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Smart search ranks by meaning as well as keywords (one row per story, last 45 days).
Next.js security advisory (AV26-851)
Canada's Cyber Centre warns Next.js 15.5 and 16.3 are affected by critical vulnerabilities; users should update to 15.5.24 and 16.3.3.
The Canadian Centre for Cyber Security (AV26-851) warns that Next.js versions 15.5 prior to 15.5.24 and 16.3 prior to 16.3.3 are affected by critical vulnerabilities. Administrators are urged to review the vendor advisory and apply the August 2026 security release updates. The bulletin provides no CVE ids or exploitation details.
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Next.js Patches Critical AVIF and Windows Flaws Enabling Unauthenticated RCE
Vercel patches two critical Next.js unauthenticated RCE flaws: a libheif AVIF heap overflow (CVSS 9.5) and a Windows path traversal (CVE-2026-75604).
Vercel patched two critical Next.js flaws enabling unauthenticated remote code execution: a heap buffer overflow in libheif's AVIF image scaling (GHSA-2xp9-vwfh-vxw4, CVSS v4 9.5) and a Windows path traversal (CVE-2026-75604, CVSS 9.0). The AVIF flaw affects only sites explicitly enabling AVIF optimization and overwrites roughly 16,384 bytes past the buffer; the path traversal affects Windows-hosted Next.js deployments on versions 13.4-15.5.23 and 16.0-16.3.2. Fixes shipped in Next.js 15.5.24 and 16.3.3 on August 25, 2026, with the AVIF researchers releasing a Python PoC demonstrating RCE on multiple applications. No exploitation had been reported as of August 27, 2026.
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Drupal core - Moderately critical - Third-party libraries - SA-CORE-2026-013
Drupal issues moderately critical advisory for XSS in bundled CKEditor affecting content editors; fixed versions released, exploitation theoretical.
Drupal published SA-CORE-2026-013, rated moderately critical (13/25), covering an XSS vulnerability in the CKEditor library used for WYSIWYG editing. An attacker able to create or edit content, even without direct CKEditor access, could exploit it to target users with WYSIWYG permissions. Affected versions include Drupal core 10.5.x, 11.0.x and 11.4.x below 11.4.7, and updated releases are available. Exploitation is rated theoretical.
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Siemens Teamcenter
Reflected XSS in Siemens Teamcenter /auth/ redirect flow lets unauthenticated attackers inject JavaScript into authenticated sessions (CVE-2026-58113).
CISA republished Siemens advisory SSA-157465 for CVE-2026-58113, a reflected cross-site scripting flaw (CVSS 6.1) in the /auth/ authentication redirect flow of Siemens Teamcenter V2412, V2506, V2512, and V2606. An unauthenticated attacker can craft a URL that injects arbitrary JavaScript into an authenticated user's browser, enabling data theft or actions within the victim's Teamcenter session. Fixed versions are available for all affected releases; Enzo Alvarez of Bishop Fox reported the vulnerability.
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llm 0.34
Version 0.34 of Simon Willison's llm CLI adds response-duration metrics to log output, plus bug fixes and faster log querying.
The open-source llm command-line tool for interacting with large language models released version 0.34. The headline change adds response duration in milliseconds and human-readable form to llm logs --usage Markdown output, plus a new duration_ms field in llm logs --short. The release includes several contributed bug fixes and a significant performance improvement to llm logs, alongside the related llm-openrouter 0.7.1 release.
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[20260802] - Core - Improper CORS origin validation
Joomla patches CVE-2026-71573, improper CORS origin validation in CMS requests, in versions 5.4.8 and 6.1.3.
Joomla disclosed improper CORS origin validation (CVE-2026-71573), where configured CORS origins were not properly validated on CORS requests, rated moderate impact/severity and moderate probability. It affects Joomla CMS 4.0.0-5.4.7 and 6.0.0-6.1.2. Fixed in Joomla 5.4.8 and 6.1.3; reported on 2026-07-09 by Agamemnon Fakas and caveeroo.
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automatic module_metadata_base.json update
Metasploit Framework's automated pipeline refreshed its module metadata file, a routine repository maintenance commit introducing no new modules or exploits.
An automated Metasploit Framework commit updated module_metadata_base.json, the metadata database consumed by module tooling. The change is routine maintenance and contains no new exploit modules or vulnerability content.
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Climate-ModernBERT: Revisiting Corpus Composition for Domain-Adaptive Continued Pretraining
Climate-ModernBERT domain-adapted encoders reach 76.3 average F1 across nine climate benchmarks, 2.8 points above vanilla ModernBERT-Base.
