All news in category “AI and Security Pulse”

🔒 Bruce Schneier reflects on his 2010 Dark Reading essay arguing that while cryptography provides strong mathematical advantages, it cannot by itself secure modern, interconnected systems. He traces how crypto has been applied since the 1990s and explains that computer security is an ongoing arms race of fragile defenses. Schneier warns that AI changes the landscape by automating vulnerability discovery and exploit creation, shifting the balance between attackers and defenders.

🧩Trustpilot built a high-volume streaming pipeline using fine-tuned Gemma models to process millions of user reviews in near real-time under tight latency and cost constraints. The team replaced variable per-token pricing with fixed infrastructure costs, fine-tuned lightweight models for tasks like NER, sentiment, and topic classification, and separated classifier and LLM endpoints. Performance tuning, vLLM optimizations, and load testing enabled scalable inference despite challenges with private networking, deployment observability, and GPU availability.

🛡️ Vendors at Infosecurity Europe 2026 agree that AI will not eliminate security operations centers but will automate repetitive triage and ticketing. Experts urge treating AI as a glass box, ensuring transparency and human-in-the-loop validation. The shift accelerates junior analysts into supervisory tier-1.5 roles and creates demand for cyber defense engineers who build and tune detection systems.

🧭 At Infosecurity Europe 2026, OWASP will unveil the Agentic Research Council to better align fast‑moving agentic AI capabilities with security research and operational practice. Launched from the GenAI Security Project’s Agentic Security Initiative, the council will prioritize a public research pipeline, convene working groups and connect academic outputs to deployable mitigations. The initiative aims to accelerate runtime‑focused defenses against multi‑agent threats.

🛡️ Cybersecurity researchers disclosed a vulnerability dubbed ChatGPhish that exploits ChatGPT's trust in Markdown links and images to perform prompt injections and enable phishing. The flaw causes the assistant to auto-fetch attacker-hosted images and render malicious links and QR codes inside the trusted UI, potentially leaking client metadata like IP and User-Agent. The technique highlights summarization as an adversarial surface that can convert benign web pages into phishing vectors.

🛰️ The Linux Foundation has proposed DNS-AID, a standards-driven extension to the Domain Name System to let AI agents discover, verify, and communicate without new infrastructure. The project leverages a well-known DNS address pattern (for example, _index._agents.{domain}) to provide a global, vendor-neutral directory for agents and MCP servers. Initial work was done by Infoblox, with contributions from Deutsche Telekom and Amazon, and the foundation is soliciting further input to keep the approach scalable and secure.

🔬 Researchers at ETH Zurich report creating a device that generates provably perfect random numbers using two superconducting qubits, a 30-meter microwave guide, and specialized software. The setup leverages quantum entanglement and an amplification algorithm to remove bias common in classical and many quantum sources. The team says the output can be certified and could serve cryptographic key generation or public randomness services.

🚀 Claude Opus 4.8 is now accessible in Microsoft Foundry, providing developers and enterprises with Anthropic’s most capable Opus model for coding, agentic tasks, and professional work. The update focuses on long-running workflows, deeper reasoning across documents and codebases, and more reliable tool use for multi-step automation. Teams can now evaluate and deploy the model within Foundry’s unified platform for building and operating AI applications.

🤖 Anthropic confirmed plans to release its Mythos-class AI models to the general public after previously restricting access because of security risks to public and private software. Initially available only to select organizations and researchers, Mythos was held back while Anthropic developed stronger safeguards. The company says it’s making swift progress and expects to offer Mythos-class models to customers in the coming weeks, noting significant gains in code reasoning and autonomy over its Opus 4.8 flagship.

🧭 This collaboration between Google Public Sector and the University of Central Oklahoma (UCO) Forensic Science Institute uses Google’s NotebookLM to rapidly analyze complex criminal case documents and construct timelines. Originating from an AI hackathon co-led by UCO’s CIO Sonya Watkins, the project leverages Gemini to prioritize high-impact prototypes and has reduced multi-month analyses to days in early trials. UCO instructors ensure AI outputs are forensically sound and reliably cited.

