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Switzerland's Federal Government Is Replacing Microsoft on 3k Computers

Switzerland's Federal Chancellery launched a pilot replacing Microsoft 365 with open-source openDesk on 3,000 federal workstations by end of 2027.

Switzerland launched a CHF 9 million pilot to migrate 3,000 federal workstations (about 7% of the federal workforce) from Microsoft 365 to the German open-source openDesk suite, targeting completion by end of 2027. The move follows a successful 172-employee proof of concept (PoC BOSS) and the 2024 EMBAG open-source law, driven by digital sovereignty concerns about foreign access to Swiss government data. The Swiss Army's Cyber Command plans a faster migration, replacing Microsoft 365 with openDesk by October 2026, while Microsoft is investing over CHF 325 million in Swiss AI and cloud infrastructure.

Hacker News · security · 9d agoPolicy & legalHN 354↑ · 278 comments

Severity Is Not a Strategy: What CISA BOD 26-04 Means for the Future of Federal Software Security

CISA's BOD 26-04 replaces severity-based federal patching with risk-based remediation deadlines of 3, 14, or 60 days.

CISA's Binding Operational Directive 26-04, released June 10, 2026, replaces BOD 19-02 and BOD 22-01 for Federal Civilian Executive Branch agencies and shifts remediation prioritization from CVSS scores to risk context. Agencies assess four factors: public exposure, KEV listing, exploit automatability, and whether exploitation grants partial or total asset control, resulting in 3-, 14-, or 60-day remediation windows or next-upgrade fixes. In CISA's first review at a large civilian agency, only 1% of vulnerabilities required three-day remediation while over 60% could wait for future system upgrades. The directive also requires forensic analysis when exploitation is suspected, and Checkmarx argues the same risk-based logic must extend upstream into software development and SBOM-driven exposure management.

Checkmarx · 7d agoPolicy & legal

Why federal cyber defense demands an offense-driven mindset

Opinion piece argues federal agencies should prioritize exploitability and autonomous penetration testing over static CVSS-based patching, citing CISA's BOD 26-04 and NSA's CAPT program.

The author argues that static CVSS-driven patching leaves federal agencies exposed because vulnerable does not equal exploitable, and adversaries chain misconfigurations and stolen credentials instead of burning zero-days. The piece cites CISA's BOD 26-04 and the NSA's Continuous Autonomous Penetration Testing (CAPT) program, which logged 28,282 completed pentests across 822 Defense Industrial Base organizations and closed 71% of critical findings within 30 days. It recommends defining risk by exploitability and mission impact and augmenting human pentesting with autonomous validation and verification.

CyberScoop · 8d agoIndustry

Whistleblower says USPS deploying new, ‘untested’ IT systems governing mail

A whistleblower alleges USPS is rushing untested IT systems that could reject thousands of mail-in ballots ahead of the 2026 midterm elections.

A whistleblower complaint released by Sen. Richard Blumenthal says USPS is deploying three new, largely untested IT systems — including the Federal Ballot Mail Portal — that could reject entire ballot batches over single scan errors. The systems were developed in weeks without standard testing or interoperability checks, and USPS allegedly continued work despite court injunctions against its rule changes. House Oversight Democrats demanded USPS halt implementation, and election experts warn the design could lead to new lawsuits and mass ballot denials.

CyberScoop · 15d agoPolicy & legal

What’s next for CISA’s CDM program that gives cybersecurity tools to federal agencies

CISA officials outline future plans for the CDM program, emphasizing speed, automation, unified data, and data-driven federal risk management.

Speaking at an Elastic Federal Cyber Defense Breakfast, CISA officials described next steps for the Continuous Diagnostics and Mitigation (CDM) program that supplies cybersecurity tools to federal agencies. Acting deputy program manager Richard Grabowski named velocity, unification, and data-driven risk management as core goals, including a three-year roadmap to expand SIEM-as-a-Service. Federal CISO Mike Duffy urged aggregating demand across agencies, buying outcomes rather than products, and designing acquisition for continuous improvement. CISA's Matt House tied the program's evolution to post-SolarWinds needs for a government-wide common operating picture.

