Keep up with cyber news, subscribe to our newsletter
Use Case

AI Risk Assessments

Generative AI introduces new cybersecurity threats and can amplify existing risks, exposing your critical assets to harm. As organizations rapidly adopt AI, they must navigate evolving AI regulations and protect their digital assets, employees, and customers. Our AI risk assessments use data-driven FAIR™ frameworks to identify threats, quantify impacts, and develop mitigation strategies that safeguard your business and users.

 communicate board executive managament
resilient digital ecosystem cyber risk
AI RIsk ASSESSMENTS

A data-driven approach to GenAI risk assessments

As regulatory requirements evolve to address AI security, cybersecurity leaders face increasing pressure to establish robust GenAI risk management practices. 

Data-drivenAI risk assessments provide a foundation for understanding GenAI risks and meeting emerging regulatory requirements. Assessing your GenAI solutions through a data-driven lens, you can identify potential exposures, quantify impact, and develop defendable strategies that align with business objectives and mitigate risk.

C-Risk Insight

Quantifying GenAI risk

For each Gen AI solution, we go through a structured process to identify critical assets (data, models, applications), map potential threat actors, analyze attack vectors (prompt injection, model poisoning), and assess potential impacts on confidentiality, integrity, and availability.

  • Start with a high-level estimation of Loss Event Frequency
  • Focus on an accurate estimation of Loss Magnitude
  • Identify most probable loss per event
  • Identify resilience controls
  • Go deeper to model preventative control treatment options 

Our quantitative risk assessments integrate the FAIR™ framework to help leaders make informed decisions on resource allocation, control implementation, and risk acceptance. This methodology allows organizations to balance innovation with appropriate risk management, ensuring GenAI adoption aligns with organizational risk tolerance.

cyber risk quantification compliance
Inventory and categorize you GenAI solutions

Assess all GenAI deployment across your digital environment. Is it a public LLM like ChatGPT, a pre-trained AI solution using your data or are you training your own model?

Scope your GenAI risk universe

For each solution, identify critical assets (data, models, applications), potential threat actors, attack vectors (prompt injection, model poisoning), and possible impacts on CIA triad.

Perform data-driven assessments

Senior executives may not have IT expertise, but they are increasingly aware of cyber risks. CRQ quantifies risk in financial terms, which can inform decisions on resource allocation and cyber risk oversight.

Bring clarity to your GenAI risks with quantitative assessments
Talk to a C-Risk expert

Our team of cyber risk experts model and measure your GenAI risk using industry standard frameworks like FAIR, providing you with strategic risk management insights.

Schedule a call
omproved commincation expert cyber risk
Zoom in

GenAI Kill Chain - understanding how GenAI amplifies existing risk scenarios

Reconnaissance

Threat actors use GenAI to scrape organizational information and dark web data, creating more comprehensive target profiles

Initial Access

GenAI enables very cybercriminals to create convincing phishing campaigns targeted at privileged users

Discovery & Lateral Movement

Attackers who compromise an account with access to internally connected LLMs, like Copilot, can rapidly learn about the environment and exploit the information

Data Exfiltration

Data exfiltration is enhanced by GenAI's ability to identify valuable data and classification systems

C-Risk

C-Risk supports GenAI Deployment

C-Risk supports risk and security leaders in their work to develop and deploy GenAI solutions in their organizations with data-driven AI risk assessments.

Would you like more information?
Contact us.

We look forward to hearing from you.

Thank you for taking the time to contact us via our form. Your message has been passed on to our teams, and we'll get back to you as soon as possible.
oops, an error has occurred!
Generative Ai risk assessments FAQ

Here are some answers to your commonly asked questions.

What is generative AI?

Generative AI is a category of artificial intelligence that generates new content based on training data. It is capable of creating new text, images, or other media that appears to be created by humans.

What is shadow AI?

Shadow AI or shadow GenAI are terms that refer to the unsanctioned use of AI tools and technologies and applications by employees of a company without organizational oversight or approval by the IT department.

What makes GenAI risks different from traditional technology risks?

GenAI introduces unique challenges including unpredictable outputs, potential data extraction through prompt engineering, model poisoning vulnerabilities, and the ability to amplify existing cyber threats.