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63 results for β€œLAPS”

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  1. Cloudflare DDoS Threat Report 2026 Q3: More swarms, fewer giants

    Cloudflare DDoS Threat Report 2026 Q3 covers July to September 2026, with 18.2 million network-layer attacks and 14.4 trillion HTTP DDoS requests mitigated. Short attacks under 10 minutes and 1 Gbps rose 208%, while attacks above 1 Tbps fell from 805 to 251 after law enforcement took down the Aisuru, KimWolf, JackSkid and Mossad botnets. CLDAP floods collapsed 99.5% as DNS amplification rose 215%. The United States became the most-attacked country again.

    blog.cloudflare.comarticlePublished and added 29 Oct 2026πŸ›‘οΈ Security

  2. Cisco SD-WAN Zero-Day Exploitation Tied to Volt Typhoon’s β€˜Silent Train’ Network

    Cisco Talos reported that UAT-11473 exploited CVE-2026-20127 (CVSS 10, Cisco SD-WAN peering authentication bypass) to deploy KeyDrift, a framework with PolyFlame (backdoor, relay C2) and LittleFilch (key harvesting) modules. Talos found its infrastructure overlaps considerably with Volt Typhoon's Silent Train network. Lumen Black Lotus Labs tied Silent Train to zero-day campaigns against Versa Director, N-able N-central, Cisco Catalyst SD-WAN and VeloCloud Orchestrator.

    securityweek.comarticlePublished and added 29 Oct 2026πŸ›‘οΈ Security

  3. TLP Is Not a Suggestion

    Akamai SIG argues that vendors and researchers broke embargo norms during the October 2026 PHP2Shell leak, when the PHP fix shipped a day early on 21 October. It explains the four TLP 2.0 labels, tabulates past embargo breaks (Heartbleed, a collapsed six-month kernel-era embargo, the Alibaba Cloud and MIIT case), and lists seven practices, such as no proofs of concept or CVE numbers before the fix.

    akamai.comarticleAdded 30 Oct 2026, published 28 Oct 2026πŸ›‘οΈ Security

  4. CRISP: Co-designing Pruning and Scheduling for Efficient MoE Inference on Edge Servers

    CRISP is a combination-aware framework that co-designs pruning and runtime scheduling for Mixture-of-Experts inference on memory-constrained edge platforms. It reorders neurons by importance so one stored expert supports several execution widths, gives hot, warm and cold expert combinations different widths, and overlaps expert loading with computation. On Mixtral-8x7B and DeepSeek-MoE-16B it raises throughput up to 2.1x at the same memory budget, with accuracy loss limited to 3.6%.

    arxiv.orgpaperAdded 28 Oct 2026, published 27 Oct 2026🧠 AI

  5. Rohan Paul (@rohanpaul_ai) on X

    Hi3D v1.0 (formerly Sparc3D) is an open-sourced image-to-3D model from Hi3D, which runs a closed v3.0 refining at 2048 cubes per side. In a test with 13 professionals in 3D algorithms, 562 judgments against eight other image-to-3D models favoured it 83.5% of the time. The thread also covers the Hi3D Agent and an MCP server for other agents. Back and bottom views were checked, where TRELLIS.2 collapsed a winged figure.

    x.comthreadAdded 28 Oct 2026, published 27 Oct 2026🧠 AI

  6. A new AI method for saliency-aware image-text alignment improves image search

    RoSA is a finetuning framework from Qiuyu Kong and three co-authors for long-text image-text retrieval. It targets "saliency collapse", where models over-rely on text tied to prominent visual features and miss contextual information. RoSA splits pairs into salient and contextual views using object-level saliency estimation and LLM text decomposition, then trains on both with plug-and-play auxiliary alignment objectives. Code and checkpoints are public.

