๐ก SOC Analyst โข ๐ Detection Engineering โข โ๏ธ Security Automation โข โ๏ธ AWS Security โข ๐ค AI-Driven SOC
Telemetry โ Detection โ Enrichment โ Case Management โ Automation โ Feedback
Name: Abdul Rehman
Role: SOC Analyst | Cybersecurity Analyst | Security Automation Builder
Location: Bengaluru, India ๐ฎ๐ณ
Primary Focus:
- SOC Operations & SIEM Monitoring
- Detection Engineering & Alert Triage
- Incident Response & Case Workflows
- AWS Security Monitoring & IAM Automation
- SOAR Workflows with Wazuh, TheHive, MISP, Cortex, n8n
- AI-Assisted Security Operations
Current Growth Tracks:
- Defensive Security Engineering
- Advanced SOC Operations
- DevSecOps & Cloud Security
- AI-Driven Security Operations
- AI Automation & Agentic Workflows
- Cybersecurity + AI Practical Lab Roadmap
Approach: Build โ Detect โ Investigate โ Automate โ Document โ Improve
Philosophy: Automate Everything
Goal: Strengthen security operations through practical automation and AI-assisted workflows
๐ Open to remote roles & freelance
Iโm a hands-on cybersecurity practitioner focused on SOC operations, SIEM monitoring, detection engineering, AWS security, incident response workflows, and open-source security tooling.
My portfolio is built around real lab execution and deep documentation โ not just learning tools, but deploying, validating, investigating, automating, documenting, and improving complete technical environments.
Over time, Iโve built and documented work across:
- SOC & SIEM operations
- Wazuh-based monitoring, detection, and alert triage
- TheHive, MISP, Cortex, and n8n-based SOAR workflows
- AWS security monitoring, IAM automation, and secure cloud infrastructure
- Linux security hardening, administration, and troubleshooting
- Incident response simulations, containment workflows, and case documentation
- Python automation, DevSecOps-style validation, and observability workflows
- AI-assisted SOC workflows, GenAI security operations, MCP/RAG learning, and agentic automation experiments
- Data science, machine learning, NLP, and analytics foundations for security-adjacent analysis
I also completed a full-year student internship alongside my cybersecurity studies and continue building a large, structured GitHub portfolio through completed labs, specialist repositories, capstone-style projects, and an active long-term hands-on learning roadmap.
| ๐ Portfolio Dimension | ๐ What It Reflects |
|---|---|
| 28 structured repositories | Specialist tracks, capstones, guided labs, learning portfolios, and documentation-first technical projects |
| 700+ completed hands-on labs & projects | Practical execution already completed across cybersecurity, Linux, cloud, automation, analytics, AI, and security operations |
| 720-lab advanced roadmap | Active next-stage roadmap across blue team, red team, DFIR, cloud security, DevSecOps, AI security, ML, automation, and advanced cyber labs |
| SOC/SOAR flagship ecosystem | 42+ projects, 6 capstones, 11 installations/setups, 6 dashboards, and connected Wazuh + TheHive + MISP + Cortex + n8n workflows |
| Cloud security engineering | AWS IAM security automation, secure infrastructure MVP, CloudTrail, GuardDuty, Config, Security Hub, VPC Flow Logs, and monitoring pipelines |
| AI-assisted security automation | GenAI detection-as-code, MCP/RAG/agentic AI security workflows, Hugging Face agents, LangChain RAG, and n8n-based SOC automation |
| Python, data & automation depth | 57-lab Data Science portfolio and 39-lab Python automation/security engineering portfolio |
| Documentation-first mindset | READMEs, architecture diagrams, workflow mapping, interview Q&A, troubleshooting, evidence packs, and technical reporting |
This matrix reflects my portfolio-wide hands-on implementation across SOC operations, SIEM, Linux security, AWS monitoring, incident response, security automation, AI-assisted security workflows, Python engineering, and analytics.