The authors continue pretraining ModernBERT-Base on three climate corpora - academic text, climate-filtered web data, and synthetic documents - and compare joint mixtures against parameter-space merging of specialized checkpoints. The best model achieves 76.3 average F1 across nine climate NLP benchmarks, a 2.8-point improvement over the vanilla baseline. Academic climate corpora provide the strongest adaptation signal, and parameter-space merging outperforms joint multi-source training while preserving complementary corpus information; all variants are released.
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automatic module_metadata_base.json update
Routine automated Metasploit Framework commit updating module metadata, with no disclosed vulnerability or exploitation activity.
The Metasploit Framework repository received an automatic update to its module_metadata_base.json file. The commit text contains no vulnerability details, CVE references, or new exploit modules. This is routine maintenance activity on the open-source penetration testing framework.
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[0day-rubbish] Royal Server 5.04.50529.0 Local privilege escalation to LocalSystem on the execution path without credential override (7.2)
0day Rubbish Research Team disclosed a CVSS 7.2 local privilege escalation (CWE-250) in Royal Server 5.04.50529.0 to LocalSystem.
Researchers publicly disclosed a local privilege escalation vulnerability in Royal Server 5.04.50529.0, classified as CWE-250 (execution with unnecessary privileges) with a CVSS score of 7.2. The flaw allows escalation to LocalSystem on the execution path without credential override. The disclosure was posted to the Full Disclosure mailing list on September 8, 2026; no patch or CVE id was mentioned in the notice.
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automatic module_metadata_base.json update
Metasploit Framework automatically updates its module metadata JSON in routine maintenance commit.
The Metasploit Framework repository received an automatic update to module_metadata_base.json, the metadata file that tracks module information. No specific new vulnerability, exploit module, or feature is described in the commit message. This is routine repository maintenance rather than a notable security event.
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automatic module_metadata_base.json update
Routine automated Metasploit Framework commit updates module_metadata_base.json with new module metadata.
The Metasploit Framework repository received an automated commit updating module_metadata_base.json, the file that tracks module metadata for the framework. This is routine maintenance accompanying new or updated exploit modules rather than a standalone disclosure. No vulnerability details, CVEs, or exploitation evidence are included.
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Critical MapLibre GL JS Vulnerability Enables Zero-Click XSS Attacks
MapLibre GL JS 6.4.1 patches CVE-2026-85061, a critical zero-click XSS in DOM.sanitize() affecting versions 6.4.0 and earlier.
A critical cross-site scripting vulnerability, CVE-2026-85061 (GHSA-jrc7-96c5-q579), affects maplibre-gl versions 6.4.0 and earlier and is fixed in 6.4.1. The flaw stems from DOM.sanitize() iterating a live NamedNodeMap while deleting attributes, causing the sanitizer to skip adjacent dangerous event-handler attributes that later execute via innerHTML. GitHub rates the issue Critical with CVSS v3.1 vector AV:N/AC:L/PR:N/UI:N/S:C/C:H/I:H/A:N, exploitable without user interaction when untrusted attribution strings are rendered. Organizations should upgrade to 6.4.1 or later, rebuild affected bundles, and sanitize attribution fields as an interim measure.
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Telegram Desktop Flaw Lets Hidden JavaScript Exfiltrate Messages From HTML Exports
Telegram Desktop HTML export XSS (CVSS 8.2) let bot messages exfiltrate exported chats; fixed in 7.0.1 but old exports stay vulnerable.
ExPatch researchers found that Telegram Desktop versions 4.15.1 (March 2024) through 6.9.3 wrote bot inline-keyboard button text into HTML chat exports without escaping, allowing a bot to plant invisible JavaScript. When a user opened the export in a browser, the script could exfiltrate every message in that 1,000-message file, rewrite the displayed content, or fake a verification form. The flaw (rated CVSS 3.1 8.2) was fixed by commit 8457d13a in 6.9.4 beta (July 3, 2026) and 7.0.1 stable (July 14, 2026), but pre-fix exports remain dangerous since updating the app does not fix old files. No CVE identifier or Telegram security advisory exists, and no exploitation in the wild is claimed.
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ZDI-26-588: Fabric.js loadFromJSON Server-Side Request Forgery Vulnerability
ZDI disclosed a server-side request forgery in Fabric.js loadFromJSON (CVE-2026-19504) that can leak sensitive information from affected implementations.
