Optimizing appsec in the technology sector
Speed and innovation are crucial for technology companies to stay competitive. As developers strive to deliver innovative products and meet market demands, security teams must adapt to accelerated development cycles.
This guide explores the following key areas to help you navigate the complexities of modern development:
- The challenges and requirements of current development cycles
- Essential security tools for maintaining speed and agility
- Strategies for fostering a successful DevSecOps culture
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Microsoft joins competitors in handing over AI models for advanced testingNews US and UK government agencies will evaluate the firm's frontier models, along with those from Google and xAI
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OpenAI turns to red teamers to prevent malicious ChatGPT use as company warns future models could pose 'high' security riskNews The ChatGPT maker wants to keep defenders ahead of attackers when it comes to AI security tools
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BT unveils sovereign platform to secure UK AI and cloud infrastructureNews The telecom giant’s new offering aims to insulate UK public and private sector data from geopolitical instability, supporting the government’s national AI strategy
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Gartner says 40% of enterprises will experience ‘shadow AI’ breaches by 2030 — educating staff is the key to avoiding disasterNews Staff need to be educated on the risks of shadow AI to prevent costly breaches
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Some of the most popular open weight AI models show ‘profound susceptibility’ to jailbreak techniquesNews Open weight AI models from Meta, OpenAI, Google, and Mistral all showed serious flaws
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Microsoft says 71% of workers have used unapproved AI tools at work – and it’s a trend that enterprises need to crack down onNews Shadow AI is by no means a new trend, but it’s creating significant risks for enterprises
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This DeepSeek-powered pen testing tool could be a Cobalt Strike successor – and hackers have downloaded it 10,000 times since JulyNews ‘Villager’, a tool developed by a China-based red team project known as Cyberspike, is being used to automate attacks under the guise of penetration testing.
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Researchers tested over 100 leading AI models on coding tasks — nearly half produced glaring security flawsNews AI models large and small were found to introduce cross-site scripting errors and seriously struggle with secure Java generation