Depth labels are evidence-based and reflect completed repositories, capstones, labs, workflow prototypes, and documented hands-on projects.
| Skill Area | Portfolio Evidence | Current Depth | Tools / Frameworks Used |
|---|---|---|---|
| ๐ก๏ธ SOC Operations & Alert Triage | Alert triage, investigation logic, false-positive review, escalation context, analyst-style documentation | High portfolio depth |
Wazuh, TheHive, MITRE ATT&CK |
| ๐ SIEM Monitoring & Detection Engineering | Wazuh monitoring, custom rules, decoders, FIM, telemetry validation, tuning, and detection-focused workflows | High portfolio depth |
Wazuh, ELK, Kibana, Sysmon, auditd |
| ๐งพ Incident Response & Case Documentation | Alert-to-case thinking, timelines, containment notes, response lifecycle, lessons learned, closure documentation | Strong applied exposure |
TheHive, Cortex, MISP, SOC reporting workflows |
| ๐ง Threat Intelligence & ATT&CK Mapping | IOC enrichment, ATT&CK mapping, observable handling, case context, threat-intel feedback loops | Strong applied exposure |
MISP, Cortex, VirusTotal, AlienVault OTX, MITRE ATT&CK |
| ๐ง Linux Security & System Hardening | SSH hardening, permissions, services, auditing, logging, firewalling, credential access monitoring | High portfolio depth |
Linux, Ubuntu, Debian, RHEL, auditd, ufw, fail2ban |
| โ๏ธ AWS Security Monitoring & Cloud Visibility | CloudTrail monitoring, IAM activity review, GuardDuty/Security Hub-style workflows, cloud event visibility | Strong applied exposure |
AWS, CloudTrail, IAM, GuardDuty, Security Hub, AWS CLI |
| โ๏ธ AWS Security Engineering & IAM Automation | IAM triage, containment workflows, scheduled IAM hygiene, secure infrastructure MVPs, assessment/remediation automation | Growing specialist depth |
AWS IAM, Security Hub, GuardDuty, CloudTrail, Config, VPC Flow Logs |
| ๐งฌ GenAI Security & Detection-as-Code | AI-app telemetry detection, Wazuh rule CI/CD, MCP/RAG/agentic runtime triage, OWASP LLM mapping | Applied / growing depth |
Wazuh, GitHub PRs, n8n, TheHive, Slack, OWASP LLM, MCP, RAG |
| โ๏ธ Python Security Automation & DevSecOps | CLI tooling, config validation, testing, backend orchestration, workflow state, logs, metrics, incident-support automation | Strong applied exposure |
Python, Bash, FastAPI, Flask, pytest, PostgreSQL, Redis, Prometheus, Grafana |
| ๐ค AI Automation, Agents, MCP & RAG | n8n workflows, prompt/context design, LangChain RAG apps, Hugging Face agents, MCP servers, tool-use workflows | Applied / growing depth |
n8n, LangChain, Hugging Face, FastMCP, smolagents, LlamaIndex, LangGraph |
| ๐งช Vulnerability Assessment & Security Validation | Vulnerability review, scan interpretation, hardening validation, posture improvement, remediation thinking | Strong applied exposure |
Nessus, OpenVAS, Checkov, CIS concepts, OWASP ZAP |
| ๐ Web / Network Security Observation | Traffic review, service visibility, WAF monitoring, IDS/NSM visibility, web log observation | Solid working depth |
Wireshark, Nmap, Burp Suite, OWASP ZAP, Nginx, Suricata, Snort, Zeek |
| ๐ฉ RHEL, Containers & Admin Automation | Enterprise-style administration exposure, container workflows, operational consistency, system management | Solid working depth |
RHEL, Podman, Docker, Kubernetes, OpenShift |
| ๐ Data Analytics, ML/NLP & Security-Oriented Analysis | Data handling, visualization, statistics, ML/NLP foundations, forecasting, deep learning foundations | Solid working depth |
Jupyter, Pandas, NumPy, Matplotlib, scikit-learn, TensorFlow, PyTorch |
- High portfolio depth = repeated implementation across multiple repositories, labs, capstones, and documented workflows
- Strong applied exposure = clear practical project evidence with hands-on implementation and technical documentation
- Growing specialist depth = active specialization supported by recent capstone or repository work
- Applied / growing depth = hands-on projects completed, with continued expansion underway
- Solid working depth = practical foundation with documented labs and ongoing growth
This matrix reflects overall portfolio capability, not one isolated repository โ covering:
