By Sarang Warudkar – Sr. CASB Technical Product Advertising and marketing Supervisor, Skyhigh Safety and John Duronio – Software program Gross sales Engineer, Skyhigh Safety
December 12, 2024 3 Minute Learn
As AI and enormous language fashions (LLMs) rework companies, they create each alternatives and dangers. Whereas AI drives effectivity and innovation, it additionally poses challenges like information breaches, compliance violations, and shadow AI utilization. The speedy adoption of AI typically outpaces governance, leaving organizations weak to reputational, monetary, and authorized dangers with out correct safety measures.
Recognizing the important significance of safe AI adoption, the White Home not too long ago issued its inaugural Nationwide Safety Memorandum on AI, mandating all U.S. federal businesses to nominate a Chief Synthetic Intelligence Officer inside 60 days of the directive.
This memorandum underscores the urgency of creating sturdy governance for AI utilization to stop cybersecurity dangers and guarantee compliance. Skyhigh Safety is on the forefront of addressing these wants with its Safe Service Edge (SSE) platform, that includes Skyhigh AI, a sophisticated answer for managing AI safety. Skyhigh AI aligns seamlessly with the Nationwide Institute of Requirements and Know-how (NIST) Synthetic Intelligence Danger Administration Framework (AI RMF 1.0), providing a structured method to managing AI dangers throughout 4 core features: Map, Measure, Handle, and Govern.
Let’s delve into how Skyhigh AI helps organizations align with the NIST AI RMF and implement safe, accountable AI practices.
1. Map: Figuring out Context and Potential Dangers
The primary perform of the NIST AI RMF emphasizes understanding the context, scope, and stakeholders concerned in an AI system. Skyhigh AI, launched on the 2024 RSA Convention, excels on this area by delivering:
- Complete visibility into sanctioned, shadow, and personal AI functions.
- Help for over 1,100 AI functions by way of the Skyhigh Cloud Registry.
- 75+ danger attributes together with AI particular attributes
This mapping functionality gives organizations with an in-depth understanding of their AI ecosystem, enabling them to determine dangers related to AI software utilization in close to real-time and mitigate potential information breaches.
2. Measure: Assessing and Analyzing Dangers
As soon as the AI ecosystem is mapped, organizations should assess and quantify dangers. Skyhigh AI provides sturdy instruments to guage the safety of LLMs, together with:
- Safety Attributes for AI apps
- LLM-based danger attributes, similar to jailbreak potential, toxicity, bias, and malware technology
- ML-based Consumer Danger Scoring to pinpoint high-risk customers
Skyhigh AI simplifies the in any other case labor-intensive strategy of steady danger evaluation, leveraging automation to make sure organizations keep up to date on rising threats whereas aligning with NIST requirements.
3. Handle: Implementing Controls and Mitigation Methods
Danger identification alone is inadequate. The NIST AI RMF’s Handle perform focuses on implementing efficient controls to mitigate high-priority dangers. Skyhigh AI, built-in with its FedRAMP Excessive-certified Safe Net Gateway and CASB, delivers:
- Governance-based controls for managing AI functions like software block, exercise controls
- Choices to disable chat historical past for ChatGPT, stopping organizational information from getting used as coaching information
- Enforced character limits and blocked shared hyperlinks inside chat functions
- Superior Information Loss Prevention (DLP) to safeguard important information uploaded to AI apps with EDM, OCR capabilities
These measures empower organizations to mitigate dangers proactively whereas fostering productiveness and innovation.
4. Govern: Establishing Oversight and Steady Enchancment
Governance and steady enchancment are important for sustainable AI adoption. Skyhigh AI helps this with:
- Steady monitoring of shadow AI utilization
- Automated danger evaluation to make sure compliance with evolving laws
- An AI-driven DLP Assistant for no-code coverage creation, decreasing errors and enhancing safety
- ML-based false optimistic discount, minimizing alert fatigue for operational effectivity
These options allow organizations to determine sturdy oversight mechanisms, guaranteeing ongoing enhancements of their AI danger administration practices.
Conclusion: Skyhigh AI – A Trusted Associate in AI Danger Administration
Skyhigh AI provides visibility into AI apps, understanding of danger together with LLM based mostly danger attributes, DLP on information going to AI apps, Risk investigation and UEBA on AI apps.
This complete Skyhigh AI method totally aligns with the NIST AI RMF. By addressing the framework’s core features—Map, Measure, Handle, and Govern—Skyhigh AI equips organizations to harness the transformative potential of AI whereas safeguarding in opposition to related dangers. As AI continues to evolve, Skyhigh AI stays a trusted accomplice in enabling safe, accountable, and progressive AI adoption.
