By Sarang Warudkar - Sr. CASB Technical Product Marketing Manager, Skyhigh Security and John Duronio - Software Sales Engineer, Skyhigh Security
December 12, 2024 3 Minute Read
As AI and large language models (LLMs) transform businesses, they bring both opportunities and risks. While AI drives efficiency and innovation, it also poses challenges like data breaches, compliance violations, and shadow AI usage. The rapid adoption of AI often outpaces governance, leaving organizations vulnerable to reputational, financial, and legal risks without proper security measures.
Recognizing the critical importance of secure AI adoption, the White House recently issued its inaugural National Security Memorandum on AI, mandating all U.S. federal agencies to appoint a Chief Artificial Intelligence Officer within 60 days of the directive.
This memorandum underscores the urgency of establishing robust governance for AI usage to prevent cybersecurity risks and ensure compliance. Skyhigh Security is at the forefront of addressing these needs with its Secure Service Edge (SSE) platform, featuring Skyhigh AI, an advanced solution for managing AI security. Skyhigh AI aligns seamlessly with the National Institute of Standards and Technology (NIST) Artificial Intelligence Risk Management Framework (AI RMF 1.0), offering a structured approach to managing AI risks across four core functions: Map, Measure, Manage, and Govern.
Figure 1. [Source: Artificial Intelligence Risk Management Framework (AI RMF 1.0)]
Let’s delve into how Skyhigh AI helps organizations align with the NIST AI RMF and implement secure, responsible AI practices.
1. Map: Identifying Context and Potential Risks
The first function of the NIST AI RMF emphasizes understanding the context, scope, and stakeholders involved in an AI system. Skyhigh AI, launched at the 2024 RSA Conference, excels in this domain by delivering:
- Comprehensive visibility into sanctioned, shadow, and private AI applications.
- Support for over 1,100 AI applications via the Skyhigh Cloud Registry.
- 75+ risk attributes including AI specific attributes
This mapping capability provides organizations with an in-depth understanding of their AI ecosystem, enabling them to identify risks associated with AI application usage in near real-time and mitigate potential data breaches.
2. Measure: Assessing and Analyzing Risks
Once the AI ecosystem is mapped, organizations must assess and quantify risks. Skyhigh AI offers robust tools to evaluate the security of LLMs, including:
- Security Attributes for AI apps
- LLM-based risk attributes, such as jailbreak potential, toxicity, bias, and malware generation
- ML-based User Risk Scoring to pinpoint high-risk users
Skyhigh AI simplifies the otherwise labor-intensive process of continuous risk assessment, leveraging automation to ensure organizations stay updated on emerging threats while aligning with NIST standards.
3. Manage: Implementing Controls and Mitigation Strategies
Risk identification alone is insufficient. The NIST AI RMF’s Manage function focuses on implementing effective controls to mitigate high-priority risks. Skyhigh AI, integrated with its FedRAMP High-certified Secure Web Gateway and CASB, delivers:
- Governance-based controls for managing AI applications like application block, activity controls
- Options to disable chat history for ChatGPT, preventing organizational data from being used as training data
- Enforced character limits and blocked shared links within chat applications
- Advanced Data Loss Prevention (DLP) to safeguard critical data uploaded to AI apps with EDM, OCR capabilities
These measures empower organizations to mitigate risks proactively while fostering productivity and innovation.
4. Govern: Establishing Oversight and Continuous Improvement
Governance and continuous improvement are essential for sustainable AI adoption. Skyhigh AI supports this with:
- Continuous monitoring of shadow AI usage
- Automated risk analysis to ensure compliance with evolving regulations
- An AI-driven DLP Assistant for no-code policy creation, reducing errors and enhancing security
- ML-based false positive reduction, minimizing alert fatigue for operational efficiency
These features enable organizations to establish robust oversight mechanisms, ensuring ongoing improvements in their AI risk management practices.
Conclusion: Skyhigh AI – A Trusted Partner in AI Risk Management
Skyhigh AI offers visibility into AI apps, understanding of risk including LLM based risk attributes, DLP on data going to AI apps, Threat investigation and UEBA on AI apps.
This comprehensive Skyhigh AI approach fully aligns with the NIST AI RMF. By addressing the framework’s core functions—Map, Measure, Manage, and Govern—Skyhigh AI equips organizations to harness the transformative potential of AI while safeguarding against associated risks. As AI continues to evolve, Skyhigh AI remains a trusted partner in enabling secure, responsible, and innovative AI adoption.
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