Explore the intersection of AI and cybersecurity. Stay informed on AI-driven security trends, tools, and threats in the ever-evolving digital landscape.
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Artificial intelligence (AI) describes computer systems that perform tasks such as recognizing patterns, making predictions, understanding language, or generating content. In security reporting, the term commonly includes machine-learning models used for detection and analysis, as well as generative AI applications that produce text, code, images, or other outputs.
AI can help analyze security telemetry, prioritize vulnerabilities, and support investigations, but its outputs can be wrong or manipulated. Important attack surfaces include prompt injection that steers an application into unintended actions, sensitive data being exposed through prompts or model outputs, and excessive permissions granted to AI systems that use external tools. Models can also be degraded by poisoned training data or evaded with carefully crafted inputs. Practitioners should protect training and operational data, limit model access and tool permissions, test for adversarial behavior, and require appropriate human validation before high-impact decisions.
Cybersecurity researchers have disclosed a zero-click flaw in OpenAI ChatGPT's Deep Research agent that could allow an attacker to leak sensitive Gmail inbox data with a single crafted email without any user action
Run by the team at workflow orchestration and AI platform Tines, the Tines library features over 1,000 pre-built workflows shared by security practitioners from across the community - all free to import and deploy through the platform's Community Edition
AI’s growing role in enterprise environments has heightened the urgency for Chief Information Security Officers (CISOs) to drive effective AI governance. When it comes to any emerging technology, governance is hard – but effective governance is even harder. The first instinct for most organizations is to respond with rigid policies. Write a policy document, circulate a set of restrictions, and
The threat actor known as TA558 has been attributed to a fresh set of attacks delivering various remote access trojans (RATs) like Venom RAT to breach hotels in Brazil and Spanish-speaking markets
Quantum computing and AI working together will bring incredible opportunities. Together, the technologies will help us extend innovation further and faster than ever before. But, imagine the flip side, waking up to news that hackers have used a quantum computer to crack your company's encryption overnight, exposing your most sensitive data, rendering much of it untrustworthy
Generative AI has gone from a curiosity to a cornerstone of enterprise productivity in just a few short years. From copilots embedded in office suites to dedicated large language model (LLM) platforms, employees now rely on these tools to code, analyze, draft, and decide. But for CISOs and security architects, the very speed of adoption has created a paradox: the more powerful the tools, the
AI agents are rapidly becoming a core part of the enterprise, being embedded across enterprise workflows, operating with autonomy, and making decisions about which systems to access and how to use them. But as agents grow in power and autonomy, so do the risks and threats. Recent studies show 80% of companies have already experienced unintended AI agent actions, from unauthorized system
In a world where threats are persistent, the modern CISO’s real job isn't just to secure technology—it's to preserve institutional trust and ensure business continuity
A new artificial intelligence (AI)-powered penetration testing tool linked to a China-based company has attracted nearly 11,000 downloads on the Python Package Index (PyPI) repository, raising concerns that it could be repurposed by cybercriminals for malicious purposes