The UK Information Commissioner’s Office has warned that AI is enabling faster, more advanced and harder-to-detect cyberattacks, urging organisations to strengthen their defences against emerging threats.
In a blog post, the regulator highlighted risks such as AI-generated phishing emails, deepfake social engineering, automated vulnerability scanning, AI-powered malware, credential attacks, data poisoning and indirect prompt injection. The ICO said cybersecurity must be treated as a shared responsibility, with organisations expected to take proactive steps to protect the personal data they hold.
The ICO said strong foundational security measures remain essential, but should be reinforced with layered defences to counter AI-powered threats. It pointed to practical steps such as patching systems, restricting access through multi-factor authentication, applying least-privilege principles and managing supplier risks.
The recommendations also include monitoring systems for unusual activity, carrying out vulnerability scanning and penetration testing, and maintaining regularly tested incident response plans. The ICO said AI can also support cyber defence, but should operate within a clear framework of human oversight and accountability.
Organisations are further advised to minimise data collection, conduct regular data audits and train staff to recognise AI-powered social engineering attacks. The ICO said AI tools processing high-risk personal data should be supported by data protection impact assessments and appropriate safeguards.
Why does it matter?
The ICO’s warning links AI-powered cyber threats directly to data protection obligations. As attackers use AI to scale phishing, exploit vulnerabilities and impersonate trusted contacts, organisations are expected not only to improve technical security, but also to limit the personal data they hold, strengthen governance and prepare for faster-moving incidents.
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The company said the summit brings together representatives from governments, technology companies, consumer groups and academia to discuss collective responses to increasingly sophisticated scams. Google said its approach combines AI-driven protections across its products with wider cooperation involving industry and public authorities.
Google highlighted the use of AI-powered systems in services including Gmail, Chrome, Search, Ads and Phone by Google. The company said Gmail blocks more than 99.9% of spam, phishing and malware, while Search filters out hundreds of millions of spam-related pages daily. It also said its systems caught more than 99% of policy-violating ads before they reached users in 2025.
User-facing tools are also part of the company’s anti-scam strategy. Google pointed to Security Checkup, Passkeys, 2-Step Verification, Circle to Search and Google Lens as tools that can help users strengthen account protection and verify suspicious messages or content.
The company also highlighted public awareness and education initiatives, including Be Scam Ready, a game-based programme that uses simulated scam scenarios to help users recognise common tactics. Google said a previous Google.org commitment of $5 million is supporting anti-scam initiatives in Europe and the Middle East, including work by the Internet Society and Oxford Information Labs.
Google also referred to cooperation through the Global Signal Exchange, a threat-intelligence sharing platform for scams and fraud. As a founding partner, Google said it both contributes to and draws from the platform, which now stores more than 1.2 billion signals used to identify and disrupt criminal activity.
The company said it also works with law enforcement agencies, including the UK’s National Crime Agency, and participates in the Industry Accord Against Online Scams and Fraud. Google also pointed to legal actions against scam operations and botnets, including cases involving Lighthouse and BadBox.
Why does it matter?
Online scams are increasingly industrialised, cross-platform and supported by AI-enabled tactics, making them difficult to address through product-level security alone. Google’s approach shows how major technology companies are combining automated detection, user education, threat-intelligence sharing and law enforcement cooperation to respond to fraud. The wider policy issue is how much responsibility large platforms should bear for detecting and disrupting scams before they reach users.
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Poland’s Ministry of Digital Affairs has launched a campaign to encourage entrepreneurs and management teams to take a more active role in protecting their companies from cyber threats.
The campaign, titled ‘Build your company’s digital security click by click’, is aimed at businesses and senior decision-makers. The ministry says its main goal is to encourage firms to address cybersecurity at both organisational and operational levels.
The campaign stresses that cybersecurity is no longer solely the responsibility of IT departments but is a key part of responsible business management. The ministry points to growing risks such as phishing and ransomware as digital technology becomes central to company operations.
According to the ministry, effective cybersecurity depends on three pillars: knowledge, processes and people. The campaign encourages firms to analyse risks, develop incident response procedures, train employees regularly and use official guidance available through cyber.gov.pl.
A separate focus is placed on medium-sized and large companies subject to requirements under Poland’s national cybersecurity system. The ministry says firms in key sectors should understand obligations related to risk management, incident reporting and the protection of information systems.
The campaign also calls on company leaders to integrate cybersecurity into business strategy, including through security policies, investment in skills and the development of a culture of responsibility across organisations.
Why does it matter?
The campaign reflects a broader shift in cybersecurity policy from technical protection towards organisational responsibility. By targeting business leaders, Poland is emphasising that cyber resilience depends not only on tools, but also on governance, staff training, incident response and compliance with national cybersecurity obligations.
