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AI Is Changing Software Security - and Businesses Need to Be Ready
Artificial intelligence is changing how software vulnerabilities can be discovered.
For businesses that depend on websites, web applications, integrations and custom software, this creates both an opportunity and a challenge.
AI-assisted research can help identify weaknesses in software that might otherwise remain undetected. However, finding a vulnerability does not automatically make a system secure. The issue still needs to be validated, the appropriate fix must be developed and tested, and affected systems need to be updated.
This distinction has become particularly relevant following a recent development involving PHP, a widely used programming language for websites and web applications.
On 21 October 2026, OpenAI published details of its Patch the Planet initiative, describing a coordinated effort involving researchers, software maintainers and security partners to address critical PHP vulnerabilities. OpenAI reported that AI-assisted research helped identify a critical flaw, while Wiz independently discovered and reported the vulnerabilities. PHP’s maintainers led the fixes and release process.
The case highlights an important point for businesses: as AI capabilities improve, the ability to identify software weaknesses must be matched by the ability to respond effectively.
What Is AI Software Vulnerability Detection?
AI software vulnerability detection refers to the use of artificial intelligence to help identify potential weaknesses in software code, applications and related systems.
Depending on the tools and approach used, AI can assist security researchers and software engineers with tasks such as:
Analysing source code to identify suspicious patterns or potential weaknesses.
Helping researchers investigate complex software behaviour.
Reviewing code changes for possible security issues.
Supporting the creation of test cases that examine how software behaves under unexpected conditions.
Helping developers understand existing code and investigate potential causes of defects.
These capabilities can support traditional software security practices, including code reviews, automated testing, vulnerability scanning and specialist security assessments.
However, AI-generated findings are not automatically confirmed vulnerabilities. Results require appropriate technical validation, and AI tools should not be treated as a replacement for sound engineering practices or qualified security expertise.
The significance is not that AI has eliminated software security risks. It is that AI is becoming another tool that can help defenders investigate and address them.
Why the Latest AI Security Developments Matter to Businesses
A vulnerability in a software component can affect many different applications and organisations if that component is widely used.
For example, a business website may depend on a programming language, content management system, framework, plugin or third-party library. A weakness in one of these components could potentially create a security risk for applications that rely on it.
The actual risk depends on several factors, including the vulnerability itself, the software version in use, the system’s configuration, its exposure to the internet and the available mitigations.
This is why businesses should not focus only on the security of the software they develop internally. They also need visibility into the technologies and dependencies on which their systems rely.
1. Vulnerabilities may affect software you did not build yourself
Most modern applications depend on existing software components and third-party services. These dependencies can make development more efficient, but they also create maintenance responsibilities.
If a vulnerability is discovered in a component used by your application, your business may need to identify affected systems, assess the potential impact and apply an appropriate update.
Without an inventory of software components and a clear update process, identifying where action is needed can be unnecessarily difficult.
2. Discovering a vulnerability is only the beginning
A vulnerability report does not automatically resolve the problem.
The affected software must be identified, the finding assessed, and an appropriate remediation plan established. Depending on the issue, this may involve applying an official security patch, updating a dependency, changing a configuration or implementing a temporary mitigation.
The fix should then be tested and deployed through an appropriate process.
The UK National Cyber Security Centre’s Software Security Code of Practice guidance emphasises vulnerability management, tested updates, timely remediation and secure software maintenance.
3. Delayed updates can leave systems exposed
When a relevant security update becomes available, postponing it without assessing the risk can leave an affected system vulnerable for longer than necessary.
Not every update requires the same response time. A critical vulnerability affecting an internet-facing application may require urgent action, while a lower-risk issue may be handled through a planned maintenance cycle.
The important thing is to have a process for assessing severity, identifying affected systems and deciding who is responsible for taking action.
Businesses should avoid assuming that installing updates occasionally is sufficient. Effective maintenance requires a consistent approach to monitoring, prioritisation, testing and deployment.
4. AI can support defenders, but it can also benefit attackers
AI capabilities can support legitimate security research, but similar advances may also help malicious actors investigate weaknesses and develop attacks.
OpenAI’s October 2026 announcement explicitly recognises this dual-use challenge.
For businesses, the practical response is not to panic or assume that every system is immediately at risk. It is to maintain visibility over software, respond to credible security advisories and ensure that systems are maintained appropriately.
Six Practical Steps to Improve Your Software Security Readiness
Businesses do not need to adopt every new AI security tool to improve their readiness. A clear software maintenance process is a sensible starting point.
1. Build an inventory of your software
Identify the applications and systems your business relies on, including websites, custom applications, frameworks, plugins, libraries and important third-party services.
Where possible, record the versions in use and the teams or suppliers responsible for maintaining them.
This inventory makes it easier to determine whether a newly disclosed vulnerability affects your environment.
2. Establish a process for monitoring vulnerabilities
Make sure someone is responsible for monitoring relevant vendor advisories, security updates and vulnerability disclosures.
For widely used technologies, follow official project announcements and trusted security guidance rather than relying solely on social media posts or unverified reports.
Automated dependency and vulnerability monitoring tools can help, particularly where applications have many components.
3. Prioritise issues according to risk
Not every vulnerability presents the same level of risk.
Consider factors such as:
The severity of the vulnerability.
Whether the affected system is accessible from the internet.
Whether the vulnerable component is actually used in the affected configuration.