CyberScoop · 1d agoPolicy & legal

Jail time for Maine child in 764 marks turning point in federal law enforcement

A 17-year-old from Maine became the first minor federally adjudicated for 764 extremist crimes, including child exploitation, signaling a policy shift on prosecuting juveniles.

The FBI said a Maine teenager is the first child federally charged and adjudicated for crimes tied to the nihilistic violent extremist collective 764, part of The Com network. Charges include conspiracy to sexually exploit a child, distributing CSAM, interstate threats, cyberstalking, and identity theft. The case marks a turning point in federal policy on prosecuting juveniles and continues heightened enforcement: Kyle Spitze was sentenced to 77 years and Alexis Chavez to 40 years in related cases. The FBI is investigating more than 500 subjects connected to 764 and its offshoots nationwide.

CyberScoop · 14d agoPolicy & legal

Lawmakers seek watchdog review of federal hacking of Americans

Sen. Wyden and Rep. Casar asked the GAO to review the federal government's use of spyware and hacking tools against Americans.

Sen. Ron Wyden and Rep. Greg Casar sent a letter to the Government Accountability Office requesting a review of federal law enforcement hacking operations, including spyware use, Rule 41 hacking powers, and acquisition of hacking tools. The letter cites ICE's confirmed work with spyware vendor Paragon and concerns about abuse of invasive surveillance capabilities. The lawmakers note the government publishes no annual reports on hacking operations unlike wiretaps.

CyberScoop · 26d agoPolicy & legal

The AI policy window is open. We need to act.

OpenAI calls for mandatory national AI safety regulation and backs four California AI safety bills as capabilities accelerate.

OpenAI argues the rapid pace of AI progress, including signs of AI-accelerated research, requires urgent policy action through mandatory, capability-based national regulation. The company endorses four California bills (SB 813, AB 1405, SB 1119, AB 1864) covering independent safety assessments, AI auditor standards, youth protections, and safeguards against AI-enabled biological threats. It also commits to industry-led frontier standards, international coordination, and strengthening internal safeguards such as universal trajectory monitoring and mandatory alignment-evaluation gates for its Astra model. The post references chief scientist Jakub Pachocki's warning about recursive self-improvement and Greg Brockman's "defenders window" concept.

OpenAI News · 7d agoAI policy

Horizon3 Names Chad Keefer Vice President of Federal Sales

Horizon3.ai appointed federal sales veteran Chad Keefer as Vice President of Federal Sales to expand its civilian, defense, and intelligence business.

Horizon3.ai named Chad Keefer, a federal go-to-market veteran, as its Vice President of Federal Sales. He will lead growth across civilian, defense, and intelligence agencies. The appointment signals a push to expand the vendor's federal market presence.

Horizon3.ai · 22d agoIndustry

Expanding AI access and cyber defense for federal, state, local, and tribal governments

OpenAI and GSA agreed to provide ChatGPT to federal, state, local, and tribal governments with $0 licenses, 50% off usage, and cyber-defense access.

OpenAI for Government and the U.S. General Services Administration announced a 27-month agreement (October 1, 2026 through December 31, 2028) waiving the $15 per-user monthly license fee and cutting usage costs 50% for federal, state, local, and tribal agencies. More than one million government employees already have ChatGPT access, with eligibility extending across a roughly 23 million-person U.S. public-sector workforce. Every verified government entity is approved for Daybreak Blue cyber-defender access at 50% off, with Daybreak Red available for vulnerability research, exploit validation, and red teaming at standard pricing. The deal builds on the $1 billion Daybreak for Frontline Defenders commitment announced the prior week.

OpenAI News · 6d agoAI industry1

The push to designate AI as the next critical infrastructure sector

Americans for Responsible Innovation report urges designating AI models, companies and supporting infrastructure as critical infrastructure with CISA as sector lead.

