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AI Penetration testing

We’re among the few firms with offensive security expertise for AI systems, not just traditional apps.

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AI PT

Stay ahead of AI-specific threats like data leakage, prompt injection, and model manipulation, before they erode trust or compliance.

At GRSee, we simulate realistic adversarial attacks on your models and surrounding infrastructure to reveal these AI-specific risks—while helping your team mitigate them before they become real-world incidents.

AI penetration testing assesses the security of AI-powered systems, models, and infrastructure by simulating adversarial attacks to identify vulnerabilities in how they process, store, and interact with data. Whether you’re using machine learning (ML), large language models (LLMs), recommendation engines, or custom AI integrations, our AI pentesting approach goes beyond traditional application security. We examine how models can be manipulated, how data can leak, and where attackers can gain unintended access or behavior.

Pentesting AI systems requires a specialized focus on unique vulnerabilities, such as: Prompt injection (in LLMs), Model inversion (reconstructing training data), Data poisoning (influencing model behavior during training), Adversarial examples (inputs designed to fool models), Over-permissive plugin behavior (in AI assistants).

AI PT Benefits

Identify AI-Specific Vulnerabilities

Discover threats unique to AI systems that traditional pen testing would miss.

Prevent Data Leakage

Ensure models don’t inadvertently expose training data, sensitive prompts, or user inputs.

Simulate Real-World AI Threats

Test how attackers can manipulate outputs or bypass business logic protections.

Streamlined Sales Processes

Meets client requirements for vendor compliance, avoiding delays in deal closures.

Reduced Risk

Mitigates potential data breaches by identifying and addressing vulnerabilities.

Scalable Framework

Establishes a foundation for future security improvements and compliance efforts.

Support Compliance with Emerging Standards

Align with frameworks like NIST AI RMF, ISO 42001, and AI-related GDPR requirements.

What sets us apart

Beyond the Basics
We go beyond automated scans, focusing on identifying high-impact vulnerabilities and uncovering business logic vulnerabilities that traditional tools and other vendors miss.
We combine strategic automation to quickly detect common vulnerabilities with manual deep-dive testing to uncover complex, hard-to-find security flaws that other miss.
Every test is customized to your unique environment, ensuring accurate and relevant results.
We provide a comprehensive report detailing identified vulnerabilities along with prioritized remediation steps to enhance your security posture effectively.
Get comprehensive test results without long wait times, helping you act quickly on findings.
Our team consists of experienced security professionals with deep expertise in offensive security.
We rely on battle-tested security testing standard, OWASP AI Testing Guide.
We believe in a hands-on, transparent approach. From scope definition to final reporting, we work closely with your team through kickoff calls, status updates, and post-assessment reviews. Our experts are available to answer questions, clarify findings, and help your team effectively implement security improvements.

Our penetration test results are delivered through a dedicated platform, giving you full visibility into the project status, remediation progress, and security insights. Track Vulnerabilities, manage fixes efficiently, and access analytics on findings in one place, to ensure a streamlined and effective security improvement process.

Service Page Asset

Simplify the Complex.
Deliver with Care.

01.

Deep Scope Mapping & Attack Surface Analysis

We start by gaining a comprehensive understanding of your environment. This includes mapping the attack surface, footprinting every aspect of the application, and analyzing entry points, architecture, configurations, technologies, operations, and documented procedures to ensure no security gaps go unnoticed.

02.

Discovery & Reconnaissance

Using a combination of manual research and automated scanning, we gather intelligence on your systems, identifying potential weaknesses and misconfigurations. This phase helps us understand how an attacker might gather information before launching an attack.

03.

Adversarial & Prompt-Based Testing

Using techniques from the OWASP for LLMs and OWASP AI Testing Guide, we simulate prompt injection, output hijacking, data leakage, model manipulation, and misuse scenarios.

04.

Comprehensive Reporting & Remediation Guidance

We provide a detailed penetration test report with findings categorized by risk levels, along with clear, prioritized remediation steps to help you address vulnerabilities efficiently.

05.

Seamless Test Management via Our Platform

All results are delivered through our dedicated platform, allowing you to track the project status, manage the remediation process, and gain insights and analytics on findings. This ensures a streamlined security improvement process with full visibility.

06.

Retesting

Once vulnerabilities are remediated, we perform retesting to validate the fixes and ensure no further security risks exist.

07.

PTaaS

For ongoing protection, we offer continuous penetration testing through our PT as a Service (PTaaS) program.

Resources

Shay Aberbach • September 1, 2025

Penetration Test for Startups: Full Guide to Early Security

Shay Mozes • September 1, 2025

Penetration Testing Checklist: What to Do Before, During, and After the Test

Shay Mozes • August 8, 2025

Vulnerability Scan vs Penetration Test

Shay Aberbach •August 26, 2025

Blue Team vs. Red Team in Cybersecurity: Differences Explained

FAQ

What types of AI systems do you test?
We test LLMs (like GPT-based models), traditional ML models, classification/regression systems, recommendation engines, generative AI (image/text), and AI-assisted features like chatbots and copilots.
Prompt injection, model inversion, adversarial input manipulation, data leakage from model outputs, overly broad plugin access, insecure fine-tuning, and indirect prompt leakage.
Traditional PT focuses on infrastructure, code, and known CVEs. AI PT targets model behavior, data flows, and human-computer interaction risks like prompt abuse, hallucination exploitation, or training data extraction, unique to AI systems.
Most projects take 2–4 weeks, depending on the system’s complexity, the number of endpoints, and the scope of AI integrations.
Yes. AI pen testing supports alignment with NIST AI RMF, ISO 42001, emerging EU AI regulations, and privacy mandates under GDPR.

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