How Ai Is Helping Hackers Get Access to Systems Quicker than Ever Before
Hackers are carrying out attacks faster than ever, with the average time between initial access and lateral movement now just 48 minutes, according to ReliaQuest research. Attackers are taking advantage of the adoption of AI by security teams and hackers, which has changed the cybercrime landscape. The report found that hackers are relying less on encryptions, with only 20% of all breaches involving data encryption.
This rapid evolution in attack techniques underscores the need for businesses to adopt a proactive and multi-layered approach to cybersecurity, incorporating AI-powered threat detection and response tools to stay ahead of emerging threats.
As AI-generated attacks become increasingly sophisticated, will we see a shift towards more "human-in-the-loop" security models that combine automated threat detection with human expertise to prevent catastrophic breaches?
Artificial Intelligence (AI) is increasingly used by cyberattackers, with 78% of IT executives fearing these threats, up 5% from 2024. However, businesses are not unprepared, as almost two-thirds of respondents said they are "adequately prepared" to defend against AI-powered threats. Despite this, a shortage of personnel and talent in the field is hindering efforts to keep up with the evolving threat landscape.
The growing sophistication of AI-powered cyberattacks highlights the urgent need for businesses to invest in AI-driven cybersecurity solutions to stay ahead of threats.
How will regulatory bodies address the lack of standardization in AI-powered cybersecurity tools, potentially creating a Wild West scenario for businesses to navigate?
Layer 7 Web DDoS attacks have surged by 550% in 2024, driven by the increasing accessibility of AI tools that enable even novice hackers to launch complex campaigns. Financial institutions and transportation services reported an almost 400% increase in DDoS attack volume, with the EMEA region bearing the brunt of these incidents. The evolving threat landscape necessitates more dynamic defense strategies as organizations struggle to differentiate between legitimate and malicious traffic.
This alarming trend highlights the urgent need for enhanced cybersecurity measures, particularly as AI continues to transform the tactics employed by cybercriminals.
What innovative approaches can organizations adopt to effectively counter the growing sophistication of DDoS attacks in the age of AI?
The modern-day cyber threat landscape has become increasingly crowded, with Advanced Persistent Threats (APTs) becoming a major concern for cybersecurity teams worldwide. Group-IB's recent research points to 2024 as a 'year of cybercriminal escalation', with a 10% rise in ransomware compared to the previous year, and a 22% rise in phishing attacks. The "Game-changing" role of AI is being used by both security teams and cybercriminals, but its maturity level is still not there yet.
This move signifies a growing trend in the beauty industry where founder-led companies are reclaiming control from outside investors, potentially setting a precedent for similar brands.
How will the dynamics of founder ownership impact the strategic direction and innovation within the beauty sector in the coming years?
A recent DeskTime study found that 72% of US workplaces adopted ChatGPT in 2024, with time spent using the tool increasing by 42.6%. Despite this growth, individual adoption rates remained lower than global averages, suggesting a slower pace of adoption among some companies. The study also revealed that AI adoption fluctuated throughout the year, with usage dropping in January but rising in October.
The slow growth of ChatGPT adoption in US workplaces may be attributed to the increasing availability and accessibility of other generative AI tools, which could potentially offer similar benefits or ease-of-use.
What role will data security concerns play in shaping the future of AI adoption in US workplaces, particularly for companies that have already implemented restrictions on ChatGPT usage?
One week in tech has seen another slew of announcements, rumors, reviews, and debate. The pace of technological progress is accelerating rapidly, with AI advancements being a major driver of innovation. As the field continues to evolve, we're seeing more natural and knowledgeable chatbots like ChatGPT, as well as significant updates to popular software like Photoshop.
The growing reliance on AI technology raises important questions about accountability and ethics in the development and deployment of these systems.
How will future breakthroughs in AI impact our personal data, online security, and overall digital literacy?
A recent survey reveals that 93% of CIOs plan to implement AI agents within two years, emphasizing the need to eliminate data silos for effective integration. Despite the widespread use of numerous applications, only 29% of enterprise apps currently share information, prompting companies to allocate significant budgets toward data infrastructure. Utilizing optimized platforms like Salesforce Agentforce can dramatically reduce the development time for agentic AI, improving accuracy and efficiency in automating complex tasks.
