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AI security

Securing AI systems, and defending against attackers who use them.

Tagged “AI security”

AI in Cybersecurity22 Jul 2026

Your Second Brain: AI Tools Every UI/UX Designer Needs to Work Smarter

Most people who start using AI carry the same bad habit into it. They jump to a solution before they understand the problem. AI makes that habit worse, not better, because it can hand you a plausible “solution” in seconds. That was the opening provocation of our recent webinar, “Yo

Surya Nathaniel Kattu

AI in Cybersecurity14 Jul 2026

AI in Cybersecurity: How it Works, Risks, and Real Use Cases

Artificial Intelligence (AI) is now on both sides of the fight. Defenders use it to spot attacks faster. Attackers use it to break in faster. According to IBM’s 2025 Cost of a Data Breach Report, 16% of breaches now involve attackers using AI tools, while organisations that lean on AI for defe

Trimikha Valentius

How to Strengthen Ransomware Protection Against Modern Attacks

AI in Cybersecurity24 Jun 2026

LLM Refusal Behavior on Open-Weight Model

Written by: Trimikha Valentius (CAIO, Head of ZENTARA Labs), Alisha Deana (AI Researcher) Conversational language models refuse harmful requests because a thin behavioural layer is added on top of a pretrained base during post-training. This article treats refusal as exactly that: a layer, not a pro

Trimikha Valentius

AI in Cybersecurity29 May 2026

Protecting Singapore’s Industry Fintech from Autonomous Agentic AI Threats

As Singapore’s fintech sector accelerates its adoption of artificial intelligence, a new class of systems is emerging: agentic AI. Unlike traditional models, agentic AI systems can plan, decide, and act autonomously across digital environments. This evolution introduces new capabilities, but it also

Trimikha Valentius

Technical Guides19 May 2026

A High-Scale Guide to Storing AI Models and Datasets

At Zentara, we are constantly pushing the boundaries of connectivity and infrastructure. As we scale our AI initiatives, one question consistently surfaces among our engineering teams: “How do we version these massive LLM models without breaking our development workflow?”. Managing sourc

Adam

AI in Cybersecurity07 May 2026

Inside AI Systems: A Research Lens on Hidden Risks

Most enterprises see AI as a simple, useful tool: a chatbot, recommendation engine, or scoring model. In reality, production AI sits on complex pipelines of data, models, configurations, and automated decisions. Small weaknesses inside that lifecycle can quietly escalate into security, privacy, oper

Alisha

AI in Cybersecurity10 Apr 2026

The Rise of Autonomous Cyber Attacks: When AI Becomes the Adversary

Artificial intelligence is reshaping cybersecurity at an unprecedented pace. While organisations adopt AI to strengthen defence, attackers are using the same technology to automate, accelerate, and scale their operations. Cyber attacks are no longer limited by human speed or manual effort. We are en

Trimikha Valentius

AI in Cybersecurity09 Apr 2026

Securing Enterprise Copilots: Preventing Prompt Injection and Data Exfiltration in LLMs

Organisations are rapidly adopting AI copilots powered by large language models (LLMs) to enhance productivity, decision-making, and workflow automation. However, with this convenience comes a new category of risk. Recent research published in 2026 highlights that LLM prompt injection vulnerabilitie

Trimikha Valentius

Executive deepfake impersonation defence

AI in Cybersecurity07 Apr 2026

The Executive Deepfake Threat: Defending Against AI-Driven Voice and Video Impersonation

Artificial intelligence has transformed how organisations operate, communicate, and innovate. However, the same technology is now being weaponised by cybercriminals to impersonate senior leaders with alarming realism. Deepfake voice and video attacks are moving from experimental to operational, and

Trimikha Valentius

Technical Guides07 Apr 2026

A Recipe for Langchain LLM Observability using Langfuse

When a standard app fails, you check the stack trace. But when an agent fails, you don’t know what to do. Is the model stuck in a recursive loop? Did it misunderstand the tool output? Is the “Critique Agent” currently hallucinating a list of reasons why the “Research Agent&#8

Adam

AI in Cybersecurity31 Mar 2026

The Hidden Security Risks in AI Adoption: Model Access and Data Leakage

AI adoption is accelerating across industries. From customer support automation to internal analytics and decision-making, organisations are embedding AI into critical workflows at speed. The promise is clear: faster insights, improved efficiency, and competitive advantage. What is less visible is t

Trimikha Valentius

AI in Cybersecurity30 Mar 2026

AI-Generated Phishing: Why Social Engineering Is Getting Harder to Detect

Phishing has always relied on deception, but historically, it was easy to spot. Poor grammar, unusual phrasing, and generic messaging often revealed malicious intent. Users were trained to recognise these signs, and for a time, it worked. That assumption no longer holds. With the rise of AI-generate

Toni Widiarto