IBM Guardium AI Security

Overview

As AI adoption accelerates, organizations are discovering they are not equipped to handle the unique risks associated with generative AI (Gen AI) and autonomous AI agents. A growing number of companies struggle to integrate security and governance into their AI initiatives due to siloed teams with disparate tools and metrics, leading to duplicated efforts and critical blind spots. According to industry data, 81% of executives say secure and trustworthy AI is essential to their business success, yet only 24% of current Gen AI projects are being secured. This leaves a staggering gap, which is amplified when unauthorized "Shadow AI" and AI agents are added to the mix. IBM Guardium has been securing the world's most sensitive data for decades. We are now extending our data security capabilities to AI with IBM Guardium AI Security, a modern, AWS-native solution designed to secure the AI lifecycle. The IBM Guardium AI Security Advantage IBM Guardium AI Security is an enterprise-grade SaaS solution that works seamlessly with your existing infrastructure, including MCP Servers and various AI tools, to manage risk and enforce a unified security posture across your AI deployments.

1. Unified AI Visibility & Governance Our solution delivers an automated, continuously updated AI inventory with full system visibility and governance. It automatically detects and brings into inventory all AI use cases, including "Shadow AI" and autonomous AI agents running in the cloud, code repositories, and embedded systems. This visibility enables you to define and manage risk from a central point.

2. Proactive Risk & Compliance Management Guardium helps achieve continuous risk validation, audit readiness, and secure deployment across the AI lifecycle. Automated Red-Teaming: Run automated penetration tests to identify security vulnerabilities and misconfigurations in AI models and create rules for immediate action. Compliance Alignment: Vulnerabilities are automatically mapped to leading frameworks like the OWASP Top 10 for LLM and NIST AI RMF, accelerating compliance efforts.

3. Secure & Responsible AI Lifecycle Enforce policy-driven lifecycle controls to manage risk and ensure safe, ethical AI deployments. Our intelligent AI Firewall provides real-time protection for your applications and models: Prompt Protection: Scan and protect input prompts against malicious injection attacks. Data Leakage Prevention: Define and enforce customized, stringent security policies to monitor and limit unintended sensitive data exposure, such as PII, via model output responses.

4. Scalable AI Lifecycle Management Guardium AI Security and IBM watsonx. governance combine security and compliance metrics on a single dashboard, facilitating streamlined operations and collaboration across product, risk, compliance, and security teams. This joint approach accelerates the adoption of trustworthy AI by ensuring governance and security teams are aligned on a common set of metrics. The AI Threat Imperative The autonomous nature and privileged access of AI agents mean that a compromised or unregulated AI system can act against your interests with machine speed and scale. Untrustworthy AI is your new "Insider Threat." That is why you need Trustworthy AI.

Highlights

• Unified Security, Governance, and Compliance for Trustworthy AI: Integrates security findings with watsonx. governance for a unified AI risk view. Automatically maps vulnerabilities to global frameworks (OWASP Top 10, NIST AI RMF, EU AI Act, ISO 42001) to ensure rapid compliance, audit readiness, and trustworthy AI across the enterprise.

• AI Firewall & Shadow AI Discovery with Prompt Protection: Gain full visibility by continuously scanning for known, unknown, and "shadow AI" across cloud and code. The AI Firewall blocks malicious input, specifically prompt injection and jailbreaking, and controls output by scanning model responses to prevent sensitive PII data leakage and exposure.

• Continuous Vulnerability Management & Automated Red Teaming: Proactively manage risks by running automated penetration tests (AI Red-teaming) against generative AI workloads. The platform identifies and fixes security vulnerabilities and misconfigurations, effectively prioritizing risks to ensure a strong defense posture for your AI applications.