This shift toward agentic AI highlights a pivotal moment for businesses, as those that embrace integrated platforms may find themselves at a substantial competitive advantage in an increasingly digital landscape.
What strategies will companies adopt to overcome the challenges of integrating complex AI systems while ensuring data security and trustworthiness?
SurgeGraph has introduced its AI Detector tool to differentiate between human-written and AI-generated content, providing a clear breakdown of results at no cost. The AI Detector leverages advanced technologies like NLP, deep learning, neural networks, and large language models to assess linguistic patterns with reported accuracy rates of 95%. This innovation has significant implications for the content creation industry, where authenticity and quality are increasingly crucial.
The proliferation of AI-generated content raises fundamental questions about authorship, ownership, and accountability in digital media.
As AI-powered writing tools become more sophisticated, how will regulatory bodies adapt to ensure that truthful labeling of AI-created content is maintained?
The average scam cost the victim £595, report claims. Deepfakes are claiming thousands of victims, with a new report from Hiya detailing the rising risk and deepfake voice scams in the UK and abroad, noting how the rise of generative AI means deepfakes are more convincing than ever, and attackers can leverage them more frequently too. AI lowers the barriers for criminals to commit fraud, and makes scamming victims easier, faster, and more effective.
The alarming rate at which these scams are spreading highlights the urgent need for robust security measures and education campaigns to protect vulnerable individuals from falling prey to sophisticated social engineering tactics.
What role should regulatory bodies play in establishing guidelines and standards for the use of AI-powered technologies, particularly those that can be exploited for malicious purposes?
Google has introduced two AI-driven features for Android devices aimed at detecting and mitigating scam activity in text messages and phone calls. The scam detection for messages analyzes ongoing conversations for suspicious behavior in real-time, while the phone call feature issues alerts during potential scam calls, enhancing user protection. Both features prioritize user privacy and are designed to combat increasingly sophisticated scams that utilize AI technologies.
This proactive approach by Google reflects a broader industry trend towards leveraging artificial intelligence for consumer protection, raising questions about the future of cybersecurity in an era dominated by digital threats.
How effective will these AI-powered detection methods be in keeping pace with the evolving tactics of scammers?
Google has introduced AI-powered features designed to enhance scam detection for both text messages and phone calls on Android devices. The new capabilities aim to identify suspicious conversations in real-time, providing users with warnings about potential scams while maintaining their privacy. As cybercriminals increasingly utilize AI to target victims, Google's proactive measures represent a significant advancement in user protection against sophisticated scams.
This development highlights the importance of leveraging technology to combat evolving cyber threats, potentially setting a standard for other tech companies to follow in safeguarding their users.
How effective will these AI-driven tools be in addressing the ever-evolving tactics of scammers, and what additional measures might be necessary to further enhance user security?
Vishing attacks have skyrocketed, with CrowdStrike tracking at least six campaigns in which attackers pretended to be IT staffers to trick employees into sharing sensitive information. The security firm's 2025 Global Threat Report revealed a 442% increase in vishing attacks during the second half of 2024 compared to the first half. These attacks often use social engineering tactics, such as help desk social engineering and callback phishing, to gain remote access to computer systems.
As the number of vishing attacks continues to rise, it is essential for organizations to prioritize employee education and training on recognizing potential phishing attempts, as these attacks often rely on human psychology rather than technical vulnerabilities.
With the increasing sophistication of vishing tactics, what measures can individuals and organizations take to protect themselves from these types of attacks in the future, particularly as they become more prevalent in the digital landscape?
Finance teams are falling behind in their adoption of AI, with only 27% of decision-makers confident about its role in finance and 19% of finance functions having no planned implementation. The slow pace of AI adoption is a danger, defined by an ever-widening chasm between those using AI tools and those who are not, leading to increased productivity, prioritized work, and unrivalled data insights.
As the use of AI becomes more widespread in finance, it's essential for businesses to develop internal policies and guardrails to ensure that their technology is used responsibly and with customer trust in mind.
What specific strategies will finance teams adopt to overcome their existing barriers and rapidly close the gap between themselves and their AI-savvy competitors?