A report from the nonprofit Americans for Responsible Innovation calls for the federal government to declare the AI sector — including frontier model designs, model weights, datacenters, AI hardware and semiconductors — the 17th critical infrastructure sector, with CISA as the lead agency for sector cyberthreats. The authors argue AI is concentrated among a handful of foundation models and interdependent with other sectors, so a single attack on the AI stack could cascade widely, citing incidents like Iranian drone attacks on Amazon datacenters. Former DHS officials note the designation would unlock federal resources such as CDM access and threat intelligence, but warn that picking a lead agency could trigger a bureaucratic turf war with Commerce and Treasury.

CyberScoop · 27d agoAI policy

Trump turns to private sector in offensive hacking operations memo

Trump signed a national security memorandum authorizing vetted private companies to conduct offensive cyber operations against transnational criminal organizations under federal oversight.

The memorandum creates a federal coordination center program authorizing 'Participating Companies' to conduct Cyber Surveillance Operations and Cyber Effects Operations against foreign cyber-enabled transnational criminal organizations. Participating firms must contract with the Justice Department or Department of Homeland Security, undergo vetting, and comply with existing laws including the Computer Fraud and Abuse Act. The White House cited sustained fraud and cyber-enabled campaigns from TCOs as justification, building on a March fraud-focused executive order. Experts including Veracode co-founder Chris Wysopal called it a major shift in U.S. cyber policy, though it stops short of broader 'hack back' proposals.

CyberScoop · Aug 13, 2026Policy & legal1

OmniMed-FL: A Robust Multimodal Federated Learning Framework for Clinical Diagnosis

OmniMed-FL benchmarks multimodal federated learning for chest radiograph diagnosis across 3-20 clients, with FedProx leading under severe non-IID skew.

OmniMed-FL studies multimodal federated learning combining chest radiographs and clinical notes for five-class condition classification under HIPAA/GDDR-compliant decentralized training. It benchmarks eight fusion strategies, imputation rules, and federated baselines under Dirichlet non-IID partitioning across 3-20 hospital clients. With 5 clients and severe skew (alpha=0.1), FedProx scored 0.737 macro-F1 versus 0.662 for FedAvg and 0.297 for local-only training. Multimodal fusion beat unimodal inputs (0.956 vs 0.934 text, 0.664 images) on the synthetic corpus.

arXiv cs.AI / cs.LG / cs.CL · 7d agoAI research1

Cascading Gradient Inversion via LT-Code Inspired Peeling in Federated Learning

New gradient inversion attacks tied to erasure-coding theory recover 94–100% of ImageNet batches, showing federated learning privacy leakage is underestimated.

The paper connects gradient inversion in federated learning to erasure-correcting code theory, constructing analytic attacks that exceed previously known recovery bounds. The attacks recover batches exactly, with every sample's label, from a single FedSGD round, and certify each recovery without ground-truth data. On eight image and tabular benchmarks, even a passive attacker observing an honestly trained network recovers 94–100% of ImageNet batches up to size 128, and more than 90% actively at batch sizes of several hundred. The authors conclude that federated learning's privacy leakage has been underestimated.

arXiv cs.CR · 7d agoResearch

ZK-Trace: Certified Collusion Tracing with Zero-Knowledge Credentials for Federated GNSS Interference Monitoring

ZK-Trace combines Tardos fingerprints and zero-knowledge credentials to trace leaked classifier copies in federated GNSS monitoring without leaker cooperation.

ZK-Trace addresses leakage of a proprietary classifier distributed to partly trusted stations in federated GNSS interference monitoring, combining public identity marks, recipient-specific Tardos fingerprints, and zero-knowledge credential verification to support offline tracing. The paper provides false-accusation and tracing-score bounds with an interval-arithmetic checker allocating a common budget across accusation and tamper decisions. In a simulated GNSS federation it isolates all 160 single-owner copies and traces 712 of 720 two-owner mixtures with a 0.001 false-naming budget, while feature marks survive feature matching in 20/20 runs at 4.8 percentage-point accuracy cost but are erased by function-only distillation.

arXiv cs.CR · 8d agoResearch

When Topology Betrays Privacy: Lattice-Based Reconstruction Attacks on Secure Aggregation in Decentralized Federated Learning

Researchers show colluding nodes in decentralized federated learning can reconstruct private updates despite secure aggregation, using lattice-based attacks tied to the Hidden Subset Sum Problem.

