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service-iconAI Security

AI & LLM Security
Testing Services

AI systems break in ways traditional apps don't. Prompt injection, data leakage through model outputs, jailbreaks that bypass safety guardrails. We test LLMs, RAG pipelines, and AI-powered applications for the vulnerabilities that standard pentesting won't catch.

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LLM & Model Expertise

We test GPT, Claude, Gemini, open-source models, and custom fine-tuned LLMs

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OWASP LLM Top 10

Full coverage of prompt injection, data poisoning, system prompt leakage, and all Top 10 risks

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Adversarial Red Teaming

We attack your AI the way real threat actors would, jailbreaks, extraction, and manipulation

The AI Security Landscape

A web app pentest won't find a prompt injection vulnerability. A network scan won't detect that your chatbot leaks customer data when asked the right question. AI systems have their own class of vulnerabilities. From jailbreaks that bypass safety filters to adversarial inputs that corrupt model behaviour and they need testing built specifically for how they fail.

Organisations deploying ChatGPT-style applications, custom LLMs, RAG systems, AI agents, and machine learning models face risks including unauthorised data extraction, model theft, adversarial inputs, and unintended harmful outputs. These vulnerabilities can lead to data breaches, compliance violations, financial losses, and severe reputation damage.

When AI is making decisions that affect customers, finances, or operations, a security flaw isn't just a bug, it's a liability.

Our AI Security Testing Services

LLM Application Security

LLM Application Security

Your LLM-powered app is only as secure as the prompts it processes. We test applications built on GPT, Claude, Gemini, and open-source models for prompt injection, jailbreaking, and data leakage. The attacks that scanners and traditional pentests miss entirely.

Prompt injection and multi-turn jailbreak chains
System prompt extraction and override
PII and training data leakage through outputs
Output Safety & Guardrail Testing

Output Safety & Guardrail Testing

Safety filters and content guardrails are only effective until someone finds the right bypass. We test your model's output controls for harmful content generation, filter evasion techniques, and edge cases where safety alignment breaks down.

Content filter and safety guardrail bypass
Harmful and biased output generation testing
Output sanitization and injection into downstream systems

RAG & Vector Database Security

RAG pipelines add a whole new attack surface. We test your retrieval layer. Pinecone, Weaviate, Chroma, pgvector, or custom setups for unauthorised knowledge access, embedding poisoning, and indirect prompt injection through retrieved documents.

Indirect prompt injection via retrieved documents
Vector database access control bypass
Embedding poisoning and knowledge base manipulation

Model Supply Chain Security

The model you downloaded from Hugging Face might not be what you think it is. We assess model provenance, check for poisoned pre-trained weights, test for malicious payloads in model files, and review your ML pipeline dependencies for known vulnerabilities.

Model file integrity and deserialization attacks
Pre-trained weight poisoning detection
ML pipeline dependency and supply chain review

OWASP LLM Top 10 Coverage

Prompt Injection
Sensitive Information Disclosure
Supply Chain
Data and Model Poisoning
Improper Output Handling
Excessive Agency
System Prompt Leakage
Vector and Embedding Weaknesses
Misinformation
Unbounded Consumption

Industry Applications

Finance & Banking

Fraud detection models, credit scoring systems, and trading algorithms that attackers can manipulate through adversarial inputs, plus chatbots that may leak customer financial data through prompt injection

Healthcare

Diagnostic AI and treatment recommendation systems where adversarial attacks could cause misdiagnosis, and where patient data extraction violates HIPAA

Enterprise SaaS

Code assistants that may leak proprietary source code, knowledge bases that expose confidential documents, and AI tools with access to internal systems

E-commerce

Recommendation engines vulnerable to poisoning, pricing models susceptible to manipulation, and customer-facing chatbots that can be tricked into revealing backend data

AI Regulations Are Here

The EU AI Act is now in effect. NIST has published the AI Risk Management Framework. ISO 42001 sets the standard for AI governance. If your AI systems haven't been security tested, you're not just carrying risk, you may be falling short of regulatory requirements. Prompt injection, data leakage, and output manipulation aren't theoretical risks anymore. They're audit findings.

AI is moving fast. Security testing for it should move just as fast. Let's make sure your models aren't leaking data or doing things they shouldn't.

Get a Quote

Why Choose XParth?

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OSCP & CREST certified testers on every engagement
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95+ security assessments across fintech, healthcare, and SaaS
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One-time assessments, retainers, or ongoing programs, your call
Reports your dev team can act on, with fix guidance and reproduction steps

Need Immediate Assistance?

Need to fast-track a pentest or discuss scope? Talk directly with our senior consultants.

+91-7070703507