Stanford researchers have analyzed over 305 million texts and discovered that AI writing tools are being adopted more rapidly in less-educated areas compared to their more educated counterparts. The study indicates that while urban regions generally show higher overall adoption, areas with lower educational attainment demonstrate a surprising trend of greater usage of AI tools, suggesting these technologies may act as equalizers in communication. This shift challenges conventional views on technology diffusion, particularly in the context of consumer advocacy and professional communications.
The findings highlight a significant transformation in how technology is utilized across different demographic groups, potentially reshaping our understanding of educational equity in the digital age.
What long-term effects might increased reliance on AI writing tools have on communication standards and information credibility in society?
The UK's push to advance its position as a global leader in AI is placing increasing pressure on its energy sector, which has become a critical target for cyber threats. As the country seeks to integrate AI into every aspect of its life, it must also fortify its defenses against increasingly sophisticated cyberattacks that could disrupt its energy grid and national security. The cost of a data breach in the energy sector is staggering, with the average loss estimated at $5.29 million, and the consequences of a successful attack could be far more severe.
The UK's reliance on ageing infrastructure and legacy systems poses a significant challenge to cybersecurity efforts, as these outdated systems are often incompatible with modern security solutions.
As AI adoption in the energy sector accelerates, it is essential for policymakers and industry leaders to address the pressing question of how to balance security with operational reliability, particularly given the growing threat of ransomware attacks.
Caspia Technologies has made a significant claim about its CODAx AI-assisted security linter, which has identified 16 security bugs in the OpenRISC CPU core in under 60 seconds. The tool uses a combination of machine learning algorithms and security rules to analyze processor designs for vulnerabilities. The discovery highlights the importance of design security and product assurance in the semiconductor industry.
The rapid identification of security flaws by CODAx underscores the need for proactive measures to address vulnerabilities in complex systems, particularly in critical applications such as automotive and media devices.
What implications will this technology have on the development of future microprocessors, where the risk of catastrophic failures due to design flaws may be exponentially higher?
Google has informed Australian authorities it received more than 250 complaints globally over nearly a year that its artificial intelligence software was used to make deepfake terrorism material, highlighting the growing concern about AI-generated harm. The tech giant also reported dozens of user reports warning about its AI program Gemini being used to create child abuse material. The disclosures underscore the need for better guardrails around AI technology to prevent such misuse.
As the use of AI-generated content becomes increasingly prevalent, it is crucial for companies and regulators to develop effective safeguards that can detect and mitigate such harm before it spreads.
How will governments balance the need for innovation with the requirement to ensure that powerful technologies like AI are not used to facilitate hate speech or extremist ideologies?
Salesforce's research suggests that nearly all (96%) developers from a global survey are enthusiastic about AI’s positive impact on their careers, with many highlighting how AI agents could help them advance in their jobs. Developers are excited to use AI, citing improvements in efficiency, quality, and problem-solving as key benefits. The technology is being seen as essential as traditional software tools by four-fifths of UK and Ireland developers.
As AI agents become increasingly integral to programming workflows, it's clear that the industry needs to prioritize data management and governance to avoid perpetuating existing power imbalances.
Can we expect the growing adoption of agentic AI to lead to a reevaluation of traditional notions of intellectual property and ownership in the software development field?
A quarter of the latest cohort of Y Combinator startups rely almost entirely on AI-generated code for their products, with 95% of their codebases being generated by artificial intelligence. This trend is driven by new AI models that are better at coding, allowing developers to focus on high-level design and strategy rather than mundane coding tasks. As the use of AI-powered coding continues to grow, experts warn that startups will need to develop skills in reading and debugging AI-generated code to sustain their products.
The increasing reliance on AI-generated code raises concerns about the long-term sustainability of these products, as human developers may become less familiar with traditional coding practices.
How will the growing use of AI-powered coding impact the future of software development, particularly for startups that prioritize rapid iteration and deployment over traditional notions of "quality" in their codebases?
