AI Agents 101
Introduction to AI Agents
AI Agents in Cybersecurity
Trusting AI Agents
Introduction to AI Agents
What are AI Agents?
An AI Agent is an advanced software program capable of interacting with its environment, processing data, and making decisions autonomously, without human intervention. They go beyond simple automation tools due to their dynamic adaptation capabilities. AI Agents excel at performing repetitive, rule-based tasks with high efficiency. These agents are designed to work across numerous tasks and domains, orchestrating activities without continuous human guidance.
How are AI Agents different from a chatbot like ChatGPT?
AI Agents are more complex and autonomous than chatbots, capable of performing a wider range of tasks and making independent decisions. Chatbots are designed for limited, often predefined, conversational interactions. An example of a chatbot is a Telegram Bot. AI Agents can be used to automate tasks like security operations, governance, risk, and compliance, as well as threat hunting.
What is the difference between AI Agents and co-pilots?
Co-pilots fall somewhere between AI Agents and chatbots. They are collaborative tools that aid humans by augmenting their abilities. They enhance human decision-making by offering suggestions, managing workflows, and automating simpler tasks. They are not designed to act independently for extended periods. An example of a co-pilot is GitHub Copilot.
What is an agentic framework?
Where are AI Agents hosted?
AI Agents can be deployed in several ways. They can be run in the cloud, or orchestrated locally, if sufficient compute is available to do so. They can also be integrated into SaaS software.
AI Agents in Cybersecurity
How can AI Agents help cybersecurity?
AI Agents can be deployed in various areas of cybersecurity to perform tasks like:
- Automating routine security tasks: Managing tasks such as patch management, vulnerability prioritization, and compliance checks.
- Conducting advanced threat hunting: Monitoring network traffic and system logs to find anomalies and potential threats.
- Offering real-time security insights and recommendations: Using machine learning to identify patterns and trends in data and providing actionable insights.
AI Agents can help organizations reduce human cognitive workload, improve threat detection and response times, save costs, achieve scalability, and enhance adaptive learning capabilities.
How do AI Agents keep up with the new emerging threats?
AI Agents require continuous training and updates to remain effective. As cyber threats evolve, the data used to train the AI Agent also needs to evolve, either through memory updating or fine-tuning the LLM or LMM.
What types of cybersecurity tasks are good for AI Agents?
- Suitable tasks for AI Agents include repetitive tasks: Processing data, automating workflows, and performing routine cybersecurity monitoring.
- Tasks involving elevated levels of data analysis: Automation, behavioral analysis, and more, where the agent can leverage time and tools effectively.
Trusting AI Agents
What is a hallucination?
Hallucination refers to the phenomenon where a large language model generates outputs that are factually incorrect or nonsensical, despite appearing confident and plausible.
Why do large language models hallucinate?
LLMs hallucinate due to numerous factors, including bias and limitations in training data, lack of real-world understanding, and the statistical nature of language modeling.
How can one detect and remove hallucinations?
Detecting and mitigating hallucinations is an active area of research. Some approaches include:
- Fact-checking against external knowledge bases: Verifying the generated text against trusted sources.
- Training LLMs to be more aware of their limitations: Teaching models to identify and flag potentially unreliable outputs.
- Using human-in-the-loop systems: Combining LLM outputs with human review and verification.
Simbian utilizes TrustedLLM™, a system designed to enhance the safety and reliability of LLMs, mitigating risks associated with hallucinations in security automation.
Is my data used to train AI Agents?
Whether or not your data is used to train an AI Agent depends on your technology provider. Providers may leverage anonymized customer data to help keep the AI Agent trained and informed of the latest threats. Like sharing threat intelligence via an ISAC, sharing anonymized information across users can increase the collective defense of anyone using that AI Agent. Any usage of your data to train an AI Agent should be made clear in the platform's licensing agreement and privacy policy.
What are my options if I wanted a private AI Agent?
Depending on your provider, you may be able to request an isolated environment for your AI Agents and opt-out of any data sharing.
What do we provide?
Simbian provides a platform of AI Agents to automate cybersecurity.