Claude for Cybersecurity

Compare traditional AI workloads with generative AI, and see how gen AI creates new content from data sources and prompts, as shown with Claude.

Learn how large-language models predict the next token from context, not knowledge. Examine how they are trained on public sources and break prompts into domains like Python.

Explain how retrieval-augmented generation (RAG) retrieves live data from sources, augments the model's knowledge, and generates more accurate, less-hallucinated responses.

Master prompt engineering to talk to gen-ai and large language models, using roles, tasks, input data, context, and output format to reduce hallucinations and improve accuracy.

Adjentic AI executes autonomous or semi-autonomous tasks after receiving instructions, unlike Gen AI. It enables autonomous coding, end-to-end ticket resolution, and coordinated multi-agent workflows.

Explore Claude, Anthropic's constitutional AI family, with Opus, Sonnet, and Haiku, and learn extended thinking for complex security tasks and enterprise deployments.

Explore how to interact with Claude for cybersecurity tasks, from explaining reverse shells to analyzing phishing emails, performing risk assessments, and guiding multi-turn incident responses.

Compare Cloud AI models Haiku, Sonnet, and Opus on a phishing email analysis task, evaluating verdicts, confidence, indicators of compromise, and recommended actions for SOC analysts.

Explore why prompt engineering matters in cybersecurity, learning how precise prompts with context, structure, and explicit outputs (JSON, tables, or MITRE ATT&CK mapping) improve AI responses.

Explore prompt engineering with Claude to analyze a PowerShell command in a cybersecurity incident triage scenario, decode payloads, map MITRE ATT&CK techniques, assess threats, and propose IOCs and responses.

Explore Cloud Code, an agentic AI tool that runs in the terminal, reads and edits files, executes commands, and reasons across codebases with a permissioned, human-in-the-loop approach for cybersecurity workflows.

Automate the lab environment setup using Claude code to install Python, create a virtual environment, and configure API keys for Anthropic, VirusTotal, and AbuseIP database across macOS, Windows, and Linux.

Install Cloud Code CLI, set your project, switch Opus or Sonnet, and explore four use cases: OWASP vulnerability review, Sentinel detection rules, log analysis, and Terraform misconfigurations.

build a python script in cloud code to call the cloud messages api, init entropiq client from environment, and analyze a cve with component, vector, impact, severity, and mitigations.

Build your first agent using the claud-agent-sdk, defining two async tools (time and read file), bundling them into an in-process MCP server, and running the agent via Cloud Code.

Claude for cybersecurity analyzes a simulated malicious macro in a Word document, performing deobfuscation, execution flow, IOC extraction, MITRE ATT&CK mapping, anti-analysis, and detection guidance for EDR and SIEM.

Create sigma and yara rules for detection engineering using cloud code for repository organization, with practical prompts and examples for Windows security scenarios.

Learn to build a complete threat actor profile with Claude, mapping tactics to MITRE ATT&CK, and detailing IOCs, detection priorities, and mitigations from the CISA Bian Lian advisory.

Develop a python IOC enrichment tool with cloud code, parsing IOCs from a text file, classifying by type, querying VirusTotal and AbuseIP database, and producing JSON and Markdown reports.

Learn to analyze CVE 2024 3400 with cloud ai and produce a vulnerability assessment for a mid-sized enterprise, including metadata, exploitation, impact, remediation, detection, mitre attack mapping, and executive summary.

Perform a security review with cloud code on a deliberately vulnerable app, identify OWASP Top 10 findings (SQL injection, XSS, broken access) by severity, and implement targeted code fixes.