All news in category “AI and Security Pulse”

🛡️ Lloyds Banking Group treats agentic AI as an engineering problem to be designed, constrained and tested at scale. At OWASP’s GenAI Security Summit, Lloyds’ security leads explained an “AI safe adoption” strategy spanning lifecycle governance, an internal agent marketplace, and multidisciplinary feature teams. Key challenges include agent identity, runtime observability and automated red‑teaming, while prioritizing low‑risk, high‑value use cases for customers.

🛡️ The Open Worldwide Application Security Project (OWASP) published a new agentic AI security maturity framework in the GenAI Security Project paper "State of Agentic AI Security and Governance" on June 3, and introduced it at Infosecurity Europe 2026 on June 4. The Enterprise Adoption Maturity Model maps deployments (from shadow AI to multi-agent systems) against governance maturity (from ad hoc to continuous oversight). It provides a decision tool to identify mismatches and prescribes either tailored controls for agentic systems or constrained agent permissions until governance catches up.

🔒 Ox Security urges that appsec be integrated directly into AI coding tools as agentic development accelerates code changes beyond traditional pipelines. Speaking at Infosecurity Europe, field CTO Boaz Barzel argued that security must become a continuous, contextual property of creation rather than a bolt-on stage. He outlined four agentic attack surfaces—input, tools, execution and output—and advocated autonomous security agents that pentest and validate every commit to reduce MTTR and achieve full coverage.

🔍 Experts at Infosecurity Europe warned that healthcare organizations must adopt AI-powered security to detect and contain threats faster. Legacy devices, hyper-connectivity and alert fatigue are creating a high-risk environment where ransomware and other attacks can endanger patient safety. Speakers urged proactive measures including full device visibility, clinical-risk-based prioritization, AI-driven signal correlation and segmentation to reduce exposure.

🔎 The Microsoft AI Red Team released a v2.0 update to the Taxonomy of Failure Modes in Agentic AI Systems, grounded in twelve months of red team engagements and operational data. The revision adds seven new failure mode categories—such as agentic supply chain compromise, goal hijacking, and visual attacks against computer-use agents—expands mitigations, and emphasizes supply chain, zero‑trust, and session hardening.

🔎 OpenAI proposed mandatory federal evaluations for the most capable AI models before public release while arguing regulators should not have authority to approve or block deployments. The company urged pre-release assessments by the Center for AI Standards and Innovation (CAISI) alongside audits, transparency reports, incident reporting, and whistleblower protections. OpenAI framed this approach as a middle ground that enhances government visibility and preserves developer responsibility for release decisions.

🔒 Microsoft’s Detection and Response Team (DART) warns that AI adoption has introduced new attack surfaces, with threat actors weaponizing AI tools in social engineering and supply chains. A highlighted campaign, ‘JustAskJacky’, disguised a malicious AI assistant that installed a Java backdoor and persistence tasks. Experts urge organisations to assess nonstandard AI apps, enforce security reviews, and make AI risk a board-level priority.

🔍 At Infosecurity Europe 2026, Bugcrowd unveiled ExploitBench, a graded benchmark assessing AI models' ability to chain vulnerability discovery into staged exploits against a vulnerable V8 build. Anthropic’s Claude Mythos outperformed OpenAI’s GPT‑5.5 in head‑to‑head runs, achieving higher average scores and more top‑tier exploits, often with occasional human nudges. The report highlights rising offensive potential of frontier LLMs and urges defenders to adopt automated remediation and prioritization.

🔐 At Infosecurity Europe, Forescout's Rik Ferguson urged organisations to accelerate transition plans to post-quantum cryptography (PQC), warning that only 8% of SSH servers support PQC. He cited NSA warnings about harvest-now-decrypt-later (HNDL) attacks and evidence from surveillance programs indicating encrypted data is already being hoovered for future decryption. Ferguson recommended urgent inventorying of encrypted assets, embedding quantum readiness into procurement, and building crypto-agility such as adopting TLS 1.3.

🛡️ Security experts at Infosecurity Europe warned that expanding access to frontier AI tools for vulnerability discovery — notably Anthropic’s Project Glasswing and OpenAI’s reported GPT-5.5 Cyber pilot — heralds a structural shift in cybersecurity. Speakers advised organisations to harden controls, run incident response exercises, and accelerate adoption to avoid falling behind attackers. The panel stressed that AI augments, not replaces, human expertise; combined use improves validation and remediation of AI-discovered issues.

