Since being published in December 2023, a lot of people are still wrapping their heads around the ISO 42001 standard. While designed to help all organizations who provide, develop, or use artificial intelligence (AI) products and services do so in a trustworthy and responsible manner with the requirements and safeguards that the standard defines—including defining your AI role.

With so much business now being done online and digitally, much—if not most—of organizational security concerns focus on beefing up technical controls. But, in fact, the human element of cybersecurity is often where the most impactful failures occur.

When seeking ISO 42001:2023 certification, you must ensure that your artificial intelligence management system (AIMS) aligns with the standard’s key clauses (4-10), each of which focuses on a specific facet—context, leadership, planning, support, operation, performance evaluation, and improvement.

Thinking Inside the Box Traditional red teaming approaches often focus on external threats—simulating how an outside attacker might breach a company’s defenses. This method is undeniably valuable, offering insights into how well an organization can withstand external cyberattacks. However, this "outside-in" perspective can sometimes overlook another aspect of security: the risks that arise from within the organization itself. While traditional red teaming is crucial for understanding external threats, thinking inside the box—examining internal processes, workflows, and implicit trusts—can reveal vulnerabilities that are just as dangerous, if not more so to an organization.

With proven real-life use cases, it’s a no-brainer that companies are looking for ways to integrate large language models (LLMs) into their existing offerings to generate content. A combination that’s often referred to as Generative AI, LLMs enable chat interfaces to have a human-like, complex conversation with customers and respond dynamically, saving you time and money. However, with all these new, exciting bits of technology come related security risks—some that can arise even at the moment of initial implementation.

When the COVID-19 pandemic spread across the globe in 2020, the need for social distancing and isolation impacted the availability of in-person, non-emergency healthcare appointments. As a result, telehealth became a common way for healthcare providers to serve their patients without seeing them in-person, and with its rise came related HIPAA compliance concerns.

As EU member states transpose the NIS 2 Directive into their national laws by October 17, 2024, organizations under its purview must also ensure they’re ready to fully comply with the new cybersecurity regulations. Penalties for non-compliance will include significant fines, so if you haven’t started on any necessary implementations, now is the time.

Need for Secure LLM Deployments As businesses increasingly integrate AI-powered Large Language Models (LLMs) into their operations via GenAI (Generative AI) solutions, ensuring the security of these systems is on the top of everyone’s mind. "AI Red Teaming" (which is closer to Penetration Testing than a Red Team Assessment) is a methodology to identify vulnerabilities within GenAI deployments proactively. By leveraging industry-recognized frameworks, we can help your organization verify that your LLM infrastructure and execution is done securely.