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Generalized Agent Iteration: One Formal Framework for Iterative Policy Improvement and Recursive Self-Improvement
Generalized Agent Iteration formally unifies iterative policy improvement and recursive self-improvement, defining axes that distinguish anchored, goal-drifting, and self-referential agents.
The paper proposes Generalized Agent Iteration (GAI), a formal framework that models learning as a cycle of agent evaluation and agent improvement, defining the agent as a configuration of modifiable components. Two dials—whether the improving mechanism is part of the agent and whether the evaluation standard is grounded outside it—separate generalized policy iteration (GPI) from recursive self-improvement (RSI) and classify systems as anchored, goal drift, or fully self-referential. The framework places existing systems on shared axes and makes defects of recursive self-improvement statable one condition at a time.
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I've factored the RSA keys of a Certificate Authority from the 90s
Security researcher factored two 512-bit RSA root CA keys from defunct 1990s certificate authority E-Certify using CADO-NFS on a desktop in roughly 30 hours each.
A researcher extracted legacy root certificates from archived Netscape and Internet Explorer installers, identifying two 512-bit RSA roots shipped with Netscape 4.51 in 1999 by the defunct Canadian CA E-Certify. Using CADO-NFS on a Ryzen 9 5950X desktop, the keys were factored in 32 and 29 hours respectively, allowing private key reconstruction. The work comes shortly after RSA-260 (862-bit) was factored, the largest known factorization to date. The researcher also built a legacy TLS server and published keys and tools on GitHub.
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A Deep Generative Model for Synthesizing Labeled Wireless Signals
Researchers propose IIns-GAN, a GAN that synthesizes realistic labeled ultra-wideband wireless signals, cutting dataset costs for wireless sensing training.
The paper introduces Inter-Instance Generative Adversarial Networks (IIns-GAN), a deep generative method that synthesizes realistic wireless signals with position-related labels to avoid costly real-world measurement and labeling. Unlike environment-model-based synthesis, the generated signals adapt to different environment scenarios and support training tasks such as distance estimation and environment identification. Experiments on public Ultra-Wideband (UWB) datasets show the synthetic signals closely mirror real measurements and improve model training performance.
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Hillingar - MirageOS Unikernels on NixOS
A technical write-up details Hillingar, enabling reproducible Nix-based builds and NixOS deployment of MirageOS OCaml unikernels such as authoritative DNS servers.
This blog post (published December 2022, updated February 2025) describes Hillingar, work from the author's master's thesis enabling reproducible builds and deployments of MirageOS OCaml unikernels using Nix and a custom NixOS module, demonstrated with an authoritative DNS server. MirageOS unikernels embed application and low-level OS code in a single kernel, allowing dead-code elimination that reduces attack surface and improves efficiency. The post covers challenges such as solving opam dependency version constraints when linking a single dependency set.
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The democratization of cyber warfare — and what it means for CISOs
CSO Online argues AI is democratizing cyber warfare, citing Taiwan's first largely autonomous AI-driven attack that hit 85 government accounts.
CSO Online argues AI is accelerating the democratization of cyber warfare by collapsing cost and skill barriers, with effects already reaching the private sector. It cites the August disclosure of the first largely autonomous AI-enabled attack on Taiwan government infrastructure, where up to eight agents operating simultaneously compromised at least 85 government accounts and exfiltrated more than 2,500 personnel records before expanding to the nuclear safety agency and energy companies. The piece places this in a historical arc from crossbows to cheap drones and cites Kane Gamble's 2015 solo social-engineering compromise of senior US intelligence officials as evidence that low-resource attackers were already viable.
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Securing Claude Code: The New Compliance API, Local Visibility, and Identity Governance
Anthropic's new Compliance API endpoints expose Claude Code local session transcripts, highlighting governance gaps for endpoint AI agents.
Anthropic added local session transcript endpoints to its Compliance API on August 11, 2026, giving security teams visibility into prompts, bash commands, file operations, and MCP commands run by Claude Code harnesses on endpoints. The article argues local harnesses break the classic shared-responsibility model, citing Token Security data that 68.6% of discovered AI agents run on endpoints, and a Cloud Security Alliance survey of 418 IT and security professionals in which 82% found an unknown agent within the past year. It outlines three governance layers: Anthropic managed settings as a policy baseline, the Compliance API for cloud-visible transcripts, and endpoint telemetry to connect agent activity to identity, credentials, and permissions.
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Confluent for Kubernetes brings cloud-native capabilities to data streams in private infrastructures
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