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The family of a victim killed in the April 2025 Florida State University shooting has filed a federal lawsuit in Florida against OpenAI, alleging that ChatGPT enabled the attack. The lawsuit was filed on Sunday by Vandana Joshi, the widow of Tiru Chabba, who was killed alongside university dining director Robert Morales.
The complaint states that the accused shooter, Phoenix Ikner, engaged in extensive conversations with ChatGPT months before leading up to the incident. According to the suit, those exchanges included images and discussions about firearms he had acquired, ideological material, ideological far-right beliefs, and possible outcomes of violent attacks.
The chatbot is further accused of providing contextual information about campus activity and commenting on factors that could increase public attention in violent incidents. This is indicated by the fact that at one point, ChatGPT said, ‘if children are involved, even 2-3 victims can draw more attention’. The filing also claims Ikner asked about legal consequences and planning considerations shortly before the attack.
The lawsuit contends that OpenAI failed to identify escalating risk indicators within the conversations and did not adequately prevent harmful guidance. It argues the system ‘failed to connect the dots’ despite Ikner’s repeated questions about suicide, terrorism and mass shootings.
OpenAI has rejected responsibility for the attack, claiming its platform is not to blame. Company spokesperson Drew Pusateri said ChatGPT generated factual responses that could be found broadly across publicly available information and did not encourage or promote illegal activity. He also stated that OpenAI continues to strengthen safeguards to identify harmful intent, reduce misuse and respond appropriately when safety risks arise.
Joshi’s complaint argues that the system reinforced the shooter’s beliefs and failed to interrupt conversations involving violent ideation. The filing alleges the ChatGPT inflamed, validated and endorsed delusional thinking and contributed to planning discussions while ‘convincing him that violent acts can be required to bring about change’.
The lawsuit forms part of a broader wave of litigation involving AI systems and alleged harm. OpenAI is already facing separate lawsuits linked to incidents involving violence and suicide, raising wider questions about safeguards and user protection
Florida’s Attorney General James Uthmeier announced a criminal investigation into OpenAI and ChatGPT following a review of chat logs connected to the case. Uthmeier said in a statement that ‘If ChatGPT is a person it would be facing charges for murder’.
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The German Federal Office for Information Security published guidance developed by the G7 Cybersecurity Working Group outlining elements for a Software Bill of Materials for AI. The document aims to support both public and private sector stakeholders in improving transparency in AI systems.
The guidance builds on a shared G7 vision introduced in 2025 and focuses on strengthening cybersecurity throughout the AI supply chain. It sets out baseline components that should be included in an AI SBOM to better track and understand system dependencies.
The document outlines seven baseline building blocks that should form part of an AI Software Bill of Materials (SBOM for AI), designed to improve visibility into how AI systems are built and how their components interact across the supply chain.
At the foundation is a Metadata cluster, which records information about the SBOM itself, including who created it, which tools and formats were used, when it was generated, and how software dependencies relate to one another.
The framework then moves to System Level Properties, covering the AI system as a whole. This includes the system’s components, producers, data flows, intended application areas, and the processing of information between internal and external services.
A dedicated Models cluster focuses on the AI models embedded within the system, documenting details such as model identifiers, versions, architectures, training methods, limitations, licenses, and dependencies. The goal is to make the origins and characteristics of models easier to trace and assess.
The document also introduces a Dataset Properties cluster to improve transparency into the data used throughout the AI lifecycle. It captures dataset provenance, content, statistical properties, sensitivity levels, licensing, and the tools used to create or modify datasets.
Beyond software and data, the framework includes an Infrastructure cluster that maps the software and hardware dependencies required to run AI systems, including links to hardware bills of materials where relevant.
Cybersecurity considerations are grouped under Security Properties, which document implemented safeguards such as encryption, access controls, adversarial robustness measures, compliance frameworks, and vulnerability references.
Finally, the framework proposes a Key Performance Indicators cluster that includes metrics related to both security and operational performance, including robustness, uptime, latency, and incident response indicators.
According to the paper, the objective is to provide practical direction that organisations can adopt to enhance visibility and manage risks linked to AI technologies. The framework is intended to support more secure development and deployment practices.
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Taiwan’s Administration for Cyber Security has warned that emerging AI models are lowering the cost and increasing the scale of cyberattacks, urging companies and government agencies to strengthen basic cyber resilience.
The agency said advanced AI models, including Anthropic’s Claude Mythos and OpenAI’s GPT-5.5, are showing stronger capabilities in vulnerability discovery and offensive cyber techniques. It said such developments could help attackers identify weaknesses faster and turn vulnerabilities into practical attack tools more efficiently.