Zero Day Initiative advisory ZDI-26-588 describes a server-side request forgery vulnerability in the Fabric.js canvas library's loadFromJSON function. Exploitation requires interaction with the library and attack vectors vary by implementation, potentially exposing sensitive information. The issue is rated 4.0 on the CVSS scale and tracked as CVE-2026-19504. The advisory does not report exploitation in the wild.
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[20260806] - Core - XSS through schema.org outputs
Joomla fixed CVE-2026-73336, an XSS in schema.org markup outputs caused by improper escaping, affecting CMS 5.1.0-5.4.7 and 6.0.0-6.1.2.
Joomla security advisory 20260806 describes CVE-2026-73336, a cross-site scripting issue in schema.org markup outputs. Improper escaping flags create an XSS vector in schema.org output; the vendor rates impact and severity as moderate with low probability. Affected versions are 5.1.0-5.4.7 and 6.0.0-6.1.2; fixes ship in 5.4.8 and 6.1.3. The issue was reported by Amin Isayev and Geo (GitHub.com/geo-chen) on 2026-07-21.
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Cohere Releases North Small Translate: A 218B MoE Translation Model That Scores 83.6 on WMT26 Across 50 Languages
Cohere released North Small Translate, an open-weight 218B MoE (25B active) translation model scoring 83.6 on WMT26 across 50 languages.
Cohere and Cohere Labs released North Small Translate, a decoder-only sparse Mixture-of-Experts translation model with 218B total and 25B active parameters, 128 experts with 8 activated per token plus shared experts, and 16K-token input and output context. In Cohere's vendor-reported WMT26 evaluation, judged by GPT-5.6-Sol, it scores 83.6 averaged across 50 languages (84.36 in an agentic multi-pass mode), ahead of DeepL NextGen (81.37), Qwen 3.5 397B A17B (81.56), GLM 5.2 (76.50), and Google Translate (68.20). The model was built with RWS's Language Weaver team, post-trained specifically for translation, and reports 112 output tokens per second versus 81 for Gemma 4 31B, with long-document xCOMET-XL scores of 48.9 versus 21.3 for Google Translate. It is available free on Cohere's Chat V2 API until rate limits, with three self-hosting checkpoints including a 4-bit NVFP4 variant running on 1x B200 or 2x H100.
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CVE-2026-86460: Apache Syncope: Cypher Injection via FIQL Search on Neo4j Persistence
Apache Syncope's Neo4j persistence layer permits Cypher injection via certain FIQL search expressions, affecting versions through 3.0.16, 4.0.7, and 4.1.2.
CVE-2026-86460 is a moderate-severity Cypher injection in Apache Syncope's syncope-core-persistence-neo4j module, triggered when processing some FIQL search strings. Affected versions are 3.0.0-M0 through 3.0.16, 4.0.0-M0 through 4.0.7, and 4.1.0-M0 through 4.1.2. No exploitation is reported; upgrade to fixed releases is advised.
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From Parameters to Answers: How LLMs Retrieve and Use Their Internal Knowledge
Interpretability study traces how Qwen, Llama, and Gemma route query information and internal knowledge across layers when answering questions.
Researchers used layerwise interventions on hidden states to separate query-routing signals from target knowledge in language models, testing Qwen, Llama, and Gemma on country-continent questions with varied answer types. A pair-conditioned request direction strengthens before interventions alter downstream knowledge, opening a causal window while answer-supporting content is still forming. Trajectories differ by model: Gemma shows a partially overlapping mid-layer routing profile, while Llama has no sustained routing-effect window under the same gates.
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Nebulon Enterprise Simulated Threats for Phishing Research (NEST-Phish): A Synthetic Enterprise Phishing Email Dataset for Behavioral and Machine-Learning Research
Researchers release NEST-Phish, a synthetic enterprise phishing email dataset with matched legitimate and phishing emails and cue annotations for detection research.
Academic researchers introduce NEST-Phish, a publicly released synthetic enterprise phishing email dataset built around a fictitious organization named Nebulon. It contains matched synthetic legitimate and phishing emails across a broad set of workplace communication themes, each with interpretable phishing-cue annotations. Human-subject categorizations and supervised classifier evaluations indicate the dataset supports meaningful variation in phishing judgments and provides learnable signal for detection models. It is intended to support work on phishing detection, human susceptibility, explainability, and benchmark development.
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Verifiable by Construction: Claim-Level Evaluation of Verbatim Citation in Clinical Question Answering
Evaluation of twelve LLMs on 222 clinical questions shows verbatim quotes rarely substantiate claims; claude-opus-5 fully substantiates only 37.1%.
