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Service

LLM Application Security

This service is ideal for organizations building or deploying AI chatbots, internal assistants, customer support bots, RAG platforms, or agent-based workflows.

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Overview

Purpose and fit

Our LLM Application Security service focuses on testing chatbots, copilots, agents, and Retrieval-Augmented Generation applications for AI-specific security risks. We assess whether large language model applications can be manipulated into leaking data, bypassing controls, or using connected tools unsafely.

This service is ideal for organizations building or deploying AI chatbots, internal assistants, customer support bots, RAG platforms, or agent-based workflows.

Business value

This service helps prevent AI data leakage, unsafe automation, unauthorized access, and reputational damage caused by insecure LLM application design.

Expected outcomes

  • Prompt injection and data exposure findings.
  • Recommendations for retrieval, tool, and permission boundaries.
  • Guardrail checklist for production launch.
Engagement details

Specific information for this service.

ACT

Key activities

We test how the LLM application responds to malicious or unintended inputs, whether it can expose confidential information, and whether connected tools are properly restricted. We also review guardrails, access controls, retrieval boundaries, and user role separation.

DEL

Deliverables

  • Prompt injection test results
  • RAG exposure review
  • Agent tool guardrail assessment
  • Data leakage findings
  • Risk-ranked vulnerability report
  • Practical mitigation guidance
  • Secure design recommendations
  • Monitoring and logging recommendations
CHK

Core checks

  • Prompt injection testing
  • RAG exposure review
  • Agent tool guardrails

Ready to scope the work?

Share your target environment, timeline, and risk concerns so we can shape the right engagement.

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