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RightCrowd Pass unifies mobile, physical, and biometric credentials

RightCrowd launched Pass, a credentialing platform unifying mobile, physical, and biometric access credentials, cutting credential revocation from 12.2 minutes to under 60 seconds.

RightCrowd announced Pass, a solution that issues and manages mobile, physical, and biometric access credentials from a single platform instead of fragmented badge programs. Mobile credentials are provisioned through a web-based API and can be suspended or revoked individually or in groups in under 60 seconds, versus an average 12.2 minutes for handling a lost or damaged physical badge. Each mobile credential is tied to a device via two-factor authentication, works with HID, Wavelynx, and LEGIC infrastructure, and counts toward LEED and BREEAM sustainability credits. The product is available now to new and existing customers and can be added to current RightCrowd SmartAccess deployments.

Help Net Security · 22d agoTools

PIA-Bench: Towards Automated Privacy Impact Assessment with Large Language Models

Researchers release PIA-Bench, the first open benchmark evaluating how accurately LLMs can automate privacy impact assessments using 73 curated federal PIAs.

PIA-Bench is the first open benchmark for evaluating large language models on real-world privacy impact assessments (PIAs). The authors audited 499 expert-authored PIAs published by US federal agencies and curated 73 structured PIAs comprising 451 privacy risk items and 831 mitigation items. Off-the-shelf LLMs were found to produce meaningful assessments while identifying clear avenues for improvement. The paper calls for domain-specific LLM agent workflows, accountable LLM infrastructure, and new quality standards for PIAs.

arXiv cs.CR · 6d agoResearch1

GDCM <= 3.2.7: six memory-safety and denial-of-service vulnerabilities, no CVE

Six memory-safety and denial-of-service flaws disclosed in the GDCM DICOM parsing library, affecting versions through 3.2.7.

Researcher Abhinav Agarwal disclosed six vulnerabilities in GDCM (Grassroots DICOM), an open-source C++ library for parsing and processing DICOM files. All six were confirmed against GDCM 3.2.6 using AddressSanitizer and UndefinedBehaviorSanitizer, and source review found the vulnerable patterns through version 3.2.7 and the upstream master snapshot. Potential impacts include heap corruption, process-memory disclosure, stack exhaustion, and process termination in applications parsing untrusted DICOM files. No CVE identifiers have been assigned at the time of disclosure.

oss-security · 7d agoVulnerability

Fortunate Recall: Ontology-Driven Memory Lifecycle Management for Persistent Coherence in LLMs

Fortunate Recall introduces ontology-based lifecycle policies for LLM memory, cutting confabulation roughly in half (e.g., 45.1% to 22.4%) versus Mem0.

Fortunate Recall (FR) is a composable policy layer that classifies personal facts into a 10+1 behavioral ontology and applies category-specific lifecycle rules including differential temporal decay, slot-key supersession, event-time validity, and retrieval routing. FR-Bank scores 76.9% on the new 516-question LifecycleBench, ahead of Mem0, A-MEM, Memory-R1, and MemoryOS (61%-70.5%), and 75.2% on LongMemEval-S. End-to-end, confabulation drops from Mem0's 45.1% to 22.4% over answered queries, with the ranking replicating on open-weight Kimi K2.5 and transferring to the independent BEAM benchmark (46.8% vs 32.9%).

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

Speculative Decoding in vLLM on AMD GPUs

vLLM benchmarks speculative decoding on AMD Instinct MI300X and MI355X GPUs across five drafting methods including EAGLE-3 and native MTP.

The vLLM project documents draft-and-verify speculative decoding support for AMD GPUs via ROCm, comparing native MTP, Gemma 4 MTP, EAGLE-3, DFlash, and DSpark drafting approaches. Output-token throughput effects varied with drafting method, proposal length, model family, draft checkpoint, workload, and acceptance behavior. The post also covers how to enable each method plus practical tuning and observability considerations.

ZGCM-1: A Fully Open and Extremely Efficient Foundation Model for Math and Agentic Search

ZGCM-1 is a fully open 7B foundation model with 256K context that stays competitive with frontier models on math reasoning and agentic search.

