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Google outlines AI-driven measures against online scams and fraud

Google has outlined new and existing measures to tackle online scams and fraud ahead of the second EMEA Anti-Scams and Fraud Summit, hosted by the Google Safety Engineering Centre in Zurich.

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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Microsoft MDASH agentic AI security system tops vulnerability discovery benchmarks

Microsoft has described a multi-model agentic AI security system, codenamed MDASH, designed to support vulnerability discovery and cybersecurity research across complex codebases.

According to Microsoft, the system helped researchers identify 16 vulnerabilities across Windows networking and authentication components, including issues in the Windows TCP/IP stack, IKEv2 services, DNS handling and Netlogon processes. Several of the vulnerabilities were reachable over networks without authentication, the company said.

MDASH was developed by Microsoft’s Autonomous Code Security team and combines more than 100 specialised AI agents with an ensemble of frontier and distilled AI models. The system is structured as a multi-stage pipeline covering code preparation, scanning, validation, deduplication and proof generation.

The publication says the system identified remote code execution flaws, denial-of-service issues, information disclosure vulnerabilities and security feature bypasses. Microsoft also described the use of specialised auditor, debater and prover agents designed to analyse vulnerabilities across multiple files and code paths.

Microsoft said MDASH uses plugins and domain-specific knowledge to support validation and proof-of-concept generation, allowing security experts to add context that foundation models may not capture on their own.

The company also reported benchmark results from internal and public tests. It said MDASH identified all 21 deliberately inserted vulnerabilities in a private test driver with zero false positives in that run, achieved 96% recall against five years of confirmed Microsoft Security Response Center cases in clfs.sys and 100% in tcpip.sys, and scored 88.45% on the public CyberGym benchmark.

Microsoft said the system is already being used by its security engineering teams and is being tested with a small group of customers through a limited private preview.

Why does it matter?

MDASH shows how agentic AI is moving into high-value cybersecurity tasks such as vulnerability discovery, validation and proof generation. If systems like this can reliably reduce false positives and help researchers find exploitable flaws earlier, they could improve defensive security at scale. The same development also raises governance questions around access, oversight and dual-use risk, since tools capable of finding and proving vulnerabilities may be valuable to both defenders and attackers.

The company also discussed broader implications for AI-assisted cybersecurity operations, including the use of agentic AI systems for vulnerability discovery, validation, and remediation workflows. Microsoft stated that the system is currently being tested internally and through a limited private preview involving selected customers.

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Poland launches campaign to boost business cybersecurity awareness

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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OpenAI sued over alleged ChatGPT role in Florida State University shooting

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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G7 working group advances cybersecurity approach for AI systems

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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IPC New South Wales’ Generative AI guidance targets privacy risks in Australia

The Information and Privacy Commission New South Wales, has issued guidance for public sector agencies in Australia on managing privacy risks associated with the use of generative AI tools.

The guide states that the Privacy and Personal Information Protection Act 1998 applies to the handling of personal information through generative AI tools. It is intended to help agencies understand and comply with privacy obligations when adopting tools such as ChatGPT, Gemini, Claude, Perplexity, and Copilot.

Generative AI can support workplace tasks such as drafting, editing, document analysis, research, translation, transcription, and process automation. However, the IPC warns that these tools can create privacy risks when prompts, uploaded files, or outputs include personal or health information.

The guide highlights risks including unexpected use or disclosure of personal information, cross-border data transfers, unauthorised disclosure, data breaches, extended retention of personal information, generation of new personal information, inaccurate or discriminatory outputs, and loss of transparency or data subject control.

Some generative AI providers may collect customer data, including prompts, uploaded files, and outputs, to train or improve their models, according to the IPC. Agencies should assess whether personal or health information uploaded to a generative AI service may be processed offshore or used for purposes beyond the original collection purpose.

Recommended measures include privacy impact assessments, updates to privacy management plans and data breach response policies, clear public notices, consent where required, acceptable use policies for staff, training, pre-deployment testing, third-party vendor assessments, and data residency in Australia where possible.

Human review is also presented as an important safeguard, especially where generative AI outputs inform decisions affecting individuals’ access to services, opportunities, or benefits. The IPC urges agencies to avoid a ‘set and forget’ approach and continuously monitor generative AI use, governance, culture, and emerging privacy risks.

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World Economic Forum highlights AI role in infrastructure security

The World Economic Forum has highlighted AI-driven network defence as a possible tool for protecting critical infrastructure, as cyberattacks on hospitals, power grids, schools and transport systems become faster and harder to detect.

Lumu Technologies founder and CEO Ricardo Villadiego says nation state actors and ransomware groups are increasingly targeting critical infrastructure such as hospitals, power grids, schools, utilities and transport networks. It argues that local authorities and community-level service providers often face these threats with limited resources and small teams.

The author points to the convergence of operational technology and internet-connected IT systems as a major source of vulnerability. As sensors, smart meters and programmable logic controllers become more connected, the attack surface expands across both digital and physical infrastructure.

The article also argues that AI is increasing the speed and stealth of cyberattacks, making it harder for human-led security teams to detect and respond to threats quickly. In response, it presents AI-driven network monitoring as one way to identify anomalies across connected systems and block malicious activity before it reaches physical control systems.