Whether exploitation is known or suspected.
The sensitivity of the data or business processes involved.
Whether an official fix or effective mitigation is available.
This approach helps teams direct their attention to the issues that require the most urgent action.
4. Test and deploy fixes responsibly
Applying security updates promptly is important, but updates should also be deployed in a controlled manner appropriate to the system and the urgency of the issue.
Where practical, test changes in a staging or non-production environment, verify that essential functionality still works, and maintain a suitable rollback or recovery plan.
For critical vulnerabilities, the business may need an accelerated process or an interim mitigation while a full fix is prepared.
The aim is to reduce exposure without introducing avoidable operational problems.
5. Include security in the software development lifecycle
Security should not be treated as a final check performed only when an application is ready to launch.
Development teams can incorporate security considerations into requirements, architecture, coding practices, code review, automated testing, deployment and ongoing maintenance.
AI-assisted tools may support parts of this process, but their findings should be reviewed and tested. Human oversight, appropriate access controls and secure development practices remain important.
6. Define ownership and response procedures
A vulnerability can become an operational problem when nobody knows who is responsible for resolving it.
Establish clear responsibilities for reviewing security alerts, assessing their impact, approving emergency changes, communicating with software suppliers and confirming that remediation has been completed.
Businesses should also consider how they will respond if a vulnerability may already have been exploited. Depending on the circumstances, this may require specialist incident-response support, investigation and recovery measures.
The UK government’s Software Security Code of Practice provides further guidance on software security and maintenance responsibilities.
What This Means for Custom Software Development
Custom software can help businesses streamline operations, connect systems and solve specific operational challenges. But software must be designed and maintained with its full lifecycle in mind.
A well-managed development process considers more than the initial feature set. It also accounts for maintainability, dependencies, testing, deployment, documentation and the ability to respond when requirements or risks change.
This becomes particularly important when applications connect to customer information, internal business systems, payment services or other critical processes.
For businesses investing in custom software, useful questions to ask a development partner include:
How are software dependencies tracked and updated?
How are defects and potential security vulnerabilities assessed?
What testing takes place before updates are deployed?
Who is responsible for maintaining the application after launch?
How are urgent updates and unexpected technical issues handled?
The answers will depend on the project’s size, complexity and risk profile. The goal is to establish clear expectations before a problem occurs, rather than trying to create a maintenance process during an emergency.
How EPSza Approaches Software Engineering
At EPSza, software engineering is about developing digital solutions that support real business needs.
Applications, integrations and automation workflows should not be viewed as isolated deliverables. They form part of a wider business environment in which reliability, maintainability and the ability to adapt matter over time.
As AI changes how software can be developed and analysed, businesses should look beyond the speed at which new code can be produced. They should also consider how that software will be tested, integrated, maintained and improved.
The right approach depends on each organisation’s needs, existing systems and technical requirements. However, the underlying principle remains the same: technology should solve problems without creating unnecessary operational complexity.
For organisations reviewing their digital systems or planning new software projects, this is an opportunity to consider maintainability and responsible engineering from the outset.
Learn more about EPSza’s software engineering and digital solutions at epsza.ch.
Frequently Asked Questions
Can AI detect software vulnerabilities?
AI can assist researchers and developers in identifying potential software vulnerabilities by analysing code, investigating software behaviour and supporting testing. Its effectiveness depends on the tools, the system being assessed and the nature of the vulnerability. Findings need to be validated, and AI does not replace comprehensive security testing.
Does AI make software more secure?
AI can support security research, code analysis and testing, but it does not automatically make software secure. Security depends on how systems are designed, developed, configured, tested, maintained and monitored.
How often should businesses update their software?
Businesses should monitor relevant security advisories and apply updates according to their urgency and risk. Critical vulnerabilities may require immediate or accelerated remediation, while routine updates can often follow a planned maintenance process. Unsupported software requires particular attention because it may no longer receive security fixes.
What is software vulnerability management?
Software vulnerability management is the ongoing process of identifying, assessing, prioritising, addressing and tracking weaknesses in software and related systems. It includes monitoring relevant disclosures, evaluating risk, applying fixes and verifying that remediation has been completed.
Should small businesses be concerned about AI-related security risks?
Yes, small businesses should take software security seriously, regardless of their size. They may depend on third-party platforms, website plugins, cloud services and external software providers. Maintaining updates, understanding dependencies and knowing who to contact when a security issue arises are practical steps that businesses of any size can take.
What should a business do if a vulnerability affects its website?
First, identify the affected technology and version, then consult the official vendor or project advisory to confirm whether the website is affected. Follow the recommended remediation or mitigation steps, prioritising urgent issues. If the vulnerability may have been exploited, seek appropriate security assistance rather than assuming that installing an update alone resolves the incident.
Conclusion: Finding Vulnerabilities Is Not the Same as Fixing Them
AI is creating new opportunities to identify weaknesses in software, including vulnerabilities in widely used components. Recent research demonstrates why this capability matters, but it also highlights the work required to turn a discovery into effective protection.
For businesses, the priority is to know which systems they depend on, understand their exposure, apply appropriate updates and establish clear responsibility for ongoing maintenance.
AI may help find the flaw. Good engineering processes help turn that discovery into a safer, more resilient system.
As software becomes increasingly connected and AI-assisted development advances, businesses should make maintainability and responsible software engineering part of their technology strategy — not an afterthought.