Secure aggregation in decentralized federated learning is widely assumed to hide individual model updates. The authors show that sparse decentralized topologies give colluding semi-honest nodes asymmetric aggregate views exposing hidden linear combinations of honest participants' private states. They establish a formal connection to the Hidden Subset Sum Problem and design a lattice-based reconstruction approach combining lattice reduction with structural filtering. Evaluations on image, tabular, and text tasks show attackers recover local updates and can reconstruct private training data.

arXiv cs.CR · 8d agoResearch

RegionFed: Federated Learning for Personalized Query Understanding in Heterogeneous Retail Environments

RegionFed is a gradient-level federated learning framework enabling personalized retail query understanding while matching centralized accuracy with differential privacy.

RegionFed is an architecture-robust federated learning framework for personalized query understanding that operates at the gradient level, using the l2 conflict between regional and global gradients to diagnose heterogeneity and control personalization. Existing parameter-level personalized FL methods collapse on transformers, falling below 10% accuracy on T5, while RegionFed deploys unchanged on T5-Small, T5-3B, RoBERTa, and CNNs. RegionFed-Meta achieves 92.27% across Amazon ESCI, Amazon Reviews, and LEAF-FEMNIST, within 0.23 percentage points of the centralized upper bound, with epsilon-approx-0.60 differential privacy.

arXiv cs.AI / cs.LG / cs.CL · 12d agoAI research1

Privacy-enhanced federated learning via asynchronous aggregation and local differential perturbation

Federated learning framework combining dynamic differential privacy, homomorphic encryption, and local DP retains 82.6% accuracy at epsilon 0.1 while cutting communication 21.3%.

The paper proposes a privacy-enhanced federated learning framework integrating Dynamic Differential Privacy, lightweight Homomorphic Encryption, and Local Differential Privacy during training. An asynchronous aggregation strategy with version control supports distributed training in asynchronous environments. On CIFAR-10 and Purchase-100, the method maintains up to 82.6% classification accuracy under stringent privacy constraints (epsilon = 0.1) and reduces communication overhead by 21.3% versus FedAvg.

arXiv cs.AI / cs.LG / cs.CL · 2d agoAI research

HybridFLow: SDN-Orchestrated Client Partitioning for Hybrid Federated Learning

HybridFLow uses SDN topology visibility to partition federated-learning clients into sync/async groups, reaching 80% accuracy 33-40% faster than SmartFLow.

HybridFLow is a closed-loop, SDN-driven orchestration framework for hybrid federated learning that integrates network-layer intelligence into cross-silo training. It leverages the SDN controller's global topology view to generate calibrated per-client communication-time estimates, partitioning clients into synchronous and asynchronous groups while balancing round latency and update staleness, with measured times fed back after each round. Across multiple network topologies it reaches 80% target accuracy 33-40% faster than SmartFLow and cuts average round duration by 30-40 seconds, while FedAsync fails to reach target accuracy under non-IID data.

arXiv cs.AI / cs.LG / cs.CL · 7d agoAI research

Federated Attack Campaign Detection via Contrastive Encoding of Threat Indicators in Gradient Updates

Researchers propose FedIoC, a federated learning framework detecting cross-organization attack campaigns from threat-indicator structure in gradient updates without sharing IoCs.

