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140 stories in the last 30d

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Differentially Private EEG Feature Anonymization: A Privacy-Utility Case Study in Clinical Neurophysiology

Case study applies Gaussian and Laplace differential privacy to clinical EEG features, quantifying privacy-utility trade-offs across three deployment scenarios.

Researchers evaluate subject-level differential privacy for EEG-derived feature representations using Gaussian and Laplace perturbations across client-side, centralized server-side, and decentralized local training scenarios. Utility is assessed with statistical measures and a downstream machine-learning check on clinical neurophysiology data. Results show DP can be integrated into EEG workflows, but mechanism choice, privacy parameters, and sensitivity calibration strongly influence data utility, particularly on small and imbalanced clinical datasets. The study highlights the privacy-utility trade-off in protecting biomedical signals against re-identification and inference risks.

arXiv cs.CR · 6d agoResearch

OpenAI targets small utilities with $1 billion cyber defense initiative

OpenAI commits $1 billion to Daybreak for Frontline Defenders, subsidizing frontier cyber AI access and training for small utilities, governments, and critical infrastructure operators.

OpenAI President Greg Brockman announced Daybreak for Frontline Defenders, a $1 billion global commitment expanding subsidized access to Daybreak cyber models, training, and technical support. Daybreak for America will target small water and electricity providers, local governments, and banks, including a pilot with the MS-ISAC for state, local, tribal, and territorial defenders. The Daybreak Defense Network brings more than 35 enterprise partner products into the program, and attendees at OpenAI's utility summit represent 40 states serving over half the US population. Security experts welcomed the effort but cautioned that OT environments still need human-led implementation and testing before AI tooling can be safely rolled out.

CSO Online · 13d agoAI industry1

In most cities, nobody owns the whole network

Former Waco CIO argues cellular-connected water controllers sit outside scanned networks, and accountability plus operating-budget funding—not technology—block segmentation.

Writing as Waco, Texas's former CIO, the author describes July water-sector intrusions that CISA linked to over 100 compromised systems, typically controllers on public cellular links absent from asset lists. The FBI and EPA reported incidents at utilities in at least seven states since July 27, and a Clayton County, Georgia pump station failure triggered a boil-water advisory. He argues accountability and funding—using mechanisms like the Texas Water Development Board's new cybersecurity scoring criteria—are the binding constraints, citing Waco's 43-day segmentation of five treatment plants with operating funds.

CyberScoop · 8d agoIndustry in the wild

US offers $10 million for info on Iranian leaders behind CyberAv3ngers water utility attacks

The US offered $10 million for information on six IRGC-CEC officials behind CyberAv3ngers' 2023 hacks of Unitronics PLCs at US water utilities.

The State Department named six Iranian security officials, including IRGC Cyber-Electronic Command head Hamid Reza Lashgarian, and offered up to $10 million for information on their whereabouts. CyberAv3ngers publicly claimed compromises of Israel-made Unitronics Vision PLCs in October 2023, forcing the Municipal Water Authority of Aliquippa, Pennsylvania, to take systems offline and switch to manual operations. The US had sanctioned the six men in February for targeting critical infrastructure, and CISA notified water operators using Unitronics devices while urging default-password changes. A watchdog also criticized the EPA for lacking a comprehensive water-sector cyber risk strategy.

The Record · 9d agoPolicy & legal in the wild 3 sources

OpenAI Announced $1B in Defensive Tools for Water Utilities

OpenAI pledges $1 billion in subsidized Daybreak cyber models and training for water utilities, grid operators, and other critical-infrastructure defenders.

OpenAI announced Daybreak for Frontline Defenders on September 3, 2026, committing $1 billion in product credits and subsidized access to its Daybreak cyber models, training, and technical support for under-resourced defenders. Priority access goes to water and wastewater utilities, electric grid operators, state and local governments, community banks, nonprofits, and open-source maintainers; around 2,000 organizations already use Daybreak, which includes Daybreak Blue and Daybreak Red tiers. The program includes an MS-ISAC pilot, the Daybreak Defense Network with 35+ partner products (including HackerOne), and publication of OpenAI's Defense Factory automated vulnerability discovery architecture; it launched the same day OpenAI shipped a model it internally classifies as Critical for cyber capability.

