Syllabus

Cyber Analyst (SOC)

The Google and Reichman SOC Analyst program in partnership with PwC NEXT trains our students for their first position in the Cyber security industry. A Security Operation Center (SOC) Analyst is primarily responsible for all activities that occur within the SOC. Analysts in Security Operations work with Security Engineers and SOC Managers to give situational awareness via detection, containment, and remediation of IT threats. In this course you will learn and understand how tech infrastructure is designed and operated, the key elements of IT architectures, networks, Cyber methodologies and best practices for succeeding in one of the most centered positions in every Cyber system.

Cyber Security Fundamentals

Operating Systems: Windows, Linux
- Fundamentals
- Investigation
- Forensics
- Logs
Networking
- Fundamentals
- Wireshark
- Deep Packet Inspection
- Network Attacks
Organizational Services: Active Directory, Identity and Access Management, VPN

Offensive Cyber Security

MITRE ATTACK and Cyber Kill-chain
Scanning
Exploitations
Lateral movement
Social Engineering
Metasploit

SIEM

Log analysis: Network Logs, Endpoint logs and more…
Alert analysis
Threat hunting
Anomaly detection
SOAR
Real Cyber-attack simulation

Cyber Defense

Cyber security defense landscape
Endpoint security
Network security
API security
Sandbox
Threat Intelligence fundamentals

Incident Response (IR)

Incident management systems
Mitigation
Recovery

Cloud Security

Cloud infrastructure and technologies basics
Container security
CWPP
CSPM
DSPM
Real Cloud Cyber-attack simulation

AI for Cyber Security and SOC productivity

AI fundamentals
- AI concepts: Machine Learning, Generative AI, LLM, and more
- Common usages, capabilities and limitations of current AI tools
- Human-in-the-loop cyber security and Gen AI approach
- Prompt engineering
SOC productivity
- Gen AI content summarization and visualization
- Principles for effective learning with LLM
- Gen AI Productivity tools using Gemini {emails, documents, slides, images, other}
AI for cyber security
- Threat interpretation
- Rule generation
- Query generation
- Code analysis
- Risk prioritization
- Attack remediation
- Incident summary
- Red and blue team security analysis using fine-tuned security LLM’s
- AI powered User Entity and Behavior Analytics (UEBA)
- Zero Trust monitoring and profiling in cloud environments
- AI and LLM powered infrastructure security recommendations and guidance

Final Project

State of the art cyber-attacks that require the students using all their knowledge and skills acquired during the course that includes: detecting the threats using SIEM and manual inspection of the devices in the network; stopping the attacks; analyzing them and finding the initial access path and root causes; blocking any new threats by creating new policies and modification to the network; Remediation of the attack and full recovery; creation of new incident response scripts and policies in the case of future similar attacks; summarization of the attack and the response; presentation to the C-level executives.