Bright Security Reports Rising Enterprise Investment in Continuous AI Security Testing

SAN FRANCISCO, California, August 2nd, 2026, FinanceWire

Bright Security, a provider of Dynamic Application Security Testing (DAST) solutions, today released new industry insights examining the growing shift in enterprise cybersecurity strategies toward continuous security testing as organizations accelerate software development and increase their use of AI-assisted coding. The analysis highlights how evolving development practices are prompting enterprises to move beyond traditional point-in-time security assessments in favor of continuous application security testing.

For two decades, the annual penetration test has long been seen as the focal point of enterprise security programs. A team of consultants would spend two weeks assessing an application, provide a report, and organizations would spend months implementing recommended changes before repeating the process. According to Bright Security, this model is becoming less effective as modern software delivery cycles continue to accelerate.

Why the Annual Pentest Model Is Breaking

Multiple security industry analyses over the past year predicted a movement in enterprise security spending from point-in-time assessments to continuous testing. The driver is very simple math. The typical enterprise is deploying code to production every day, and lots of engineering teams are deploying multiple times per day. A penetration test in January does not imply that there is an application in March.

Security leaders will no longer accept a six-figure consulting fee for results that are valuable only until before they read the report. This is why continuous DAST platforms have become an important part of enterprise budgets and are shifting from a niche solution to a regular staple that scans running apps on each build, and identifies vulnerable application weaknesses before the code is even finished.

AI-Generated Code Widened the Gap

The problem has been compounded by AI coding assistants. When teams deploy GitHub Copilot and other code generation models, they deploy features faster than they could get manual reviews on time. AI-driven code has been shown to introduce vulnerabilities at a rate that is similar to or greater than human code, and with the volume of code created, the number of vulnerabilities entering into production has skyrocketed.

What was already too little testing is now too little. Earlier scanning tools weren't popular with developers because they flagged false positives, but vendors like Bright Security have already responded with results that they've confirmed based on the current application rather than on theory.

The Economics Favor Early Detection

Industry breach cost studies consistently place the average data breach in the multimillion-dollar range, with application-layer attacks among the most common entry points. The cost difference between catching a vulnerability in the pipeline versus a post-breach forensic investigation runs into the millions. CFOs who once treated security testing as a compliance checkbox now view it as risk-adjusted insurance with measurable returns.

AI Security Becomes Its Own Budget Line

There is a second category growing even faster. AI security has become one of the most funded areas in enterprise technology, as organizations confront attackers using the same generative models as defenders. AI-assisted exploit development and machine-speed attack campaigns have shortened the window between disclosure and active exploitation from weeks to days, and in some cases to hours. Teams on quarterly assessment cycles cannot respond at that tempo.

The convergence is producing a new architecture: continuous scanning of applications and APIs paired with platforms that validate whether a vulnerability is actually exploitable and suggest verified fixes. This step of validation is important as security teams have always been inundated with alerts that prove to be false. First, a confirmation of exploitability allows teams to concentrate on remediation efforts where they can have the greatest impact on actual risk reduction.

Where This Leaves the Human Tester

The ownership of security testing is shifting from external consultants to engineering organizations and is becoming part of the CI/CD pipeline and repository. Developers view the findings in the same tools they write code in and fixes are released in the same sprint that the fault was added to the code base.

Manual penetration testing isn't going away. There is still a need for human creativity in complex business logic attacks, social engineering, and red team exercises. But, that's aging to the problems that machines can't handle and regular vulnerability detection is becoming a continuous platform. Now, for businesses still planning their tests around a yearly cycle, the question is, what level of exposure will they face as they wait?

About Bright Security

Bright Security provides Dynamic Application Security Testing (DAST) solutions designed to help organizations identify, validate, and remediate application vulnerabilities throughout the software development lifecycle. Its platform integrates with modern development workflows to support continuous application security testing across web applications and APIs.

Website: https://brightsec.com

Contact

Eyal Dror
Bright Security
eyal.dror@brightsec.com
+546526651

Disclaimer. This is a paid press release.