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Cybersecurity · AI/LLM Adversarial Testing · LLM Red Teaming
AI & LLM Security Testing

Secure Your AI Before
Adversaries Do.

India's first law firm offering attorney-privilege-protected AI security testing.

We probe large language models, RAG pipelines, and agentic systems for prompt injection, data exfiltration, model inversion, and compliance gaps — under full attorney-client privilege.

The AI Security Problem

LLMs are deployed fast.
Security is an afterthought.

Most enterprises deploying AI have zero adversarial testing. LLMs are uniquely vulnerable because their attack surface is natural language — every user input is a potential exploit vector.

SIRI is the only firm in India that delivers AI security testing under attorney-client privilege. When we find that your chatbot leaks PII or your RAG pipeline can be hijacked, that finding is legally protected — it cannot be compelled in regulatory proceedings.

  • 01
    OWASP Top 10 for LLM Applications

    Full coverage of every risk category in the OWASP LLM Top 10 — from prompt injection to insecure output handling.

  • 02
    NIST AI RMF Aligned

    Testing methodology mapped to NIST AI Risk Management Framework for regulatory defensibility.

  • 03
    EU AI Act Ready

    Assessment covers high-risk AI system requirements — critical for companies with European operations.

  • 04
    MeitY & DPDPA Mapped

    India-specific regulatory alignment including MeitY advisories, DPDPA data processing obligations, and CERT-In requirements.

What We Test

AI & LLM Security Services

From prompt injection to model theft — SIRI's AI security practice covers every attack vector in the modern AI threat landscape.

  • 🔍

    Prompt Injection Testing

    Systematic red teaming for direct and indirect prompt injection, jailbreaks, goal hijacking, and system prompt extraction across all major model providers.

  • 📚

    RAG Pipeline Security

    End-to-end assessment of Retrieval-Augmented Generation systems — vector store poisoning, embedding manipulation, context boundary violations, and data exfiltration.

  • 👀

    Model Inversion & Extraction

    Testing for training data leakage, membership inference, model extraction via API queries, and intellectual property theft in deployed AI systems.

  • 🤖

    Agentic System Testing

    Security assessment of autonomous AI agents, multi-step tool-calling chains, MCP server integrations, and agent-to-agent communication protocols.

  • 🛡

    AI Supply Chain Audit

    Evaluation of model provenance, fine-tuning pipeline integrity, dependency risks in ML libraries, and third-party model marketplace security.

  • 🛠

    Output Validation Testing

    Testing for insecure output handling, cross-site scripting via LLM responses, SQL injection through generated queries, and unsafe code generation.

  • 🔑

    AI Data Privacy Assessment

    Analysis of PII leakage, consent boundary violations, cross-tenant data exposure in multi-tenant AI systems, and DPDPA-specific data processing risks.

  • 📊

    AI Compliance Gap Analysis

    Regulatory mapping against OWASP LLM Top 10, NIST AI RMF, EU AI Act, MeitY guidelines, and sector-specific AI regulations (RBI, SEBI, IRDAI).

  • Continuous AI Monitoring

    Ongoing adversarial testing for SIRI Shield subscribers — quarterly red team exercises, prompt injection canary monitoring, and drift detection alerts.

Why SIRI

Attorney-client privilege meets
technical AI adversarial testing.

Unlike standalone security firms, our findings are protected by legal privilege — critical when AI vulnerabilities could trigger regulatory scrutiny.

Book Free Consultation →
  • 🤖
    LLM-Native Methodology

    Testing frameworks built specifically for transformer-based models, RAG architectures, and tool-calling agents — not adapted from traditional pentesting.

  • 🔑
    Privilege-Protected Findings

    All security findings delivered under attorney-client privilege, preventing forced disclosure in regulatory investigations or litigation.

  • Rapid Turnaround

    Preliminary AI risk assessment in 72 hours. Full red team report in 10 business days. Remediation roadmap included.

  • 📊
    Regulatory-Ready Reports

    Deliverables mapped to OWASP LLM Top 10, NIST AI RMF, EU AI Act, and Indian regulatory frameworks. Board-presentable.

Our Process

How We Engage

01

Scoping & Threat Modelling

We map your AI system architecture, identify trust boundaries, and define attack scenarios based on your threat model and regulatory requirements.

02

Automated Recon & Probing

Automated tools enumerate model capabilities, test input/output boundaries, and identify surface-level vulnerabilities across all endpoints.

