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All news with #ai security tag

1047 articles · page 22 of 53

Microsoft Security updates and new capabilities — May 2026

🔒 Microsoft announced a set of security enhancements designed to protect agents, data, and identities as organizations scale AI. Highlights include the general availability of Microsoft Purview DSPM, expanded investigation capabilities with OCR and custom examinations, and a new Entra ID Account recovery flow for restoring organizational access. Public preview of Windows 365 for Agents and integration with Microsoft Agent 365 aim to govern and secure agent workloads in managed Cloud PCs.
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Three-Quarters Admit Shipping Vulnerable Code

🛡️ New studies reveal that 75% of organizations often or sometimes deploy code they know is vulnerable, down from 81% last year but still alarmingly high. Checkmarx warns that AI-augmented attackers are dramatically shortening time-to-exploit, while Verizon’s DBIR links increased initial access to vulnerability exploitation aided by AI. A QBE survey found UK firms are worried about suppliers' AI use, yet few audit third-party AI or maintain formal AI governance.
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AI Becomes SOC Imperative to Counter Emerging Threats

🛡️ Security professionals at DTX argued that integrating AI into SOCs is now essential to counter autonomous attacker tooling and AI-accelerated threats. Panelists stressed sustaining core cyberdefence fundamentals—system hardening, patching, access control and monitoring—before deploying AI, and preserving human oversight to manage model risk. They noted role shifts toward validation, prompt engineering and GRC, and urged rigorous testing and SDLC-like deployment controls.
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Measuring AI Security: Limits of Benchmarks and Assurance

🔒 AI security cannot be reduced to a single benchmark. Over the past 30 years software security evolved from black‑box penetration testing to white‑box analysis and process-driven standards such as BSIMM, and the report argues that AI requires a similar assurance-first approach. Benchmarks fail to capture emergent, systemic properties, so organizations should clean up their WHAT piles, adopt risk-based processes, and accept that there is no simple security meter for AI.
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AI-Driven Scanning Raises Vulnerability Expectations

🔍 ENISA chief Hans de Vries told ESET World that AI-powered vulnerability scanners mean firms can no longer claim ignorance of software bugs. He warned that the Cyber Resilience Act and emerging AI tools require security by design and that failure to use AI coherently risks exploitation and litigation. The NCSC also expects AI to expose poorly coded systems while vendors adopt AI to remove flaws.
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AI Attack Capability Rising Faster Than Expected Per UK Tests

🔍 New benchmarks from the UK’s AI Security Institute (AISI) show leading AI models rapidly improving at multi-stage penetration testing, with the difficulty of tasks solvable by models doubling every 4.7 months as of early 2026. The tests measure the longest task an AI can complete with 80% success relative to human work-hours, emphasizing autonomous chaining of steps rather than raw speed. While there are caveats — token limits and inconsistent model performance — the findings highlight growing offensive and defensive implications for enterprise security.
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UK Regulators Warn Financial Firms on Frontier AI Risks

⚠️ On May 15 the UK government, the Financial Conduct Authority and the Bank of England issued a joint warning about cybersecurity threats from frontier AI. They noted models can outperform skilled practitioners at greater speed, scale and lower cost, amplifying risks to firms, customers and financial stability. The statement urges firms to strengthen governance, vulnerability management, third-party controls, protection and response capabilities and points to NCSC resources and prior resilience guidance.
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AWS AI Security Framework: Controls by Layer and Phase

🔒 The AWS AI Security Framework presents a structured model that helps security and business leaders align the right controls to the right use case, at the right layer, and at the right phase so AI can move from prototype to production securely. Its core principle is that you build AI on top of security, not add security later. The post maps controls across three layers—infrastructure, identity and data, and AI application—and across four use cases from answering to agentic and physical AI. It highlights Amazon Bedrock and AgentCore as pillars that decouple model choice from security infrastructure.
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Preparing for an Imminent Surge in Software Patching

🔧 Cisco Talos argues that rapid advances in AI-driven code analysis will soon expose decades of latent software defects, triggering a likely surge in vulnerability disclosures and urgent patches. While AI can augment human reviewers by scanning code at scale, threat actors will also use these tools to find exploits. Organizations should reassess patch prioritization, scale deployment processes, and plan for systems that cannot be quickly patched. Talos recommends zero trust, centralized logging, PowerShell script block logging, and updated incident response playbooks.
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Threatsday Bulletin: PAN-OS RCE, AI Risks, Supply-Chain

🔥 Palo Alto released fixes for CVE-2026-0300, a critical PAN-OS buffer-overflow exploited in the wild to drop payloads like EarthWorm and ReverseSocks5. The bulletin also highlights new and recurring threats including zero-auth API data leaks at an AI training vendor, an FCC extension for router updates, supply-chain contests, and sophisticated phishing campaigns. Several incidents employ weaponized attachments, tokenizer tampering in AI models, and open-source tools to achieve stealthy remote access and long-term persistence.
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Defense in Depth for Autonomous AI Agents

