AI Security Assessment
Secure your artificial intelligence deployments against adversarial attacks and data leakage.
Book AssessmentSecuring the Future of Generative Intelligence
Atgardas AI Security Assessment is designed to help organizations safely adopt artificial intelligence while minimizing risk exposure. As enterprises rapidly integrate large language models (LLMs), generative AI, and machine learning systems, new attack surfaces emerge that traditional security frameworks fail to address.
Our approach combines adversarial testing, model analysis, and governance evaluation to identify vulnerabilities such as prompt injection, model manipulation, data leakage, and insecure API integrations. We simulate real-world attack scenarios to uncover how threat actors could exploit AI systems to extract sensitive data or manipulate outputs.
Beyond technical testing, we evaluate your AI governance, compliance alignment, and operational controls. The result is a comprehensive report including risk prioritization, remediation strategies, and executive-level insights to support secure AI adoption at scale.
Key Benefits & Deliverables
Adversarial LLM Testing
Simulation of prompt injection, jailbreaking, and bypassing safety filters on your custom models or integrations.
Data Leakage Prevention
Rigorous testing to ensure your models do not inadvertently disclose sensitive training data or PII to unauthorized users.
Governance & Compliance Map
Alignment with emerging AI security frameworks and standards, such as NIST AI RMF, ISO, and GDPR requirements.
Engagement Process
Architecture Review
Mapping the AI system architecture, data flows, API integrations, and trust boundaries.
Adversarial Simulation
Active red-team testing of the model and interface layer using advanced bypass methodologies.
Impact Analysis
Evaluating the severity of potential data exfiltration or logic manipulation on business operations.
Strategic Reporting
Delivery of actionable remediation steps and executive summaries for leadership teams.
Frequently Asked Questions
It evaluates the security risks of AI systems, including vulnerabilities in models, data handling, and integrations.
AI introduces new risks like prompt injection, data leakage, and model manipulation that traditional security does not cover.
Yes, we specifically test LLMs for prompt injection, jailbreaks, and sensitive data exposure.
Absolutely. We assess both internal and customer-facing AI systems.
Finance, healthcare, SaaS, government, and any organization using AI.
Yes, we align findings with standards like ISO, NIST, and GDPR.
Typically 2–4 weeks depending on system complexity.
No, testing is controlled and designed to avoid operational impact.
Yes, detailed and prioritized fixes are included.
Both options are available depending on your AI maturity.
See What a Real Finding Looks Like
Download a redacted example from past engagements to understand our reporting methodology, risk scoring, and remediation guidance.
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