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New Proofpoint Enterprise Archive capabilities help streamline e-discovery and supervision processes
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Passkey-themed social engineering leads to identity and cloud compromise
Microsoft tracks ongoing cloud intrusions where passkey-themed helpdesk lures enable AiTM credential theft, MFA persistence, and SharePoint data theft.
Microsoft Security Research is tracking active cloud-based intrusions, observed since May 2026, that begin with helpdesk impersonation calls and SMS lures urging urgent passkey, MFA, or SSO updates. The lures lead to adversary-in-the-middle phishing or device-code authentication flows that capture credentials and session tokens or grant actor access, after which the actors add authentication methods, conduct Microsoft Graph reconnaissance, and download SharePoint and OneDrive content via REST APIs. Phishing domains embed victim organization names as subdomains (e.g., contoso.add-passkey[.]com), are often registered with Nicenic, and go operational within hours. Microsoft advises revoking sessions and removing unauthorized authentication methods for confirmed compromises.
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Why The Vulnerability Backlog Is About To Get Worse
Recorded Future analysis says AI-driven vulnerability discovery and faster weaponization will grow the triage backlog while shrinking defenders' response windows.
Disclosed vulnerabilities rose from roughly 21,000 in 2021 to nearly 50,000 in 2025, while Recorded Future assessed only 446 as actively exploited in 2025. VulnCheck found nearly 29% of 2025 KEV entries were exploited on or before CVE publication. The authors argue AI-assisted discovery and automated exploit development will multiply credible reports, cut disclosure-to-exploit time toward minutes, and force re-evaluation of medium-severity flaws as exploit-chain components.
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Top 10 Best Cloud Access Security Broker (CASB) Solutions in 2026
2026 CASB guide ranks Netskope first for depth and Microsoft Defender for Cloud Apps for Microsoft estates, as standalone CASB fades into SSE.
Buyer's guide covers ten CASB products across four enforcement modes: API, forward proxy, reverse proxy and log-based discovery. Netskope leads on SaaS activity context depth, while Microsoft Defender for Cloud Apps wins on Microsoft 365 E5 estate economics. The guide argues standalone CASB purchases have largely disappeared into SSE platforms and increasingly overlap with SSPM.
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Dream-RSI: Recursive Self-Improvement through Evolving Worlds
Dream-RSI refines exploration policies by dreaming in replay simulators built from discovery history, cutting discovery costs across coding tasks.
Dream-RSI is a framework for scalable recursive self-improvement in autonomous coding agents, where a lightweight orchestration layer makes exploration explicit and programmable while leaving the underlying agent unchanged. Its core insight is that accumulated discovery history can serve as a replay simulator over the realized search space, providing immediate, low-cost off-policy feedback to evaluate and refine exploration policies without expensive online evaluations. Across algorithm engineering, mathematical optimization, and GPU kernel engineering, Dream-RSI achieves competitive or improved discovery quality at substantially reduced cost.
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When an Attacker Meets a Group of Agents: Navigating Amazon Bedrock's Multi
Unit 42 red-teamed Amazon Bedrock multi-agent applications, demonstrating prompt-injection attack chains that leak agent instructions and invoke tools, mitigated by Bedrock Guardrails.
Unit 42 red-teamed Amazon Bedrock Agents' multi-agent collaboration in Supervisor and Supervisor with Routing modes. The demonstrated attack chain detects the operating mode, discovers collaborator agents, delivers attacker-controlled payloads, and can disclose agent instructions and tool schemas and invoke tools with attacker-supplied inputs. No vulnerabilities were found in Bedrock itself, and the built-in prompt attack Guardrail blocked the attacks when properly configured. The researchers collaborated with Amazon's security team and frame the findings as a broader prompt injection risk for LLM-based systems.
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