security risks of AI-generated website code

AI-generated code for user authentication and authorization often lacks advanced security considerations. For instance, it might implement weak password storage methods (e.g., MD5 hashing) or fail to enforce account lockouts after repeated failed login attempts. These weaknesses allow attackers to exploit authentication systems, gain unauthorized access, and potentially compromise sensitive data.

AI tools may generate database queries without implementing proper input sanitization or parameterized queries. This oversight exposes websites to SQL injection attacks, where malicious actors manipulate queries to access or destroy sensitive data. If deployed in production, such vulnerabilities can result in data breaches, financial losses, or legal repercussions.

AI often recommends third-party libraries or plugins to optimize development. However, these suggestions may include outdated, unmaintained, or insecure components. Without thorough vetting, developers may introduce critical vulnerabilities, enabling attackers to exploit security flaws in dependencies or compromise the software supply chain.

Many AI-generated scripts fail to enforce stringent input validation and output encoding. This negligence leaves websites vulnerable to injection attacks, such as cross-site scripting (XSS), where attackers inject malicious scripts into user-facing elements. These attacks can steal user credentials, redirect users to malicious sites, or compromise browser sessions.

AI-generated code may overlook proper error-handling mechanisms, such as sanitizing error messages before displaying them to users. Detailed error outputs can inadvertently reveal sensitive information about the server, database schema, or internal logic, providing attackers with valuable insights to exploit the application.

AI tools might generate code that assumes default or insecure configurations for hosting environments, frameworks, or servers. For example, it may leave debug modes enabled, expose sensitive files, or fail to disable unused services. Such misconfigurations create an expanded attack surface, leaving the website vulnerable to exploitation.

AI might suggest improper cryptographic practices, such as using outdated encryption algorithms or failing to implement secure key management. Poor cryptography compromises the integrity and confidentiality of sensitive data, leaving it susceptible to interception or tampering during transmission or storage.

AI-generated code often does not account for industry-specific security standards. Without adherence to applicable regulations, websites may be non-compliant, exposing site owners to additional risks and loss of customer trust.

Websites developed at NWLYNX are coded by NWLYNX. With exception to a limited number of trusted 3rd party libraries, all base code for web sites are authored in-house. This includes front-end languages as well as advanced programming and server-side technologies.

Each website project has a dedicated, secure staging environment where source code additions and modifications are fully tested prior to launch or re-launch. These environments are served with isolated encryption certificates as well as custom error-handling not available in production-level projects.

Site configurations for production environments are created at the master configuration level VS in project-level directories and files. Isolated rule-sets and special instructions are created with a Zero-Trust policy in mind. Upper-level security policies applicable to projects server-wide cascade, ensuring all projects deploy with shared security minimums in place from the beginning.

Using Zero-Trust as a philosophy, incoming and outgoing user data is treated equally. It is assumed that every request will contain some form of malicious intent. Cleansing data, validating input, proper encoding & safe presentation of user-data, and safely prepared SQL queries are a just few examples of where applying modern security standards will decrease risk and build customer trust.

Popular content management systems such as WordPress can generate website code requiring dozens of included scripts, sometimes hundreds. Many are pulled blindly from off-server, outside-network sources, introducing additional security risks in the form of supply chain or upstream exploits, then negatively affecting any source file, system, or function requiring them. Websites built at NWLYNX contain very few required scripts from outside sources, reducing the number of vectors available for exploitation.