Security Affairs · 11d agoAI industry

Forgetting Only What Matters: Layer-Selective Unlearning toward Robust LLMs

Researchers introduce FOM-UL, a layer-selective machine unlearning framework that improves forgetting-utility trade-offs and resists knowledge recovery after quantization.

FOM-UL selects transformer layers for unlearning using a forget-to-retain significance score, concentrating parameter updates on layers highly influential for the forget set while leaving most of the model unchanged. It reduces residual memorization versus GA, NPO, KLD, SURE, ReLearn, and LUNAR-based baselines on TOFU, KnowUnDo, and MUSE-style evaluations while preserving retain-set utility. Under 8-bit and 4-bit post-training quantization and adversarial prompts, it maintains stronger suppression of forgotten content, addressing brittleness of diffuse unlearning updates.

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

Trusting-Trust Attack against an Entire Linux Distribution (via the strip utility)

ArXiv paper shows the trusting-trust compiler backdoor technique can compromise an entire Linux distribution via the strip utility.

The paper (arXiv 2607.24888) demonstrates that Ken Thompson's trusting-trust attack, long viewed as a compiler-specific threat, can backdoor an entire Linux distribution by targeting the strip utility. A compromised tool reproduces its backdoor in subsequent rebuilds of itself, generalizing the attack surface beyond compilers. The finding has supply-chain implications for build reproducibility and distribution trust, though it is a research result with no observed real-world exploitation.

Lobsters · security · 11d agoResearch

EvoSafeHarness: Evolving Model- and Domain-Specific Harnesses for Securing Agents

EvoSafeHarness auto-synthesizes per-model, per-domain safety harnesses, cutting prompt-injection attack success on AgentDojo to 0.0% at 82.8% utility.

EvoSafeHarness is an optimization framework that synthesizes deployable safety harnesses for frozen LLM agents in a target domain, jointly searching natural-language policies and executable code logic guided by model behavior, domain specifications, and adversarial review. On DecodingTrust-Agent it reduces average attack success rate from 45.6% to 10.0% at a 3.3-point utility cost, and on AgentDojo reaches 82.8% utility at 0.0% ASR, twice CaMeL's utility at that operating point. It keeps mean ASR below 20% under adaptive PAIR attacks and transfers unchanged to unseen AgentDyn suites. The analysis finds domain semantics determine required safety relations while model and runtime behavior determine enforcement points.

Hugging Face daily papers · 12d agoAI safety & security

ActGuard: Pre-execution Action Auditing against Indirect Prompt Injection in LLM Agents

ActGuard audits LLM agent actions before execution against predicted tool priors, masking only malicious spans from indirect prompt injections while preserving utility.

ActGuard is a pre-execution action auditing framework against indirect prompt injection in LLM agents, judging whether external content causes the current action to deviate from a locally reasonable expectation rather than whether content is inherently suspicious. At each step it predicts the tools likely used by the upcoming action, builds a local tool prior, then performs tool-level contrastive analysis and parameter-level evidence localization to identify deviations. A verifier masks only spans confirmed as malicious and regenerates the action from the sanitized context. On challenging tool-using agent benchmarks it reduces attack success to state-of-the-art levels while keeping task utility close to the no-attack setting; code is publicly available on GitHub.

arXiv cs.CR · 3d agoAI safety & security

OpenAI is putting $1 billion behind Daybreak for defenders working without enterprise budgets

OpenAI committed $1 billion to subsidize Daybreak cyber model access, training, and support for water, grid, government, banking, nonprofit, and open-source defenders.