According to the agency, recent international cybersecurity assessments suggest Claude Mythos Preview has identified thousands of high-severity vulnerabilities across major operating systems and web browsers. At the same time, GPT-5.5 could increase the efficiency and scale of existing attack methods.
Taiwan outlined three responses to the emerging threat. The administration said it would monitor defensive tools and international experience related to AI-enabled cyber operations, convene government, industry and academic decision-makers to discuss national-level response strategies, and strengthen support for small and medium-sized enterprises through TWCERT/CC.
The agency also urged organisations to return to cybersecurity basics, including vulnerability management, offline and recoverable backups, business continuity planning, least-privilege access, multi-factor authentication, passkeys based on FIDO2 standards, and the disabling of unnecessary external services and test interfaces.
Taiwan’s cyber agency said AI is changing the speed and cost of attacks, but not the core principles of cybersecurity. It said organisations should shift from focusing only on preventing breaches towards improving resilience, recovery time and damage control.
Why does it matter?
The warning shows how governments are beginning to treat AI-enabled vulnerability discovery and exploitation as a practical cybersecurity risk, not a future scenario. As AI reduces the time and expertise needed to identify and exploit weaknesses, organisations may need to place greater emphasis on resilience, rapid recovery, access controls and continuous vulnerability management, especially where smaller businesses and public bodies lack advanced cyber capabilities.
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The Office of National Security of South Korea held a cybersecurity meeting to review how government agencies are responding to AI-driven cyber threats. The session focused on the growing risks posed by the misuse of advanced AI technologies.
Officials from multiple ministries attended, including science, defence and intelligence bodies, to coordinate responses. The government warned that AI-enabled hacking capabilities are becoming increasingly realistic as global technology companies release more advanced models.
Authorities have instructed relevant agencies to strengthen cooperation with businesses and institutions and distributed guidance on responding to AI-based security risks. Discussions also covered practical measures to support rapid responses to cybersecurity vulnerabilities across public and private sectors.
The government plans to establish a joint technical response team to improve information sharing and enable immediate action. Officials emphasised that while AI increases cyber risks, it also offers opportunities to strengthen security capabilities in South Korea.
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The Council of the European Union has extended restrictive measures against individuals and entities involved in cyber-attacks threatening the EU and its member states until 18 May 2027. The legal framework behind the sanctions regime had already been extended until 18 May 2028.
The framework allows the EU to impose targeted sanctions on persons or entities involved in significant cyber-attacks that constitute an external threat to the Union or its member states. Measures can also be imposed in response to cyber-attacks against third countries or international organisations, where they support Common Foreign and Security Policy objectives.
Current listings under the regime apply to 19 individuals and seven entities. Sanctioned actors face asset freezes, while the EU citizens and companies are prohibited from making funds or economic resources available to them. Listed individuals are also subject to travel bans preventing them from entering or transiting through the EU territory.
The Council said the individual listings will continue to be reviewed every 12 months. It also said the measures are intended to deter malicious cyber activity and uphold the international rules-based order by ensuring accountability for those responsible.
The sanctions mechanism forms part of the EU’s broader cyber diplomacy toolbox, established in 2017 to strengthen coordinated diplomatic responses to malicious cyber activity. The Council said the EU and its member states would continue working with international partners to promote an open, free, stable and secure cyberspace.
Why does it matter?
The decision shows how cybersecurity has become part of the EU’s foreign policy and sanctions toolkit, not only a matter of technical defence. By extending cyber sanctions listings, the EU is reinforcing its use of diplomatic and economic measures to deter malicious cyber activity, attribute responsibility and signal that significant cyber-attacks can carry geopolitical consequences.
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Australia’s New South Wales state has clarified that creating, sharing, or threatening to share sexually explicit images, videos, or audio of a person without consent is a criminal offence, including where the material has been digitally altered or generated using AI.
The state government strengthened protections in 2025 by amending the Crimes Act 1900 to cover digitally generated deepfakes. The law already applied to sexually explicit image material, but now also covers content created or altered by AI to place someone in a sexual situation they were never in.
The reforms mean that non-consensual sexual images or audio are covered regardless of how they were made. Threatening to create or share such material is also a criminal offence in New South Wales, with penalties of up to three years in prison, a fine of up to A$11,000, or both.
Courts can also order offenders to remove or delete the material. Failure to comply with such an order can result in up to 2 years’ imprisonment, a fine of up to A$5,500, or both.
The law operates alongside existing child abuse material offences. Under criminal law, any material depicting a person under 18 in a sexually explicit way can be treated as child abuse material, including AI-generated content.
