Neural networks and their effect on test and measurement [Q&A]
Historically test and measurement has been simply about collecting data and exporting it for later analysis. Now though neural networks make it possible to carry out the analysis in real time.
We spoke to Daniel Shaddock, CEO of Liquid Instruments, to find out more about what this means for businesses.
Free open-source Woodpecker aims to make red-teaming more accessible
Runtime AI defense platform Operant AI is launching Woodpecker, an open-source, automated red teaming engine, that isn't for the birds but aims to make advanced security testing accessible to organizations of all sizes.
As organizations increasingly adopt complex cloud-native applications and AI technologies, security vulnerabilities have become more sophisticated and challenging to detect. Woodpecker is designed to help organizations proactively detect and address security vulnerabilities across AI systems, Kubernetes environments, and APIs.
Enterprises shift to software-based pentesting
The latest State of Pentesting report from Pentera reveals that over 50 percent of enterprise CISOs now report using software-based pentesting to support their in-house testing practices.
Based on research conducted by Global Surveyz, the report notes that 50 percent of CISOs now identify software-based testing as a primary method for uncovering exploitable security gaps within their organizations.
Detectify improves app security testing with intelligent recommendations
Security teams know they need to test their main applications, but they often struggle to identify which other assets to cover. On average, organizations can miss testing nine out of 10 of their complex web apps.
Security testing platform Detectify is announcing the launch of its new Asset Classification and Scan Recommendations capabilities which enable organizations to easily identify and swiftly act on their complex web applications.
Google calls the AI fuzz to find vulnerabilities
Not familiar with 'fuzzing'? It's a software testing technique that involves feeding invalid, unexpected, or random data into a program to detect coding errors and security vulnerabilities.
Back in August 2023, Google introduced AI-Powered Fuzzing, using large language models (LLM) to improve fuzzing coverage to find more vulnerabilities automatically -- before malicious attackers could exploit them.
Uncovering GenAI's unsung heroes [Q&A]
There's no doubt that AI is seen as flavor of the month across many sectors at the moment. But how much of this is hype and how much genuine value?
We spoke to Martin Hawksey, collaboration engineer at Qodea, to discuss GenAI and the areas where GenAI is making a real difference, some of which you may not be aware of.
Only 16 percent of companies think their software testing is efficient
A new survey of 401 tech professionals from Leapwork shows that only 16 percent of businesses think their current testing practices are efficient.
Interestingly, AI could be making this worse, although 85 percent of total respondents have integrated AI apps into tech stacks in the past year, most (68 percent) have experienced issues with their performance, accuracy, and reliability.
Critical vulnerabilities rise but remediation times improve
A new report from security testing platform Synack shows a rise in critical-severity vulnerabilities in 2023 compared to 2022.
On a positive note though, despite mounting pressures on security teams, organizations have reduced their mean time to remediation for critical-severity vulnerabilities by 24 days and high-severity vulnerabilities by 18 days, down to 56 and 74 days, respectively.
More testing needed to ensure security of web applications
A new report from CyCognito looks at the challenges faced by cybersecurity professionals in protecting web applications, which have become prime targets for cyberattacks.
Organizations maintain dozens, often hundreds, of custom web apps, developed in-house and by third-party partners. What's more over 60 percent update web applications weekly or more often.
How AI is having an impact on software testing [Q&A]
Artificial intelligence is making its way into many areas of the tech industry, with the introduction of large language models making it much more accessible.
One of the areas where it's having a big impact is software testing, where it allows companies to provide better support to existing software teams and refocus their efforts on development.
Which comes first? The pentest or the bug bounty program? [Q&A]
Bug bounty and penetration testing programs are often grouped as interchangeable, but they perform distinct functions.
To determine whether both deserve a place within a cybersecurity strategy, it is important to understand their specific qualities and how they have matured over recent years. We spoke to Chris Campbell, lead solutions engineer at HackerOne, to learn more.
Mobile app developers turn to AI for testing
The use of AI tools for mobile app development and testing is growing, and developers and testers are keen to further expand the use of these tools, according to a new report.
The study from Kobiton finds 60 of respondents say they are currently using generative AI tools in their QA cycles to update scripts or code, 55 percent are using these tools to analyze test results, and 47 percent are using them to generate test scripts.
Software testers turn to AI to improve productivity
A new global study of over 1,600 software testers reveals that 78 percent have already adopted some form of AI to improve productivity.
The report from LambdaTest also shows companies are working to respond to the need for greater software reliability with 72 percent of organizations involving testers in 'sprint' planning sessions, signaling a substantial shift towards software quality being considered earlier in the software development lifecycle.
90 percent of testing professionals are concerned about AI bias
A new survey of over 3,000 digital testing professionals reveals concerns about bias, copyright issues and privacy.
The study from testing specialist Applause shows that 90 percent of respondents expressed concern, with 25 percent 'very concerned' that bias may affect the accuracy, tone or relevance of the content produced by AI.
New tool uses AI to help ensure AI-generated content is fit for humans
Experts reckon that over 90 percent of internet content could be AI generated by the end of the decade. But we all know that AI isn't perfect; it can introduce biases and errors.
Checking material to ensure it's suitable for the target audience is therefore essential. User experience research platform WEVO is launching a new research tool, WEVO 3.0, to ensure that AI-generated products and experiences are well received by their target human audience.
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