SOC โ Detection โ Investigation โ Enrichment โ Hardening โ Monitoring โ Automation โ Documentation โ Continuous Improvement
| ๐งญ Domain | ๐ Focus |
|---|---|
| SOC Operations | alert triage, case context, event analysis, escalation thinking, documentation, and analyst workflow discipline |
| SIEM & Detection Engineering | Wazuh monitoring, rules, decoders, FIM, telemetry validation, detection tuning, and alert quality improvement |
| Incident Response Workflows | investigation flow, containment logic, IOC enrichment, MITRE ATT&CK mapping, reporting, and lessons learned |
| Threat Intelligence & Case Enrichment | MISP, Cortex, VirusTotal, OTX, observable context, case comments, and threat-intel feedback loops |
| Linux Security | hardening, SSH security, permissions, auditing, services, endpoint visibility, and system defense |
| AWS Security & IAM Automation | CloudTrail, IAM activity, GuardDuty, Security Hub, Config, identity triage, containment, and hygiene monitoring |
| Secure Cloud Infrastructure | segmented AWS architecture, bastion access, encrypted logging, monitoring controls, validation, and remediation |
| Security Automation / SOAR | n8n, Slack, TheHive, DataTables, workflow state, alert-to-case automation, and closure synchronization |
| AI Security & GenAI Detection | AI-app telemetry, OWASP LLM mapping, MCP/RAG/agentic runtime detection, Wazuh detection-as-code, and SOC triage prototypes |
| Python Automation & DevSecOps | secure CLI tooling, backend orchestration, validation, testing, observability, metrics, and evidence generation |
| Security Analytics | data thinking, statistics, ML/NLP foundations, dashboards, forecasting, and security-oriented analytical reasoning |
| Highlight | What It Shows |
|---|---|
| ๐ก End-to-End SOC + SOAR Ecosystem on AWS | Connected security operations lab using Wazuh, TheHive, MISP, Cortex, n8n, AWS, dashboards, case workflows, and analyst-style documentation |
| ๐ Detection Engineering & Cyber Defense Portfolio | Endpoint, network, web, cloud, Linux, Windows, Wazuh rules/decoders, validation workflows, and alert-quality improvement |
| โ๏ธ AWS Security & IAM Automation | CloudTrail visibility, IAM triage, GuardDuty/Security Hub-style workflows, secure infrastructure, Config, VPC Flow Logs, and remediation automation |
| ๐งฌ GenAI Detection-as-Code & AI Security Workflows | Wazuh CI/CD, GitHub PR validation, OWASP LLM mapping, MCP/RAG/agentic runtime telemetry, Slack, TheHive, n8n, and audit tables |
| โ๏ธ Python Automation, DevSecOps & Observability | 39-lab Python automation engineering portfolio covering CLI tools, backend workflows, testing, logs, metrics, compliance evidence, and AI-assisted runbooks |
| ๐ Data Science, ML/NLP & Analytics Foundations | 57-lab Data Science portfolio covering Python, pandas, NumPy, visualization, statistics, ML, NLP, forecasting, TensorFlow, and PyTorch |
| ๐ค AI, Hugging Face, LangChain & MCP Learning | Hugging Face Agents/LLM/MCP tracks, LangChain RAG app work, MCP automation workflows, AI agents, and source-grounded chatbot development |
| ๐ Documentation-First Portfolio Discipline | Strong READMEs, architecture diagrams, troubleshooting notes, interview Q&A, evidence packs, project reports, and technical storytelling |
I am working toward becoming a stronger cybersecurity professional who can improve security operations through defensive engineering, automation, cloud security, and practical AI-assisted workflows.
My long-term direction is to build useful security systems that connect:
- SOC monitoring and detection engineering
- incident response and case workflow discipline
- cloud security, IAM visibility, and DevSecOps-style validation
- Python automation, observability, and evidence-driven reporting
- AI-assisted triage, agentic workflows, MCP/RAG learning, and human-in-the-loop automation
The goal is not to automate everything blindly. The goal is to automate the repetitive, high-context, and evidence-heavy work that can help analysts move faster while keeping security decisions explainable and reviewable.