Criminal proceedings against people under 16 can begin only with the approval of the Director of Public Prosecutions, which is intended to ensure that only the most serious matters involving young people enter the criminal justice system.
Limited exemptions apply for proper purposes, including genuine medical, scientific, law enforcement, or legal proceedings-related purposes. A review of the law will take place 12 months after it comes into effect to assess how it is working and whether changes are needed.
The changes are intended to address the misuse of AI and deepfake technology to harass, shame, or exploit people through fake digital content. New South Wales says its criminal law works alongside national online safety frameworks, including the work of Australia’s eSafety Commissioner, as It seeks to keep privacy and consent protections aligned with emerging technologies.
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With the rapid expansion of AI technologies, agentic AI is rapidly moving from experimentation to deployment on a scale larger than ever before. As a result, these systems have been given far greater autonomy to perform tasks with limited human input, much to the delight of enterprise magnates.
Companies such as Microsoft, Google, Anthropic, and OpenAI are increasingly developing agentic AI systems capable of automating vulnerability detection, incident response, code analysis, and other security tasks traditionally handled by human teams.
The appeal of using agentic AI as a first line of defence is palpable, as cybersecurity teams face mounting pressure from the growing volume of attacks. According to the Microsoft Digital Defense Report 2025, the company now detects more than 600 million cyberattacks daily, ranging from ransomware and phishing campaigns to identity attacks. Additionally, the International Monetary Fund has also warned that cyber incidents have more than doubled since the COVID-19 pandemic, potentially triggering institutional failures and incurring enormous financial losses.
To add insult to injury, ransomware groups such as Conti, LockBit, and Salt Typhoon have shown increased activity from 2024 through early 2026, targeting critical infrastructure and global communications, as if aware of the upcoming cybersecurity fortifications and using a limited window of time to incur as much damage as possible.
In such circumstances, fully embracing agentic AI may seem like an ideal answer to the cybersecurity challenges looming on the horizon. Systems capable of autonomously detecting threats, analysing vulnerabilities, and accelerating response times could significantly strengthen cyber resilience.
Yet the same autonomy that makes these systems attractive to defenders could also be exploited by malicious actors. If agentic AI becomes a defining feature of cyber defence, policymakers and companies may soon face a more difficult question: how can they maximise its benefits without creating an entirely new layer of cyber risk?
Why cybersecurity is turning to agentic AI
The growing interest in agentic AI is not simply driven by the rise in cyber threats. It is also a response to the operational limitations of modern security teams, which are often overwhelmed by repetitive tasks that consume time and resources.
Security analysts routinely handle phishing alerts, identity verification requests, vulnerability assessments, patch management, and incident prioritisation — processes that can become difficult to manage at scale. Many of these tasks require speed rather than strategic decision-making, creating a natural opening for AI systems to operate with greater autonomy.
Microsoft has aggressively moved into this space. In March 2025, the company introduced Security Copilot agents designed to autonomously handle phishing triage, data security investigations, and identity management. Rather than replacing human analysts, Microsoft positioned the tools to reduce repetitive workloads and enable security teams to focus on more complex threats.
Google has approached the issue through vulnerability research. Through Project Naptime, the company demonstrated how AI systems could replicate parts of the workflow traditionally handled by human security researchers by identifying vulnerabilities, testing hypotheses, and reproducing findings.
Anthropic introduced another layer of complexity through Claude Mythos, a model built for high-risk cybersecurity tasks. While the company presented the model as a controlled release for defensive purposes, the announcement also highlighted how advanced cyber capabilities are becoming increasingly embedded in frontier AI systems.
Meanwhile, OpenAI has expanded partnerships with cybersecurity organisations and broadened access to specialised tools for defenders, signalling that major AI firms increasingly view cybersecurity as one of the most commercially viable applications for autonomous systems.
Together, these developments show that agentic AI is gradually becoming embedded in the cybersecurity infrastructure. For many companies, the question is no longer whether autonomous systems can support cyber defence, but how much responsibility they should be given.
When agentic AI tools become offensive weapons
The same capabilities that make agentic AI valuable to defenders also make it attractive to malicious actors. Systems designed to identify vulnerabilities, analyse code, automate workflows, and accelerate decision-making can be repurposed for offensive cyber operations.
Anthropic offered one of the clearest examples of that risk when it disclosed that malicious actors had used Claude in cyber campaigns. The company said attackers were not simply using the model for basic assistance, but were integrating it into broader operational workflows. The incident showed how agentic AI can move cyber misuse beyond advice and into execution.