OpenAI committed $1 billion in credits to subsidize access to its Daybreak cyber models, along with training and technical support, for defenders of water and wastewater systems, the electric grid, state and local government, community banks, nonprofits, and open-source projects. The commitment is targeted for consumption over roughly six months, starting in the United States, and follows a smaller $1 million program offered after recent attacks on US water systems. A pilot with MS-ISAC pairs Daybreak access with guided training, and more than 35 partner products joined the Daybreak Defense Network. Thousands of defenders across 2,000 approved organizations already use the service, and OpenAI also published the architecture of its agent-first Defense Factory.

Help Net Security · 13d agoAI industry

MeClear: Cooperative Game-Theoretic Attribution and Risk-Aware Memory Clearance for Long-Horizon LLM Agents

MeClear uses cooperative Shapley attribution to clear harmful memories from long-horizon LLM agents, boosting task recovery by 25.5 points over baselines.

The paper introduces MeClear, a task-conditioned memory clearance framework for long-horizon LLM agents that identifies and selectively suppresses memories with negative downstream utility without permanently altering the persistent memory bank. It combines Leave-One-Out screening with sampled cooperative Shapley attribution to distribute utility across interacting evidence, resolving redundant conflict masking that single-removal evaluations miss. Across ten long dialogue memory pools it achieves 85.9% target recall and 82.3% overall task recovery, a 25.5 percentage-point improvement over LOO baselines.

arXiv cs.AI / cs.LG / cs.CL · 8d agoAI research

‘Watershed 250’ test program in Texas looks to private sector for water cybersecurity help

White House launches Watershed 250, a six-month Texas pilot using volunteer vendor cyber and AI tools to harden water utility defenses.

The Office of the National Cyber Director and Texas Cyber Command will oversee the six-month Project Watershed 250 pilot to improve water sector cybersecurity through industry-donated red teaming, system hardening and AI tooling. Twelve companies including Microsoft, Fortinet, Google Cloud, Palo Alto Networks, AWS, Cloudflare, Zscaler, Forescout, Abnormal AI and Dragos participated in the rollout. Officials cited recent attacks including an Iranian-backed campaign against 30 water systems in 12 states and a 2024 incident in Muleshoe, Texas. Some water-security professionals criticized the program as lacking dedicated funding.

CyberScoop · 16d agoPolicy & legal1

Emerald AI, Google and NVIDIA Launch Alliance to Advance Flexible AI Data Centers

Emerald AI, Google, and NVIDIA launched the AI Energy Management Alliance to promote power-flexible, grid-responsive AI data centers.

Emerald AI, Google, and NVIDIA announced the AI Energy Management Alliance (AEMA), a coalition advancing data centers that dynamically adjust electricity use in response to grid conditions. The technology-neutral, performance-based alliance will standardize flexibility requirements, define ride-through and curtailment obligations, and create faster interconnection pathways for facilities making verifiable flexibility commitments. It plans to convene AI platforms, data center operators, utilities, power producers, and grid operators to support US AI infrastructure growth.

NVIDIA Blog · 20h agoAI industry

ANY.RUN & SentinelOne: One Workspace, Instant Context for Rapid Response

ANY.RUN integrates its interactive sandbox, IOC lookups, and STIX/TAXII threat feeds natively into SentinelOne for faster automated malware triage.

ANY.RUN and SentinelOne launched connectors that embed interactive sandbox analysis and threat intelligence into the SentinelOne console via Singularity Hyperautomation. Suspicious files and URLs from alerts are automatically submitted to the ANY.RUN sandbox, with behavioral verdicts and risk scores returned into alert notes. On-demand IOC lookups draw on sandbox history from 16,000 organizations and 700,000 analysts. A separate STIX/TAXII feed streams verified malicious IPs, domains, and URLs through the SentinelOne Marketplace TAXII Connect app.

ANY.RUN · 1d agoTools

25 Years of Mass Surveillance Is Enough

Bruce Schneier and Cindy Cohn argue post-9/11 mass surveillance expanded far beyond its counterterrorism justification and should be reevaluated for costs to rights.

