Algorithmic opacity refers to the lack of transparency in how algorithms, especially those used in artificial intelligence and machine learning, reach their decisions or outputs. This occurs when the internal workings of an algorithm are complex, proprietary, or inadequately documented, making it difficult for users, auditors, or regulators to understand, interpret, or challenge the results produced. In cybersecurity, algorithmic opacity can hinder the detection of biases, errors, or malicious behavior within automated systems, potentially leading to unintentional security vulnerabilities or unfair outcomes. Addressing algorithmic opacity is crucial for ensuring accountability, trust, and compliance with ethical and legal standards in digital systems.