🚀 This tutorial shows how to build an AI agent with Google’s Agent Development Kit (ADK), containerize it, and deploy it to GKE Autopilot using Vertex AI (Gemini) as the model backend. It walks through local testing, creating a multi-stage Docker image, pushing to Artifact Registry, and configuring a Kubernetes Deployment and Service. The guide emphasizes secure authentication with Workload Identity and exposes the agent via the Kubernetes Gateway API with a Google-managed TLS certificate.

🛠️ The Amazon Bedrock console has been redesigned to match real-world model development workflows: experiment, iterate, and scale. The refreshed UI centers on the bedrock-mantle endpoint and is compatible with the OpenAI Responses API, OpenAI Chat Completions API, and the Anthropic Messages API. Users can browse and compare models, create projects to run evaluations, and get project-aware code snippets prefilled with model ID, region, endpoint URL, and API key references. The new experience is available in all Regions where the bedrock-mantle endpoint is offered.

🧭 Amazon SageMaker AI introduces multi-turn reinforcement learning (RL), a serverless model customization method for fine-tuning models on multi-step, agentic tasks. The feature trains models against users' agent environments, rewarding entire decision sequences to improve task accuracy of smaller, cost‑effective models versus larger general-purpose models. It integrates with Amazon Bedrock AgentCore Runtime and other deployment targets, and handles rollout orchestration, trajectory collection, training, and checkpoints, with MLflow tracking and evaluation metrics. Multi-turn RL runs serverlessly and is available in SageMaker Studio and the SageMaker Python SDK, supporting several foundation models in specific regions.

🔒 Microsoft announced new controls to contain agentic AI workloads, including the Microsoft Execution Container (MXC) runtime and enhancements to the multi-agent vulnerability research system MDASH. MXC is a policy-driven sandbox for specifying and enforcing access to files, networks, credentials, and resources at runtime across Windows, Linux, and macOS. The company also highlighted Agent 365 SDK, Windows 365 for Agents, and two open-source standards—ASSERT and Agent Control Specifications—to govern agent behavior across platforms.

🔒 The rapid rise of frontier and agentic AI is creating board-level urgency that may finally unlock sustained cybersecurity funding. Industry leaders at recent conferences noted that autonomous AI systems expose operational risk, widen attack surfaces, and outpace traditional security architectures. CISOs are reframing cybersecurity as an operational enabler for safe AI adoption, pushing for investments in visibility, identity, monitoring, and AI-specific controls. Vendors and experts caution that budget requests need clear business cases tied to measurable outcomes.

🛡️ Anthropic has broadened Project Glasswing, giving 150 additional organizations access to its most capable model, Claude Mythos Preview, to help find vulnerabilities in critical software. The program, first opened to roughly 50 partners in April, claims more than 10,000 high- or critical-severity flaws discovered to date. New participants span 15+ countries and underrepresented sectors like power, water, healthcare and hardware, chosen for the potential catastrophic impact of breaches. Anthropic warned that while discovery is accelerating, safe public release of Mythos-class models remains restricted due to incomplete safeguards.

🔍 Halcyon research reveals a dramatic rise in AI-powered cybercrime tooling across underground markets, jumping from 38 mentions in December to 1,486 in February. Cynthia Kaiser, SVP of Halcyon’s Ransomware Research Center, detailed four product categories: weaponized LLMs, AI-enabled identity fraud, AI-augmented malware/infrastructure, and jailbroken or stolen AI services. She warned that automated distribution, freemium models and redundant channels have lowered the financial barrier to entry and increased resilience against takedown efforts.

🔎 Anthropic has added 150 additional companies to its Project Glasswing initiative, prioritizing critical infrastructure sectors like power, water, healthcare, communications, and hardware. Analysts view the expansion positively for increasing vulnerability discovery, but warn of a remediation bottleneck: vendors and SOCs may struggle to validate, prioritize, and patch a potential 10x or greater increase in findings. Experts emphasize the need for confidence scoring, automation, and third-party validation to maintain trust and ensure timely remediation.

🔒 Reporting suggests attackers used Meta’s AI support chatbot to change recovery emails on high-profile Instagram accounts, leading to notable takeovers. The core issue isn’t just prompt injection or a model jailbreak but that the AI operated within a sensitive account recovery workflow with insufficient independent verification. Organizations must treat AI-driven support actions as part of the security boundary and constrain authority, permissions, and verification around such agents.

🧭 Microsoft announces the general availability of Microsoft Discovery, a platform for building and governing agentic AI workflows tailored to scientific and engineering R&D. The release includes a preview of the Microsoft Discovery app, a local desktop experience for researchers and small teams to explore hypotheses, literature, and iterative experimentation. The platform emphasizes evidence preservation, traceability, governance, and integration with existing tools and institutional data to support repeatable, transparent scientific workflows.