This occurs when an attacker can insert or manipulate SQL queries in the input fields to be executed by the database. It can lead to unauthorized data manipulation or access.
Cross-Site Scripting (XSS)
XSS vulnerabilities occur when an application includes unvalidated and unescaped user input as part of HTML output. It allows attackers to execute malicious scripts in a user’s browser, potentially stealing cookies, session tokens, or other sensitive information that leads to identity theft.
Cross-Site Request Forgery (CSRF)
This type of attack forces an end user to execute unwanted actions on a web application in which they are currently authenticated. CSRF attacks specifically target state-changing requests, not theft of data, since the attacker has no way to see the response to the forged request.
Buffer Overflow
This occurs when a program writes more data to a buffer than it can hold. This can lead to arbitrary code execution, where an attacker could take control of a system.
Use of Hard-coded Credentials
Embedding fixed usernames and passwords in source code can lead to unauthorized access if the codebase is exposed.
Compromised development and management tools present a significant threat to software supply chains. Attackers may target essential components such as code repositories, build servers, and integrated development environments (IDEs) to inject malicious code. This strategy causes developers and/or users to distribute compromised software without knowing it.
Vulnerability prioritization is the practice of assessing and ranking identified security vulnerabilities based on critical factors such as severity, potential impact, exploitability, and business context. This ranking helps security experts and executives avoid alert fatigue to focus remediation efforts on the most critical vulnerabilities.
Application security posture management entails continuously assessing applications for threats, risks, and vulnerabilities throughout the software development lifecycle (SDLC).
AI risk management is a set of tools and practices for assessing and securing artificial intelligence environments. Because of the non-deterministic, fast-evolving, and deep-tech nature of AI, effective AI risk management and SecOps requires more than just reactive measures.
SAST (Static Application Security Testing) analyzes custom source code to identify potential security vulnerabilities, while SCA (Software Composition Analysis) focuses on assessing third-party and open source components for known vulnerabilities and license compliance.
Static Application Security Testing (SAST) is a method of identifying security vulnerabilities in an application's source code, bytecode, or binary code before the software is deployed or executed.