Generative AI Security: Addressing OWASP LLM Top 10 Risks with Forcepoint AI Data Security

The active adoption of generative artificial intelligence (GenAI) and large language models (LLMs) opens up new opportunities for business, but simultaneously creates serious risks for information protection. Forcepoint, one of the global leaders in cybersecurity, emphasizes the need for systemic control over employee interactions with AI services.

To systematize the main threats, the international OWASP community formed the OWASP Top 10 for LLM Applications ranking. Without reliable control tools, the use of GenAI can lead to leaks of intellectual property, personally identifiable information (PII), and regulatory compliance violations. Forcepoint offers a comprehensive solution, Forcepoint AI Data Security, allowing companies to safely leverage the benefits of innovation.

Main security threats when working with LLMs according to OWASP

The use of AI models in an enterprise environment creates specific vulnerabilities that cannot be covered by standard security tools:

• LLM01: Prompt Injection: manipulation of prompts (direct or indirect) to bypass internal model constraints and force it to perform unintended actions.
• LLM02: Sensitive Information Disclosure: accidental or intentional disclosure of confidential data, source code, financial reports, or PII to public AI services.
• LLM03: Supply Chain Vulnerabilities: risks associated with using third-party training datasets, third-party models, plugins, and outdated libraries.
• LLM04: Data and Model Poisoning: intentional modification of training data or fine-tuning processes to create hidden vulnerabilities or distort results.
• LLM05: Improper Output Handling: failure to validate and filter model outputs before passing them to other systems, which can lead to XSS, SQL injection, or arbitrary code execution.
• LLM06: Excessive Agency: granting AI models and plugins overly broad permissions to perform actions in enterprise systems without proper human confirmation.
• LLM07: System Prompt Leakage: compromise of internal system instructions (system prompts) that may contain trade secrets or proprietary algorithms.
• LLM08: Vector and Embedding Weaknesses: improper security of vector embeddings and vector databases, which can lead to context data leaks.
• LLM09: Misconfiguration and Rogue AI: security configuration errors in the AI runtime environment or the emergence of unmanaged "shadow" AI models (Shadow AI).
• LLM10: Model Theft: unauthorized access, extraction via targeted queries, or exfiltration of proprietary models and training datasets.

Organizations should not have to choose between adopting artificial intelligence and ensuring cybersecurity. The key to success is smart data control in real time.

How Forcepoint AI Data Security addresses AI security challenges

The Forcepoint AI Data Security solution is designed to protect sensitive data at all stages of its interaction with web services, cloud applications, and AI tools (ChatGPT, Claude, Copilot, etc.).

Automated monitoring and data loss prevention (DLP for AI)

• Accurate contextual analysis: utilization of patented Exact Data Matching (EDM) algorithms and machine learning to block the transfer of confidential files in AI prompts.
• Real-time protection: automatic detection of PII, trade secrets, and source code when typed into text fields of public AI chats.

Visibility and usage control (AI Governance)

• Shadow AI discovery: complete visibility into which AI services employees are using and what volumes of data are being sent there.
• Flexible access policies: the ability to differentiate GenAI usage permissions based on user roles and data sensitivity levels.

Adaptive protection considering user behavior

• Behavioral analysis (Risk-Adaptive Protection): dynamic adjustment of security policy enforcement based on an individual user's risk level.
• Employee education: detection of risky actions and display of pop-up guidance explaining the risks of sharing corporate data.

Comparison of data protection approaches when working with AI

Traditional DLP and Web Security

• Focus: blocking websites or standard files (PDF, Docx) based on basic pattern matching.
• Limitations: unable to recognize sensitive context inside prompts or predict risks specific to LLM architecture.

Forcepoint AI Data Security

• Focus: deep real-time analysis of prompt text, data context, and user behavior.
• Advantage: enables safe authorization of GenAI usage by blocking only unsafe actions without interrupting employee productivity.

Why implement Forcepoint solutions with Softprom

Softprom is an official distributor of Forcepoint. We provide a full range of services for selecting, testing, and deploying data protection systems.

• Expertise: certified Softprom specialists will help configure security policies to match your organization's standards.
• Pilot projects (PoC): free proof-of-concept testing of Forcepoint AI Data Security in your actual infrastructure environment.
• Support: technical guidance at all stages of project design, deployment, and ongoing maintenance.