AI Security Risk Assessment

Protect Your AI Integration

As organizations integrate AI capabilities into their applications, new security challenges emerge that traditional testing doesn’t address. From prompt injection attacks to sensitive data disclosure and model manipulation, AI-specific vulnerabilities can lead to data breaches, compromised decisions, and operational disruptions.

Forward Security’s AI Security Risk Assessment protects your AI-powered applications using the OWASP Top 10 for LLM Applications, ensuring your AI integrations are resilient against emerging threats.

Specialized Security Testing for AI Applications

Our AI Security Risk Assessment is designed for applications that integrate Large Language Models (LLMs) or AI capabilities. Whether you’re using third-party AI APIs like OpenAI, Anthropic Claude, Google Gemini, or running self-hosted models, we test the security of your AI integration points.

Common AI Patterns We Secure:

AI chatbots and virtual assistants
RAG (Retrieval-Augmented Generation) systems
Document analysis and processing
AI-powered code assistants
Content generation tools

AI Platforms We Test:

OpenAI (GPT-4, GPT-3.5)
Anthropic Claude
Google Gemini/Vertex AI
AWS Bedrock
Azure OpenAI Service
Self-hosted open-source models (Llama, Mistral, etc.)

OWASP LLM Top 10 Coverage

Our assessment covers all 10 critical risks from the OWASP Top 10 for LLM Applications 2025:

LLM Category	Description
LLM01: Prompt Injection	Testing for direct and indirect manipulation of AI behavior through crafted inputs.
LLM02: Sensitive Information Disclosure	Verifying that the AI does not inadvertently reveal confidential data, personally identifiable information (PII), or proprietary information.
LLM03: Supply Chain Vulnerabilities	Assessing risks introduced by third-party AI components, models, training data, plugins, or dependencies.
LLM04: Data and Model Poisoning	Evaluating exposure to manipulated or malicious training data, fine-tuning datasets, or embeddings.
LLM05: Improper Output Handling	Testing the validation, sanitization, and secure handling of AI-generated outputs.
LLM06: Excessive Agency	Assessing controls that limit AI autonomy and prevent unintended or unauthorized actions.
LLM07: System Prompt Leakage	Verifying protections against exposure of system prompts, internal instructions, or sensitive configuration details.
LLM08: Vector and Embedding Weaknesses	Testing the security of retrieval-augmented generation (RAG) systems, vector databases, and embedding storage.
LLM09: Misinformation	Assessing the accuracy, reliability, and trustworthiness of AI-generated outputs and decisions.
LLM10: Unbounded Consumption	Testing for resource exhaustion risks, including denial-of-service conditions and uncontrolled compute or token usage.

Service Tiers

Express (Rapid Assessment)

High-priority OWASP LLM Top 10 items
Focus on runtime vulnerabilities and immediate risks
Primarily black-box testing
Best for: Initial AI security baseline, simple AI integrations
Duration: 1-2 weeks

Book your Free Consultation

Level 1 (Comprehensive Assessment)

Complete OWASP LLM Top 10 coverage
Full security posture including architecture review
Black-box + gray-box testing with design review
Best for: Production AI applications, sensitive data handling, regulatory requirements
Duration: 2-4 weeks

Book your Free Consultation

Our Process

AI Integration Discovery

Architecture Review

Security Testing

Risk Assessment & Reporting

1. AI Integration Discovery

We work with your team to understand how your application integrates with AI services, what data is sent in prompts, how responses are processed, and where user input intersects with AI functionality.

2. Architecture Review

We review your AI integration architecture, prompt construction methods, data handling practices, and security controls specific to AI interactions.

3. Security Testing

Our team conducts comprehensive testing covering prompt injection, output validation, data leakage, and all applicable OWASP LLM Top 10 controls using manual and automated methods.

4. Risk Assessment & Reporting

We document all findings with risk levels, integrate them into threat scenarios, and provide recommended controls for securing your AI integrations.

Comprehensive Security Documentation

AI Security Risk Assessment Report – Detailed findings with risk ratings based on impact and likelihood, specific to your AI implementation

Technical Details of Findings – Step-by-step reproduction guidance for your development team to validate and fix vulnerabilities

Threat Scenarios – Real-world attack scenarios specific to your AI integration architecture

Recommended Controls – Practical security controls and best practices for securing AI interactions

Standalone or Bundled

Bundled with Application Security Assessment

Add AI security testing to your existing AppSec assessment for integrated coverage and cost savings.

Standalone AI Security Assessment

Focused AI security testing for applications where traditional AppSec testing is already complete.

Part of Annual Security Program

Include AI security testing in your ongoing security assurance program as AI capabilities evolve.

Why Choose Forward Security for AI Security?

Developer-Driven Expertise

Our team of ex-software developers understands both application security and AI integration patterns. We know how development teams build with AI APIs and can identify vulnerabilities that generic security testing misses.