AI Security Audit Services in India for Businesses Using AI
Find out what your models, prompts and data pipelines expose, and what to fix first, before an attacker or an auditor asks.
Aanetic reviews AI systems the way an attacker would and the way an auditor would, then hands you a ranked remediation plan your engineers can act on.
Untrusted input, jailbreaks & overrides
Tenant boundaries & index leakage
API permissions, DB & network egress
Downstream XSS, SSRF & blind trust
Untrusted input, jailbreaks & overrides
Tenant boundaries & index leakage
API permissions, DB & network egress
Downstream XSS, SSRF & blind trust
Where Modern AI Actually Breaks
Most AI security failures don't happen in the model weights—they happen at the interface between probabilistic AI, company data, and autonomous tools.
The 4 Enterprise Failure Points
Prompt & Context Injection
Untrusted web data, PDFs, or user input can override system instructions, bypass guardrails, and leak private prompts.
RAG & Vector Pipeline Leakage
Vector databases without strict tenant boundaries can expose confidential IP or employee data in unauthorized search results.
Autonomous Tool Exploitation
Agents with too many API, database, or shell permissions might make unintended changes, delete data, or send requests outside the network.
Insecure Output Execution
Downstream applications blindly trust LLM outputs, triggering cross-site scripting (XSS), server-side attacks, or data exfiltration.
We audit your entire application, from vector index boundaries to agent execution chains, before vulnerabilities reach production.
Our AI Security Assessment Approach
Our AI security assessment focuses on your real deployment, not just a generic checklist. We usually follow five main stages.
Scoping and AI inventory
We start by identifying which AI systems you use, even those informally adopted by business teams. We record the models, data sources, integrations, users, and owners. Shadow AI is common, and you cannot assess what you have not found.
Scoping and AI inventory
We start by identifying which AI systems you use, even those informally adopted by business teams. We record the models, data sources, integrations, users, and owners. Shadow AI is common, and you cannot assess what you have not found.
Threat modelling
For each system in scope, we map out realistic attack paths based on how it is used, who can access it, and what it can reach. We set priorities based on your risk context, not a fixed template.
Threat modelling
For each system in scope, we map out realistic attack paths based on how it is used, who can access it, and what it can reach. We set priorities based on your risk context, not a fixed template.
Technical testing
Depending on the scope, this includes adversarial testing of prompts and inputs, reviewing API and authentication controls, checking retrieval and vector database setups, assessing cloud and MLOps infrastructure, and evaluating data handling throughout the pipeline.
Technical testing
Depending on the scope, this includes adversarial testing of prompts and inputs, reviewing API and authentication controls, checking retrieval and vector database setups, assessing cloud and MLOps infrastructure, and evaluating data handling throughout the pipeline.
Governance and process review
Technical controls work only when supported by strong processes. We review your policies, access management, model approval and change processes, vendor oversight, human review of AI output, and incident response plans.
Governance and process review
Technical controls work only when supported by strong processes. We review your policies, access management, model approval and change processes, vendor oversight, human review of AI output, and incident response plans.
Reporting and remediation support
You receive findings ranked by severity and business impact, along with clear, actionable recommendations. We guide your technical and leadership teams through the results and can help with retesting after fixes.
Reporting and remediation support
You receive findings ranked by severity and business impact, along with clear, actionable recommendations. We guide your technical and leadership teams through the results and can help with retesting after fixes.
What You Receive
The deliverables are designed to be used by different people in your organization:
Executive Summary
An executive summary for leadership and board-level discussion.
Detailed Technical Report
A detailed technical report with reproducible findings and evidence.
Prioritized Remediation Roadmap
A prioritized remediation roadmap with suggested owners and timelines.
AI Risk Register
An AI risk register you can maintain as your systems evolve.
Governance Gap Summary
A governance gap summary mapped to the frameworks relevant to your business.
Frameworks & Compliance Benchmarks We Map To
An AI security compliance assessment must serve both engineering resilience and regulatory requirements. We translate complex security findings into established enterprise frameworks:
OWASP Top 10 for LLM Applications
Immediate identification of prompt injections, sensitive data exposure, improper output handling, and excessive agency.
ISO/IEC 42001 (AIMS)
Assessment of risk management controls, documentation readiness, and data governance for artificial intelligence management systems.
NIST AI Risk Management Framework
Structuring measurable controls across the Govern, Map, Measure, and Manage pillars.
Digital Personal Data Protection Act
Verifying that customer data processed, embedded, or cached by LLM pipelines satisfies Indian statutory privacy obligations.
Who Needs an AI Security Audit?
AI security audits for businesses are no longer limited to technology companies. We see demand from:
Banks, NBFCs, and Fintech Companies
Banks, NBFCs, and fintech companies use models for credit scoring, fraud detection, and customer verification.
Healthcare and Life Sciences
Healthcare and life sciences organizations apply AI to diagnostics, records, and patient engagement.
SaaS and IT Services Companies
SaaS and IT services companies embedded LLMs and AI agents into products sold to enterprise customers.
E-commerce and Retail
E-commerce and retail businesses running recommendation, pricing and customer-service models.
Enterprise Copilots & Chatbots
Enterprises that have rolled out internal copilots and chatbots connected to confidential data.
Why Organizations Work with Aanetic
Security first expertise
Our team comes from cybersecurity and compliance practice. We understand how AI systems fit into real enterprise environments, including the legacy systems, vendor dependencies, and access controls that surround them.
Practical findings
Reports should help your engineers fix problems, not just document them. We aim to provide specific recommendations that your team can implement.
Understanding of Indian business context
We work with the regulatory, contractual and operational realities Indian organizations face, including data protection obligations and customer security requirements.
Honest scoping
We explain what an audit can and cannot determine. No assessment can guarantee a system is risk-free, and we will not claim otherwise.
Strengthen Your Production AI Defence with Aanetic
Do not wait for a critical prompt jailbreak, an unauthorized data extraction, or a compliance audit failure to discover where your models are vulnerable. Partner with Aanetic to secure your AI architecture across the data pipeline and into autonomous tool execution.
“Speak directly with our technical audit specialists to define your assessment scope and protect your production of AI deployments.”
Aanetic AI Security & LLM Assurance Practice
Adversarial Testing for LLMs, RAG Pipelines & Autonomous Agents