Getting Started with SRC Bug Bounty Hunting: A Complete Learning Path from Zero to AI-Assisted Vulnerability Research

Cybersecurity has always been one of the hottest areas in tech, and SRC (Security Response Center) bug bounty hunting stands out for its combination of technical challenge and earning potential — drawing in a large number of learners. A Bilibili creator recently released a comprehensive cybersecurity course that took five months to produce, covering everything from zero-knowledge basics to AI-assisted vulnerability research. This article uses that course's framework to map out a clear SRC bug bounty learning path and highlight the key milestones along the way.

Why Self-Teaching Cybersecurity Is Still So Hard

According to the creator, before building the course, he spent a month going through the most popular cybersecurity tutorials online. His conclusion: the landscape is a mess. Some tutorials are stuck four or five years in the past; others are cobbled together and full of gaps. For beginners, this fragmented, outdated material actually raises the barrier to entry rather than lowering it.

This observation cuts to the core of self-teaching cybersecurity: the knowledge base is enormous and evolves extremely fast. Web security, systems security, penetration testing, and vulnerability exploitation each form their own sub-disciplines, with attack techniques and defensive strategies constantly shifting as technology advances. Without a proven learning path, beginners easily fall into the trap of "learning a lot of tools but having no idea how to connect them." That's exactly why a structured, up-to-date curriculum that combines theory with hands-on practice has genuine value.

A Three-Phase Learning Framework: From Fundamentals to Real-World Practice

The course divides its content into three sections — Foundations, Advanced Attack and Defense, and Hands-On Practice — a layered approach that mirrors how most technical skills are best learned.

Phase 1 — Foundations: Building a Solid Base

The foundations section covers cybersecurity law and regulations, Linux, HTML, PHP, databases, and other prerequisite knowledge, and walks students through setting up a local security lab environment. This phase might seem dry, but it's the bedrock of everything that follows.

For example, understanding SQL injection requires knowing databases and SQL syntax first. Understanding XSS (Cross-Site Scripting) requires HTML and JavaScript fundamentals. And PHP, as the server-side language powering a huge portion of web applications, is essential for analyzing source-level vulnerabilities. Getting familiar with legal boundaries from the start is equally critical — the legitimacy of SRC bug hunting hinges on "authorized testing." Any unauthorized penetration attempt can cross a legal line, and that awareness needs to be established right at the beginning.

Phase 2 — Advanced Attack and Defense: Penetration Testing Methodology and Toolchain

The advanced section focuses on the full penetration testing workflow, common tools, attack techniques, defensive strategies, and vulnerability discovery.

Penetration testing generally follows a standardized process: reconnaissance → vulnerability scanning → exploitation → privilege escalation → post-exploitation → report writing. Core tools like Burp Suite (web traffic interception and vulnerability testing), Nmap (port and service scanning), and SQLMap (automated SQL injection detection) are all covered here. The course also includes mind maps and reference documents to help learners build a structured knowledge framework — genuinely useful for memorizing and reviewing attack techniques.

SRC Bug Bounty Hunting in Practice and Legitimate Earnings

The most compelling part of the course is the hands-on section, which includes reproducing popular CVE vulnerabilities, incident response practice, live SRC bug hunting, and online CTF competitions.

CVE Reproduction and CTF Competitions: Turning Theory into Muscle Memory

Reproducing CVE vulnerabilities is one of the most effective ways to build practical skills. CVE (Common Vulnerabilities and Exposures) is a public registry of disclosed vulnerabilities. By setting up environments with known vulnerabilities and exploiting them hands-on, learners develop a deep understanding of how vulnerabilities arise and how exploit chains work. CTF (Capture the Flag) competitions train well-rounded skills in a competitive format, spanning Web security, reverse engineering, cryptography, Pwn, and more — a great way to stress-test everything you've learned.

