All news in category “AI and Security Pulse”

🔍 Modern attackers use AI to imitate trusted users, tools, and services, making many incidents malware-free and harder to detect. The article compares these tactics to art forger Elmyr de Hory and outlines threats such as agentic AI, supply-chain impostors, cloaked tunnels, rogue infrastructure, and sophisticated phishing. Network Detection and Response (NDR), including Corelight’s Open NDR Platform, is highlighted as essential for spotting behavioral anomalies, protocol inconsistencies, and contextual metadata to expose impostors early.

🤖 Flare's analysis of hundreds of fraud-forum posts finds premium AI subscriptions (including ChatGPT, Claude, and Microsoft Copilot) are widely advertised, bundled, and resold in underground markets. Listings tout discounted subscriptions, multi-service bundles, API keys, and claims of reduced restrictions. Patterns point to exposed keys, credential theft, large-scale account creation, trial abuse, and shared subscriptions fueling the trade, increasing operational and data risk for organizations.

🔐 At the World Economic Forum’s Industry Strategy Meeting in Munich, leaders explored how rapid AI deployment and rising data sovereignty pressures are reshaping digital infrastructure and investment. The piece argues that cybersecurity must be embedded from day zero to enable trusted data exchange, interoperability between sovereign systems, and secure distributed AI. It highlights the shift from large general models toward specialized, context-aware architectures and notes Fortinet’s role in public-private collaboration to operationalize secure systems.

⚠️ AI agents embedded across SaaS environments can render the traditional kill chain ineffective when they are compromised. The piece cites a September 2025 Anthropic disclosure where a state-backed actor used an AI coding agent to perform autonomous espionage, handling the majority of tactical operations. Because agents already hold broad permissions and move data as part of normal workflows, a breach looks like legitimate activity. Reco is positioned as a solution to discover agents, map blast radius, enforce least privilege, and detect anomalous agent behavior in real time.

🛡️ Security researchers have warned of malicious Chrome extensions that silently monitor and exfiltrate users' AI chat content. According to Expel, extensions watch open tabs and capture prompts and responses via API interception or DOM scraping before sending the data to external servers. Attackers either impersonate popular tools or convert legitimate extensions into malicious ones after building a user base. Organisations are urged to block unvetted AI extensions and centrally manage and audit extension use.

🤖 AI-assisted triage is changing vulnerability workflows and forcing organizations to redesign ownership and decision-making. By enriching findings with exploitability indicators, ownership metadata and business-impact signals, AI platforms accelerate detection and reduce manual triage. Security teams must shift from routine investigation to governing models, defining owners, and maintaining human checkpoints for high‑risk actions. Treat AI-driven features as first-class risk surfaces and assign clear owners for model behavior, prompt safety and misuse prevention.

🔐 CrowdStrike introduces Charlotte AI AgentWorks and Charlotte Agentic SOAR to enable agentic security operations that orchestrate context-aware agent fleets and automate responses at machine speed. The platform integrates frontier models from Anthropic, NVIDIA and OpenAI and leverages Falcon telemetry, threat intelligence, and industry partners to keep agents context-aware and secure. Built-in guardrails preserve human oversight and governed autonomy while mission-ready agents handle tasks from triage to malware analysis. Customers report sharply reduced manual workloads, restored analyst capacity, and improved decision accuracy.

🔐 The UK NCSC's chief executive Richard Horne told the RSA Conference (March 24) to 'seize the disruptive vibe coding opportunity' while urgently developing safeguards. He warned AI-assisted development can either reduce systemic vulnerability or propagate new flaws depending on model design and controls. NCSC CTO David C published Secure Vibe Coding Commandments advocating secure-by-default models, provable provenance, AI-powered audits, deterministic guardrails and sandboxed hosting.

🧭 This article presents a practical framework for governing AI agents by aligning user, developer, role-based, and organizational intent. It prescribes a precedence model—organization, role, developer, then user—to resolve conflicts and preserve security and compliance. The authors illustrate expected agent behaviors (refuse, escalate, clarify, or proceed) and advocate for guardrails, least-privilege access, continuous evaluation, telemetry, and human-in-the-loop controls to sustain safe, reliable agent operations.

🔒 Gartner's inaugural Market Guide for Guardian Agents defines a new enterprise control layer that supervises AI agents to keep their actions aligned with organizational goals and boundaries. The article stresses risks from unmanaged non-human identities—so-called identity dark matter—and lists mandatory capabilities across visibility, continuous assurance, and runtime enforcement. It urges enterprises to adopt an enterprise-owned guardian layer rather than relying solely on platform-native controls.