The risk extends beyond large-scale cyber operations. Agentic AI systems could make phishing campaigns more scalable, automate reconnaissance, accelerate vulnerability discovery, and reduce the technical expertise needed to launch certain attacks. Tasks that once required specialist teams could become easier to coordinate through autonomous systems.
Security researchers have repeatedly warned that generative AI is already making social engineering more convincing through realistic phishing emails, cloned voices, and synthetic identities. More autonomous systems could further push those risks by combining content generation with independent action.
The concern is not that agentic AI will replace human hackers. Cybercrime could become faster, cheaper, and more scalable, mirroring the same efficiencies that organisations hope to achieve through AI-powered defence.
The agentic AI governance gap
The governance challenge surrounding agentic AI is no longer theoretical. As autonomous systems gain access to internal networks, cloud infrastructure, code repositories, and sensitive datasets, companies and regulators are being forced to confront risks that existing cybersecurity frameworks were not designed to manage.
Policymakers are starting to respond. In February 2026, the US National Institute of Standards and Technology (NIST) launched its AI Agent Standards Initiative, focused on identity verification and authentication frameworks for AI agents operating across digital environments. The aim is simple but important: organisations need to know which agents can be trusted, what they are allowed to do, and how their actions can be traced.
Governments are also becoming more cautious about deployment risks. In May 2026, the Cybersecurity and Infrastructure Security Agency (CISA) joined cybersecurity agencies from Australia, Canada, New Zealand, and the United Kingdom in issuing guidance on the secure adoption of agentic AI services. The warning was clear: autonomous systems become more dangerous when they are connected to sensitive infrastructure, external tools, and internal permissions.
The private sector is adjusting as well. Companies are increasingly discussing safeguards such as restricted permissions, audit logs, human approval checkpoints, and sandboxed environments to limit the degree of autonomy granted to AI agents.
The questions facing businesses are becoming practical. Should an AI agent be allowed to patch vulnerabilities without approval? Can it disable accounts, quarantine systems, or modify infrastructure independently? Who is held accountable when an autonomous system makes the wrong decision?
Agentic AI may become one of cybersecurity’s most effective defensive tools. Its success, however, will depend on whether governance frameworks evolve quickly enough to keep pace with the technology itself.
How companies are building guardrails around agentic AI
As concerns around autonomous cyber systems grow, companies are increasingly experimenting with safeguards designed to prevent agentic AI from becoming an uncontrolled risk. Rather than granting unrestricted access, many organisations are limiting what AI agents can see, what systems they can interact with, and what actions they can execute without human approval.
Anthropic has restricted access to Claude Mythos over concerns about offensive misuse, while OpenAI has recently expanded its Trusted Access for Cyber programme to provide vetted defenders with broader access to advanced cyber tools. Both approaches reflect a growing consensus that powerful cyber capabilities may require tiered access rather than unrestricted deployment.
The broader industry is moving in a similar direction. CrowdStrike has increasingly integrated AI-driven automation into threat intelligence and incident response workflows while maintaining human oversight for critical decisions. Palo Alto Networks has also expanded its AI-powered security automation tools designed to reduce response times without fully removing human analysts from the decision-making process.
Cloud providers are also becoming more cautious about autonomous access. Amazon Web Services, Google Cloud, and Microsoft Azure have increasingly emphasised zero-trust security models, role-based permissions, and segmented access controls as enterprises deploy more automated tools across sensitive infrastructure.
Meanwhile, sectors such as finance, healthcare, and critical infrastructure remain particularly cautious about fully autonomous deployment due to the potential consequences of false positives, accidental shutdowns, or disruptions to essential services.
As a result, security teams are increasingly discussing safeguards such as audit logs, sandboxed environments, role-based permissions, staged deployments, and human approval checkpoints to balance speed with accountability. For now, many companies seem ready to embrace agentic AI, but without keeping one hand on the emergency brake.
The future of cybersecurity may be agentic
Agentic AI is unlikely to remain a niche experiment for long. The scale of modern cyber threats, combined with the mounting pressure on security teams, means organisations will continue to look for faster and more scalable defensive tools.
That shift could significantly improve cybersecurity resilience. Autonomous systems may help organisations detect threats earlier, reduce response times, address workforce shortages, and manage the growing volume of attacks that human teams increasingly struggle to handle alone.
At the same time, the technology’s long-term success will depend as much on restraint as on innovation. Without clear governance frameworks, operational safeguards, and human oversight, the same tools designed to strengthen cyber defence could introduce entirely new vulnerabilities.
The future of cybersecurity may increasingly belong to agentic AI. Whether that future becomes safer or more volatile may depend on how responsibly governments, companies, and security teams manage the transition.
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