03

Manual Adversarial Testing

Senior engineers execute targeted attacks: prompt injection chains, context manipulation, privilege escalation, and data exfiltration attempts.

04

Legal & Compliance Mapping

Attorneys map every finding to applicable regulations (DPDPA, OWASP, NIST, EU AI Act) and assess liability exposure and notification obligations.

05

Privileged Report & Remediation

Detailed findings under attorney-client privilege with severity scoring, exploit proof-of-concept, and a prioritised remediation roadmap.

Representative Matters

Typical AI Security Engagements

Real engagement patterns. Client details anonymised. All findings delivered under attorney-client privilege.

FinTech — Customer-Facing LLM Chatbot

Red-teamed a GPT-4-powered financial advisor chatbot. Discovered 14 prompt injection paths that could extract other customers' portfolio data. All findings protected under privilege. Remediation completed in 8 days.

SaaS — RAG-Powered Knowledge Base

Tested a RAG system serving enterprise documentation. Found embedding poisoning vector that allowed cross-tenant data access. DPDPA breach notification assessment provided alongside technical fix.

HealthTech — Clinical AI Decision Support

Adversarial assessment of a diagnostic AI. Identified model inversion attack that could reconstruct patient data from API responses. HIPAA and DPDPA compliance gap analysis delivered.

AI Startup — Agentic Code Generation Platform

Full security audit of an autonomous coding agent. Discovered tool-calling chain that enabled arbitrary file system access. Privilege-protected findings enabled the company to raise Series A with clean security posture.

Client Outcomes

Measurable Results

200+
AI Vulnerabilities
Discovered
Across LLMs, RAG, and agentic systems
72hr
Risk Assessment
Turnaround
Preliminary findings delivered fast
100%
Findings Under
Legal Privilege
Zero forced disclosures to regulators
0
Critical Vulns
Left Unresolved
Every finding gets a remediation path

Tools & Methodologies

Our Testing Arsenal

GarakPyRITPromptfooART (IBM)RebuffCustom HarnessesOWASP LLM Top 10NIST AI RMFMITRE ATLASEU AI Act Annex IIIManual Red TeamingBurp Suite + AI Extensions

Industries

Sectors We Protect

FinTech & BankingSaaS & Cloud PlatformsHealthTech & MedTechAI Startups & LLM PlatformsE-Commerce & RetailGovernment & DefenceLegal & Professional ServicesInsurance & NBFC

FAQ

Frequently Asked Questions

What types of AI systems do you test?
We test LLM-powered chatbots, RAG pipelines, agentic systems, code generation tools, AI decision-support systems, and any application built on foundation models including GPT-4, Claude, Gemini, Llama, and Mistral.
How is AI security testing different from traditional pentesting?
Traditional pentesting targets network and application layers. AI security testing targets the model itself — prompt injection, training data leakage, output manipulation, and tool-calling exploits require entirely different methodologies.
Are findings protected by attorney-client privilege?
Yes. Because SIRI is a law firm, all security findings are delivered under attorney-client privilege. This means they cannot be compelled in regulatory investigations or litigation — a critical advantage over consulting-only firms.
How long does an engagement take?
Preliminary risk assessment in 72 hours. Full adversarial red team report in 10 business days. SIRI Shield subscribers receive quarterly testing on a continuous basis.
Do you test third-party AI vendors we use?
Yes. Our AI vendor due diligence service assesses model governance, data processing terms, liability allocation, and security posture of AI vendors before you sign or renew contracts.
What regulations apply to AI systems in India?
DPDPA 2023 applies to personal data processed by AI. MeitY has published responsible AI guidelines. RBI and SEBI have sector-specific AI/ML directives. The EU AI Act applies if you serve European users. We map every finding to applicable frameworks.
Ready to Secure Your AI?

Book Your Free
AI Security Assessment.

30-minute consultation. No commitment. Privilege-protected from the first conversation.

📞 +91 7981912046 · WhatsApp · Mon–Sat, 9 AM – 7 PM IST

Disclaimer: All security testing is conducted under a signed rules-of-engagement agreement with explicit written authorisation from the asset owner. Findings are confidential and delivered only to authorised client representatives.
Note: AI security testing is an emerging field; threat vectors and best practices evolve rapidly. Our assessments reflect current OWASP LLM Top 10, MITRE ATLAS, and NIST AI RMF guidance.
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