🤖 Japan’s recent election highlighted Team Mirai, a new political party that used AI-driven engagement tools to deepen civic participation and shape policy. Its AI Interviewer walked voters through issues, while the gamified Action Board mobilized volunteers and the open-source Gikai portal summarized legislation. Mirai collected tens of thousands of public inputs and converted them into a manifesto focused on democratic reform rather than traditional left‑right politics.

🤖 Early this year, enterprises began experimenting with autonomous, agentic tools such as Anthropic’s Claude Cowork and the open-source OpenClaw, which can access apps, files and the web to execute multi-step workflows on users’ behalf. Proponents highlight large efficiency gains and the ability to offload routine IT tasks to non-technical staff, while security researchers warn of misalignment, prompt‑injection flaws and unintended destructive actions. IT leaders are advised to permit controlled experimentation, enforce strict permissions and monitoring, and invest in clean operational context to reduce amplified mistakes and limit shadow‑AI risk.

🛡️ AI-driven honeypots pair large language models with deception servers to create dynamic, realistic environments that keep attackers engaged longer and collect richer threat intelligence. Academic research by Dr. M. Abdullah Canbaz and others showed LLMs can parse traffic and handle complex Linux commands, prompting open-source and commercial efforts such as Beelzebub and Deutsche Telekom’s T-Pot. These systems significantly lower the cost and engineering effort of high-interaction deception while enabling deployment in novel locations like APIs and AI agents. However, defenders must balance benefits with risks—attackers are using AI to automate attacks and may develop countermeasures such as deception-detection services or data poisoning—so CISOs should view AI honeypots as a complement to existing sensors and an important tool for improved visibility and hunting.

📚 OpenAI has begun rolling out a new ChatGPT Library feature that stores personal files and images in its cloud so they can be referenced in future chats. The feature is available to Plus, Pro, and Business subscribers worldwide except in the European Economic Area, Switzerland, and the United Kingdom. Files uploaded in chats or via the composer are saved by default to a secure, dedicated location and remain in the Library until manually deleted; deleting a chat does not remove the stored file.

🚨 New ISACA research finds that 56% of IT and cybersecurity professionals cannot say how quickly they could shut down AI systems after a cyber-attack or security incident. The global survey of over 3,400 security and digital professionals found just 32% believe they could halt compromised AI within an hour, and 7% expect it would take longer. Respondents reported confusion over AI ownership, with many unsure who is accountable, limited human oversight of AI actions, and mixed confidence in their organisation's ability to investigate and explain serious AI incidents.

🧠 This article presents a blueprint architecture for securing AI data centers and AI factories as enterprises shift from consuming AI to producing it. It explains how organizations can protect LLMs, data pipelines, and compute infrastructure against emerging, AI-specific threats by combining network segmentation, identity and access controls, data governance, and advanced threat prevention. Check Point emphasizes operational practices and industrial-grade security controls to enable secure, revenue-generating AI deployments.

🔒 At RSAC, Check Point outlined how enterprises can secure their AI transformation by protecting sensitive data, models, and communications from emerging attack vectors. The company emphasized integrated controls—data loss prevention, access governance, model protection and runtime threat detection—paired with unified visibility across cloud and on‑prem environments. Check Point shared practical steps for safe AI adoption, from discovery and policy enforcement to automated response, helping organizations reduce leakage and compliance risk while enabling productive AI use.

🔒 XM Cyber researchers identified eight validated attack vectors inside AWS Bedrock, showing that integrations and permissions — not the foundation models themselves — are the primary risk. The team highlights log manipulation, knowledge base compromise, agent hijacking, flow injection, guardrail degradation, and prompt poisoning as practical paths to data exfiltration and operational abuse. Their findings show how a single over-privileged identity can redirect logs, steal credentials, or subvert agents and prompts. Security teams should inventory AI workloads, enforce least privilege, and map cross-environment attack paths to reduce exposure.

🔒 CrowdStrike announced a suite of innovations that expand AI detection and response across endpoints, SaaS, and cloud environments. New capabilities include runtime monitoring for desktop AI applications and Copilot Studio agents, unified discovery and classification of AI agents across SaaS, and data-flow visibility for cloud-hosted AI workloads. Several features are in pre-beta or early beta with staged GA rollouts planned over upcoming quarters.

🔐At the NRF Big Show in January 2026, Google introduced the Universal Commerce Protocol (UCP) and highlighted compatibility with the Agent Payments Protocol (AP2), promising tokenized payments and verifiable credentials. Unit 42 warns that indirect prompt injection—where agents ingest hidden instructions while browsing—can enable novel fraud such as gift card payload poisoning and refund logic hijacking. Industry forecasts (Bain, McKinsey) predict substantial agentic commerce adoption, increasing the attack surface. Recommended mitigations include protocol guardrails (AP2), Know Your Agent, agent reputation scoring, Unit 42 AI Security Assessments and Prisma AIRS.