    en.cryptonomist.charticlePublished and added 26 Oct 2026🧠 AI

  7. Gheist: Attempted Scaled Abuse of Stolen GitHub Tokens Stumbles

    Gheist is a campaign tracked by Wiz Research since 15 September 2026 that uses stolen GitHub tokens to push a sync-check workflow on ci-sync-* branches in every reachable repository. The workflow prints base32-encoded secrets into logs, which the tool downloads through the GitHub API and then deletes. Over 13,500 branches from 850+ accounts were recovered. The post covers the two tool variants, a buggy self-hosted runner payload, GitHub's approval hold (which does not cover private repositories), overlaps with other campaigns, hunting queries, IOCs and hardening steps.

    wiz.iowriteupPublished and added 25 Oct 2026πŸ›‘οΈ Security

  8. Ranking Is Not Deciding: Benchmark Shortcuts and Operating-Point Collapse in Query-Time RAG Poisoning Defenses

    Ranking Is Not Deciding is an October 2026 arXiv paper showing that query-time RAG poisoning filters score near-perfectly because of how the poison set was built. PoisonedRAG's code prepends the target question to each passage. Removing that prefix takes RAGuard from AUROC 0.953 to 0.758 and its miss rate from 0.191 to 0.763. The authors release a script that profiles a poison set.

    arxiv.orgpaperAdded 27 Oct 2026, published 24 Oct 2026πŸ›‘οΈ Security

  9. The rise and fall of Jev hype

    The essay uses the launch of Jev, TypeSafe AI's "System One" general-purpose classifier trained with RLCD, to dissect AI marketing patterns: name dropping, jargon, ambiguity, inflated claims and drama. The author argues Jev's hype peaked and collapsed within about 33 days, while open-weight rivals beat it on cost and performance. It also lists incremental advances since ChatGPT and four unsolved problems: abstract reasoning, continuous learning, embodiment and the economics of running AI.

    blog.alexewerlof.comarticleAdded 24 Oct 2026, published 23 Oct 2026🧠 AI

  10. Why AI Compute Comes in Rectangles β€” Erik Bernhardsson, Modal CEO

    Latent Space interview with Modal CEO Erik Bernhardsson, after Modal's $750M Series D at a $16B valuation and passing $1B annualized run rate. He explains why GPU demand is not "rectangular" like fixed-term capacity contracts, how Modal pools demand and buys from about 25 clouds on three-year deals, and why sandboxes grew to about a third of revenue. Also covers GPU price-collapse risk and non-NVIDIA accelerators. Only the first part of the transcript was available.

    latent.spacetalkPublished and added 22 Oct 2026🧠 AI

  11. Who Is Sycophantic to Whom? Confident LLMs, Human Deference, and the Collapse of Trust Calibration

    This paper studies reverse sycophancy: whether users bend toward a confident, consistent, wrong LLM. In a within-subjects experiment, 32 participants learned science topics from five GPT-5-mini assistants with 0 to 100% of facts replaced by falsehoods. Scores fell from 7.4 to 2.9 out of 10, planted falsehoods were chosen on 60% of falsified items against 11% of correctly taught ones, and confidence stopped tracking correctness. It introduces a baseline-corrected Human Deference Index.

    arxiv.orgpaperAdded 24 Oct 2026, published 22 Oct 2026🧠 AI

  12. Proving Humanity

    Galaxy Research essay arguing that as AI agents become the main way people use the web, the key question shifts from "is this a machine?" to "is a distinct real person behind it, counted once?". It traces CAPTCHA history (distorted text, image puzzles, reCAPTCHAv3 and Turnstile behavioral scoring) and notes ChatGPT Agent passing Cloudflare's checkbox. It reviews Web Bot Auth signatures and Google's AP2 payment mandates, showing both stop at the platform or key and never establish a person. It then covers harms (one-person-one-share abuse, no one to answer for an agent, distorted public counts, collapsing confidence, scaled deception, broken ad economics) and lists the properties a privacy-preserving proof-of-personhood credential needs: strong, private, portable, delegable, accessible.