🛡️ Microsoft Security explains how rising agentic autonomy reorients security from models to how agents are assembled, constrained, and governed inside applications. The post identifies amplified risks—agent hijacking, intent breaking, data leakage, supply chain compromise—and shows why the application layer is decisive because builders fully control permissions, tool access, and failure handling. It recommends concrete design patterns: agents as microservices, least permissions, deterministic human-in-the-loop, and distinct agent identity to limit blast radius and preserve auditability.
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Most Organizations Deploy AI Agents Despite Identity Risks

🔒 Semperis finds that 93% of global organizations use or plan to use AI agents for security tasks such as password resets and VPN access, while 92% report AI on endpoints with SSH and encryption key access. The survey of 1,100 organizations warns of over‑permissioned and abandoned 'zombie' non‑human identities that increase hijack risk. Semperis recommends treating agents as NHIs, enforcing least‑privilege, and improving observability and recovery readiness.
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ICO issues five-step guidance on AI-driven cyber risk

🔐 The ICO has published a five-step guide urging organisations to prepare for AI-enhanced cyber threats, including deepfake social engineering, adaptive malware and automated exploitation. It points readers to the NCSC's updated Cyber Assessment Framework and expects baseline adoption of Cyber Essentials and the UK Cyber Governance Code. The guidance emphasises robust patching, MFA, least‑privilege, supply‑chain vetting, DPIAs for high‑risk AI and human oversight of AI-enabled defences.
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Fired Employee Used AI to Hide Deletion of Federal Data

🔒 Two former hosting-company employees allegedly deleted dozens of customer and federal databases after being fired; one brother was convicted on computer-fraud and related charges. Investigators say one used a public AI chatbot to ask how to clear SQL and Windows logs, aiding evidence destruction. Experts warn this underscores failures in off-boarding and privileged access controls and call for stronger AI guardrails and real-time revocation.
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Palo Alto Networks Expands Frontier AI Defense Alliance

🛡️ Palo Alto Networks is expanding its Frontier AI Alliance to scale delivery of autonomous, real-time defenses. Building on the Frontier AI Defense initiative and recent testing of frontier models (including Anthropic’s Mythos, Claude Opus 4.7, and OpenAI’s GPT-5.5-Cyber), the company has added a new cohort of strategic partners. By pairing Palo Alto Networks’ technology with partners’ consulting expertise, the program aims to deliver AI readiness at scale and machine-speed MTTR to customers.
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Defender's Guide: Frontier AI Impact on Cybersecurity

🔒 Palo Alto Networks reports ongoing testing of frontier AI models, including Anthropic and OpenAI, finding they rapidly surface code vulnerabilities and potential exploit paths. In the May 'Patch Wednesday' advisories the majority of findings originated from these AI scans, prompting broad rescanning and remediation. The company warns of a narrow three-to-five-month window before AI-driven exploits spread and offers Unit 42 services to help organizations respond.
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Building Resilient Transportation Systems with Google AI

🚦Google outlines a blueprint for safer, more resilient transportation systems powered by AI. Leaders from Utah DOT, CalSTA, and Deloitte describe tools like Roadway Safety Insights (RSI) that integrate dozens of datasets to predict and mitigate risks, shifting agencies from reactive fixes to proactive safety. The article stresses resolving fragmented data and creating trusted single sources of truth to maximize AI value. Readers are invited to a Best of Next Public Sector Webinar and live demos at ITS America in June.
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Microsoft MDASH: Multi-Model AI for Vulnerability Discovery

🛡️ Microsoft introduced MDASH (multi-model agentic scanning harness), a model-agnostic AI system in limited private preview designed to discover, validate, and prove exploitable defects in large codebases. The system orchestrates more than 100 specialized agents across frontier and distilled models in a structured pipeline that builds threat models, runs auditor and debater stages, groups equivalent findings, and proves vulnerabilities. Microsoft reports MDASH uncovered 16 issues fixed in this month’s Patch Tuesday, including two critical Windows networking and authentication flaws.
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From WarGames to Cyberwar: Nation-State Cyber Threats

🔍 In a RSA 2025 conversation, Allie Mellen, author of Code War, frames modern cyber conflict through historical doctrine, showing how nations' distinct strategies shape attacks and espionage. She cautions that attribution based solely on technical signals is insufficient because actors can forge signatures and deploy false flags, so motive and context matter. Mellen warns that AI will make attacks faster and more adaptive, and urges defenders to strengthen fundamentals and adopt automation and AI on the defensive side.
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Autonomous Validation: Closing the AI-Speed Breach Gap

🛡️ In a post-Mythos environment, AI-driven attacks can weaponize vulnerabilities within hours or minutes, outpacing traditional defensive cycles. Picus Security argues defenders must pair continuous Breach and Attack Simulation (BAS) with autonomous pentesting to validate controls and reveal genuine attack paths. Operational friction — the "spaghetti handoff" between tools and teams —, not tooling alone, is the main cause of delayed response, so validation must be automated end-to-end.
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