Career Paths in Cybersecurity: Every Role Explained
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Browse cybersecurity guides, AI tutorials, certification paths, career resources, practice labs, and checklists across all topics in the Cybersanso Learn Hub.
SOC Analyst and Penetration Tester: The Two Most Common Entry Paths
Cybersecurity is not one job. It is a collection of different disciplines that require different skill sets, personalities, and backgrounds. Someone who thrives as a penetration tester would be miserable doing compliance work, and vice versa.
SOC Analyst (Security Operations Centre): The most common entry-level cybersecurity role. SOC analysts monitor security events, investigate alerts, and escalate or respond to incidents. Tier 1 handles initial alert triage, Tier 2 investigates escalated events, Tier 3 handles complex incidents and threat hunting. Day-to-day reality: reviewing SIEM alerts, investigating suspicious activity, documenting findings. Key skills: SIEM platforms (Splunk, Microsoft Sentinel), log analysis, incident response fundamentals, MITRE ATT&CK framework. Entry certification: CompTIA Security+. Salary range: $45,000 to $70,000 USD entry level, $90,000 to $130,000 for senior Tier 3.
Penetration Tester: Pen testers simulate attacks on systems, networks, and applications to identify vulnerabilities before real attackers do. This is not typically an entry-level role. Most pen testers start in SOC, IT administration, or development before moving into offensive security. Key skills: networking, web application security (OWASP Top 10, Burp Suite), Python and Bash scripting, Kali Linux, report writing. Build a portfolio through Hack The Box, TryHackMe, and bug bounty programmes. CEH or OSCP certifications help. Salary range: $60,000 to $90,000 junior, $100,000 to $150,000 senior.
Cloud Security Engineer, Digital Forensics and Threat Intelligence
Cloud Security Engineer: One of the fastest-growing and highest-compensated cybersecurity specialisations. Cloud security engineers protect cloud infrastructure and workloads in AWS, Azure, or GCP environments. Key skills: at least one major cloud platform in depth, cloud IAM, infrastructure as code (Terraform), container security (Docker and Kubernetes), and general security fundamentals. AWS Certified Security Specialty and CCSP are the most recognised certifications. Salary range: $100,000 to $160,000 USD.
Digital Forensics Investigator: Analyses digital evidence from computers, mobile devices, and networks to reconstruct what happened during an incident. Works in law enforcement, corporate security, legal firms, and incident response consultancies. Key skills: forensic acquisition tools (FTK, EnCase, Autopsy), memory analysis (Volatility), network forensics, chain-of-custody requirements. SANS FOR courses and GCFE or GCFA certifications are well-regarded.
Threat Intelligence Analyst: Collects, processes, analyses, and communicates information about current and potential threats. Less technical exploitation, more research, analysis, and communication. Key skills: OSINT techniques, MITRE ATT&CK navigation, threat actor group knowledge, report writing, and the ability to translate technical findings into business-relevant language. Many enter from SOC backgrounds. Academic backgrounds in security studies or international relations are also relevant.
- SOC Analyst: Security+, Splunk, SIEM, log analysis, MITRE ATT&CK
- Penetration Tester: Kali Linux, Burp Suite, Python, Hack The Box, OSCP
- Cloud Security Engineer: AWS or Azure or GCP, IAM, Terraform, CCSP
- Digital Forensics: Autopsy, Volatility, FTK, GCFA certification
- Threat Intelligence: OSINT, ATT&CK, threat actor research, report writing
- All roles benefit from TryHackMe, home lab practice, and documented projects
How to Get Your First Cybersecurity Job Without Prior Experience
Build a practical portfolio before applying: Complete TryHackMe learning paths and share your profile link. Work through Hack The Box machines and write up what you learned. Build and document a home lab. Write about what you are learning on LinkedIn or a personal blog. GitHub repositories with security projects, scripts, tools, and notes demonstrate initiative that a CV alone cannot.
Get the right first certification: CompTIA Security+ is the most cost-effective credential signal for entry-level roles. Network+ before that helps if you have no networking background. Google’s Cybersecurity Certificate on Coursera is a lower-cost starting point that some employers recognise. Do not spend money on certifications until you have built a foundation of practical knowledge through free resources.
Target the right first roles: Junior SOC Analyst, IT Support with Security Focus, Security Operations Helpdesk, and Junior Vulnerability Analyst are realistic first roles. These build the experience needed to progress. Many people also enter cybersecurity from IT administration, software development, or helpdesk roles by moving laterally within their current employer, which avoids the experience paradox entirely.
Address the experience paradox directly: Every entry-level job seems to require experience. The way around this is to build demonstrable skills before applying. Lab work, CTF competitions, bug bounty participation, and open source contributions create a portfolio that proves capability without requiring employer-granted experience.
No single LLM wins every category in 2025 - 2026:
• Claude (Anthropic) - best for coding (SWE-Bench) and long documents
• GPT-4o / GPT-5 (OpenAI) - best for reasoning (GPQA) and multimodal tasks
• Gemini 2.0 (Google) - best for ultra-long context (1M tokens) and video
The best LLM depends on your specific task, not the overall ranking.
• Developer: Claude = Anthropic, ChatGPT = OpenAI (GPT-4o / GPT-5)
• Coding: Claude leads on SWE-Bench Verified (real software engineering)
• Images & tools: ChatGPT/GPT-4o is more widely integrated
• Long docs: Claude is preferred for large context window tasks
• Tone: Claude is more cautious; ChatGPT is more versatile across apps
Best LLMs for coding (2025 - 2026):
1. Claude Opus/Sonnet (Anthropic) - #1 on SWE-Bench Verified
2. GPT-4o / o3 (OpenAI) - strong debugging & explanation
3. DeepSeek-V3 / R1 - frontier-class coding at low cost
4. Llama 4 / Code Llama (Meta) - best open-weight self-hosted option
5. Qwen 3 (Alibaba) - cheap, capable, open-weight
Cheapest LLM APIs in 2025 - 2026 (per million tokens):
• Qwen 3.5 0.8B - ~$0.01 (cheapest available)
• Gemma 3n (Google) - free tier via Google AI Studio
• Mistral 7B / Mixtral - $0.05 - $0.20 via Groq / Together AI
• GPT-4o mini (OpenAI) - ~$0.15 input / $0.60 output
• Claude Haiku (Anthropic) - ~$0.25 input / $1.25 output
Open-weight models via Groq or Together AI are 5 - 10x cheaper than proprietary APIs.
Choosing open-source vs proprietary LLM - 5 factors:
1. Data privacy - self-host open-weight models (Llama, Mistral) if data can't leave your infra
2. Cost - open-weight is cheaper at high token volumes
3. Customisation - open-weight models can be fine-tuned; proprietary usually can't
4. Performance - frontier proprietary models (Claude, GPT-5) still lead on hardest tasks
5. Maintenance - proprietary APIs are managed; self-hosting needs GPU infra + DevOps
Choosing open-source vs proprietary LLM - 5 factors:
1. Data privacy - self-host open-weight models (Llama, Mistral) if data can't leave your infra
2. Cost - open-weight is cheaper at high token volumes
3. Customisation - open-weight models can be fine-tuned; proprietary usually can't
4. Performance - frontier proprietary models (Claude, GPT-5) still lead on hardest tasks
5. Maintenance - proprietary APIs are managed; self-hosting needs GPU infra + DevOps