Securing the Next Generation of AI Systems

Service Overview

AI systems, particularly large language models (LLMs) and machine learning applications, introduce unique attack surfaces that adversaries can exploit. These models are susceptible to adversarial manipulation, data poisoning, model extraction, and prompt injection attacks.

SilentGrid’s AI/LLM Penetration Testing evaluates the security of AI models, uncovering vulnerabilities that could lead to malicious model manipulation, privacy violations, and data leakage. Our engagements focus on securing AI pipelines, model integrity, and deployment environments.

Why AI/LLM Security is Critical

The Expanding AI Attack Surface

• Prompt Injection – Attackers manipulate LLM responses by crafting malicious prompts to bypass guardrails or extract sensitive data.
• Model Extraction – Adversaries attempt to reverse engineer AI models, stealing intellectual property or replicating models for malicious use.
• Data Poisoning – Manipulation of training data to inject bias, backdoors, or malicious behaviours into deployed models.
• Insecure Endpoints – Exposed AI APIs and inference endpoints provide new vectors for unauthorised access and manipulation.

SilentGrid’s Approach to AI/LLM Testing

SilentGrid leverages a combination of adversarial AI techniques, manual testing, and proprietary tooling to simulate real-world attacks on AI/LLM systems. Our experts assess AI pipelines from data ingestion to model deployment, identifying weaknesses at every stage.

Key Testing Areas

1. Prompt Injection and Output Manipulation

   • Testing LLMs for prompt injection vulnerabilities that lead to model misalignment, data leakage, or output control.
   • Evaluating model guardrails for bypass techniques.

2. Model Extraction and Theft

   • Simulating adversaries attempting to extract model weights, parameters, or training data through API interaction.
   • Testing for query-based model extraction techniques.

3. Adversarial Input Manipulation

   • Crafting adversarial inputs that trigger incorrect outputs or misclassification in AI systems.
   • Evaluating vision-based models for image perturbations and audio-based models for adversarial waveforms.

4. Data Poisoning and Model Integrity

   • Testing the resilience of models against data poisoning attacks during the training phase.
   • Simulating data manipulation that introduces bias or backdoors into production models.

5. API and Endpoint Security

   • Assessing inference APIs for improper authentication, excessive permissions, and insecure deployments.
   • Testing for model abuse, misuse, and unauthorised access to AI pipelines.

Deliverables and Reporting

SilentGrid provides in-depth insights into AI/LLM vulnerabilities, ensuring your models and deployment pipelines are resilient against adversarial threats.

You will receive:

• Adversarial Testing Report – Documentation of successful prompt injections, model theft attempts, and adversarial perturbations.
• Model Extraction Analysis – Highlighting pathways that lead to partial or complete model extraction.
• Training Data Security Report – Identifying data poisoning risks and model integrity issues.
• API/Endpoint Vulnerability Analysis – Assessing AI deployment endpoints for access control weaknesses and misconfigurations.
• Executive Summary – A high-level overview for leadership, summarising the impact of AI/LLM vulnerabilities and recommended mitigations.

Benefits of AI/LLM Penetration Testing

• Protect Model Integrity
  Ensure AI models remain free from manipulation, poisoning, or adversarial bias.

• Secure AI Pipelines
  Harden the entire AI lifecycle, from data ingestion to deployment.

• Prevent Model Theft and Extraction
  Safeguard intellectual property by detecting model extraction vulnerabilities.

• Harden Inference Endpoints
  Lock down AI/LLM APIs and inference points to prevent abuse and exploitation.

Is AI/LLM Testing Right for Your Organisation?

AI/LLM penetration testing is essential for:

• Organisations deploying LLMs, AI chatbots, or machine learning models in production.
• Businesses handling sensitive data through AI models.
• Companies developing proprietary AI/ML solutions and seeking to protect intellectual property.
• Enterprises integrating AI into customer-facing services or automation pipelines.

Get Started with AI/LLM Penetration Testing

SilentGrid’s AI/LLM Penetration Testing service helps secure cutting-edge AI models and machine learning pipelines, preventing adversarial attacks before they happen.
Contact Us to schedule an engagement and fortify your AI/LLM environment.