Category: CompTIA SecurityX

As artificial intelligence (AI) adoption accelerates, establishing frameworks for ethical governance is crucial to address unique information security challenges. Ethical governance in AI involves ensuring

As AI models, particularly natural language processing (NLP) and large language models (LLMs), become more sophisticated, they are increasingly used in applications that rely on

In AI systems, insecure output handling refers to vulnerabilities in how a model’s predictions or outputs are managed, shared, and protected. If not handled securely,

As artificial intelligence (AI) and machine learning (ML) increasingly power critical decision-making, securing training data has become a top priority. One of the most significant

With AI models increasingly used to power critical services, the potential for Model Denial of Service (DoS) attacks has grown. In a Model DoS attack,

As artificial intelligence (AI) adoption grows, so does the complexity of the AI supply chain. From data collection and model development to deployment and maintenance,

As artificial intelligence (AI) becomes central to business operations, organizations invest heavily in training proprietary models for competitive advantage. Model theft—also known as model extraction

With the rise of artificial intelligence (AI) and machine learning (ML), organizations increasingly rely on complex models to make data-driven decisions. While these models bring

The growing use of artificial intelligence (AI) within applications and platforms has led to the development of plug-ins—modular components that extend functionality and enhance user

AI-powered deepfakes are a form of digital media manipulation that leverages machine learning to create highly realistic images, videos, and audio that can mimic real

As artificial intelligence (AI) becomes more embedded in business operations, organizations increasingly rely on complex AI pipelines—automated workflows that handle data ingestion, model training, and

AI technology has transformed social engineering, enabling attackers to automate and personalize tactics at a previously unattainable scale and sophistication. AI-driven social engineering leverages data