All news with #ai security tag

🔒 AI has increased employee awareness of cyber risks, but understanding threats is not the same as being ready to respond. The 2025 Security Awareness and Training report shows high awareness but a clear readiness gap: only 40% of organizations say employees are highly prepared for AI-based threats. Fortinet advocates behavior-first, role-based training with short scenario-driven modules to help employees apply judgment, verify requests, protect data, and use AI tools safely.

🛡️ A new phishing-as-a-service operation named Forg365 targets Microsoft 365 by combining device-code phishing, AitM tactics, antibot evasion, AI-assisted lure creation, and post-compromise mailbox operations. Distributed via Telegram and offered as a subscription, the kit uses legitimate delivery infrastructure like Amazon SES and SendGrid to blend into normal email flows before redirecting victims to attacker-controlled domains. The platform includes a clearnet operator panel, OAuth and token handling, and a Chromium extension called ForgCookie that automates cookie refresh and sustained access to compromised accounts.

🛡️ Kaspersky explains a new capability to detect AI-generated business email compromise (BEC) messages by identifying both BEC-specific phrases and linguistic patterns typical of machine-generated text. The company notes that cybercriminals increasingly use large language models to craft persuasive phishing and BEC campaigns, and this detection works across eight languages. The feature is integrated into Kaspersky Secure Mail Gateway and available with the KSMS Plus license after the KSMG 3.1 update.

🧠 The article argues that effective AI-enabled SOCs should mirror Kahneman’s dual-system model: a fast, autonomous layer handling ~98% of alerts and a slow, deliberative layer for the small fraction needing human judgment. It warns against asking analysts or large language models to perform repetitive triage and emphasizes in-house investigation to retain the knowledge base. The right architecture frees analysts to supervise and improves detection over time.

🦖 The article compares Jurassic Park’s failed containment to modern cybersecurity, arguing that visibility is often mistaken for control. It asserts that tooling, dashboards, and backups provide friction but not guaranteed survivability, and that dynamic cloud and AI-driven change invalidate static recovery assumptions. The piece recommends continuous resilience engineering, dependency awareness, and validation to operate through inevitable disruptions rather than assume they can be prevented.

🔒 At AWS and other large vendors, AI is compressing months of security work into minutes by automating red-team findings, generating detections, and accelerating remediation. Experts debate whether this will widen an existing security class divide—where large organizations have talent, data, and infrastructure while smaller ones struggle—or democratize advanced capabilities. Key concerns include costs, privacy tradeoffs, token pricing, and the operational depth needed to safely run AI in production.

🛠️ Amazon EMR on EKS now integrates an Apache Spark troubleshooting agent that provides automated root cause analysis and PySpark recommendations through natural language, simplifying diagnosis of job failures. The agent inspects Spark History Server data, executor logs, and cluster configs to detect issues like memory errors, data skew, resource contention, and connectivity problems. Accessible via a "Troubleshoot with AI" option in the EMR on EKS console and via MCP with compatible AI coding agents, the feature is read-only, IAM-authenticated, logged in CloudTrail, and available in Regions with SageMaker Unified Studio.

🔒 This progress report outlines Microsoft’s Secure Future Initiative (SFI) two-year effort to strengthen security foundations, apply AI for proactive defense, and prepare for future challenges such as post-quantum risks. It highlights layered controls—identity, access governance, segmentation, and secure engineering defaults—paired with cultural and governance measures to make protections durable. The report also shares lessons, practical guidance, and metrics of organizational adoption.

🛡️ Microsoft says it is deploying AI-driven analysis to uncover more zero-day vulnerabilities across the Windows codebase, warning customers to expect an increased number of security updates. The company described a multi-model agentic scanning harness (MDASH) and a separate prove pipeline to validate findings, aiming to reduce false positives and shorten review windows. Microsoft also plans to update its Secure Development Lifecycle to address AI-enabled attack techniques while retaining human oversight to ensure update quality.

🔐 The article argues that CISOs must shift from merely securing the business to enabling secure business operations with AI. It emphasizes focusing on intent, governance, and scope rather than assigning blame to AI agents, and recommends partnering with engineering, prioritizing high-risk exposures, and embedding continuous assurance into CI/CD. The piece frames AI security as a strategic enabler that preserves speed and mitigates risk.

