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AI SecurityServices

AI / LLM Security

We test LLM-based applications against a new class of risks such as prompt injection, data leakage and insecure output handling.

Scope

  • OWASP LLM Top 10 assessment
  • Direct and indirect prompt injection
  • RAG and data access boundaries
  • Output validation and guardrail testing

Approach

  1. 01

    System map

    We map models, data sources, tools and user interactions.

  2. 02

    Threat modeling

    We define injection, data leakage and abuse scenarios.

  3. 03

    Attack and evaluation

    We challenge the system with manual and automated attack sets.

  4. 04

    Guardrails

    We recommend permission boundaries, validation and monitoring.

Deliverables

  • AI threat model
  • Successful attack examples with evidence
  • Guardrail and architecture recommendations
  • Re-evaluation results

Let’s define the scope together.

Tell us what you need and our specialists will prepare a tailored proposal.