๐ Click to Expand / Collapse Technical Skills
| Area | Practical Work |
|---|---|
| ๐ SOC Operations & SIEM Monitoring | Alert triage, log analysis, Wazuh monitoring, detection review, escalation logic, and analyst-ready notes |
| ๐ง Threat Intelligence & Case Context | IOC enrichment, MISP/Cortex workflows, VirusTotal/OTX checks, ATT&CK mapping, and case comments |
| ๐ง Linux Security & Administration | Hardening, permissions, SSH security, audit visibility, services, logs, firewalling, and troubleshooting |
| โ๏ธ AWS Security & IAM Automation | CloudTrail visibility, IAM event review, identity triage, hygiene checks, GuardDuty/Security Hub-style workflows |
| ๐ฐ Secure Cloud Infrastructure | Segmented AWS architecture, bastion patterns, least-privilege IAM, encrypted logging, assessment, remediation, and monitoring controls |
| ๐งฌ GenAI Detection-as-Code | Wazuh detection CI/CD, AI-app telemetry, OWASP LLM mapping, MCP/RAG/agentic alert routing, and TheHive case workflows |
| ๐ค AI Automation & n8n Workflows | Prompt/context design, Slack notifications, analyst summaries, workflow orchestration, DataTables, and closure sync |
| โ๏ธ Python Automation & DevSecOps | CLI tools, API services, validation gates, testing, drift checks, logs, metrics, dashboards, and evidence generation |
| ๐ Data Science & ML/NLP Foundations | Python analytics, data cleaning, visualization, statistics, ML/NLP basics, forecasting, and model-evaluation practice |
- Cloud Cyber Security Certificate โ Al-Nafi International College (issued Jan 2026)
- EduQual RQF Level 3 Diploma in Cloud Cyber Security โ Al-Nafi International College
- Cyber Security Internship โ Al-Nafi International College
- CISSP-aligned Training โ Al-Nafi International College
- Certified in Cybersecurity (CC) โ ISC2
- ISO/IEC 27001:2022 Lead Auditor โ Mastermind
- Certified Fundamentals in Cybersecurity โ Fortinet
- SOC Analyst & Cybersecurity Job Simulations โ Forage (TATA, Deloitte, AIG, Datacom, Telstra, Commonwealth Bank)
- Certified Phishing Prevention Specialist (CPPS) โ Hack & Fix
- Certified Threat Intelligence & Governance Analyst (CTIGA) โ Red Team Leaders
- Certified Red Team Operations Management (CRTOM) โ Red Team Leaders
- Cybersecurity Fundamentals, SOC in Practice, Enterprise Security, Threat Intelligence & Hunting โ IBM SkillsBuild
- Hugging Face AI Learning Tracks โ Agents Course, LLM Fundamentals, Fundamentals of MCP, MCP for Production Automation
- Anthropic AI Fluency & Claude Learning โ AI Fluency, Claude 101, Claude Code 101, Claude Code in Action, Claude Cowork
- Anthropic MCP / Agentic Workflow Certificates โ Introduction to MCP, MCP Advanced Topics, Subagents, Agent Skills
- AI Masterclass & Workshops โ Dhruv Rathee Academy, GrowthSchool, be10x
- AWS DevOps and Agentic AI Masterclass โ Train with Shubham
- Data Analytics Essentials โ Cisco Networking Academy
- Introduction to Data Science โ Cisco Networking Academy
| ๐งญ Current Strengths | ๐ Areas Iโm Actively Advancing |
|---|---|
SOC Operations, Defensive Security & Automation
|
Security Growth, Engineering Depth & AI Automation Direction
|
| ๐ก๏ธ SOC + SOAR Malware Incident Response | ๐ค AI-Driven SOC Alert Triage Automation |
|---|---|
๐ Alert โ Investigation โ Case โ Threat Intel
|
โ๏ธ Wazuh โ n8n โ Gemini โ Analyst Report
|
| โ๏ธ AWS IAM Identity Security Automation | ๐ฐ Secure AWS Infrastructure MVP |
๐ Identity Finding โ Enrichment โ Containment โ Closure
|
๐งฑ Build โ Govern โ Assess โ Remediate โ Monitor
|
| ๐งฌ GenAI Detection-as-Code CI/CD for Wazuh | ๐ง GenAI Detection-as-Code V2 โ MCP, RAG & Agentic AI |
๐ฆ Detection Code โ CI Gate โ Wazuh Deploy โ Runtime Triage
|
๐งฉ MCP Tool Risk โ RAG/Memory Risk โ Agentic Runtime Risk
|
This section highlights the original SOC / SOAR malware investigation architecture, analyst workflow, and threat-intelligence feedback loop using Wazuh, TheHive, Cortex, MISP, AWS, and Sysmon. The featured capstone table above shows how the portfolio has expanded further into AWS IAM automation, secure AWS infrastructure, GenAI detection-as-code, MCP/RAG security, and agentic AI-assisted security operations.