🛡️ At Engage 2026 in Paris, Check Point CTO Jonathan Zanger discussed how AI is reshaping cybersecurity operations, enabling defenders to scale threat monitoring and red-team testing while also empowering attackers. He warned that AI increases attack surface as organizations connect models to enterprise systems and urged integrating security from the start of any AI project. Zanger emphasized prevention, collaboration across defenders, and protecting AI platforms themselves to mitigate rapidly evolving AI-driven threats.

🛡️ A Wiz report details "GhostApproval," a vulnerability pattern in six AI coding assistants that lets malicious repos use symlinks to escape sandboxes and trick human approvers into authorizing writes outside the workspace. Vendors including AWS, Cursor and Google patched quickly; others acknowledged or had already fixed the issue. Analysts warn this reflects a category-wide design problem where human-in-the-loop prompts can be misleading and enterprises must treat these tools as privileged software and enforce stronger controls.

🛡️ Microsoft says AI-driven discovery is increasing the pace of vulnerability identification in Windows, leading to a likely rise in monthly security updates. The company uses its MDASH system to scan critical binaries and validate potential issues with multiple AI models, then runs a Windows-specific validation pipeline to reduce false positives. Microsoft also applies AI to accelerate triage, suggest fixes, and find similar bugs, while keeping humans in the review loop. The firm is updating its Secure Development Lifecycle to address AI-enabled attack techniques as adversaries also leverage AI.

🔒 The UK’s NCSC and DSIT unveiled a blueprint called Cyber Shield to deploy autonomous AI agents that detect and neutralize cyberattacks at machine speed. The plan uses cooperating “red” and “blue” agents to identify weaknesses, detect threats and progressively automate remediation while operating under organizational control. The initiative emphasizes explainable and federated AI, industry partnerships, and a staged rollout beginning with government and critical sectors.

🔒 A MetaCompliance report (July 9) based on responses from over 200 European CISOs finds 78% believe C-level executives do not fully grasp cybersecurity risks tied to employee behaviour. The survey highlights fading leadership support for security awareness, with 79% saying backing wanes over time and 40% worried employees share sensitive data with generative AI tools. AI-driven social engineering is cited as a key factor eroding confidence in organisational cyber resilience.

🛡️ Five Eyes agencies warned that AI's rapid development raises cyber risks, particularly autonomous hacking and automated attacks. Bruce Schneier explains that AI widens the gap between skill and ability, enabling less-skilled actors to cause greater harm while also offering defensive tools. He argues that guardrails on large platforms won't stop open-source models and urges using AI for defense across all heightened risks.

🔒 This article examines the risks of agentic AI and non-human identities in enterprise environments, illustrating incidents where LLM-based agents caused outages due to weak identity controls. It argues that existing IAM models are insufficient for agents that act autonomously, and cites industry guidance from Gartner, OWASP, CISA and NIST. The author proposes six minimum requirements and a cumulative six-stage NHI maturity model to ensure defensible production deployments.

🔒 Over 70 cybersecurity organisations have signed the new CREST AI Charter, launched on July 9, committing to nine principles governing AI-enabled cybersecurity activities. The charter covers accountability and governance, transparency of use, documentation and auditability, boundaries and control, data handling and sovereignty, security and confidentiality, secure development, supply chain assurance and resilience. Signatories will maintain human oversight, document AI use, disclose data practices and implement secure development and supply chain controls. CREST intends the charter as a self-regulatory foundation to drive standards and harmonisation across industry and regulators.

🤖 ESET analysis shows cybercriminals increasingly use AI agents and chatbots to autonomously plan and execute attacks. Researchers reviewed 900,000 AI skills in public repositories and found tens of thousands of suspicious and thousands of malicious toolsets, expanding the attack surface. These agentic tools can exfiltrate data, execute malware, override instructions, and be repurposed from legitimate utilities into harmful capabilities. ESET urges organizations to enforce policies and caution users about downloading free tools from untrusted sources.

🖼️ Meta introduced Muse Image, an image-focused AI from Superintelligence Labs that can use public Instagram posts and reels to generate AI-created images, enabled by default. The feature lets users @-mention public accounts in the Meta AI app to incorporate specific profiles' media into new images and is being integrated into Instagram and WhatsApp in select countries. Users can opt out via Instagram Settings > Sharing and reuse, though previously created content will remain if generated before disabling the setting. For minors with public accounts, only followers may reuse their media if allowed; existing remixes won't notify original owners, and deleted content may be removed if accounts go private for over 24 hours.