control design, monitoring, and guardrails.

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