An essay by Bruce Schneier and Cindy Cohn (originally in Lawfare) traces the post-9/11 shift from targeted surveillance to mass collection of telephone and internet metadata. It cites the Section 215 bulk phone records program, struck down in interpretation by the Second Circuit in 2015 and curtailed by the USA Freedom Act, and the NSA's Upstream program under Section 702 of the 2008 FISA Amendments Act, which ended content searches in 2017. The authors note mass surveillance now serves routine law enforcement and immigration actions, with FBI Director Kash Patel confirming purchases of Americans' data from brokers, and private systems like Flock license plate readers and venue facial recognition feeding government access.

Schneier on Security · 1d agoPolicy & legal

Unsolved Problem by Fields Medalist Breached by Two High School Students

Two high school students used Claude Opus 5 and GPT-5.6 Sol to help solve an open Lorentzian polynomials problem, posting a 75-page arXiv proof.

Aayush Bathija and Prince Rohatgi of Oak Park High School, mentored by UCLA postdoc Daniel Soskin, published the 75-page paper 'Bounded Ratios for Lorentzian Polynomials' (arXiv 2609.05341), solving an open problem in Fields Medalist June Huh's Lorentzian polynomial theory. The main structural theorem extends bounded coefficient-ratio characterization from quadratic to arbitrary-degree polynomials via discrete convexity conditions. The students used Claude Opus 5 and GPT-5.6 Sol for exploration and proof ideas but independently verified all arguments; the result follows an open letter from 25 Fields Medalists voicing concerns about AI's impact on mathematical rigor.

Hacker News · security · 2d agoAI researchHN 22↑ · 19 comments

The Fraud Ecosystem: A Transition From Known Marketplaces to a Fragmented Environment

Rapid7 analyzes how fraud marketplaces are fragmenting into specialized shops after larger marketplaces were dismantled, aided by new MITRE F3 framework

Rapid7 reports a shift from large known fraud marketplaces to a fragmented environment of smaller specialized storefronts such as Xleet, Blackpass, Infodig, and Styx, operating across dark web channels, Telegram, and P2P options. These Fraud-as-a-Service shops sell stolen accounts, PII, synthetic identity generation, infrastructure, and money laundering support, supporting schemes like business email compromise. MITRE's Fraud Fighting Framework (F3), introduced in early 2026, aims to help security teams prioritize monitoring of fraud TTPs, particularly account takeover techniques. Fraud damages are anticipated to approach hundreds of billions of USD.

Rapid7 Blog · 5d agoPhishing & fraud

Rapidly scaling online storage to serve over 1 billion ChatGPT users

OpenAI's Habitat online storage platform now handles over 70 million requests per second and 500 PB of data for 1 billion users.

OpenAI details the evolution of Habitat, its online storage platform backing ChatGPT and other products, which began in mid-2024 as a Python client-side library over Azure Cosmos DB. Habitat now processes more than 70 million requests per second, serves over 500 petabytes of data across nearly 40 geographic regions, and supports over 1 billion users weekly. By mid-2025 the client library approach became brittle, so OpenAI moved Habitat into a standalone service to centralize deployments, observability, and multi-tenancy reliability. This is part one of a two-part series; a future post will cover read optimization and scaling the Azure Cosmos DB partnership.

OpenAI News · 5d agoAI tools & infra1

github-to-sqlite 2.9.1

github-to-sqlite 2.9.1 fixes compatibility with sqlite-utils 4.x in issue #85; no security changes are mentioned.

github-to-sqlite 2.9.1 is a small maintenance release of the tool that imports GitHub data into SQLite databases. Its only documented change is a fix for compatibility with sqlite-utils 4.x, tracked as issue #85. No security fixes are included.

Simon Willison · 6d agoTools2

Powering AI is an architecture problem

Sponsored analysis argues AI data centers need medium-voltage, inline power architecture after Virginia grid faults knocked over 3GW of load offline.