CVE identifiers are managed by MITRE, with each ID mapping to a unique public vulnerability record that includes a description, affected versions, CVSS score, and remediation advice. NVD (National Vulnerability Database) complements CVE by providing more detailed technical information and affected software versions. In practice, learners typically use Docker or virtual machines to spin up vulnerable environments quickly. Vulhub is the most widely used open-source vulnerability lab project in China, offering one-click reproduction environments for hundreds of real CVEs — ideal for systematic practice. For CTFs, popular Chinese platforms include BUUCTF and NSSCTF; beginners should start with Web and Misc challenges, which align most directly with the web penetration skills needed for SRC hunting.

SRC Bug Bounty Earnings: A Legitimate Path for White Hats

SRC bug bounty hunting attracts so much attention because it offers a legal path to "apply what you've learned and get paid for it." Major Chinese internet companies all run SRC platforms where white-hat researchers can submit valid vulnerabilities in exchange for points, prizes, or cash rewards. It's both a way to monetize technical skills and a way to build a reputation in the industry. One thing bears repeating: compliance and authorization are always the prerequisite for earning anything — never cross the line.

Well-known SRC platforms in China include Alibaba Cloud's Xianzhizhi, Tencent's Security Response Center (TSRC), and ByteDance's Security Response Center (BSRC). Each platform typically classifies vulnerabilities into four severity tiers — critical, high, medium, and low — with rewards ranging from a few hundred to tens of thousands of RMB. Critical vulnerabilities sometimes trigger bonus surprise rewards. When submitting, white hats are expected to follow a "minimal testing principle": verify that the vulnerability exists without expanding its impact, accessing user data, or causing disruption. Platforms generally conduct a manual review after receiving a report to confirm validity, and the full cycle from submission to reward typically takes anywhere from a few days to a few weeks. For beginners, it's worth starting with smaller SRC platforms or targets with broader scope to accumulate experience before tackling high-value targets on tier-one platforms.

AI-Assisted Vulnerability Research: An Emerging Trend in Security

The course title specifically mentions "AI-assisted bug hunting in practice," reflecting an important shift happening across the security field. As large language models grow more capable, AI is starting to play a supporting role in vulnerability research — including automated code auditing, fuzzing test case generation, vulnerability pattern recognition, and using LLMs to help analyze source code logic flaws.

That said, a realistic perspective is warranted: AI today is primarily an efficiency tool that augments human researchers, not an automated engine that replaces them. Discovering genuinely valuable vulnerabilities still depends heavily on a researcher's deep understanding of business logic, attack surface, and defensive mechanisms. For learners, mastering AI tools can meaningfully speed up the information gathering and initial analysis phases — but the underlying security mindset remains the irreplaceable core competency.

In terms of concrete applications, AI-assisted security research has already produced some established practices: GPT-class models can help read and explain complex C/C++ or PHP source code, helping researchers quickly identify dangerous function call chains. Tools like GitHub Copilot significantly speed up writing PoC (proof-of-concept) code. Security-specific fine-tuned models (such as PentestGPT) attempt to guide penetration testing thinking through conversation. On the fuzzing side, AFL++ combined with machine learning-guided coverage strategies triggers deeper code paths far more efficiently than traditional random fuzzing. One important caveat: AI-generated vulnerability analysis is susceptible to hallucinations, so researchers need enough foundational knowledge to verify AI outputs rather than accepting them at face value.

Conclusion: A Systematic Learning Path Is the Key to Getting Started

Looking at how this course is designed, it's clearly trying to solve the biggest pain point for beginners — the lack of a proven, continuously updated learning path that combines theory with real-world practice. Regardless of which learning resources you ultimately choose, the methodology embedded in this framework is worth adopting: start by solidifying your foundations in Linux, web development, and databases; then systematically master the penetration testing workflow and toolchain; finally, close the loop with CVE reproduction, CTF competitions, and live SRC submissions.

For anyone looking to break into cybersecurity, two non-negotiables should be established from day one: legal compliance — all testing must stay within authorized boundaries — and continuous learning, because security offense and defense is a domain that never stops evolving. Treat AI as an efficiency multiplier, use a systematic learning path as your skeleton, and let hands-on practice be the muscle and flesh. That's how you build a sustainable career in SRC bug bounty hunting.