ZGCM-1 is a fully open 7B dense foundation model trained from scratch using an efficiency-focused recipe: interleaved gated sliding-window and full attention, a stable FP8 Muon optimizer, and MDP-based mid-training with context scaling across 16K, 64K, and 256K. On mathematical reasoning and agentic search suites it remains competitive with much larger frontier models such as Qwen3-235B-A22B and GLM-5.1. The recipe yields a ~4.2x improvement in 16K pre-training time-to-loss, and all weights, checkpoints, training code, data recipes, and W&B logs are open-sourced.

Hugging Face daily papers · 6d agoModel release

Generative Marketing Mix Modeling: A Causal Inference Framework Linking GEO and GEM to Business Impact

Paper proposes Generative Marketing Mix Modeling to causally estimate Generative Engine Optimization and Marketing effects on business outcomes.

The authors develop GMMM, a causal inference framework for measuring how often users see and notice a firm's name in generated answers, which standard marketing data ignore. For GEO it combines repeated generated answers with question counts, shares of generative-system usage and notice probabilities; for GEM it uses sponsored placement records with notice probabilities. The framework compares expected business responses under alternative treatment sequences, establishes identification conditions, and is evaluated on simulated product-recommendation answers in English and Japanese.

arXiv cs.AI / cs.LG / cs.CL · 6d agoAI research

Before You Poll with LLMs: A Deliberative Diagnostic Framework

Deliberative diagnostic shows all five tested frontier LLMs misrepresent human belief shifts after arguments, with GPT-5.1 reversing on outgroup questions.

The Deliberative Polling Diagnostic Framework compares human and LLM persona belief shifts after identical informational interventions, using data from America in One Room (526 personas, 72 questions). All five frontier models tested failed uniquely: GPT-5.1 exhibited partisan reversal (80% on outgroup vs 26% on policy questions), Gemini 2.0 Flash, Claude Sonnet 4.5 and Llama 3.3 70B overshot at 5-7x human magnitude, and DeepSeek V3 showed near-zero change (rigidity). The authors term the underlying signature 'self-sycophancy', conformity to the model's internal persona stereotype rather than reasoning from provided information.

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

ZDI-26-608: Linux Kernel KVM IOAPIC Use-After-Free Local Privilege Escalation Vulnerability

The Linux kernel KVM IOAPIC has a use-after-free (CVSS 8.2) allowing local privilege escalation, but exploitation requires high-privileged code execution first.

ZDI-26-608 describes a use-after-free vulnerability in the Linux kernel's KVM IOAPIC component, with a CVSS score of 8.2. An attacker must first obtain the ability to execute high-privileged code on the target system, which limits the practical impact of the privilege escalation. The advisory text does not list an assigned CVE identifier.

ZDI Published Advisories · 24d agoVulnerability

ConvMem: Convolutional Memory for Long-Context Reasoning

Researchers propose ConvMem, a training-free framework treating LLMs as convolutional kernels for parallelizable long-context reasoning beyond fixed context windows.

ConvMem reformulates long-context reasoning as a hierarchical convolution in which the LLM summarizes text segments hierarchically, shortening the reasoning path from a linear chain to a logarithmic tree. It uses configurable strides, skip connections, and multi-kernel convolution to capture evidence, decompose queries, and enable massive parallelization across segments and reasoning threads. On RULER-HotpotQA and RULER-2WikiMultiHopQA it outperforms training-free baselines and avoids the out-of-distribution overfitting seen in RL-trained approaches like MemAgent.

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

CVE-2026-89775: Guest-to-Host Escape in KVM/arm64

Disclosed CVE-2026-89775 lets a guest VM escape to the host on KVM/arm64 systems with nested virtualization enabled.

Researcher Hyunwoo Kim disclosed CVE-2026-89775, a guest-to-host escape in KVM/arm64, after the embargo agreed with linux-distros maintainers expired. The root cause is a type truncation of the stage-1 walk level that makes a size computation return 0, the value meaning 'size unknown'. The VNCR pseudo-TLB invalidation path then interprets that 0 as a valid value on ARM64 hosts where nested virtualization is enabled.

oss-security · 20h agoVulnerabilityCVE-2026-89775

Locus: A Framework for Exploring and Optimizing Point Addition Hardware for Zero-Knowledge Proofs

Locus framework automates ASIC and FPGA point-addition designs for elliptic curves, achieving 2.71x speedups and 3.11x area reductions for ZKPs.