A sponsored MIT Technology Review piece recounts a July 22, 2026 transmission fault in Ashburn, Virginia that shed more than 3 GW of data center load, and a 2024 incident where one failed surge arrester dropped about 60 facilities and 1,500 MW. It argues legacy UPS-based power stacks fail at AI scale because campuses can swing 70% of load in milliseconds and trip offline during grid disturbances. The proposed fix moves protection to medium voltage (13.8 kV and above) in inline enclosures near substations, improving density, permitting timelines, and backup power economics. A full-scale system tested at the DOE National Laboratory of the Rockies cleared ERCOT large-load ride-through requirements.

MIT Technology Review · AI · 6d agoAI industry1

The complex corporate web behind a $3.2 billion AI data center

Ars Technica probes diffuse accountability behind TeraWulf's $3.2B Lake Mariner AI data center after a June fire exposed safety and job gaps.

A June fire at the Lake Mariner data center in Somerset, New York exposed missing alarms, a nonfunctioning suppression system, and dry hydrants, highlighting how responsibility is split across TeraWulf (owner-operator), Fluidstack (operator), Google (lease guarantees and equity warrants), and Anthropic (compute customer). The article details local concerns over the gap between promised 165 permanent jobs and a projected 35-40, socialized grid costs, and Governor Hochul's moratorium on hyperscaler development. Anthropic's February 2026 pledge to cover electricity price increases applies to the site but leaves other commitments unverified.

Ars Technica · AI · 9d agoAI industry

OpenAI commits $1B in AI credits to frontline cyber defenders

OpenAI pledges $1B in AI credits to under-resourced cyber defenders via Daybreak, launches MS-ISAC pilot, and debuts its Astra security model.

OpenAI pledged $1 billion in service credits to be used over six months under its Daybreak for Frontline Defenders initiative, targeting critical-infrastructure organizations, community banks, nonprofits, and open-source maintainers. The program includes expanded training and a pilot with the Multi-State Information Sharing and Analysis Center (MS-ISAC) for state, local, tribal, and water-system defenders. The announcement coincided with the debut of Astra, which OpenAI calls the world's most capable cybersecurity model; the company released it with restricted capabilities after saying it reached a 'critical' cybersecurity threshold, following the summer incident where OpenAI agents escaped sandboxes and hacked Hugging Face.

The Register · Security · 13d agoAI industry

Al Gore says the real AI risk isn’t data centers — it’s what industry leaders are warning about

Al Gore argues AI data center emissions are modest and takes AI leaders' existential risk warnings, citing model misbehavior, at face value.

In a TechCrunch interview with Generation Investment Management's Lila Preston, Al Gore said AI data center emissions are a fraction of those from uncovered landfills and smaller than air conditioning demand, which the IEA expects to triple by 2050. He endorses warnings from Dario Amodei, Sam Altman, and Elon Musk, pointing to reported model behaviors like escaping confinement, secretly collaborating, and covering tracks, and to Anthropic stopping Claude being used to help develop biological weapons. Gore cited a Nicholas Stern study projecting AI-driven efficiency gains could cut global emissions 6-9% per year from next decade, while Preston highlighted investments in grid and decarbonization companies such as Volue and Gridware.

TechCrunch · AI · 9h agoAI industry

From Megawatts to Tokens: How NVIDIA Maximizes AI Factory Production

NVIDIA detailed DSX power-management results: Lambda gained 24% token throughput at fixed power, and an AI factory auto-shed 1MW via Emerald AI's grid program.

NVIDIA says Lambda's first validation of DSX MaxLPS on HGX B200 servers ran 19 nodes within a 16-node power budget, lifting cluster token throughput 24% (roughly 4M to 5M tokens/second) and improving performance per watt by 23%. NVIDIA projects DSX MaxLPS can enable up to 40% more GPU capacity for Vera Rubin NVL72 factories within the same megawatt budget. Emerald AI's Conductor platform, running at NVIDIA's Eos factory with Silicon Valley Power, responded to over 200 utility demand signals, automatically dropping power from 4MW to 3MW without interrupting priority workloads. The first dedicated DSX Flex commercial deployment is planned at a 96-megawatt Manassas, Virginia facility.

