Today’s executives are expected to be visible—on LinkedIn, in the press, at conferences, and across digital channels. That visibility fuels brand trust, investor confidence, and talent attraction. But it also creates a dangerous imbalance: as executive exposure increases, digital threats accelerate even faster.

This is the Visibility Paradox.

Most executive risk doesn’t start with sophisticated hacks. It starts with unmanaged digital exposure—home addresses, family details, travel patterns, and credentials scattered across the open and dark web. These gaps turn influence into liability.

Our latest thought leadership article introduces a modern framework for Safe Visibility, built on five critical pillars:

• Public data elimination
• Continuous monitoring and rapid removal
• Secure communication protocols
• Organization-wide security alignment
• Integrated physical security

Each pillar matters. Miss one, and the entire protection strategy weakens. The ultimate metric? High executive visibility with zero digital or physical incidents. VanishID is the category leader in executive digital-risk protection, delivering end-to-end coverage—from PII removal and dark web monitoring to real-time exposure dashboards and fully managed operations with zero lift for security teams.

Welcome to CYBER_AI, a new newsletter from the Packt team focusing on—well, exactly what it says on the tin: cybersecurity in the age of AI.

Here we go on another step into the future, into a world where the world of cybersecurity brims with the confidence that AI can bring to our practice. Of course, this goal—like all goals—requires us to set up the foundations properly and figure out how we stand on them. That means, for all those struggling to make these ambitious bounds forward, establishing the “101” topics and making sure they are widely understood. For a look into the future, here's our plan:

1. What “Cybersecurity AI” Actually Means

2. Machine Learning 101 for Security Professionals

3. Threat Detection with AI: From Rules to Models

4. Adversarial Machine Learning Basics

5. LLMs in Cybersecurity: Capabilities and Limitations

6. Securing AI Models and Pipelines (AI Supply Chain Security)

7. AI-Enhanced Offensive Techniques

8. Privacy and Data Protection in AI Systems

9. AI Governance, Ethics, and Risk Management

10. Building a Security-Aware AI Workflow

Sound good? Head over to Substack and sign up there!

In this newsletter, we’ll explore how AI is transforming cybersecurity—what’s new, what’s next, and what you can do to stay secure in the age of intelligent threats.

Welcome aboard! The future of cyber defence starts here.

Cheers!
Austin Miller
Editor-in-Chief

Head over to Substack to check out this week's article!

Geopolitics and AI Among Top Trends for Cybersecurity 2026”: Cybersecurity in 2026 is poised to evolve rapidly with artificial intelligence deeply integrated into both attacks and defenses. The report highlights AI’s role in threat automation, geopolitical fragmentation increasing risk complexity, and a widening technological divide shaping how nations and corporations secure digital assets.

Cybersecurity Can Be The Next Mega Trend Thanks To AI: AI’s growing influence on cybersecurity has attracted significant investor interest and market momentum. The article discusses how AI-driven detection, response automation, and predictive technologies position the cybersecurity sector as a premier investment trend, with implications for enterprise resilience and future risk management.

AI and Cybersecurity Trends That Will Define 2026: A forward-looking analysis of how AI will reshape the cybersecurity landscape globally, focusing on regions like India. Key trends include more advanced threat sophistication, broader AI adoption in defensive stacks, and the urgent need for frameworks to govern AI risk.

Businesses Are Finally Taking Action to Crack Down on AI Security Risks: Based on a World Economic Forum (WEF) and Accenture report, this piece details how companies are increasingly incorporating AI risk assessments before deployment. It notes a sharp rise in AI vulnerabilities such as deepfakes and automated social engineering, alongside growing adoption of AI tools for phishing and intrusion detection.

AI’s Hacking Skills Are Approaching an ‘Inflection Point’: With advancements in AI reasoning and autonomous problem analysis, tools like RunSybil are uncovering complex system vulnerabilities with a sophistication that rivals human experts. While promising for defense, these capabilities also heighten concerns that adversaries could weaponize similar AI systems.

Belgian Cybersecurity Startup Aikido Hits Unicorn Status With New Funding Round: Aikido Security, a European cybersecurity startup focused on developer-centric and AI-friendly risk tools, has raised $60 million at a $1 billion valuation. The funding reflects broader demand for security solutions tailored to modern AI-heavy software development workflows.

