Carriage return (CR) and line feed (LF), also known as CRLF injection is a type of vulnerability that allows a hacker to enter special characters into a web application, altering its operation or confusing the administrator. Log poisoning and HTTP response splitting are two prominent harmful uses of this technique. Additionally, CRLF injection can be used by an attacker to exploit other vulnerabilities, such as cross-site scripting (XSS). According to Open Web Application Security Project (OWASP), CRLF vulnerabilities are among the top 10 vulnerabilities and are a type of injection attack. Automated testing can help to quickly identify CRLF vulnerabilities, and is particularly useful for companies to test their applications before releasing them. However, CRLF vulnerabilities foster a better approach to mitigate CRLF vulnerabilities in the early stage and help secure applications against high-risk known vulnerabilities. There has been less research on CRLF vulnerabilities and how to detect them with automated testing. There is room for further research to be done on this subject matter in order to develop creative solutions to problems. It will also help to reduce false positive alerts by checking the header response of each request. Security automation is an important issue for companies trying to protect themselves against security threats. Automated alerts from security systems can provide a quicker and more accurate understanding of potential vulnerabilities and can help to reduce false positive alerts. Despite the extensive research on various types of vulnerabilities in web applications, CRLF vulnerabilities have only recently been included in the research. Utilizing automated testing as a recurring task can assist companies in receiving consistent updates about their systems and enhance their security.
翻译:电车回车(CRR)和线路馈送(LF),也称为CRLF注射(CRLF)是一种脆弱性,使黑客能够将特殊人物输入网络应用程序,改变其运作或混淆管理员; 记录中毒和HTTP反应分解是这一技术的两大有害用途; 此外,攻击者可以使用CRLF注射来利用其他脆弱性,如跨现场脚本(XSS)等; 根据开放网络应用程序安全项目(OWASP), CRLF脆弱性属于前十大脆弱性,是一种注射式袭击; 自动测试有助于快速识别CRLF脆弱性,对于公司在释放前测试其应用程序特别有用。 然而,CRLF脆弱性促进一种更好的方法,在早期阶段减轻CRLF脆弱性,帮助其应用防范已知的高风险。 对CRLF的脆弱性和如何用自动测试来检测这些脆弱性的研究较少。 根据开放网络应用程序,CLF的脆弱性只能通过检查每份请求的负责人反应来减少错误的正面警报。 安全自动化自动化是公司努力提高安全警戒状态的一个重要问题。</s>