The paper introduces FedIoC, a modular federated learning framework in which clients encode locally matched indicators of compromise into gradient updates using a supervised contrastive loss over IoC-matched flows. The server clusters client updates by cosine similarity to recover global attack-campaign patterns without any direct IoC transmission across organizational or national boundaries. Evaluations on two public threat-detection benchmarks, distributed across clients holding only fragments of each campaign and disjoint indicator sets, show the server recovers cross-organizational campaign cohorts from gradient geometry alone. The authors identify non-IID gradient structure as the main driver of recovery and define open problems for encoder design.

arXiv cs.CR · 12d agoResearch

Client-Side Probing of Deleted Ridge Statistics in Federated Unlearning

Researchers show malicious federated learning clients can probe broadcast classifiers to recover deleted samples, exposing exact label leakage on MNIST and CIFAR-10.

The paper shows that federated unlearning systems broadcasting updated linear classifiers leak compact additive training summaries to clients. A malicious client can submit known changes, identify server states from returned classifiers, and compare states around an isolated deletion to expose the deleted sample, class, or client summary, potentially enabling reinsertion. On MNIST and CIFAR-10, high-precision broadcasts allowed exact label recovery for every tested deletion, while lower precision sharply reduced fine-grained recovery.

arXiv cs.CR · 13d agoResearch

FCC proposes public scorecard to rate telecoms on anti-robocall efforts

The FCC proposed a public scorecard rating telecoms' anti-robocall effectiveness and removed 14 providers from US networks for compliance failures.

The Federal Communications Commission issued a public notice proposing a scorecard that would assess how effectively retail voice providers, including wireless, wireline and VoIP, prevent illegal robocalls, drawing on Robocall Mitigation Database filings, consumer complaint and enforcement data. The agency stressed it is not a rulemaking imposing new requirements, and it is seeking comment on scope, such as whether to focus on larger providers. The same day, the FCC removed 14 providers from the Robocall Mitigation Database for non-compliance, effectively requiring other US providers to block their traffic within two days.

CyberScoop · 14d agoPolicy & legal

Trump blacklisting of "woke" Anthropic deemed illegal by federal judge

A federal judge ruled the Trump administration's blacklisting of Anthropic, tied to its stance on autonomous warfare, illegal.

A US federal judge found the Trump administration's blacklisting of Anthropic to be unlawful. The action had targeted the AI lab after it refused to support lethal autonomous warfare and mass surveillance. The ruling is a notable check on the administration's ability to penalize AI companies over policy disagreements.

Ars Technica · AI · 19d agoAI policy1

Two alleged TeamPCP members arrested and charged after months of software supply

Australian Federal Police, with FBI support, arrested two alleged TeamPCP members behind supply-chain attacks that compromised over 1,000 organizations.

The AFP charged two Western Australian men, identified by media as Ruben Ian Thomson (21) and Louis Michael Gaebler (23), with 14 combined offences including unauthorized data modification and dealing in criminal proceeds. TeamPCP is blamed for poisoning open-source software releases including Trivy, LiteLLM, and the mini Shai-Hulud worm campaign, exposing over 500,000 credentials and at least 300 GB of data. Victims included the European Commission and GitHub, with remediation costs estimated in the hundreds of millions of dollars. Researchers from Flare traced one suspect through leaked passwords, a GitHub alias, and a Steam profile.

CyberScoop · 20d agoPolicy & legal1

CISA's logging guidance works beyond government

CISA released its Logging Reference Architecture in August 2026 to help federal agencies meet OMB M-26-14 logging requirements, usable as a benchmark by critical infrastructure operators.

CISA's Logging Reference Architecture (LRA), released in August 2026, helps US federal civilian agencies satisfy logging requirements in OMB Memorandum M-26-14 and explicitly encourages critical infrastructure operators to use it as a benchmark. The framework is organized around continuous event monitoring and threat hunting, investigation, response, and forensics, with a federal baseline of six months searchable and one year retrievable logs. Agencies must submit Agency Logging Plans within 90 days and work toward Advanced maturity within 320 days; the guidance also treats AI outputs as derived data requiring human review and preserved metadata.

Help Net Security · 23d agoAdvisory

Eight years later, federal authorities re-up charges against alleged Iranian hackers at Mabna Institute

US prosecutors unsealed a superseding indictment charging 17 Iranians in the Mabna Institute's state-sponsored theft of 31.5 terabytes from universities and companies.