Locus is a framework that automatically generates ASIC and FPGA implementations of elliptic curve point addition (PADD) for supported equation forms, enabling exploration of over 1,000 design points. On a 12nm technology node, its designs achieve a 2.71x geomean speedup and 3.11x geomean area reduction versus prior ASICs, plus 34.67x geomean speedup over CPU. Integrated into a prior ZKP accelerator at iso-area, it yields a 3.15x geomean speedup on end-to-end proof generation. The framework is open source on GitHub.

arXiv cs.CR · 21h agoResearch1

Hackers breach F5 BIG-IP APM devices to deploy Linux rootkit

Sophos analyzed a Linux rootkit on F5 BIG-IP APM devices that injects a fileless PHP web shell, likely after CVE-2025-53521 exploitation.

Sophos analyzed a Linux rootkit targeting F5 BIG-IP APM environments, also tracked by ESET as PoisonedRefresh, which hijacks Apache's apr_dso_load module loader to inject a fileless PHP web shell into memory. The implant intercepts __libc_start_main, hides strings with RC4, creates a password-protected local UNIX socket backdoor for interactive Bash access, and persists across BIG-IP upgrade images while modifying SELinux configuration. It is likely a second-stage payload following exploitation of CVE-2025-53521, a critical RCE flaw F5 reclassified from a DoS issue in March. The ShadowServer Foundation tracked 795 F5 BIG-IP APM endpoints exposed online.

BleepingComputer · 8d agoMalware in the wildCVE-2025-53521

ZDI-26-591: NVIDIA TensorRT ONNX File Parsing Heap-based Buffer Overflow Remote Code Execution Vulnerability

ZDI disclosed a heap-based buffer overflow RCE (CVE-2026-24272, CVSS 7.8) in NVIDIA TensorRT ONNX parsing, requiring user interaction to exploit.

The Zero Day Initiative published advisory ZDI-26-591 covering a heap-based buffer overflow in NVIDIA TensorRT's ONNX file parsing. Successful exploitation allows remote code execution when a user opens a malicious ONNX file or visits a crafted page. ZDI rated the vulnerability CVSS 7.8 and assigned CVE-2026-24272.

USN-8772-1: AOM vulnerabilities

Ubuntu USN-8772-1 patches four libaom flaws (CVE-2026-56208 to CVE-2026-56211) that could cause heap overflow, arbitrary memory writes, or code execution.

Ubuntu Security Notice USN-8772-1 fixes a heap buffer overflow in libaom's first-pass statistics buffer handling in Look-Ahead Processing mode (CVE-2026-56208), potentially causing denial of service or arbitrary code execution. Three additional flaws in spatial and temporal layer ID validation in the SVC encoder controls (CVE-2026-56209, CVE-2026-56210, CVE-2026-56211) allow arbitrary memory writes, out-of-bounds heap reads, or code execution. Users should apply the updated packages.

Ubuntu Security Noticesupdated · 16h agofirst · 1d agoAdvisory 7 sourcesCVE-2026-56208CVE-2026-56209CVE-2026-56210+1 CVEs

ZDI-26-593: NVIDIA TensorRT ONNX File Parsing Heap-based Buffer Overflow Remote Code Execution Vulnerability

ZDI disclosed a second TensorRT heap-based buffer overflow RCE (CVE-2026-24268, CVSS 7.8) in ONNX file parsing, requiring user interaction.

The Zero Day Initiative published advisory ZDI-26-593 covering another heap-based buffer overflow in NVIDIA TensorRT's ONNX file parsing. A remote attacker can execute arbitrary code if the target opens a malicious file or visits a crafted page. ZDI rated the vulnerability CVSS 7.8 and assigned CVE-2026-24268.

Stealth rootkit targeting F5 BIG-IP could expose enterprise identity gateways

Sophos analyzed a stealth Linux rootkit that hides a web shell in memory on compromised F5 BIG-IP APM identity gateways, evading file-based detection.