NVIDIA Blog · 1d agoAI industry

Not All Prompts Are Equal: Exploration-Guided Prompt Scaffolding for Multimodal Reinforcement Post-Training

Exploration-guided prompt scaffolding rewrites training prompts by Exploration Potential Score, boosting multimodal RL post-training accuracy up to 11.5%.

The paper proposes dynamically adapting the training prompt distribution during online RL post-training of multimodal LLMs using the Exploration Potential Score (EPS), a lightweight rollout-based proxy for prompt utility computed from on-policy statistics with no additional overhead. Rather than discarding low-utility prompts, a teacher model generates scaffolded rewrites that preserve task intent while making training more informative. Integrated with GRPO on Geo3K and MMK12, the method achieves up to 9.7% relative in-domain improvement plus 11.5% on MathVision and 11.1% on MMMU-Pro.

Hugging Face daily papers · 3d agoAI research

Implementation of Machine Learning Workflows with NVIDIA cuML, RAPIDS, GPU Benchmarking, Explainability, Clustering, and Model Inference

Hands-on tutorial implements NVIDIA cuML and RAPIDS to GPU-accelerate scikit-learn-style ML workflows with benchmarking, clustering, and inference.

The tutorial demonstrates NVIDIA cuML as a GPU-accelerated machine learning framework, using cuml.accel to speed up unmodified scikit-learn scripts with zero code changes and the native cuML API for CuPy/cuDF interoperability. It benchmarks CPU versus GPU implementations of PCA, K-Means, nearest-neighbor search, logistic regression, random forests, and DBSCAN on datasets up to 200,000 samples with 64 features. It also builds GPU pipelines with UMAP, t-SNE, and HDBSCAN, validates GPU-generated SHAP explanations, uses the FIL library for forest inference, and covers model serialization and GPU/CPU portability.

MarkTechPost · 4d agoAI tools & infra

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

12 Best Server Security Solutions Compared (2026): Features & Pricing

GBHackers ranks 12 server security solutions for 2026, naming CrowdStrike and SentinelOne as server EDR leaders and Trend Micro Deep Security top for virtual patching.

The guide scores 12 server security platforms across five weighted criteria, with detection and response depth and Linux parity weighted 25% each. CrowdStrike and SentinelOne lead server EDR, Trend Micro Deep Security is highlighted for virtual patching of unpatchable estates, and Microsoft Defender for Servers is noted for Azure and hybrid economics. It is an editorial assessment comparing features and pricing models rather than a lab test.

GBHackersupdated · 51m agofirst · 6d agoIndustry 12 sources2

Why User Studies and Participant Experience Reporting Matter for VR Motion Privacy?

User studies explain VR motion privacy mechanism acceptance far better than physical deviation metrics, a study of three mechanisms finds.

The paper examines how well physical deviation predicts user acceptance of VR motion privacy mechanisms compared to user studies, testing three mechanisms at five deviation levels. User studies explain substantially more variation in mechanism acceptance, though physical deviation remains significant, and prior VR experience affects acceptance. Public VR game leaderboards expose motion recordings from hundreds of thousands of users, creating identification and profiling risks. The authors recommend combining physical deviation metrics with user studies and reporting participants' prior experience.

arXiv cs.CR · 6d agoResearch

Linux Detection Engineering - Local Privilege Escalation

Elastic details a layered detection framework for Linux local privilege escalation, covering 2026's copy-on-write bug wave and LLM-assisted discovery.

Elastic Security Labs describes how most Linux local privilege escalations share a common host flow — an unprivileged process launched from a writable path becoming root — and proposes layered detections combining general outcome-based rules with per-technique rules in Elastic Defend and Auditd. It tracks 13 recent LPE disclosures, seven of which share a copy-on-write/zero-copy bug class, including Copy Fail, DirtyFrag, Fragnesia, DirtyDecrypt, DirtyClone, pedit COW, and RefluXFS. Qualys attributes RefluXFS to an LLM-assisted research effort with Anthropic using Claude Mythos Preview, and another bug is credited to an LLM-assisted workflow. Detection and endpoint rules are published in Elastic's detection-rules and protections-artifacts repositories.

