By Sarang Warudkar - Sr. CASB Technical Product Marketing Manager, Skyhigh Security
December 16, 2024 3 Minute Read
The rapid adoption of Large Language Models (LLMs) has revolutionized organizations’ use of AI, from improving customer interactions to enabling advanced data analysis. However, with AI’s power comes the responsibility to address emerging security vulnerabilities. Simple prompt-level protections are no longer enough—what’s needed is a strong, system-wide approach to secure AI pipelines effectively.
Skyhigh SSE, a pioneer in AI security, delivers a comprehensive framework aligned with the 2025 OWASP Top 10 LLM threats, ensuring AI systems remain safe, ethical, and reliable. Let’s explore the key risks and how Skyhigh SSE mitigates them.
The OWASP Top 10 LLM threats provide a clear roadmap for securing LLM applications, emphasizing visibility and controls across every stage of the AI system—from inputs and outputs to model training and supply chains.
1. Prompt Injection
Prompt injection manipulates LLM behavior through malicious inputs, compromising outputs and sensitive data.
Mitigation using Skyhigh SSE:
2. Sensitive Information Disclosure
LLMs can unintentionally expose PII, financial data, or business-critical information.
Mitigation using Skyhigh SSE:
3. Supply Chain Vulnerabilities
Third-party models, datasets, or plugins may introduce backdoors, biases, or security flaws.
Mitigation using Skyhigh SSE:
4. Data and Model Poisoning
Attackers inject malicious data during training, corrupting model behavior.
Mitigation using Skyhigh SSE:
5. Improper Output Handling
Unvalidated outputs may expose sensitive data or enable risks like SQL injection.
Mitigation using Skyhigh SSE:
6. Excessive Agency
LLMs with excessive privileges can interact with unauthorized systems or data.
Mitigation:
7. System Prompt Leakage
Attackers exploit system-level instructions to access sensitive configurations.
Mitigation using Skyhigh SSE:
8. Vector and Embedding Weaknesses
Insecure embeddings and vector databases can be manipulated for unauthorized access.
Mitigation:
Mitigation using Skyhigh SSE:
9. Misinformation
LLMs may generate inaccurate or misleading outputs (hallucinations), harming reliability.
Mitigation:
10. Unbounded Consumption
Excessive queries can overwhelm systems, leading to resource exhaustion.
Mitigation using Skyhigh SSE:
The interconnected, data-driven nature of modern AI systems demands a proactive, system-level security approach. Skyhigh SSE leads the way by addressing the full spectrum of OWASP Top 10 vulnerabilities.
By mitigating risks such as prompt injection, sensitive data leaks, and excessive agency, Skyhigh SSE enables organizations to secure their AI applications while maintaining performance and scalability.
Skyhigh SSE empowers businesses to unlock the full potential of AI safely and ethically. With its advanced security tools and multi-layered protections, Skyhigh SSE ensures that AI deployments remain trustworthy, scalable, and compliant.
Together, we can secure the future of AI.
Are you ready to secure your organization’s AI journey? Click here to learn more about how Skyhigh Security is safeguarding AI applications and leading the way in data protection for the AI era.
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