Sophos analyzed a second-stage Linux rootkit implant found in compromised F5 BIG-IP APM environments running Apache and PHP, linked to exploitation of CVE-2025-53521, an unauthenticated RCE. The implant hooks Apache's PHP-loading process and serves modified in-memory versions of three legitimate webtop PHP files (apm_css.php3, full_wt.php3, webtop_popup_css.php3), leaving on-disk files untouched so hashes and integrity checks pass. It also establishes access via an authenticated local UNIX socket that can provide an interactive /bin/bash session. Experts warn compromised APM appliances, which handle federated SSO and terminate TLS at enterprise perimeters, could enable SSO token theft and lateral movement to trusted downstream applications.

CSO Online · 7d agoMalware in the wildCVE-2025-53521

Molecular Déjà Vu: Digit-Level Retrieval of Published Values in Frontier Language Models

Audit of 22 frontier models finds widespread verbatim retrieval of published molecular property values, with higher reasoning increasing recall of memorized numbers.

An arXiv audit tests 22 frontier LLMs across 12 molecular regression benchmarks for verbatim retrieval of published values. More than 50% of the LLMs show verbatim retrieval on five datasets, and identical experiments are flagged 89% more often at a high reasoning level than at the lowest one. Suppressing retrieval moves model prediction errors closer together in relative terms, suggesting predictive capability is not determined solely by memorized values.

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

Necessary or Sufficient? Evaluating LLM Explanations With Behavioural Evidence

New framework tests whether LLM-cited explanation factors are necessary or sufficient, finding weak correlation across Claude, GPT, and Gemini models.

An arXiv paper introduces black-box intervention tests measuring whether factors LLMs cite in their explanations are necessary or sufficient for their outputs in agent oversight workflows. Across eight models from the Claude, GPT, and Gemini families, Spearman correlations between cited rankings and measured influence ranged from 0.349-0.354 (advisor recommendation) to 0.431-0.580 (prompt monitoring). Uncited factors scored above the lowest cited factor in up to 57.6% of advisor responses, showing cited top-three factors do not reliably identify the most influential inputs.

Fly Language Model (FLM) Wires the Full Fruit Fly Connectome Into a Frozen 1.2B LLM, and Its Own Controls Show the Wiring Does Not Help

Researchers wire the full fruit fly connectome (166,700 nodes) into a frozen LiquidAI LFM2.5-1.2B LLM, but controls show no fly-specific benefit.

The Fly Language Model (FLM) couples the complete MaleCNS v1.0 fruit fly connectome (166,700 nodes, 25,582,938 edges) to a frozen LiquidAI LFM2.5-1.2B-Instruct backbone, training only a 278,528-parameter readout (~0.0238% of backbone parameters). The fly readout improved NLL by 0.0222 nats/token (perplexity 3.98 to 3.90) on 32 SmolTalk dialogues, but a direct-input control without the graph beat it in all three seeds. Relabeling node identities removes the gain and the recurrence contracts state differences by 0.6 per token, so the connectome adds no long-range memory. The MIT-licensed code runs locally on Python 3.12, but study artifacts remain private, limiting independent reproducibility.

MarkTechPost · 4d agoAI research1

LLMs and Contextual Integrity

Bruce Schneier highlights two papers: the CIMemories benchmark shows frontier LLMs leak memory attributes up to 69%, and an RL method reduces inappropriate disclosures.

Bruce Schneier discusses contextual integrity in LLMs, referencing the CIMemories benchmark, which uses synthetic profiles with 100+ attributes per user to test whether models with persistent memory disclose sensitive information appropriately. Evaluation showed frontier models exhibit up to 69% attribute-level violations, with GPT-5's violation rate rising from 0.1% to 9.6% across 40 tasks and reaching 25.1% with repeated prompting, showing unstable leakage behavior. A second paper introduces a reinforcement learning framework trained on a synthetic 700-example dataset that substantially reduces inappropriate disclosure while maintaining task performance, with improvements transferring to the human-annotated PrivacyLens benchmark.

Schneier on Security · Aug 18, 2026AI safety & security1

Hackers deploy Linux rootkit on F5 BIG-IP APM devices, hiding web shell in memory

Sophos analyzed a Linux rootkit, tracked as PoisonedRefresh, on hacked F5 BIG-IP APM devices hiding an in-memory web shell linked to exploited CVE-2025-53521.