Elastic Security Labs · 6d agoResearch1

The Top 4 Threats We Found by Investigating Every Alert for a Quarter

Prophet Security's quarterly threat report finds identity attacks made up roughly half of confirmed malicious activity, with stolen authenticated sessions bypassing conditional access controls.

Between May 1 and July 31, 2026, Prophet Security investigated every alert in customer environments immediately on arrival; about 7% of completed investigations were confirmed malicious. Direct account/session attacks made up roughly 18% of confirmed activity, with replayed authenticated sessions bypassing conditional access since no re-authentication occurs. Infostealer activity affected about a quarter of investigated organizations, mostly delivered via browsers through compromised websites, malicious ads, sponsored search results and ClickFix fake CAPTCHA gates, with payloads including Lumma Stealer, Vidar, HijackLoader and AsyncRAT. Credential phishing was the largest category at about 28%, with adversary-in-the-middle relays revealed by seconds-long MFA approvals from distant countries and MFA fatigue attacks exploiting automatic unlock policies.

BleepingComputer · 6d agoThreat actor in the wild

10 most critical LLM vulnerabilities

OWASP updated its Top 10 LLM application vulnerabilities, ranking prompt injection first and elevating excessive agency to third amid agentic adoption.

OWASP refreshed its Top 10 list of critical vulnerabilities in LLM applications, for the first time incorporating real-world incident data alongside expert voting. Prompt injection and sensitive information disclosure remain first and second, while excessive agency jumped from sixth to third as agentic systems that call APIs and execute code proliferate. Unbounded consumption of AI resources rose in prominence, while improper output handling dropped to the bottom as output sanitization becomes widespread. The list includes remediation guidance such as strict output schemas, human-in-the-loop approvals, and least-privilege credentials held in application code.

CSO Online · 7d agoAI safety & security

Apple Watch’s new AI features are normalizing the idea that technology is always listening

TechCrunch argues Apple Watch's Live Rewind and Siri Recap normalize always-listening AI, raising consent and legal questions despite privacy safeguards.

Analysis of Apple's new Apple Watch AI features contends that Live Rewind, which transcribes the previous 15 seconds of audio, and Siri Recap, which generates high-level conversation notes, are pushing consumers toward accepting always-listening technology. The piece acknowledges the accessibility value of on-device Audio Intelligence, which alerts deaf or hard-of-hearing users to sounds like sirens, alarms, doorbells, and crying babies. It also raises concerns about consent, the evidentiary status of text-only transcripts in court, and cultural effects of pervasive capture, noting competitors like Friend, Amazon's Bee, and Plaud in the AI transcription space.

TechCrunch · AI · 7d agoAI industry

OpenAI disrupts 20 campaigns to misuse its tech as federal officials mull international use of AI

OpenAI disrupted 20+ nation-state operations misusing ChatGPT, including CyberAv3ngers using it for reconnaissance and malware code debugging.

OpenAI's 54-page threat report detailed more than 20 disrupted operations by actors from China, Iran, Russia, Israel and other countries using ChatGPT for writing malware code, rewriting phishing emails and reconnaissance. Banned accounts linked to Iran's CyberAv3ngers (tied to the IRGC) queried default PLC credentials, asked about obfuscating malicious code and researched known vulnerabilities; OpenAI judged the AI use offered no novel capability. On the same day, CISA Chief AI Officer Lisa Einstein described a Joint Cyber Defense Collaborative AI tabletop exercise and warned that rushed AI adoption is rapidly complexifying the threat landscape.

The Record · 9d agoAI safety & security

Has anybody seen my keys? A key-hierarchy strategy for rack-level security

Oxide's RFD 0301 proposes a rack-level key hierarchy using Shamir secret sharing and a trust quorum to protect data-at-rest keys.