๐ View Mermaid Workflow Diagram
flowchart LR
%% =========================================================
%% SOC + SOAR + TI โ End-to-End Workflow (Swimlanes, Boxed)
%% with stronger lane separators (GitHub Mermaid friendly)
%% =========================================================
A_ENR[" "]:::anchor
A_IR[" "]:::anchor
A_TI[" "]:::anchor
A_FB1[" "]:::anchor
A_FB2[" "]:::anchor
F1[" "]:::frame
F2[" "]:::frame
F3[" "]:::frame
F4[" "]:::frame
F5[" "]:::frame
F6[" "]:::frame
F1 -.-> F2
F2 -.-> F3
F3 -.-> F4
F4 -.-> F5
F5 -.-> F6
subgraph L1[" "]
direction TB
H1["๐ช Endpoint"]:::laneHeader
SIM["๐งจ Controlled Attack Simulation<br/>PowerShell โข DNS โข File Drop โข Persistence โข Network"]:::stage
ENDPOINT["Sysmon + Wazuh Agent<br/>Telemetry collection"]:::stage
H1 --> SIM --> ENDPOINT --> F1
end
subgraph L2[" "]
direction TB
H2["๐ก๏ธ SIEM / XDR (Wazuh)"]:::laneHeader
WAZ["Wazuh Manager<br/>Rules โข Correlation โข Alerts"]:::stage
IDX["Wazuh Indexer<br/>OpenSearch"]:::stage
WDASH["Wazuh Dashboard<br/>Hunting โข Evidence โข Discover"]:::stage
H2 --> WAZ --> IDX --> WDASH --> F2
end
subgraph L3[" "]
direction TB
H3["๐จโ๐ป SOC Analyst"]:::laneHeader
ANALYST["Triage + Investigation<br/>Review โ Correlate โ Extract IOCs"]:::human
GATE["Decision Gate<br/>True Positive confirmed?"]:::decision
H3 --> ANALYST --> GATE --> F3
end
subgraph L4[" "]
direction TB
H4["๐๏ธ Case Mgmt + SOAR (TheHive + Cortex)"]:::laneHeader
THEHIVE["TheHive Case<br/>Alert โ Case โ Tasks โ Timeline"]:::stage
OBS["Observables / IOCs<br/>Hash โข Domain โข IP โข URL โข File โข Registry"]:::stage
CORTEX["Cortex Automation<br/>Analyzers / Responders"]:::stage
ENR["Enrichment Results<br/>VT โข OTX โข MISP lookups etc."]:::stage
MITRE["MITRE ATT&CK Mapping<br/>Evidence โ Techniques โ TTPs"]:::stage
H4 --> THEHIVE --> OBS --> A_ENR
A_ENR --> CORTEX --> ENR --> A_ENR
ENR --> THEHIVE
THEHIVE --> MITRE --> A_IR --> F4
end
subgraph L5[" "]
direction TB
H5["๐ ๏ธ Incident Response"]:::laneHeader
IRFLOW["IR Lifecycle<br/>Identify โ Analyze โ Contain โ Eradicate โ Recover โ Review"]:::ir
ACTIONS["Endpoint Actions<br/>Triage โข Kill proc โข Block C2 โข Remove persistence โข Export EVTX"]:::action
CLOSE["Case Closure<br/>Final report โข Timeline โข Metrics โข Lessons learned"]:::outcome
H5 --> IRFLOW --> ACTIONS --> IRFLOW
IRFLOW --> CLOSE --> A_TI --> F5
end
subgraph L6[" "]
direction TB
H6["๐ง Threat Intelligence (MISP)"]:::laneHeader
MISP["MISP Event<br/>Validated IOCs + Tags + Context"]:::ti
SHARE["Share / Reuse<br/>Correlation โข Community โข Future detections"]:::ti
H6 --> MISP --> SHARE --> F6
end
ENDPOINT -->|๐ค Sysmon telemetry| WAZ
WDASH --> ANALYST
GATE -->|๐ Escalate IOCs + evidence| THEHIVE
A_IR --> IRFLOW
A_TI -->|โ
Export validated IOCs| MISP
SHARE -.-> A_FB1 -.->|โป๏ธ Improve detections| WAZ
SHARE -.-> A_FB2 -.->|๐ Faster correlation| WDASH
OUT["๐ Outcome<br/>End-to-end SOC workflow + SOAR automation + TI feedback loop"]:::outcome
CLOSE --> OUT
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classDef stage fill:#111827,stroke:#475569,stroke-width:1px,color:#e5e7eb;
classDef human fill:#0f172a,stroke:#22c55e,stroke-width:1px,color:#e5e7eb;
classDef decision fill:#0f172a,stroke:#f59e0b,stroke-width:2px,color:#e5e7eb;
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classDef action fill:#0f172a,stroke:#ef4444,stroke-width:1px,color:#e5e7eb;
classDef ti fill:#0f172a,stroke:#a78bfa,stroke-width:1px,color:#e5e7eb;
classDef outcome fill:#0f172a,stroke:#14b8a6,stroke-width:2px,color:#e5e7eb;
classDef anchor fill:transparent,stroke:transparent,color:transparent;