Sophos and ESET analyzed an implant (named PoisonedRefresh by ESET) deployed on compromised F5 BIG-IP APM appliances, which serves enterprise, financial, government, and public sector deployments. The second-stage payload intercepts __libc_start_main, hooks Apache's APR module loader (apr_dso_load), RC4-encodes key strings, and rewrites PHP file reads in memory to embed a web shell inside legitimate scripts like apm_css.php3, full_wt.php3, and webtop_popup_css.php3, leaving on-disk files unchanged. A related installer component infects /usr/sbin/httpd, persists across BIG-IP upgrade images, modifies SELinux configuration, and deploys the payload. The malware also creates a Unix domain socket at /run/bigtlog.pipe that hands authenticated local connections to /bin/bash; F5 links the activity to CVE-2025-53521, an unauthenticated RCE in BIG-IP APM already exploited in the wild.

Help Net Security · 8d agoMalware in the wildCVE-2025-535211

F5 BIG-IP APM Malware Injects a PHP Web Shell Into Memory, Evading Disk Scans

Sophos found F5 BIG-IP APM malware that injects a PHP web shell into Apache's memory, evading disk scans, linked to exploited CVE-2025-53521.

Sophos's September 7 analysis describes malware tied to F5's c05d5254 activity that hooks apr_dso_load, modifies the libphp PHP module in memory, and injects a PHP web shell when Apache loads apm_css.php3, full_wt.php3 or webtop_popup_css.php3, leaving on-disk files clean. A separate installer infects /usr/sbin/httpd and umount, runs before Apache starts, disables SELinux (per ESET's related PoisonedRefresh analysis), and opens a local socket at /run/bigtlog.pipe for shell access. The activity is linked to CVE-2025-53521 in BIG-IP APM, rated 9.8 CVSS 3.1, patched in October 2025, added to CISA KEV on March 27, 2026.

The Hacker News · 8d agoMalware in the wildCVE-2025-53521

ZDI-26-576: Linux Kernel XFRM Race Condition Local Privilege Escalation Vulnerability

ZDI disclosed a race condition local privilege escalation flaw in the Linux Kernel XFRM subsystem, CVSS 7.5, with no CVE assigned.

The Zero Day Initiative published ZDI-26-576 describing a race condition in the Linux Kernel XFRM subsystem. Local attackers can escalate privileges, but the advisory states an attacker must first be able to execute high-privileged code on the target. ZDI assigned a CVSS score of 7.5; no CVE identifier is listed in the advisory text.

ZDI Published Advisories · Aug 13, 2026Vulnerability

OpenWAM: An Open, Modular Exploration Towards Systematic World-Action Model Pretraining

OpenWAM releases an open modular stack for world-action model pretraining, plus OpenWAM-alpha trained on about 6,400 hours of egocentric and robot data.

OpenWAM is an open research stack that factorizes World-Action Model pretraining into composable infrastructure, study, and model components with unified training, inference, and evaluation. Controlled experiments distill three principles on knowledge inheritance, world-action synergy, and out-of-domain generalization gains from embodied co-training. The resulting OpenWAM-alpha, pretrained on roughly 6,400 hours of egocentric human and robot data, achieves top-tier results across eight simulation benchmarks and real-robot tests spanning single-arm, bimanual, and dexterous embodiments. The full stack, including infrastructure, evaluation protocols, pretrained models, and data recipes, is released openly.

Hugging Face daily papers · 10d agoAI research

ZDI-26-572: Linux Kernel XFRM Race Condition Local Privilege Escalation Vulnerability

ZDI publishes ZDI-26-572, a CVSS 7.5 race condition local privilege escalation in the Linux kernel's XFRM subsystem.

The Zero Day Initiative disclosed a race condition in the Linux kernel's XFRM (transform) subsystem allowing local attackers to escalate privileges. Exploitation requires the attacker to first run high-privileged code on the affected system. The advisory carries a CVSS rating of 7.5; no CVE id is listed in the disclosure text.

ZDI Published Advisories · Aug 13, 2026Advisory

MetroLLM-Bench: Evaluating Language Models as Transit Kiosk Runtimes

MetroLLM-Bench is a 955-case benchmark testing language models as transit kiosk tool-calling runtimes across six real metro systems.

