AI/LLM Security Assessments
Harden AI Systems Before They Become Your Weakest Link
Offensive Security
CyberOne’s AI/LLM Security Assessments uncover where your AI systems are vulnerable before those weaknesses can be exploited.
We assess the security of your AI infrastructure, models, and data pipelines across on-prem, cloud, and hybrid environments. Whether you’re building with large language models (LLMs), training in AWS, or deploying inference pipelines at scale, we deliver a structured AI security assessment that exposes real threats and gives you actionable steps to harden your stack.
Don’t wait for attackers to show you where your AI is exposed, let CyberOne show you first.
What Our AI/LLM Security Assessment Includes
We begin by reviewing your model architecture, training data flows, API exposure, and deployment surface. Using a mix of offensive testing and architectural review, we identify prompt injection risks, insecure endpoints, weak IAM policies, model extraction vectors, and exposure to LLM-specific vulnerabilities. This isn’t a theoretical scan, it’s a true AI security risk assessment grounded in real-world attack methods.
CyberOne also delivers tailored assessments for cloud-native environments, including AWS AI security assessment capabilities, ensuring your model pipelines and infrastructure meet the security standards expected in regulated and high-risk industries.
If your organization is leveraging GenAI, open-source LLMs, or integrating LLMs into production apps, we’ll help you understand and close the gap between innovation and protection. Whether you’re worried about LLM cyber security or hardening LLM security controls, CyberOne delivers clarity and next steps you can act on immediately.
