AI SECURITY

AI Penetration Testing

One of very few firms in India offering dedicated AI/LLM security testing. As organisations deploy LLMs, ML models, and AI-powered applications, a new attack surface emerges that traditional security tools cannot address.

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Why This Matters

65%

of enterprises have AI in production (2024)

LLM Top 10

OWASP published a dedicated AI threat taxonomy

Weaponised

AI can exfiltrate data and bypass guardrails if unsecured

Our Methodology

A structured, repeatable approach that delivers consistent results

1

AI System Recon

System mapping and analysis

Model Type IDAPI Surface MappingIntegration PointsSystem Prompt ReviewGuardrail Analysis
2

Prompt Injection

Core LLM attack testing

Direct InjectionIndirect via RAGJailbreaking (DAN)Role-Play AttacksMulti-Turn Context
3

Data Exfil & Privacy

Leakage testing

Training Data ExtractionPII LeakageSystem Prompt ExtractionRAG PoisoningMemorisation Attacks
4

Model & Infrastructure

Backend security

API Auth/Rate LimitingModel InversionAdversarial InputsSupply Chain RisksFine-Tuning Integrity
5

Agent & Tool Use

Agentic AI security

Privilege EscalationAgent Loop InjectionFunction Calling AbuseTool Use Exploitation

Standards & Frameworks

OWASP LLM Top 10 (2025)MITRE ATLASNIST AI RMFEU AI Act

Deliverables

  • AI Security Report
  • Threat Model
  • Remediation Playbook
  • Guardrail Assessment
  • Free Re-test for Critical/High

Timeline

7–15 business days

From scoping call to final report

Engagement Types

Frequently Asked Questions

We test LLM-powered applications (GPT, Claude, Gemini), RAG systems, AI chatbots, autonomous agents, ML model APIs, and custom fine-tuned models. If it uses AI, we can test it.

Prompt injection is when an attacker crafts inputs that override or manipulate the AI system's intended behavior — similar to SQL injection for databases but targeting language models.

With 65% of enterprises running AI in production and OWASP publishing a dedicated LLM Top 10, the attack surface is real and growing. AI systems can be weaponised to exfiltrate data, bypass guardrails, and generate harmful outputs.

Yes. We specifically test autonomous agent architectures including function calling, tool use, multi-agent systems, and the unique risks of LLM agents with access to external tools and data.

We follow OWASP LLM Top 10 (2025), MITRE ATLAS for adversarial threat modelling, NIST AI RMF for risk management, and EU AI Act alignment for compliance readiness.

Traditional pen tests focus on network, web, and API vulnerabilities. AI pen testing requires entirely different techniques — prompt engineering, adversarial ML, and understanding of model architectures.

Yes. As of 2025–2026, very few firms in India offer dedicated AI/LLM penetration testing. Our team has specialised AI security certifications and custom testing frameworks.

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