SRC

Privilege level and data access scope determine the severity of a vulnerability.

Common SRC platforms include Alibaba Cloud Xianzhī, Tencent Security Response Center, and Vulbox.

AI-generated vulnerability reports are only first drafts; they must be manually reviewed before final submission, otherwise handing everything over to AI for automatic submission is very likely to result in being blacklisted.

In the SRC vulnerability mining field, there is a widely used 'universal three-step method for finding vulnerabilities': information gathering, packet capture analysis with parameter tampering to verify vulnerabilities, and validating vulnerabilities and writing reports.

The core application points of AI in penetration testing are rapidly enumerating target assets during the information gathering phase, assisting in understanding principles during the vulnerability analysis phase, and vulnerability validation and report generation.

Most domestic SRC platforms classify vulnerabilities into four levels—critical, high, medium, and low—and at certain leading internet companies, a single critical vulnerability can yield rewards of tens of thousands of yuan, while low-severity vulnerabilities may only receive point rewards of a few dozen to a few hundred yuan.

SRC（安全应急响应中心）是企业设立的漏洞收集平台，企业付费购买未公开的安全漏洞，安全研究者发现并提交后审核通过可获得赏金

The CVSS Common Vulnerability Scoring System classifies vulnerability severity into four levels: low, medium, high, and critical.

When submitting vulnerabilities on SRC platforms, a POC that can be reliably reproduced is often the key basis for a report to be accepted, directly affecting the vulnerability rating and reward.

Beginners commonly make three types of mistakes in SRC bug hunting: weak authorization awareness that treats oral requests as authorization, public disclosure before a vulnerability is fixed, and skipping labs to go straight into live testing.

The boundaries of legal SRC testing are determined entirely by the enterprise's written authorization, and any operation beyond the testing scope constitutes a violation.

Domestic SRCs are mostly built by enterprises themselves, with considerable variation in rules, and their requirements for report format and reproduction details are often stricter than those of public bug bounty platforms (such as HackerOne).

AI-based automated SRC vulnerability hunting is still at the tool-assisted stage, and task definition, skill writing, and result review cannot be separated from humans.

The universal three-step method for SRC vulnerability hunting is understanding the target, discovering vulnerabilities, and writing a report.

Before testing against real SRC targets, the stability and accuracy of the AI workbench should first be verified in test ranges (such as DVWA, VulnHub, and OWASP Juice Shop) to avoid false positives and compliance risks.

The core difference between SRC bug hunting and penetration testing is: SRC usually targets real production environments, testing must be within the authorized scope, and it emphasizes the real harm and reproducibility of vulnerabilities.

What SRC pursues is not the number of vulnerabilities, but verifiable, fixable, valid vulnerabilities.

White hats' sources of income usually include vulnerability bounties paid by corporate SRCs, project compensation from crowdsourced testing platforms, and formal positions at security vendors.

In the SRC context, the testing scope description published by the company and the written authorization email are the prerequisite basis for all testing behavior carried out by white hats.

The standard workflow of an SRC is: white hats search for vulnerabilities within the authorized scope, submit reports through the SRC platform, the corporate security team verifies them, fixes them after confirmation, and issues monetary or honorary rewards based on the vulnerability level.