GenAI & LLM Security Risk Assessment

Specialized security assessment for AI-powered applications, covering prompt injection, model manipulation, data leakage, and emerging AI-specific vulnerabilities.

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What We Assess

AI and LLM applications introduce entirely new attack surfaces that traditional security testing doesn't cover. Our specialized assessments identify vulnerabilities unique to generative AI systems, from prompt injection to model theft and data poisoning.

We follow the OWASP Top 10 for LLM Applications, NIST AI Risk Management Framework, and emerging AI security best practices to protect your AI investments.

Coverage Includes

  • Prompt Injection & Jailbreaking
  • Sensitive Data Exposure in Outputs
  • Training Data Poisoning Risks
  • Model Theft & Extraction Attacks
  • Insecure Plugin & Integration Security
  • Supply Chain & Model Provenance

Our Assessment Methodology

A cutting-edge approach to AI security evaluation

01

AI Architecture Review

We map your AI system architecture including model types, data flows, integrations, and trust boundaries.

02

Adversarial Testing

Systematic prompt injection, jailbreak attempts, and adversarial inputs to bypass safety guardrails and extract sensitive information.

03

Data & Model Security

Evaluation of training data handling, model storage security, API protection, and potential model extraction risks.

04

AI-Specific Findings

Detailed report with AI security risks, attack demonstrations, and practical mitigation strategies tailored to your AI use case.

Common AI Security Risks We Find

CRITICAL

Prompt Injection Attacks

Malicious inputs that manipulate LLM behavior to bypass instructions, access unauthorized data, or execute unintended actions.

CRITICAL

Training Data Extraction

Attackers extracting sensitive information from training data through carefully crafted prompts or model inversion attacks.

HIGH

Insecure Plugin Execution

LLM plugins or tool integrations that execute arbitrary code, access sensitive systems, or perform unauthorized actions.

HIGH

Model Denial of Service

Resource-intensive prompts designed to overwhelm models, causing service degradation or excessive API costs.

MEDIUM

Inadequate Guardrails

Missing or bypassable content filters, safety checks, and output validation leading to harmful or inappropriate outputs.

MEDIUM

Model Manipulation

Supply chain attacks through compromised models, weights, or fine-tuning processes introducing backdoors or biases.

What You'll Receive

AI Risk Assessment Report

Comprehensive analysis of AI-specific vulnerabilities with risk ratings based on potential business impact.

Attack Demonstrations

Proof-of-concept examples showing successful prompt injections, jailbreaks, and other AI-specific exploits.

Mitigation Strategies

Practical recommendations for prompt hardening, input validation, output filtering, and AI security controls.

AI Security Playbook

Customized guidelines for secure AI development, deployment, and ongoing monitoring of your AI applications.

Ready to Secure Your AI Applications?

Get started with a free 15-minute security snapshot to identify AI-specific security risks.

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