Traditional pentest
Focuses on infrastructure, code and known CVEs.
Still needed for the app and cloud around your AI.
Certify & attest
Industry programs
Run it for you
Penetration testing
OneAudit
Every framework, one audit, one timeline.SOC 2, ISO 27001, PCI DSS and pentesting run together, with evidence collected once.
How OneAudit worksGRSee has become a trusted advisor when it comes to all security and compliance issues.Eilon Reshef, CTO & Co-Founder, Gong



Learn
Free tools
Stay ahead of AI-specific threats like prompt injection, data leakage and model manipulation, before they erode trust or compliance. We bring offensive security expertise for AI systems, not just traditional apps.
We were impressed by how deep and thorough the GRSee team got familiar with our platform during the onboarding process.Omri Mendelevich, CTO & Co-Founder, Dynamic Yield



Even when your cloud, APIs and application are secure, a model can still be manipulated into leaking data, ignoring its instructions or taking actions it should not. We simulate realistic adversarial attacks on your models and the infrastructure around them.
We examine how models can be manipulated, how data can leak, and where attackers can gain unintended access, then help your team mitigate it before it becomes a real incident.
Scope, test, report, retest: agreed with your team before we start.
Scope
Test
Report
Fix and keep going
Focuses on infrastructure, code and known CVEs.
Still needed for the app and cloud around your AI.
Targets model behavior, data flows and human-AI interaction.
Prompt abuse, hallucination exploitation and training data extraction.
Many teams need both: AI testing for the model, traditional testing for the app and cloud around it.
GRSee has become a trusted advisor when it comes to all security and compliance issues.Eilon Reshef, CTO & Co-Founder, Gong
Related services
Working with GRSee felt like working with an extension of our own team.Tomer Cohavi, VP Engineering, Snappy



Still not sure? Bring your questions to a scoping call.
LLMs, traditional machine learning models, classification and regression systems, recommendation engines, generative AI for images and text, and AI features such as 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.
Yes. Infrastructure security does not address AI-specific risks. Models can still be vulnerable to prompt injection, output manipulation, data leakage or adversarial attacks on their behavior.
Yes. We assess how third-party tools, plugins, APIs and embedded models handle permissions, data access, authentication and user input.
Testing is planned to minimize disruption. We agree scope, attack scenarios and safety boundaries with your team before we begin.
Most projects take 2 to 4 weeks, depending on the system's complexity, the number of endpoints and the AI integrations in scope.
Yes. It supports alignment with NIST AI RMF, ISO 42001, emerging EU AI regulation and privacy requirements under GDPR.
A report with vulnerabilities, attack scenarios, business impact, affected components and prioritized remediation, plus technical walkthroughs to help validate fixes.
Pick a time that suits you. You leave with a scope and a fixed quote.
Local teams, your time zone
We work in your time zone and support you in multiple languages.
We truly enjoyed working with you and highly recommend your services to anyone looking for professionalism and excellence in cybersecurity.Kobi Lechner, Co-Founder and COO, Rescana