classDef frame fill:transparent,stroke:transparent,color:transparent;
class A_ENR,A_IR,A_TI,A_FB1,A_FB2 anchor;
class F1,F2,F3,F4,F5,F6 frame;
linkStyle 0 stroke:#94a3b8,stroke-width:4px,stroke-dasharray:10 6,opacity:0.95;
linkStyle 1 stroke:#94a3b8,stroke-width:4px,stroke-dasharray:10 6,opacity:0.95;
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๐ ๏ธ Monitoring, Detection & Logging Arsenal (Click to expand)
- Wazuh โ SIEM/XDR, endpoint monitoring, FIM, vulnerability detection, custom rules, decoders, and alert routing
- ELK Stack โ Elasticsearch, Logstash, Kibana
- OpenSearch โ dashboarding and search-style visibility exposure
- Kibana โ dashboards, visualization, and security monitoring views
- Splunk โ log analysis and operational visibility
- CloudTrail โ AWS activity visibility and event review
- VPC Flow Logs โ cloud network visibility
- AWS Config โ compliance posture and configuration visibility
- GuardDuty / Security Hub โ AWS security finding and routing concepts
- Elasticsearch โ log indexing and search
- Logstash โ ingestion and parsing
- Wazuh Decoders & Rules โ event classification and alerting logic
- Wazuh Custom Integrations โ forwarding security alerts into automation workflows
- auditd โ Linux audit logging
- Sysmon / Sysmon for Linux โ endpoint telemetry and event visibility
- Osquery โ endpoint state inspection and threat-hunting visibility
- Syslog / Linux Logs โ operational and security visibility
- Alert Tuning Concepts โ relevance filtering and signal improvement
- TheHive 5 โ incident, alert, case, task, comment, and lifecycle management
- MISP โ IOC enrichment and sharing concepts
- Cortex โ analyzer-oriented enrichment support
- VirusTotal / AlienVault OTX โ external IOC enrichment
- MITRE ATT&CK โ technique mapping and analyst context
- MITRE ATLAS-style mapping โ AI threat-context language for GenAI security detections
- OWASP LLM / GenAI Security โ LLM risk classification and AI-app security reference
- OWASP MCP โ MCP-specific AI tool-risk reference
๐ Network Security, Traffic Analysis & Security Testing Tools (Click to expand)
- pfSense โ firewall and network edge concepts
- Nginx / Apache โ web stack exposure and log visibility
- ModSecurity + OWASP CRS โ WAF detection and web attack monitoring
- Fail2Ban โ automated host-level blocking for repeated attack behavior
- Wireshark โ traffic inspection and packet analysis
- tcpdump โ packet capture and CLI-based visibility
- Nmap โ service enumeration and discovery
- Suricata / Snort / Zeek โ IDS/NSM visibility, alerting, and protocol-aware detection
- OpenVAS โ vulnerability scanning exposure
- Qualys โ cloud security and assessment awareness
- Nessus โ vulnerability review
- Burp Suite โ web security testing workflows
- OWASP ZAP โ web application testing exposure
- Checkov โ infrastructure-as-code security scanning
- CIS concepts โ baseline hardening and control awareness
- Metasploit โ offensive simulation in lab contexts
- Kali Linux โ testing and research environment
- Atomic Red Team concepts โ adversary emulation awareness
- VirusTotal โ file/hash/domain/IP enrichment
- Custom replay/test events โ detection validation and regression thinking
๐ป Command Line, Systems, Containers & Automation Stack (Click to expand)
- AWS CLI โ cloud interaction and operational support
- AWS IAM โ identity, access, policy, and credential hygiene workflows
- AWS EC2 / VPC / S3 / CloudWatch โ cloud lab operations and monitoring
- Terraform โ infrastructure-as-code for secure AWS MVP design