A key concern is the reliance on endpoint-only security. The article notes that many critical infrastructure environments contain unmanaged or outdated devices, such as industrial systems, medical equipment and physical control assets, where conventional security agents may not be practical.

Why does it matter?

Critical infrastructure cybersecurity is increasingly about the connection between digital systems and physical services. As hospitals, utilities, schools and transport networks become more connected, cyberattacks can cause real-world disruption. AI-driven defence tools may help overstretched teams monitor complex environments more effectively, but their use also raises questions about reliability, oversight and dependence on automated security decisions in essential services.

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India accelerates AI-driven financial inclusion through digital public infrastructure

The role of AI in financial inclusion has been expanded in India by combining AI systems with large-scale digital public infrastructure (DPI). The framework connects identity verification, digital payments, consent-based data sharing and AI-powered credit analysis to improve access to formal finance for underserved communities.

A system that is built around the JAM Trinity – Jan Dhan bank accounts, Aadhaar digital identity and mobile connectivity – alongside platforms such as UPI and Direct Benefit Transfer. By March 2026, Jan Dhan accounts had reached 58.16 crore, while UPI processed more than 2,264 crore transactions worth ₹29.53 lakh crore in a single month.

The infrastructure is generating large volumes of financial and behavioural data that AI systems can use for risk assessment, fraud detection and personalised financial services.

AI-driven lending models are becoming increasingly important for MSMEs, informal workers and first-time borrowers who often lack conventional credit histories. Through the Unified Lending Interface, lenders can analyse alternative datasets including GST records, utility payments, land records and digital transaction histories instead of relying only on traditional credit scores.

Local authorities estimate that AI-enabled credit systems could help address a credit gap worth between $130 billion and $170 billion.

India is also strengthening multilingual and regulatory support for AI finance systems. The Reserve Bank of India (RBI) and Digital India BHASHINI Division are developing ‘Banking BHASHINI’, a specialised language AI model designed to support banking terminology and financial services across all 22 scheduled Indian languages. The initiative aims to reduce literacy and language barriers while expanding nationwide access to digital banking.

Additional initiatives include the RBI Regulatory Sandbox for testing fintech innovations, MuleHunter.AI for detecting suspicious mule accounts linked to cybercrime, and the proposed Digital ShramSetu mission focused on informal workers and AI-enabled economic inclusion.

Authorities argue that combining AI with interoperable digital infrastructure could help India build a more resilient and scalable financial ecosystem as part of its broader Viksit Bharat 2047 strategy.

Why does it matter?

The expansion of AI-powered financial inclusion is crucial because it demonstrates how large-scale digital public infrastructure can reshape access to banking, credit and public services for hundreds of millions of people. Additionally, it highlights how AI can move beyond consumer applications into core economic infrastructure, influencing financial resilience, productivity, fraud prevention and long-term digital development.

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Taiwan urges stronger defences amid AI-driven cyber threats

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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WEF report highlights supply chain risks in quantum-safe cybersecurity transition

A new World Economic Forum (WEF) analysis argues that coordination failures across global technology supply chains could slow the transition towards quantum-safe cybersecurity, despite growing pressure from governments, regulators, and major technology companies to accelerate adoption of post-quantum cryptography (PQC).

The article highlights how the migration towards quantum-safe security has shifted from long-term planning into active deployment after the National Institute of Standards and Technology finalised its first PQC standards in 2024. The UK’s National Cyber Security Centre has already set phased migration targets extending to 2035, while Google has set 2029 as the target timeline for parts of its own transition roadmap.

Furthermore, WEF argues that post-quantum migration cannot be treated as a routine software update because quantum-safe security depends on every layer of the digital ecosystem. Semiconductors, firmware, operating systems, applications, cloud services, telecoms infrastructure, and critical national infrastructure all need coordinated upgrades. Delays at one stage of the supply chain could affect every downstream deployment.

Critical infrastructure operators face particular pressure because many systems rely on long operational cycles, globally sourced equipment, and tightly regulated procurement frameworks. Energy networks, telecoms systems, transport infrastructure, and financial institutions are already making procurement decisions that may shape cybersecurity resilience for decades.

According to the report, deploying infrastructure without a clear PQC migration pathway could create substantial future remediation costs and operational risks.

The piece also links the post-quantum transition to broader cyber resilience concerns tied to AI. Frontier AI systems are increasingly being used to identify vulnerabilities at scale, accelerating both defensive security testing and potential offensive cyber capabilities.

The article references Anthropic and its Claude Mythos model, along with examples of Mozilla Firefox vulnerability discovery, as evidence that AI is rapidly changing software assurance and implementation testing.

Organisations treating PQC migration as a coordinated resilience programme instead of a narrow compliance exercise will be better positioned to protect critical services, economic stability, and trust in digital systems over the coming decade.

Why does it matter?

Quantum computing is steadily moving from theoretical risk to practical cybersecurity challenge, forcing governments and industries to rethink the foundations of digital security. The WEF analysis shows that the greatest obstacle may not be the cryptographic technology itself, but the coordination required across suppliers, infrastructure operators, regulators, cloud providers, and hardware manufacturers.

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