AI Agents for Cybersecurity

About this course

In today’s fast‑paced security landscape, manual vulnerability triage can’t keep up. This course empowers you to build fully autonomous AI agents that streamline every stage of vulnerability management—from data ingestion through remediation and alerting. You’ll gain hands‑on experience designing agents that fetch CVE records in real time, prioritize threats by severity, summarize issues with an LLM, and push actionable alerts to your team. By the end, you’ll have a cloud‑native, production‑grade pipeline that continuously secures your environment with minimal human intervention.

Data Integration & Processing:- Source Aggregation:

Learn how to pull vulnerability data from multiple feeds—NVD’s CVE API, Nessus scan results via pyTenable, and host‑specific insights from Shodan.- Data Normalization:

Standardize severity scores, merge records, and filter out noise so your agent focuses on the highest‑impact threats.- Log Management:

• Build append‑only logs in JSON‑lines format to retain a complete audit trail of every fetched CVE for compliance and analytics.

AI‑Powered Remediation:- Prompt Engineering:

Use LangChain and OpenAI to frame your LLM as a vulnerability remediation specialist.- Summarization:

Automatically transform raw CVE data into 1–2 sentence overviews.- Patch Recommendations:

• Generate 3–5 bullet‑step remediation guides complete with official advisory links, giving your security team clear, actionable next steps.

Security, Validation & Sandboxing:- Input Validation:

Enforce JSONSchema rules and strict type checks to block malicious or malformed input before it reaches your core agent logic.- Sandbox Isolation:

• Contain risky operations in jailed subprocesses or containers with CPU, memory, and system‑call restrictions.

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