- EventBridge / SNS โ cloud event routing and notification concepts
- Ansible โ automation and repeatable administration
- n8n โ workflow orchestration and SOC/SOAR automation
- Docker โ container workflows
- Podman โ daemonless containers
- kubectl โ Kubernetes CLI exposure
- OpenShift โ enterprise container platform exposure
- Linux CLI โ core administration and troubleshooting
- bash โ automation and shell scripting
- PowerShell โ Windows-side scripting exposure
- python โ scripting, analytics, backend services, and automation
- vim / nano โ CLI editing
- systemctl / journalctl โ service and log management
- iptables / ufw โ firewall and containment actions
- curl โ HTTP / API checks
- wget โ downloads and testing
- netcat (nc) โ networking utility
- dig โ DNS lookup utility
- traceroute โ path tracing
- ping โ connectivity validation
- ip / ss / netstat โ network inspection
- ssh โ secure access and admin workflows
- openssl โ SSL/TLS tooling
- fail2ban โ brute-force mitigation
- ufw โ firewall management
- SELinux / AppArmor โ access control and hardening exposure
๐งฉ Python Automation, DevSecOps & Observability Stack (Click to expand)
- Python โ CLI tooling, scripts, data processing, workflow support, and service logic
- Bash โ repeatable execution, validation scripts, and lab automation
- FastAPI / Flask โ API services, policy/status endpoints, and integration workflows
- PostgreSQL โ workflow state, job registry, and queryable job history
- Redis โ queueing and worker-support patterns
- pytest / coverage โ testing, validation, and quality gates
- pre-commit โ local quality gate and security checks
- GitHub / GitHub Actions โ PR workflows, validation signals, CI-style automation, and documentation versioning
- Artifact versioning โ repeatable delivery and rollback-aware workflow thinking
- Configuration validation โ schema checks, drift detection, golden config enforcement
- Policy engineering โ automation guardrails, rule enforcement, and compliance evidence
- Structured Logging โ correlation IDs, JSON logs, and operational traceability
- Prometheus โ metrics instrumentation
- Grafana โ dashboard evidence and operational visualization
- Runbooks / Reports โ incident support, CI triage, evidence generation, and documentation
๐ค AI Automation, Workflow Design & Prompting Stack (Click to expand)
- n8n โ workflow orchestration, node chaining, Slack/TheHive routing, DataTable state, and automation prototypes
- Gemini API โ AI-assisted SOC triage and RAG application workflows
- AI Agents โ task-driven automation experiments and tool-use workflows
- Hugging Face โ agents, LLM fundamentals, MCP learning, Spaces, and model ecosystem practice
- smolagents / LlamaIndex / LangGraph โ agent and RAG-oriented learning exposure
- FastMCP / MCP servers โ MCP workflow servers, tools, resources, and automation integrations
- GitHub Actions + Slack automation โ production-inspired MCP notification and workflow automation practice
- RAG Basics โ retrieval-augmented generation exposure
- Vector Workflow Basics โ vector-based retrieval understanding
- Prompt Engineering โ structuring effective instructions
- Context Design โ grounding and response quality improvement
- Workflow Prompt Chaining โ passing instructions across nodes and tasks
- Human-in-the-Loop Design โ keeping analyst review, approval, and decision quality in automation workflows
- LLM-Assisted Automation Thinking โ using AI to reduce repetitive operational work responsibly
- Detection-as-Code โ detection content validation, deployment gating, and regression thinking