🖼️ Google Cloud announced Nano Banana 2 (Gemini 3.1 Flash Image) and Nano Banana Pro (Gemini 3 Pro Image) are generally available via the Gemini Enterprise Agent Platform, offering enterprise-grade image generation and editing. Nano Banana 2 now supports video files as input in preview, enabling deep video understanding to generate context-aware images. 1K and 2K outputs are GA while 4K remains in preview. The models are integrated by partners like Adobe, WPP, Shopify, URBN, and Magnopus to scale creative workflows and production pipelines.

🤖 AWS now offers Claude Opus 4.8, Anthropic's most capable generally available model, bringing advances in agentic coding, professional knowledge work, and autonomous long-running tasks for developers and enterprises. The model sustains longer sessions, reasons more deeply, and maintains consistency for production workflows. Customers can access Opus 4.8 via Amazon Bedrock or the Claude Platform on AWS, with AWS-managed features and unified billing.

🛡️ CIOs rushing to deploy AI agents without visibility risk major failures; experts warn that observability and governance are required. Many organizations treat agents like RPA and set-and-forget systems, but agents operate in model runtimes and need end-to-end tracing, least-privilege permissions, and human-in-the-loop checks. Vendors and cloud providers offer tools, yet governance can become a bottleneck if it’s not scalable and actionable.

🔍 Cisco researchers found that popular frontier LLMs from OpenAI, Anthropic, Google, xAI, and Amazon exhibit substantially higher risk when subjected to multi-turn adversarial attacks than when assessed with single-prompt safety benchmarks. The team ran tens of thousands of single-turn and multi-turn attacks across 15 models and multiple configurations, revealing wide gaps in attack success rates (ASRs) and configuration-dependent safety behavior. They urge improved benchmarks, transparency on configuration impacts, and publication of paired single- and multi-turn ASRs to better inform procurement and governance decisions.

🧭 This article examines practical strategies to reduce AI cold-start latency on Cloud Run when serving GPU-backed models. It outlines the four-phase cold-start process, highlights storage and model-format choices (Cloud Storage, container images, GGUF, Safetensors, quantization), and explains Cloud Run features like image streaming, temporary CPU boosts, and concurrency tuning. The piece also shares operational tactics—warmup endpoints, startup probe tuning, regional deployment choices—and production patterns used by Elastic to treat GPUs as fungible compute.

🔒 Cisco researchers warn that safety guardrails in several leading large language models (LLMs) can be bypassed through multi-turn conversations. They tested frontier models including ChatGPT, Claude, Gemini, Nova and Grok, finding many were susceptible to manipulation that yields disallowed outputs. Techniques such as roleplay, ambiguity, reframing, and persona adoption were effective, and model configuration affected resilience.

🛡️ Recent developments show AI moving from automation to autonomous cyber operations, shifting how offense and defense interact. The Anthropic Mythos Preview and related incidents illustrate models discovering and chaining vulnerabilities with limited human direction, prompting coordinated defensive responses from major vendors. Policy and procurement are adapting, and security leaders must treat AI agents as principals, invest in adaptive defenses, and reframe risk models for continuous compromise.

🩺 Generative AI chatbots are increasingly used for health questions, but they carry significant risks ranging from incorrect diagnoses to privacy exposures. Users may unknowingly share sensitive medical details that could be used for model training or passed to third parties. Health-focused services vary in their data-handling promises, and most consumer chatbots are not covered by HIPAA. Follow practical precautions and always verify AI advice with qualified medical professionals.

📡 Researchers show WiFi signals can reveal people and environments by analyzing how radio waves reflect, scatter, and absorb compared with expected patterns. WiFi sensing uses these variations to infer spatial structure and presence, effectively creating an image of surroundings and occupants. Thorsten Strufe of KIT explains it functions like a camera, but with radio waves instead of light, enabling recognition through signal propagation analysis.

🚦The author argues that traditional post-hoc compliance reviews fail for AI because AI systems change continuously. Drawing on research into Chinese and EU approaches, the piece recommends embedding governance into CI/CD pipelines so model cards, data lineage and risk evaluations are generated and enforced as deployment gates. It also urges treating agent identity as first-class security control and positioning compliance as operational release infrastructure rather than a review layer.