AI + Automated Vulnerability Hunting Tutorial: How Beginners Can Find Their First SRC Vulnerability from Scratch

When Vulnerability Hunting Meets AI: A Shortcut for Beginners or Just Hype?

In the cybersecurity field, SRC (Security Response Center) vulnerability hunting has long been an important way for white-hat hackers to earn bounties and build experience. But for beginners just starting out, the vast landscape of vulnerability principles, asset collection, and tool usage often feels overwhelming. Recently, a systematic course titled "The Most Beginner-Friendly AI + Automated Vulnerability Hunting Tutorial for 2026" appeared on Bilibili, claiming it can guide zero-foundation students through the entire AI + automated vulnerability hunting workflow and help them find their first SRC vulnerability. Does this course really pave the way for beginners? And what role does AI play in it?

Course Structure: A Four-Step Learning Path

According to the UP host, the course is divided into four parts: Fundamentals, Vulnerability Principles, AI Tools, and Practical Hunting. It aims to hand-hold students through high-frequency vulnerability principles, asset information gathering, hands-on tool operation, CVE vulnerability reproduction, and SRC hunting practice. This phased design follows the progressive logic of skill learning and is especially suitable for beginners lacking systematic training.

A notable detail: the course includes a dedicated "AI Tools" section, indicating that AI technology has been integrated into vulnerability hunting education. Although the UP host didn't specify which AI tools are used, it's reasonable to infer that it may involve automated information gathering, vulnerability scanning assistance, and code audit support. The addition of AI is expected to lower the barrier of repetitive work, allowing beginners to focus more on understanding the essence of vulnerabilities and hunting logic.

SRC (Security Response Center) is a security response center established by enterprises or organizations to receive vulnerability reports submitted by external security researchers. White-hat hackers can earn bounties, points, or recognition by submitting valid vulnerabilities to SRCs. Common domestic SRCs include platforms built by internet companies such as Tencent, Alibaba, and ByteDance, as well as third-party crowdtesting platforms like Butian and Vulbox. For beginners, SRC hunting is a practical scenario to test learning outcomes, but platform rules and laws must be followed—testing target systems without authorization may violate the law.

How Does AI Empower Vulnerability Hunting?

In the vulnerability hunting workflow, AI can be applied at multiple stages. For example, during asset collection, AI can help identify and classify target assets and quickly map the attack surface; during vulnerability discovery, AI can assist in analyzing anomalous patterns in code or traffic to improve efficiency; during exploitation, AI can generate or optimize payloads to reduce manual trial-and-error costs. Although course details are limited, the "AI + automation" positioning suggests these possibilities.

For beginners, the greatest value of AI tools lies in lowering the technical barrier while preserving understanding of core concepts. However, over-reliance on AI can also lead to weak fundamentals. Therefore, placing the AI Tools section after the Vulnerability Principles section may be precisely to ensure students first master the basics before using AI to boost efficiency.

CVE (Common Vulnerabilities and Exposures) is an internationally recognized vulnerability numbering system. Every publicly disclosed vulnerability is assigned a unique identifier (e.g., CVE-2024-1234), along with a description, affected versions, and reference links. CVE vulnerability reproduction refers to researchers setting up a local vulnerable environment and recreating the vulnerability trigger process according to public information, in order to understand the vulnerability's principles and exploitation methods. For beginners, reproducing CVEs is an important way to learn vulnerability hunting, but it must be done in isolated environments (such as virtual machines or Docker) to avoid harming real systems.

From Learning to Practice: Finding Your First Vulnerability

The course's goal is to guide students to find their first SRC vulnerability. This requires students to make the leap from theory to practice. The Practical Hunting section likely includes demonstrations in real environments, covering how to select targets, conduct information gathering, verify vulnerabilities, and submit reports. For beginners, finding the first vulnerability is not only a technical breakthrough but also a confidence builder.

The UP host mentions that after completing the course, students can switch careers to cybersecurity and become white hats at big companies, or hunt vulnerabilities from home to earn bounties. This indeed reflects the talent demand in the cybersecurity industry, but it's worth noting that improving hunting skills requires continuous learning and practice—the course is only a starting point.

Payload in vulnerability exploitation refers to the input data constructed by an attacker to trigger a vulnerability or execute malicious operations. Examples include malicious SQL statements in SQL injection, specific byte sequences in buffer overflows, and malicious scripts in XSS. Payload design directly affects the success rate of exploitation. AI can assist in generating or mutating payloads—for example, using genetic algorithms or reinforcement learning to search for payload variants that bypass WAF (Web Application Firewall)—but this also requires users to understand vulnerability principles; otherwise, it's difficult to effectively evaluate and adjust AI-generated payloads.

Course Resources and Learning Advice

To ensure learning effectiveness, the UP host provides resources such as study plans, video tutorials, study notes, and tool installation packages. These supporting materials are very practical for beginners, reducing time spent on environment setup and material collection. However, learners still need to think actively and experiment hands-on to truly master the skills.

Overall, this course provides a structured learning framework for beginners, and the addition of AI elements aligns with technological trends. But the actual effectiveness depends on content depth and student engagement. Interested learners are advised to preview part of the content first, assess how well it matches their needs, and then decide whether to invest time.

One-line Summary

Bilibili's AI + automated vulnerability hunting course offers beginners a structured learning path, but results depend on course depth and student engagement.

Paragraph Summary

The article introduces a systematic course on Bilibili titled "The Most Beginner-Friendly AI + Automated Vulnerability Hunting Tutorial for 2026." The course is divided into four stages—fundamentals, vulnerability principles, AI tools, and practical hunting—aiming to help zero-foundation students navigate the entire AI + automated vulnerability hunting workflow and find their first SRC vulnerability. The article analyzes possible AI applications in asset collection, vulnerability discovery, and payload generation, concluding that AI can lower technical barriers but requires mastering fundamentals first. The course provides study plans, notes, and toolkits, and the UP host claims graduates can switch to cybersecurity careers or earn bounties. Overall, the course offers a structured framework, but actual results depend on content depth and student engagement—previewing before committing is recommended.