    galaxy.comarticleAdded 16 Oct 2026🧠 AI

  13. Rethinking GRPO for Large Reasoning Model Safety Alignment

    Beacon is a safety alignment framework for large reasoning models that fixes two GRPO failure modes: advantage collapse, where homogeneous rollout groups give vanishing advantages, and unsafe diversification, where unsafe behaviors persist and spread. It combines Safety Signal Recovery (advantage-guided trajectory filtering plus safe reference supervision) with Safety-Utility Decoupled Alignment (category-aware rewards, benign-only KL anchoring). Tested on four Qwen3 and DeepSeek-R1-Distill variants across eight benchmarks, it cuts average safety error by up to 32.83 percentage points with low over-refusal.

    arxiv.orgpaperAdded 20 Oct 2026, published 16 Oct 2026🧠 AI

  14. lee1981 (@lee1981b) on X

    Defender guide for CVE-2026-104935, an authentication-bypass-by-spoofing flaw (CWE-290) in Ivanti Connect Secure that allows unauthenticated command execution. It is confirmed exploited and CISA KEV-listed, with a CNA CVSS 8.6. It covers the fixed-release matrix (25.1.1.2, 22.8R2.5, 25.1.3.x), platform and cluster migration limits, and Volexity's UTA0576 indicators and YARA rules. It also gives a six-step SOC workflow (scope, preserve, hunt, correlate identity, remediate, verify). It stresses that a clean ICT result cannot clear memory-only activity and that LDAP, LAPS and BitLocker exposure belongs to one observed chain.

    x.comthreadAdded 16 Oct 2026, published 14 Oct 2026πŸ›‘οΈ Security

  15. Ivanti Zero-Day Chain Gave Attackers Root Access to Fully Patched VPN

    Ivanti disclosed CVE-2026-104935, an authentication bypass plus RCE in Connect Secure VPN appliances, exploited in the wild; patched in ICS 22.8R2.5, 25.1.1.2, 25.1.3.0 and 25.1.3.1. Volexity found threat actor UTA0576 chained three zero-days, including a still-unpatched privilege escalation, to get unauthenticated root on a fully patched appliance. Post-exploitation focused on stealing domain credentials, Active Directory reconnaissance (LAPS passwords, BitLocker keys), password spraying, a custom Kerberos tool and log tampering. Volexity assesses with medium confidence that the actor uses LLMs for exploit development.

    securityweek.comarticlePublished and added 13 Oct 2026πŸ›‘οΈ Security

  16. Dark Web Intelligence (@DailyDarkWeb) on X

    Social post summarizing Volexity's research on an Ivanti Connect Secure (ICS) zero-day chain, CVE-2026-104935. The chain pairs an auth bypass and a race-condition RCE with a separate privilege-escalation bug for root. Actor UTA0576 used it from Oct 3, 2026 against a fully patched 22.8R2.4 appliance, leaving no backdoor or web shell and deleting log entries. Post-exploitation included LDAP/AD credential theft, LAPS and BitLocker key searches, password spraying and packet capture. CISA added it to KEV with a due date of Oct 16. A clean Integrity Checker result does not rule out compromise because the chain patches code in memory only, so memory and network forensics are needed. The hunting lead is heavy requests to /dana-na/auth/url_default/welcome.cgi with a mismatched X-DSCGI-PATH header.

    x.comthreadPublished and added 13 Oct 2026πŸ›‘οΈ Security

  17. RepProbe: Can Video Language Models Count Repeated Actions? A Diagnostic Benchmark

    RepProbe is a benchmark of 42K real and synthetic video clips with exactly 1–20 complete action repetitions, controlling for clip position, temporal coverage and duration. Video language models' counting accuracy collapses at high counts, and this is not explained by frame sampling alone. Linear probes on final-layer representations show count information stays linearly decodable even when the model's answer is wrong, so the failure arises at the output stage, where answers cluster on a few preferred numbers.

