Application Security
We've curated 113 cybersecurity statistics about Application security to help you understand how safeguarding software from vulnerabilities and attacks is evolving in 2025. This includes best practices, emerging threats, and essential technologies to secure your applications effectively.
Related Topics
Showing 41-60 of 113 results
81% of CISOs and AppSec executives are willing to pivot to new MCP protection tools.
55% of CISOs and AppSec executives are willing to replace RASP.
52% of CISOs and AppSec executives are willing to replace SCA.
49% of CISOs and AppSec executives are willing to replace SAST/DAST.
Over 75% of security professionals do not have the real-time production insight necessary to validate risk and understand how their code behaves in real-world environments.
Malicious web application and API transactions rose 128% year over year.
72% of organizations experience at least one mobile app security incident in the past year.
91% of mobile app developers and security leaders prefer security that spans the entire software development lifecycle.
63% of mid-sized AppSec teams (11–50 members) that use SCA cite the inability to verify if vulnerabilities are exploitable in production as their biggest pain point.
38% of small AppSec teams (1–10 members) that use SCA cite the inability to verify if vulnerabilities are exploitable in production as their biggest pain point.
58% of large AppSec teams (50 members or more) that use SCA cite the inability to verify if vulnerabilities are exploitable in production as a major pain point.
13% of CISOs and AppSec executives use agent-based deployment.
16% of CISOs and AppSec executives want to consolidate the AppSec toolchain into one platform.
14.5% of AI agent configuration files grant arbitrary code execution permissions for Python.
14.4% of AI agent configuration files grant arbitrary code execution permissions for Node.js.
Almost 20% of developers let AI automatically save changes to the project's main code repository without human review.
Use of risk-ranking methods to determine where LLM-generated code is safe to deploy increased by 12%.
Establishment of standardized technology stacks rose by more than 40%.
Teams using attack intelligence to track emerging AI vulnerabilities increased by 10%.
Automated verification of infrastructure security surged by more than 50%.