Artificial Intelligence (AI)
Artificial intelligence (AI) is the capability of a computer system to perform tasks that normally require human judgment. That includes recognizing patterns, understanding language, making decisions, and generating content. In cybersecurity, AI has become central to both how organizations defend themselves and how attackers operate.
Security teams use AI to detect threats at a speed and scale no human analyst can match. Attackers use the same technology to automate phishing, generate malware, and bypass controls. Understanding what AI is and what risks it introduces is now a baseline requirement for anyone working in security.
How AI Works
Most AI systems in use today are built on machine learning (ML), where a model learns patterns from large datasets rather than following hand-coded rules. Feed a model enough labeled examples of malicious network traffic, and it learns to identify similar traffic, including patterns it has never seen before.
The most significant development in recent years is the rise of large language models (LLMs). These are AI systems trained on vast amounts of text that can understand and generate human language with striking accuracy. LLMs power tools like ChatGPT, Claude, and Gemini, and they are increasingly embedded in developer tools, security platforms, and business applications.
What the OWASP GenAI Security Project Says About AI Risk
The Project addresses AI security directly through the OWASP GenAI Security Project’s Top 10 for Large Language Model Applications. The list identifies the most critical risks organizations face when building or using LLM-powered systems.
The top risks include prompt injection, where an attacker manipulates input to override the model’s intended behavior; insecure output handling, where applications pass AI-generated content to other systems without validation; and training data poisoning, where an attacker corrupts the data used to train a model. Supply chain vulnerabilities, excessive agency, and model denial-of-service round out the most pressing concerns.
These risks are not hypothetical. Prompt injection attacks against real applications have been documented publicly, and training data poisoning has been demonstrated in research settings against production-grade models.
What is artificial intelligence in cybersecurity?
In cybersecurity, AI refers to machine learning systems and language models used to automate threat detection, analyze security data, and, in adversarial cases, carry out attacks. It introduces both new defensive capabilities and risks that require active management.