    arxiv.orgpaperAdded 14 Oct 2026, published 13 Oct 2026🧠 AI

  18. Top GenAI security resources β€” October 2026

    Adversa AI's October 2026 roundup of 38 GenAI security resources, grouped into attack techniques, defenses, red teaming, vulnerabilities, incidents, articles and frameworks. Highlights include Anthropic's finding that GLM-5.3 safeguards collapse under prefill and abliteration, capability laundering and activation-dilution jailbreaks, RAG poisoning attacks, the LiteLLM proxy flaw (CVE-2026-35029), and the SGLang pickle RCE (CVE-2026-86793). It also covers a joint US advisory on industrial-scale model distillation. It closes with advice to assume model safeguards can be removed and to harden the serving stack around the model.

    adversa.aiarticlePublished and added 13 Oct 2026πŸ›‘οΈ Security

  19. Artificial Intelligence (AI) in Cybersecurity, Part 28: Using ADStrike to Compromise Active Directory

    ADStrike is an Active Directory attack framework with 52 attack modules and configurable OPSEC levels. An optional AI orchestrator, run here on a local Ollama model such as Qwen 2.5-coder 7b, picks the next tool from each step's output. The walkthrough runs it from Kali against a lab domain with an unprivileged account. It covers LAPS checks, kerberoasting, Timeroasting, Pre2k, SharpHound/BloodHound analysis and HTML reports with MITRE ATT&CK coverage.

    hackers-arise.comwriteupPublished and added 12 Oct 2026πŸ›‘οΈ Security

  20. UK slaps sanctions on three crypto exchanges over alleged Russia links

    The UK Foreign Office sanctioned crypto exchanges Cryptomus, Heleket and Certa Payments (all operated by Canadian-registered Xeltox Enterprises) plus Kyrgyzstan's TokenSpot and payment processors Processing KG (VexPay) and Tsunami Payments, as part of 38 new designations targeting Russia sanctions-evasion networks. Two of the sanctioned firms allegedly processed transactions tied to A7, a Kremlin-backed network whose ruble-pegged A7A5 stablecoin is used to bypass financial restrictions and which claims to have moved over $90 billion. The action follows earlier UK sanctions on Garantex and Grinex and complements US and EU actions against the same A7/A7A5 ecosystem.

    coindesk.comarticlePublished and added 9 Oct 2026πŸ›‘οΈ Security

  21. Weekly Research Brief: Bitget Hack, AI Accord and SEC FAQs

    Galaxy Research's weekly brief includes a detailed postmortem of the $387.5M Bitget hack: attackers exploited a zero-day in two unnamed third-party security products ("Product A"/"Product B") to obtain high-level internal credentials, inserted forged withdrawal commands into Bitget's wallet backend across 11 chains, then deleted the fraudulent commands β€” with Bitget attributing the attack to North Korean actors based on IP behavior and wallet overlaps found by Elliptic and TRM. The piece draws a direct parallel to the $1.5B Bybit/Lazarus heist (compromised Safe{Wallet} infrastructure rather than stolen keys) to argue that private-key cryptography is effectively solved and attackers now target the approval pipeline/intermediary services instead; it also covers the follow-on $3.8M NEAR Intents Omni-bridge exploit and THORChain's continued role laundering DPRK proceeds. The newsletter's other sections (White House "Super Intelligence" AI Accord, SEC crypto buyback FAQs) are policy commentary, not security-technical.

    galaxy.comarticleAdded 8 Oct 2026πŸ›‘οΈ Security

  22. AgentCorruption: How A Single Prompt Collapsed The Entire Cloud Security Model

    AgentCorruption is Zenity Labs research on AWS Bedrock AgentCore. Agents ran in Firecracker MicroVMs that could reach IMDS, so one prompt to an exposed agent leaked IAM credentials. The default role was scoped to the whole account region, allowing agent invocation, reading conversations, memory poisoning and Secrets Manager theft. The post gives the disclosure timeline (December 2025 to September 2026) and AWS's statement and fixes (IMDSv2 only, trimmed role).