Like Social Media, AI Requires Difficult Choices: In his 2020 book, “Future Politics,” British barrister Jamie Susskind wrote that the dominant question of the 20th century was “How much of our collective life should be determined by the state, and what should be left to the market and civil society?” But in the early decades of this century, Susskind suggested that we face a different question: “To what extent should our lives be directed and controlled by powerful digital systems—and on what terms?”

Banning VPNs:This is crazy. Lawmakers in several US states are contemplatingbanning VPNs, because…think of the children!

As of this writing, Wisconsin lawmakers are escalating their war on privacy by targeting VPNs in the name of “protecting children” inA.B. 105/S.B. 130. It’s an age verification bill that requires all websites distributing material that could conceivably be deemed “sexual content” to both implement an age verification system and also to block the access of users connected via VPN. The bill seeks to broadly expand the definition of materials that are “harmful to minors” beyond the type of speech that states can prohibit minors from accessing­ potentially encompassing things like depictions and discussions of human anatomy, sexuality, and reproduction.

The EFF link explains why this is a terrible idea.

Four Ways AI Is Being Used to Strengthen Democracies Worldwide: Democracy is colliding with the technologies of artificial intelligence. Judging from the audience reaction at the recentWorld Forum on Democracy in Strasbourg, the general expectation is that democracy will be the worse for it. We have another narrative. Yes, there are risks to democracy from AI, but there are also opportunities. We have just published the bookRewiring Democracy: How AI will Transform Politics, Government, and Citizenship.In it, we take a clear-eyed view of how AI is undermining confidence in our information ecosystem, how the use of biased AI can harm constituents of democracies and how elected officials with authoritarian tendencies can use it to consolidate power. But we also give positive examples of how AI is transforming democratic governance and politics for the better.

AI-Driven Cybersecurity Threats: A Survey of Emerging Risks and Defensive Strategies (Sai Teja Erukude, Viswa Chaitanya Marella, Suhasnadh Reddy Veluru): This 2026 survey paper examines the dual-use nature of AI in cybersecurity, identifying novel threat vectors such as deepfakes, adversarial AI attacks, automated malware, and AI-enabled social engineering. The authors present a comparative taxonomy linking specific AI capabilities with corresponding threat modalities and defense strategies, drawing on over 70 academic and industry references. It also highlights critical gaps in explainability, interdisciplinary defenses, and regulatory alignment necessary to sustain digital trust.

The Promptware Kill Chain: How Prompt Injections Gradually Evolved Into a Multi-Step Malware (Ben Nassi, Bruce Schneier, Oleg Brodt): This paper reframes prompt injection vulnerabilities in large-language-model (LLM) systems as a structured chain of attack steps akin to classical malware campaigns. The authors propose a new “promptware kill chain” model with defined phases—from initial access through privilege escalation to data exfiltration—offering a common framework for threat modeling and cross-domain research between AI safety and cybersecurity.

Artificial intelligence and machine learning in cybersecurity: a deep dive into state-of-the-art techniques and future paradigms: This extensive review analyzes how AI and machine learning (ML) are transforming core cybersecurity functions—including intrusion detection, malware classification, behavioral analytics, and threat intelligence. The paper discusses adversarial machine learning, explainable AI, federated learning, and quantum integration as future paradigms, offering a comprehensive roadmap for intelligence-driven, scalable security architectures.

Generative AI revolution in cybersecurity: a comprehensive review of threat intelligence and operations: Focused on the rise of generative AI (GAI), this work explores how generative models can autonomously detect threats, augment human judgment, and contribute to defensive operations. It also critically assesses the limitations and misuse potential of these models, such as incorrect outputs and exploitation by adversaries, highlighting the balance needed for secure adoption.

A cybersecurity AI agent selection and decision support framework (Masike Malatji): This paper introduces a structured decision support framework that aligns diverse AI agent architectures (reactive, cognitive, hybrid) with the NIST Cybersecurity Framework (CSF) 2.0. It formalizes how AI agents should be selected and deployed across detection, response, and governance functions, offering a practical schema for organizations to move beyond isolated AI tools toward holistic, standards-aligned deployments.

Integrating Artificial Intelligence into the Cybersecurity Curriculum in Higher Education: A Systematic Literature Review (Jing Tian): While focused on education, this systematic literature review is trending among academics because it synthesizes research on how AI and cybersecurity education are being combined in higher education curricula. It examines course design, instructional tools, and pedagogical practices that prepare the next generation of cybersecurity professionals to use and defend against advanced AI systems.