The superseding indictment unsealed in the Southern District of New York charges 17 people affiliated with Tehran's Mabna Institute, adding eight defendants to the 2018 indictment of nine. The institute allegedly compromised over 100,000 professor email accounts worldwide, including 8,000 accounts at 144 US universities, and stole at least 31.5 terabytes of academic journals, dissertations, and e-books. US universities spent approximately $3.4 billion procuring the stolen data, and victims also included at least five federal and state agencies, 42 US companies, and 11 foreign companies including HBO. The State Department's Rewards for Justice program is offering up to $10 million for information on four of the defendants.

CyberScoop · 29d agoPolicy & legal

Trump taps cyber firms to go on offensive against criminals

Presidential memorandum allows vetted private companies to conduct offensive cyber operations against transnational cybercrime with advance DOJ and DHS approval.

A presidential memorandum released Wednesday lets vetted US companies partner with the Justice and Homeland Security departments on offensive operations and surveillance targeting transnational cybercrime, fraud and predatory schemes, with written pre-approval required for every operation. Operations may not cause loss of life or rise to the level of use of force or armed attack under international law. Participating firms face penalties of at least $1 million for contract violations, must disclose all contractual relationships, and face annual evaluation, while agencies have two months to develop participation standards. The move builds on a March executive order; the White House says Americans reported $20.8 billion in cyber-related losses last year.

The Record · Aug 13, 2026Policy & legal

CISA and NIST Issue Guidance to Protect Cloud Identity Tokens

CISA and NIST published Interagency Report 8587 with voluntary guidance to harden cloud identity tokens against theft, forgery, and lateral movement.

CISA and NIST released NIST Interagency Report 8587 on September 15 with final voluntary guidance for federal agencies, cloud providers, and their customers on protecting SSO, federation, and API tokens. Requirements include one-hour maximum token lifetimes, 90-day signing key rotation for high-impact systems, hardware-backed key storage, explicit audience fields, and keeping tokens out of logs. The guidance was motivated by the 2020 ADFS compromise where forged SAML assertions bypassed MFA, and an incident where a leaked consumer signing key enabled token forgery and theft of 60,000+ emails from one agency. Nearly 250 public comments shaped the text, with input from Google, Microsoft, Okta, AWS, Oracle, IBM, HashiCorp, Wiz, and the OpenID Foundation via the Joint Cyber Defense Collaborative.

Infosecurity Magazine · 8h agoAdvisory

Privacy-Aligned Personalized Federated Learning with Compact Adaptation and Variable-Length Gaussian Communication

Paper releases a private client context once and confines adaptation to coefficients, matching full-model differential privacy with 2.67x less uplink on CIFAR-10.

The paper addresses the dimensionality misalignment between record-level differential privacy and low-dimensional client variation in personalized federated learning by releasing a private client context once and restricting repeated adaptation to a fixed coefficient space. A variable-length quantized Gaussian mechanism lets quantization error itself serve as the required privacy perturbation. On MNIST and CIFAR-10, the design matches or outperforms full-model private adaptation across privacy budgets and client heterogeneity while cutting protected uplink 2.67x at epsilon=16 on CIFAR-10.

arXiv cs.AI / cs.LG / cs.CL · 2d agoAI research1

The EPA Is Planning to Scrap Public Review Rules for Data Center Pollution

The EPA plans to eliminate mandatory public review of air-pollution permits for AI data centers and their power plants, reducing community input.

The EPA proposes scrapping a federal requirement that states notify the public and accept comments before approving air-pollution permits for industrial facilities, including AI data centers and their power plants. A related proposal would let developers begin construction before permits are approved. Nearly 200 advocacy groups and more than a dozen states oppose the changes; critics cite health risks, rising utility bills, housing displacement, and disproportionate impacts on Black communities in the rural South, while the EPA argues the changes speed permitting. The proposal is expected to be finalized within the next year.

Hacker News · security · 5d agoAI policyHN 33↑ · 6 comments1