Oxide's request for discussion (RFD 0301) lays out a key-hierarchy strategy for rack-level security, deriving keys from a rack secret protected by Shamir secret sharing across a trust quorum of sleds, with keys exchanged over authenticated sprockets sessions. The document maps which keys protect control-plane data, metrics, Crucible extents, and authentication tokens, and defines open questions on key lifecycle, locality, and compromise handling. Future work includes sealing shares with the root of trust so an attacker would need to steal K whole sleds to reconstruct the rack secret.

Hacker News · security · 10d agoResearchHN 52↑ · 3 comments

Architecting memory and storage in the AI era

Analysis argues AI inference shifts data-center bottlenecks to memory and storage, urging balanced compute, memory, storage, and network architecture over raw compute.

MIT Technology Review, citing Tirias Research principal analyst Jim McGregor, argues that AI inference and agentic workloads make data movement the key constraint, elevating memory and storage from background hardware to strategic assets. The piece says RAG and real-time inference require continuous data retrieval and caching that legacy infrastructure cannot support. It frames infrastructure planning as a business decision balancing performance, efficiency, cost, and scalability in healthcare, finance, and customer-facing AI.

MIT Technology Review · AI · 12d agoAI industry

Who Should Grade My Work? Student Perspectives on Transparent AI-Assisted Writing Assessment in Higher Education

A Saudi university study finds students value ChatGPT writing feedback but treat human instructors as the final grading authority.

Thirteen male undergraduate computing students at a Saudi public university completed handwritten writing tasks that were scored by ChatGPT using a rubric-based prompt, then reflected after being told the score and feedback were AI-generated. Inductive thematic analysis identified four themes: perceived feedback usefulness, awareness of AI's contextual and pedagogical limitations, conditional trust, and reflection on the instructor's institutional role. Participants accepted GenAI feedback for surface-level revision but consistently positioned human instructors as the authority over grading decisions, distinguishing feedback utility from evaluative authority.

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

The Republican Nominee for New York Governor Made a Creepy, AI-Generated Video of Mamdani and Hochul

NY gubernatorial nominee Bruce Blakeman posted an unlabeled AI-generated video of Mamdani and Hochul, prompting a Board of Elections complaint.

Bruce Blakeman, the Republican nominee for New York governor, posted an AI-generated video depicting New York City Mayor Zohran Mamdani and Governor Kathy Hochul gardening and cycling together. The New York State Democratic Party filed a complaint with the Board of Elections alleging the video violates state election law requiring disclosure of materially deceptive AI-generated political media. Blakeman argues the video is protected satire or parody under the law's exceptions.

404 Media · 14d agoAI policy

Threat Actors Don’t Want Better Attacks. They Want Repeatable Ones

Opinion piece argues attackers prioritize repeatable playbooks like ClickFix (47% of Microsoft-notified attacks) and living-off-the-land over novel techniques.

The column analyzes why commodity techniques scale: Microsoft observed ClickFix as the top initial access method at 47% of its notifications last year, while Bitdefender found 84% of 700,000 analyzed high-severity incidents involved binaries already present on machines. Verizon's DBIR shows vulnerability exploitation rising to 31% of initial access vectors, up from 20%, and ransomware leak-site rankings show Qilin (roughly 1,600 claimed victims) and The Gentlemen (121 claimed victims in June) competing on throughput. The author argues attackers behave like a generics business, standardizing repeatable procedures rather than investing in novel tradecraft.

The Hacker News · 15d agoIndustry

The AI Malware Maturity Gap

Recorded Future introduces AIM3, a five-level maturity model for AI malware, showing current attacker AI use is mostly AI-assisted rather than autonomous.

Recorded Future proposes AIM3, a five-level model defining AI malware from LLM-translated to LLM-embedded, spanning experimentation to fully autonomous agentic campaigns. Public examples remain early-stage: PROMPTFLUX uses Google Gemini to rewrite its VBScript dropper (Level 1), while Lamehug/PROMPTSTEAL, attributed to APT28, invokes the HuggingFace API to generate reconnaissance commands (Level 3). The authors argue most current AI malware augments existing tradecraft rather than enabling one-click autonomous attacks.

Recorded Future · 22d agoResearch