- OWASP LLM / GenAI risk mapping โ prompt injection, output handling, sensitive disclosure, and excessive agency thinking
- MCP/RAG/Agentic AI security โ MCP tool misuse, context injection, memory poisoning, retrieval risk, and agentic action monitoring
- TheHive + Slack + DataTables โ analyst-facing case, notification, and audit evidence handling for AI security alerts
๐ Data Science, Analytics & AI Toolkit (Click to expand)
- Jupyter Notebook / Google Colab โ interactive coding and lab documentation
- Pandas โ cleaning, filtering, and analysis
- NumPy โ numerical workflows
- Regex / JSON / CSV workflows โ practical extraction and data handling
- Exploratory Data Analysis โ dataset understanding and pattern discovery
- Matplotlib โ static charting
- Seaborn โ statistical visualization
- Plotly / Bokeh / Dash / Streamlit โ interactive visualization, dashboards, and app-style reporting
- Folium / GeoJSON โ geospatial visualization exposure
- Notebook Reporting โ documenting technical insights clearly
- Descriptive Statistics โ summarization and variability analysis
- Probability Concepts โ statistical reasoning
- A/B Testing & Hypothesis Testing โ experiment-style analysis
- scikit-learn โ ML foundations
- Feature Engineering โ preprocessing and transformation
- Model Evaluation โ comparing outputs and improving quality
- NLP Concepts โ text processing and language-oriented workflows
- Time Series Concepts โ trend and forecasting exposure
- TensorFlow / Keras / PyTorch โ deep learning foundations
- CNN / RNN / Transformer Foundations โ computer vision and sequence-model learning exposure
- Analytical Thinking for Security โ data-backed reasoning for security-adjacent workflows
| ๐ Outdoor & Fitness | ๐ฎ Gaming (PC) |
|---|---|
|
๐ Basketball โ agility, movement & teamwork |
๐ GTA V โ strategy & exploration |
| ๐ง Professional Interests | ๐ Continuous Learning |
|---|---|
|
๐ก SOC Operations & Detection Engineering |
๐ Hands-on labs & portfolio building |
- ๐ SOC Monitoring & Alert Triage โ Alert review, triage support, escalation notes, and analyst-style reporting.
- ๐ Wazuh SIEM & Detection Support โ Log visibility, rule/decoder support, dashboard checks, and detection workflow improvement.
- ๐ง Threat Intelligence & IOC Enrichment โ IOC review, enrichment, ATT&CK mapping, and investigation context building.
- ๐ Incident Response Documentation โ Case notes, timelines, containment tracking, lessons learned, and response reporting.
- ๐ง Linux Security Hardening โ SSH hardening, firewall setup, permissions, audit visibility, and service security checks.
- ๐ Web & Network Security Visibility โ Web logs, WAF visibility, traffic review, Nmap/Wireshark analysis, and monitoring support.
- ๐งช Vulnerability Review & Validation โ Finding review, prioritization, hardening recommendations, and remediation documentation.
- ๐ค AI Security Automation & n8n Workflows โ Alert-to-case automation, AI-assisted triage, Slack/TheHive routing, and workflow prototyping.
- โ๏ธ Python / Bash / DevSecOps Automation โ Helper scripts, log parsing, CLI tools, validation checks, and lightweight automation.
- ๐ Technical Documentation & Portfolio Writing โ GitHub READMEs, architecture writeups, project documentation, and technical presentation.
โIn cybersecurity, continuous learning is not optional โ it is survival.โ
โ Bruce Schneier
โA man who builds from scratch never fears loss, because what made him cannot be taken away: knowledge, experience, and resilience.โ
โ Mastering Manhood
Made with ๐ by Abdul Rehman
Last Updated: May 2026







