Proactive LLM Application Security Testing & AI Risk Validation

Simulate real-world attacks to strengthen AI defenses and trust. 

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Trust a proven framework to protect your LLM applications at scale.

LLM Application Penetration Testing Process

We identify all components — UI, APIs, data sources, model, and plugins — mapping the full interaction chain. 

We study the architecture, training data, integrations, and data flows to uncover strengths and weaknesses. 

We assess risks using OWASP LLM Top 10, including prompt injection, insecure outputs, data leaks, and plugin misuse. 

We conduct hands‑on tests to actively challenge the model and its integrations under real‑world conditions. 

We document vulnerabilities, explain their impact, and provide clear, actionable mitigation strategies. 

We implement fixes — validation, encoding, access controls, rate limiting — and embed continuous checks in CI/CD pipelines. 

Reduce AI and LLM Security Risk with ValueMentor’s Proven Expertise

Why ValueMentor

We help organizations identify and mitigate real-world risks in LLM-powered applications. ValueMentor combines advanced penetration testing, AI threat modeling, and governance alignment to ensure secure, resilient, and compliant AI systems. 

V-Trust Methodology

PMO-Led Delivery

Faster Delivery Accelerators

Secusy & AI driven GRC platform

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Secure your AI journey with confidence.

FAQs

Absolutely. We assess multi-agent systems, tool usage, memory handling, decision automation, and privilege escalation risks across AI-driven workflows. 

Testing can be performed in staging or controlled production environments using safe testing techniques to avoid service disruption or data loss. 

You receive a detailed report covering identified risks, real-world impact, exploit scenarios, severity ratings, and clear remediation guidance. 

Read our latest blog for advanced security insights and strategies to strengthen your defenses.

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