DeepSeek has broken into the mainstream consciousness after its chatbot app rose to the top of the Apple App Store charts (and Google Play, as well). DeepSeek's AI models, trained using compute-efficient techniques, have led Wall Street analysts — and technologists — to question whether the U.S. can maintain its lead in the AI race and whether the demand for AI chips will sustain. The company's ability to offer a general-purpose text- and image-analyzing system at a lower cost than comparable models has forced domestic competition to cut prices, making some models completely free.
This sudden shift in the AI landscape may have significant implications for the development of new applications and industries that rely on sophisticated chatbot technology.
How will the widespread adoption of DeepSeek's models impact the balance of power between established players like OpenAI and newer entrants from China?
Google Messages is rolling out an AI feature designed to assist Android users in identifying and managing text message scams effectively. This new scam detection tool evaluates SMS, MMS, and RCS messages in real time, issuing alerts for suspicious patterns while preserving user privacy by processing data on-device. Additionally, the update includes features like live location sharing and enhancements for Pixel devices, aiming to improve overall user safety and functionality.
The introduction of AI in scam detection reflects a significant shift in how tech companies are addressing evolving scam tactics, emphasizing the need for proactive and intelligent solutions in user safety.
As scammers become increasingly sophisticated, what additional measures can tech companies implement to further protect users from evolving threats?
Businesses are increasingly recognizing the importance of a solid data foundation as they seek to leverage artificial intelligence (AI) for competitive advantage. A well-structured data strategy allows organizations to effectively analyze and utilize their data, transforming it from a mere asset into a critical driver of decision-making and innovation. As companies navigate economic challenges, those with robust data practices will be better positioned to adapt and thrive in an AI-driven landscape.
This emphasis on data strategy reflects a broader shift in how organizations view data, moving from a passive resource to an active component of business strategy that fuels growth and resilience.
What specific steps can businesses take to cultivate a data-centric culture that supports effective AI implementation and harnesses the full potential of their data assets?
More than 600 Scottish students have been accused of misusing AI during part of their studies last year, with a rise of 121% on 2023 figures. Academics are concerned about the increasing reliance on generative artificial intelligence (AI) tools, such as Chat GPT, which can enable cognitive offloading and make it easier for students to cheat in assessments. The use of AI poses a real challenge around keeping the grading process "fair".
As universities invest more in AI detection software, they must also consider redesigning assessment methods that are less susceptible to AI-facilitated cheating.
Will the increasing use of AI in education lead to a culture where students view cheating as an acceptable shortcut, rather than a serious academic offense?
Google Cloud has launched its AI Protection security suite, designed to identify, assess, and protect AI assets from vulnerabilities across various platforms. This suite aims to enhance security for businesses as they navigate the complexities of AI adoption, providing a centralized view of AI-related risks and threat management capabilities. With features such as AI Inventory Discovery and Model Armor, Google Cloud is positioning itself as a leader in securing AI workloads against emerging threats.
This initiative highlights the increasing importance of robust security measures in the rapidly evolving landscape of AI technologies, where the stakes for businesses are continually rising.
How will the introduction of AI Protection tools influence the competitive landscape of cloud service providers in terms of security offerings?
U.S. chip stocks have stumbled this year, with investors shifting their focus to software companies in search of the next big thing in artificial intelligence. The emergence of lower-cost AI models from China's DeepSeek has dimmed demand for semiconductors, while several analysts see software's rise as a longer-term evolution in the AI space. As attention shifts away from semiconductor shares, some investors are betting on software companies to benefit from the growth of AI technology.
The rotation out of chip stocks and into software companies may be a sign that investors are recognizing the limitations of semiconductors in driving long-term growth in the AI space.
What role will governments play in regulating the development and deployment of AI, and how might this impact the competitive landscape for software companies?
DeepSeek R1 has shattered the monopoly on large language models, making AI accessible to all without financial barriers. The release of this open-source model is a direct challenge to the business model of companies that rely on selling expensive AI services and tools. By democratizing access to AI capabilities, DeepSeek's R1 model threatens the lucrative industry built around artificial intelligence.
This shift in the AI landscape could lead to a fundamental reevaluation of how industries are structured and funded, potentially disrupting the status quo and forcing companies to adapt to new economic models.
Will the widespread adoption of AI technologies like DeepSeek R1's R1 model lead to a post-scarcity economy where traditional notions of work and industry become obsolete?