Where Public LLMs Fall Short in Safety, Security, and Compliance Controls

While public LLMs do provide some level of AI security and safety, deploying a dedicated AI governance software can significantly enhance safety, security, and compliance, tailored to specific organizational needs and risk profiles.

Benefits of an AI Firewall like AIceberg

1. Advanced AI Threat Detection: AI Firewalls can be equipped with sophisticated monitoring tools that detect and mitigate potential AI cybersecurity threats in real time. This includes AI security against data leaks, unauthorized access, and other cybersecurity threats that might not be fully addressed by the LLM's built-in safeguards.

2. Control Over Model Interactions: AI security solutions provide more granular control over how users interact with the LLM. This includes managing access levels, tracking usage patterns, and preventing misuse of the AI system, which can be critical for maintaining operational security and integrity.

3. Enhanced Data Privacy: By using generative AI security, sensitive information can be better protected. Prevent sensitive data from being sent to the LLM provider, thus maintaining data privacy and complying with stringent data protection regulations like GDPR.

4. Customized Security Policies: Dedicated AI governance software allows for the implementation of security policies that are tailored specifically to your organization's needs. This can include stricter content filters, specific data handling rules, and bespoke behavioral restrictions that may not be available through public LLM settings.

5. Improved Compliance Control: For organizations subject to strict regulatory requirements, an AI compliance software can help ensure compliance with industry-specific regulations. This is particularly important in sectors like healthcare, finance, and legal where data handling and processing are heavily regulated.

6. Redundancy and Layered Defense: Add an additional layer of security, creating a more robust defense strategy. Even if the built-in safeguards of a public LLM are bypassed or fail, AI security solutions serve as a secondary checkpoint to prevent exploitation.

7. Adaptability to Emerging Threats: Enable fast response to new and evolving AI cybersecurity threats, something that built-in safeguards in public LLMs may be significantly slower to address due to their standardized nature.

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Agentic Workflows Increase Risk

In the context of agentic workflows, where AI systems may autonomously make decisions or act on behalf of users, deploying a dedicated AI risk management solution becomes seven more critical. Here are several reasons why this additional layer of AI security is beneficial, even when public LLMs include built-in safeguards and allow for some control through system prompts:

1. Prevention of Rogue AI Behavior: In agentic workflows, there is a potential for AI systems to develop or trigger unintended or rogue behaviors. AI security solutions can monitor and intercept such behaviors before they affect operations or lead to security breaches.

2. Real-Time Threat Response: AI Firewalls can provide real-time AI threat detection and response to security threats, which is crucial in fast-paced environments where agentic AI systems operate. This immediate response can mitigate potential damages more effectively than built-in safeguards that may not update as quickly.

3. Granular Access and Action Controls: AI governance software can provide detailed control over what actions AI agents are permitted to execute, particularly in sensitive environments like finance or healthcare. This helps prevent actions that could lead to compliance violations or expose sensitive data.

4. Enhanced Autonomy Control: Agentic AI systems often have higher autonomy in decision-making, which can pose unique security risks. A dedicated AI governance can enforce stricter rules and protocols to manage and control the autonomous actions taken by these AIs, ensuring they align with organizational policies and ethical guidelines.

5. Dynamic Security Adaptations: Agentic AI systems can adapt and learn from interactions, potentially evolving beyond their initial programming. Dedicated AI security solutions can dynamically adjust its security measures based on the AI's learning and changes in behavior, providing continuous protection that evolves with the AI.

6. Isolation from External Threats: Isolate agentic AI systems from external threats, such as malicious inputs that might exploit AI vulnerabilities. This isolation is crucial in maintaining the integrity of the AI’s operational environment.

7. Audit and Compliance Assurance: For agentic AIs, maintaining a clear audit trail of decisions and actions is crucial for compliance and review. AI compliance software logs and monitors all AI interactions and decisions to ensure compliance with legal and regulatory standards.

8. Limiting Scope of Action: By setting boundaries on what actions an AI can perform, AI governance help ensure that agentic systems operate within predefined limits, reducing the risk of unexpected or undesired outcomes.

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