You're deploying it wrong! TeamCity, Subversion & Web Deploy part 4: Continuous builds with TeamCity
Why don't machine learning research agents overfit?
Amazon researchers explain why ML research agents avoid benchmark overfitting, attributing generalization to compressibility of successful strategies.
Amazon Science summarizes the paper "What fits (into few tokens) doesn't overfit: Compression and generalization in ML research agents," which investigates why benchmark hill-climbing loops, whether run by human communities or LLM research agents, do not produce rampant overfitting. The explanation formalizes Occam's razor via a counting argument: successful ML strategies are highly compressible, so short descriptions lack room to memorize benchmark data and must capture real structure. LLM-based agents, being resettable and controllable, allow this hypothesis to be tested empirically.
ClearFake WebDAV infection chain delivers Amatera stealer, ZigCryptoStealer, and NetSupport Manager
Cisco Talos details ClearFake WebDAV chains delivering Amatera stealer to a Ukrainian government organization, with cryptocurrency and credential theft payloads.
Cisco Talos investigated DLL executions named 'verification.google' via WebDAV UNC paths at a Ukrainian government organization, tracking the actor as UAT-10820 and assessing with moderate confidence the activity is Russian and opportunistic rather than targeted. The infection chain uses ClearFake JavaScript injected via a Cloudflare Worker, EtherHiding storage on BNB Smart Chain contracts, and a ClickFix fake Google CAPTCHA prompt to deliver Amatera stealer. Secondary payloads differ by C2: one loader deploys ZigCryptoStealer with a Go reverse TCP proxy and a vulnerable driver that kills EDR, while the other installs an unauthorized NetSupport Manager with a Russia-based C2. Similar Amatera chains were separately documented by Malwarebytes and Blackpoint Cyber, but with no shared infrastructure.
Foundation Models for Generalizable Semantic and Goal-Oriented Communication
FMSGOC uses vision-language foundation model priors plus diffusion reconstruction to enable generalizable semantic communication at 0.039 bits per pixel for 6G.
FMSGOC targets generalization failures in semantic and goal-oriented communication for 6G by leveraging broad visual-linguistic foundation model priors. A vision-language model selects sparse, goal-aligned semantic anchors while a fine-tuned diffusion model performs masked completion to reconstruct images at the receiver, decoupling what to send from how to reconstruct. On CIFAR-10 it reaches 0.039 bits per pixel with cosine similarity 0.87-0.90 and 0.83-0.86 on unseen ImageNet inputs, outperforming end-to-end baselines at lower bit rates.
Critical Cisco Nexus 9000 Flaw Lets Unauthenticated Remote Attackers Run Code as Root
Cisco patches critical CVE-2026-20212 (CVSS 9.8) in Nexus 9000 switches allowing unauthenticated remote root code execution, plus IOS XR hardening release.
Cisco released fixes for CVE-2026-20212 (CVSS 9.8), a flaw in 10 Silicon One-based Nexus 9000 switch models that binds a service to an unrestricted IP, leaving TCP ports 43210/43211 reachable in the default Layer 3 VRF and allowing unauthenticated remote attackers to execute code as root; exploitation attempts can also crash the S1HAL process. 45 NX-OS releases (10.3(1) through 10.6(3s)) are affected, with mitigations including infrastructure ACLs, the Live Protect shield lp00031, and fixed releases identified via Cisco's Software Checker. Cisco simultaneously issued an IOS XR hardening release bundling 7 umbrella CVEs, two rated 9.8 (CVE-2026-20274 for memory-safety bugs and CVE-2026-20279 for access-control bugs), affecting all releases with SMUs available for 14 releases and upgrades required for 93 of 111 listed releases. No malicious exploitation was reported as of the September 2 disclosure.