The benchmark covers 37-414-station metro systems and eleven task categories including routing, fare calculation, disruptions, accessibility, and adversarial input, with 14 deterministic and 8 semantic scoring components. Of 26 models from six vendors, a PEFT-tuned 4B Qwen 3.5 student scored 91.3 on Tier 1, exceeding GPT-5.6 (90.6/90.0), while Muse Glimmer 30B led the composite ranking. A deterministic rule-based baseline reached 84.6, and PEFT gains over base models shrank from +7.03 points at 2B to -0.91 at 27B.

Hugging Face daily papers · 8d agoAI research1

Ivanti Patches 10 EPMM, Neurons for ITSM and Sentry Flaws Enabling RCE and Admin Access

Ivanti patches 10 flaws in EPMM, Neurons for ITSM, and Sentry, including two 9.8-rated unauthenticated RCEs in ITSM.

Ivanti released fixes for 10 vulnerabilities across Endpoint Manager Mobile, Neurons for ITSM, and Sentry, and said it was not aware of active exploitation at disclosure. The most severe are CVE-2026-12744 and CVE-2026-12745, unauthenticated deserialization RCEs rated 9.8 in Neurons for ITSM, alongside authenticated deserialization and missing-authorization RCEs rated up to 9.9. CVE-2026-18851 is an 8.8-rated EPMM privilege escalation to administrator, and CVE-2026-83527 is an 8.1-rated unauthenticated authentication bypass in Sentry granting administrative access. Ivanti said the ITSM weaknesses were found using large language models; Cloud/SaaS fixes shipped August 9, 2026, and on-premises patches are available from September 2026.

SonicWall security advisory (AV26-884)

Canada's Cyber Centre issued advisory AV26-884 warning that SonicWall Network Security Manager On-Prem 4.3.0 and earlier are affected by multiple vulnerabilities.

The Canadian Centre for Cyber Security published advisory AV26-884 on September 4, 2026, flagging SonicWall Network Security Manager (NSM) On-Prem across VMware, Hyper-V, Azure, and KVM deployments, versions 4.3.0 and earlier, as affected by multiple vulnerabilities. The advisory does not list CVE identifiers, exploit details, or in-the-wild exploitation. Administrators are encouraged to review the referenced links and apply updates as they become available.

Canadian Centre for Cyber Security · 8d agoAdvisory

CVE-2026-67211: Apache OpenNLP: OOM DoS via Unbounded Array Allocation in SymSpellModelSerializer

Apache OpenNLP CVE-2026-67211: unbounded map pre-sizing in SymSpellModelSerializer enables out-of-memory denial of service in opennlp-symspell 3.0.0-M4/M5.

CVE-2026-67211 affects the opennlp-symspell artifact in versions 3.0.0-M4 and 3.0.0-M5 only. The SymSpellModelSerializer.create() method performs unbounded map pre-sizing, allowing crafted input to trigger out-of-memory denial of service. Releases 1.x and 2.x are unaffected because the spellcheck extension was introduced in 3.0.0-M4; the issue is resolved in 3.0.0-M6.

Ivanti EPMM, Neurons and Sentry Vulnerabilities Enable Privilege Escalation and RCE Attacks

Ivanti patched ten CVEs across EPMM, Neurons for ITSM and Sentry, including critical unauthenticated deserialization RCE; no active exploitation reported.

On September 8, 2026, Ivanti disclosed advisories covering ten CVEs in Endpoint Manager Mobile (EPMM), Neurons for ITSM, and Sentry. The most severe are two unauthenticated deserialization RCE flaws in Neurons for ITSM, CVE-2026-12744 and CVE-2026-12745 (CVSS 9.8), plus three missing-authorization RCE bugs rated 9.9 and three authenticated deserialization RCE flaws. EPMM has CVE-2026-18851 (CVSS 8.8), an authenticated privilege escalation flaw, and Sentry has CVE-2026-83527 (CVSS 8.1), an authentication bypass. Ivanti reports no evidence of active exploitation; cloud/SaaS ITSM was patched on August 9, 2026, while on-premises 2025.2 through 2026.1 require September 2026 patches.