Generative AI is a class of AI models that create new content, such as text, images, audio or video. NIST defines it as models that emulate the structure and characteristics of input data to generate derived synthetic content. It is also called GenAI.
- Also Called3other namesGenAI · Gen AI
- Related Terms3linked entriesAI agents · Shadow AI · Deepfake
What Is Generative AI?
Generative AI is a kind of artificial intelligence that creates new content, such as text, images, audio or video. The NIST glossary defines it as the class of AI models that emulate the structure and characteristics of input data in order to generate derived synthetic content. Synthetic content means content made by a model, not by a person. The glossary cites NIST SP 800-218A for this definition and uses the short form GenAI.
What Does a Generative Model Do?
In the NIST definition, a model takes in data and learns its structure and characteristics. It can then produce new content that follows the same patterns. Large language models, often shortened to LLMs, are one common type. They work with text. OWASP uses the phrase “LLMs and Gen AI Apps” for the systems and applications built on them.
A simple illustration: a person types a question into a chat tool, and the model writes a draft answer in plain language.
Why Does Generative AI Matter for Security?
NIST published the AI Risk Management Framework: Generative AI Profile (NIST AI 600-1) on 26 July 2024. It is a companion to the NIST AI Risk Management Framework (AI RMF 1.0). NIST says its aim is to improve the ability of organizations to build trustworthiness considerations into the design, development, use and evaluation of AI products, services and systems.
OWASP publishes a Top 10 list of risks for LLM and generative AI applications. The 2025 list names these items:
- Prompt injection
- Sensitive information disclosure
- Supply chain
- Data and model poisoning
- Improper output handling
- Excessive agency
- System prompt leakage
- Vector and embedding weaknesses
- Misinformation
- Unbounded consumption
The UK NCSC says agentic systems built on language models inherit known risks, such as jailbreaking and prompt injection.
Which NIST Documents Cover Generative AI?
NIST has built its guidance in layers. The base framework came first, and two documents for generative AI followed in 2024. See the NIST AI RMF page and the SP 800-218A record.
- 26 January 2023NIST releases AI RMF 1.0.The base framework. The later generative AI profile is built on it.
- July 2024NIST publishes SP 800-218A.SSDF community profile that adds AI model development practices for generative AI.
- 26 July 2024NIST publishes AI 600-1.Generative AI Profile, a companion to AI RMF 1.0, which names the risks unique to generative AI and proposes actions.
How Can Organizations Manage Generative AI Risk?
The sources above are frameworks and risk lists, so they give a way to organize the work. NIST AI 600-1 is voluntary and is meant to support trustworthiness in how AI is designed, developed, used and evaluated. The OWASP list gives teams a set of named risks to check applications against. The NCSC advises meaningful human oversight and control of agentic systems.
Which Terms Sit Next to Generative AI?
The NCSC describes agentic systems as advanced generative AI. An AI agent is software that uses a model to act towards a goal. Staff use of AI tools without approval is often called shadow AI. A deepfake is synthetic media that imitates a real person, and it is one kind of content a generative model can produce.
Is Generative AI the Same as AI?
No. AI is the wider field. Generative AI is the class of models, in the NIST definition, that create new synthetic content from patterns in input data.
Is a Large Language Model the Same as Generative AI?
Not exactly. A large language model is one type of generative model, built for text. Generative AI also covers models that produce images, audio and video.
Related Pages in the Knowledge Hub
Also Called.
- NameGenAI
- NameGen AI
- Namegenerative artificial intelligence
Questions.
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What is generative AI?
Generative AI is a class of AI models that create new content, such as text, images, audio or video. NIST defines it as models that emulate the structure and characteristics of input data to generate derived synthetic content.
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Is a large language model the same as generative AI?
Not exactly. A large language model is one type of generative model, built for text. Generative AI also covers models that produce images, audio and video.
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Why does generative AI matter for security?
NIST published a Generative AI Profile (NIST AI 600-1) for its AI risk framework, and OWASP publishes a Top 10 of risks for LLM and generative AI apps, led by prompt injection. The UK NCSC notes agentic systems inherit risks such as jailbreaking.
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How can organizations reduce generative AI risk?
The NIST profile and the OWASP list give a way to organize the work and a set of named risks to check applications against. The NCSC advises meaningful human oversight and control of agentic systems.
Sources
- 1 Artificial Intelligence Risk Management Framework: Generative Artificial Intelligence Profile, NIST
- 2 LLMRisks Archive - OWASP Gen AI Security Project, OWASP
- 3 Artificial Intelligence Risk Management Framework, NIST
- 4 SP 800-218A, Secure Software Development Practices for Generative AI and Dual-Use Foundation Models: An SSDF Community Profile, NIST
In Our Research
- 1 How GenAI is Revolutionizing Threat Detection and Response August 2024
- 2 Strengthening Cyber Defense with Advanced GenAI Threat Intelligence Feeds August 2024
- 3 The Role of GenAI in Enhancing Cybersecurity Strategies August 2024
- 4 North Korea AI Hacking: What Microsoft Documented Across Eight Groups October 2026
- 5 How Cybercriminals Are Attacking Financial Firms Worldwide October 2026
- 6 Red Team Your Threat Intel Agent With Garak, Promptfoo and PyRIT October 2026