AI / LLM Pentesting
At EZ Solutions, our AI and LLM penetration testing is built for the new generation of applications powered by large language models, RAG pipelines, and autonomous agents. Every assessment is led by a Certified Ethical Hacker (CEH) and combines manual adversarial testing with proven offensive techniques to uncover the AI-specific risks that traditional scanners and code reviews simply cannot detect.
OWASP LLM Top 10 Coverage
We systematically test against the OWASP Top 10 for LLM Applications — including prompt injection, insecure output handling, training data poisoning, model denial of service, and excessive agency — to ensure your AI features are hardened against the most impactful real-world attacks.
Prompt Injection & Jailbreaks
We perform direct and indirect prompt injection attacks, jailbreak attempts, and system prompt extraction to confirm whether attackers can override your instructions, bypass safety controls, or hijack the model's behavior through user input or untrusted content.
Data Leakage & Sensitive Output
We test whether the model can be coerced into leaking system prompts, secrets, training data, customer PII, or content from other tenants — including through clever prompts, context manipulation, and side-channel techniques.
RAG & Knowledge Base Abuse
For retrieval-augmented generation systems, we assess vector stores, document ingestion pipelines, and access controls to identify cross-tenant leakage, indirect prompt injection via stored documents, and unauthorized retrieval of restricted content.
Agent & Tool Abuse
When LLMs are wired to tools, APIs, or actions, we test the full attack surface — confirming that agents cannot be tricked into making unauthorized API calls, exfiltrating data, executing commands, or chaining tools to escalate privilege.
Model & API Authentication
We assess how your application authenticates to model providers and how end users authenticate to your AI features — covering API key handling, rate limiting, quota abuse, and cost-amplification attacks against expensive endpoints.
Output Handling & Downstream Risk
LLM output is untrusted input. We test whether model responses are safely rendered and consumed downstream — looking for XSS via generated HTML, SQL injection via generated queries, and command injection via generated code or shell snippets.
Business Logic & Misuse
We map your AI workflows and abuse them the way a real attacker or malicious user would — bypassing content policies, manipulating decisions, gaming pricing or scoring logic, and uncovering misuse paths unique to your product.
Clear, Actionable Reporting
You receive a detailed report with prioritized findings, reproduction steps, evidence, and concrete remediation guidance — written so that both your engineers and your leadership team can act on it quickly.
Request an AI / LLM Pentest
Ready to harden your AI features? Get in touch and our team will scope an assessment tailored to your model stack and risk profile.