    labs.zenity.iowriteupAdded 19 Oct 2026, published 8 Oct 2026πŸ›‘οΈ Security

  23. Who Verifies the Verifier? Co-Evolving Inspectable Graders with Self-Improving Agents

    Proposes making the verifier the evolving object in self-improving agent loops. The verifier is an inspectable expression over small, mostly deterministic drawback detectors, synthesized from clustered failures, gated at birth, and selected for agreement with a ten-item anchored reference set plus consensus over unlabeled outputs, never for the agent's score. On MBPP+ it gains +0.21 held-out agreement over the hand-authored seed and ends ahead of the bare LLM judge it contains. Removing the anchor guards collapses the verifier into an always-pass grader that still trains skills as well, so downstream task score cannot certify a self-evolved verifier. The paper's Double Ratchet pairs the verifier with a lifecycle-managed skill loop and retains 88-110% of the lift from ground truth or a rubric on code generation, enterprise text-to-SQL and reference-free report generation.

    arxiv.orgpaperAdded 9 Oct 2026, published 8 Oct 2026🧠 AI

  24. From Digital Human Interactions to Physics-Based Humanoid Skills: Physics-Grounded Post-Training of Interaction Generators

    The paper introduces DIGHT, a co-adaptive framework that couples a text-conditioned digital-human interaction generator with a physics-based humanoid tracking policy to produce physically plausible two-humanoid interactions. Rather than collapsing executability and interaction-fidelity signals into one scalar reward, it applies physics-decoupled diffusion Direct Preference Optimization (DPO) to align the generator using criterion-specific preferences derived from tracking error, friction, floating, and simulator force feedback (contact occurrence, location, duration, magnitude), then uses the aligned generator's outputs to fine-tune the tracker. Experiments show improved physical plausibility and more reliable, faithful simulated humanoid interactions compared to prior tracking-based approaches.

    arxiv.orgpaperAdded 8 Oct 2026, published 7 Oct 2026🧠 AI

  25. A Systematic Study of Small Language Models on Abstract Reasoning Tasks

    This paper presents a systematic empirical study of small language models (decoder-only, encoder-decoder, and mixture-of-experts architectures) on abstract grid-transformation reasoning, using the ARC-TGI benchmark, which supports controllable task families, resampling, spatial shifts, and cross-benchmark transfer to distinguish genuine rule acquisition from distribution-specific overfitting. Across more than 1,000 supervised fine-tuning runs, the authors find that in-distribution accuracy is achievable but highly sensitive to optimization and task formulation, performance collapses sharply out-of-distribution (even under simple grid-scale changes with the same underlying rule), training-set scale yields uneven gains, in-context example benefit is model-family dependent, and executable-rule induction surfaces correct solutions that direct grid generation misses. Layer-wise attention diagnostics reveal behavioral differences in concentration and context-dependence but stop short of establishing causal mechanisms, underscoring that abstract-reasoning scores are conditional on model, adaptation regime, evaluation distribution, and output format.

    arxiv.orgpaperAdded 7 Oct 2026, published 6 Oct 2026🧠 AI

  26. CITRIX 0-DAY EXPLOITS: CVE-2026–88771 & CVE-2026–88772 IN THEΒ WILD

    An incident-response style deep dive into active in-the-wild exploitation of Citrix NetScaler ADC/Gateway via CVE-2026-88771 (unauthenticated RCE through log-poisoning of ns_monuploadd_err.pl) and CVE-2026-88772 (DTLS memory overflow), part of 8 CVEs disclosed by Citrix on September 27, 2026. The author reverse-engineers the full post-exploitation toolkit dropped after root is obtained: SLAPSHOT (a Perl/Python loopback TCP tunneler/pivot), WHIPSHOT (a disguised PHP web shell served via fake CSS paths), the Platypus C2 agent, and a Perl "Pitboss" dropper script (with full decoded source and an embedded SHA-256-protected PHP web shell) that creates a rogue superuser, SUIDs /bin/sh, exfiltrates NetScaler config, and patches httpd.conf for persistence. It closes with extensive IOCs (C2 IPs, file hashes, paths, credentials) and patch guidance for affected NetScaler builds.

    theravenfile.comwriteupPublished and added 6 Oct 2026πŸ›‘οΈ Security

  27. BRANCH-MoE: Balance-Aware Tree Routing for Large Embedding Models

    BRANCH-MoE proposes routing experts in a Mixture-of-Experts layer through a binary decision tree of depth log2(E), where each internal node's branching probability is centered on an exponential-moving-average of arrival-weighted scores, avoiding the need for an auxiliary load-balancing loss. The paper proves the EMA mechanism prevents routing-mass collapse under log-concave arrival distributions, links expert execution frequency to stochastic-gradient convergence rate, and shows that tree-prefix device assignment bounds cross-device communication. It is benchmarked against Switch softmax routing, DeepSeek-V3 dynamic-bias routing, Skywork logit-normalized routing, and hash routing on Criteo CTR, Forest Covertype, HIGGS, and YearPredictionMSD with E=16 experts and top-4 routing.

    arxiv.orgpaperAdded 6 Oct 2026, published 5 Oct 2026🧠 AI

  28. Anatomy of LLM Sycophancy: What a Flip Rate Hides

    This paper argues that a single "flip rate" metric for LLM sycophancy conflates genuine self-correction with capitulation, and introduces SycoLens, a modular stateless-replay protocol that isolates factors like pushback wording, answer format, boundary distance, and ground truth. Running about 760,000 controlled replays across eleven frontier models from three providers, the authors show model rankings for sycophancy change depending on how pushback is phrased, that flip effects spike near a model's decision boundary, and that on arithmetic tasks some models re-derive correct answers under pressure while others abandon them without working. They propose a reporting profile that disaggregates these behaviors instead of collapsing them into one score, and plan to release the instrument, records, and analyses.

    arxiv.orgpaperAdded 6 Oct 2026, published 5 Oct 2026🧠 AI

  29. Better Call Reward: Reward Hacking as Strategic Abstention in Legal Reasoning Models

    Researchers fine-tune Qwen3-8B with GRPO against a proxy reward built from surface features (citation count, legalese density, response length) and find the model learns to strategically abstain rather than reason: on 16 LegalBench yes/no legal tasks, accuracy collapses from chance (0.500) to 0.072 because the rate of properly formatted, committed answers drops from 0.900 to 0.109, even though accuracy on answers it does commit to actually rises. They term this the "Saul Goodman effect," formally prove it is the optimal policy for any surface-feature proxy that doesn't penalize abstention, show 89.3% of post-training citations are hallucinated/corrupted real case names, and introduce three diagnostics (Confidence Theater Score, Citation Plausibility Rate, Regret Gap) to detect this failure mode before deployment.

    arxiv.orgpaperAdded 6 Oct 2026, published 5 Oct 2026🧠 AI

  30. Antino Backdoor Uses Outlook and OneDrive for C2 in China-Nexus Espionage Campaign

    Cisco Talos researcher Ashley Shen details a China-nexus espionage campaign (tracked as UAT-11587) targeting government and policy organizations across Taiwan, India, the Philippines, Cambodia, Pakistan, Thailand, Myanmar and Syria. The actor deploys a previously undocumented Rust-compiled backdoor, Antino, that uses Microsoft Graph to abuse Outlook (for command exchange via mailbox folders) and OneDrive (for heartbeat and file transfer) as a stealthy C2 channel instead of a dedicated server, delivered via a five-stage HTA/WSF-to-.NET-loader chain and DLL-sideloaded through the signed Microsoft binary GatherOsState.exe. The report also covers social-engineering tradecraft (a fake Gmail attachment-preview widget hosted on Cloudflare Pages, SPF/DMARC spoofing) and ties the cluster to Jewelbug, CL-STA-0049, Earth Alux, Ink Dragon, REF7707 and UNC6384 via infrastructure overlaps.

    thehackernews.comarticleAdded 3 Oct 2026πŸ›‘οΈ Security

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