The authors build a standardized harness over four clinical practice guidelines and evaluate twelve LLMs on 222 synthetic clinical questions, measuring citation attachment, verbatim quote production, and claim substantiation. Most models attach verbatim quotes to over 90% of claims from prompting alone, though lightweight models like claude-haiku-4.5 struggle. Quotes frequently fail to substantiate claims: claude-opus-5 quotes 98.0% of claims but fully substantiates only 37.1%, exposing a capability gap for verifiable clinical QA.
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automatic module_metadata_base.json update
Automated Metasploit Framework commit refreshes module_metadata_base.json with no new exploit content or vulnerability details.
An automated commit updated module_metadata_base.json in the Rapid7 Metasploit Framework repository. The change reflects routine metadata maintenance and introduces no new modules, exploits, or vulnerability information.
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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.
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Flextype v1.0.0-alpha.3 Server-Side Request Forgery via fetch() in Query API
Flextype CMS v1.0.0-alpha.3 exposes an SSRF flaw in its /api/v1/query endpoint, letting authenticated users make the server send arbitrary HTTP requests.
Flextype CMS v1.0.0-alpha.3 contains a server-side request forgery vulnerability in the expression-processing functionality of the /api/v1/query endpoint. An authenticated remote attacker can supply an arbitrary URL to the exposed fetch() function, causing the server to issue outbound HTTP requests. The application does not sufficiently restrict destination hosts, enabling requests to attacker-controlled or internal targets.
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Large Language Models for HVAC Operations in Building Energy Systems: A Critical Review of Methods, Applications, and Deployment Readiness
Systematic review of 66 studies finds LLMs for HVAC operations are mostly research-stage, with no ready-now deployment and only four pilot-level studies.
A critical review of 66 peer-reviewed studies from 2023 to March 2026 examines LLMs for HVAC operations in building energy systems. Only four studies reach pilot-level evidence, none reports sustained operational deployment, and 63 of 66 are research-only. Conventional ML, MPC, and RL remain dominant for high-frequency control and short-horizon forecasting, and the evidence supports LLMs primarily as semantic and workflow layers rather than autonomous controllers.
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CVE-2026-50522: Patch Critical SharePoint RCE Now
Microsoft patched CVE-2026-50522 (CVSS 9.8), an unauthenticated deserialization RCE in on-premises SharePoint servers, in its July 2026 updates; no exploitation confirmed at disclosure.
CVE-2026-50522 is a critical (CVSS 9.8) deserialization of untrusted data flaw (CWE-502) allowing unauthenticated remote code execution on on-premises Microsoft SharePoint servers. It affects SharePoint Enterprise Server 2016, SharePoint Server 2019, and SharePoint Server Subscription Edition, with fixes shipped in Microsoft's July 14, 2026 security updates; SharePoint Online is not listed as affected. No public evidence of active exploitation of this specific CVE existed at disclosure, though CISA's SSVC judged the attack automatable with total technical impact.
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U.S. CISA adds Apple macOS, Microsoft SharePoint, Broadcom VMware vCenter, and Microsoft IKE flaws to its Known Exploited Vulnerabilities catalog
CISA adds actively exploited flaws in Microsoft IKE, SharePoint, VMware vCenter, and macOS Screen Sharing to KEV catalog, due August 21.
CISA added four vulnerabilities to its Known Exploited Vulnerabilities catalog: CVE-2026-33824 (Windows IKE remote code execution, CVSS 9.8), CVE-2026-55040 (SharePoint JWT authentication bypass, CVSS 9.1), CVE-2026-59310 (VMware vCenter Syslog path traversal, CVSS 9.8), and CVE-2026-65400 (macOS Screen Sharing improper authentication). The SharePoint flaw combines four weaknesses including alg:none JWT forging to impersonate any user, with Defused researchers observing attackers using Rapid7's PoC against honeypots. The Dutch NCSC confirmed active exploitation of the macOS Screen Sharing flaw on August 15, 2026. Federal agencies must patch by August 21, 2026.
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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.
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Training a 3.8B LLM to 0.384 CORE for $998 – Hugo Vergnes
Independent developer Hugo Vergnes trained a 3.8B-parameter Llama-style model to 0.384 CORE on 65B tokens for $998 in 43 hours on rented B200s.
Hugo Vergnes trained little-lm, a 3.848B-parameter decoder-only LLM, on 65.3B tokens in 43 hours for $998 using rented NVIDIA B200s, scoring 0.384 on the CORE benchmark and beating nanochat d32 (0.310) at similar cost. The Llama-style architecture uses RMSNorm, RoPE, GQA with 24 query and 8 KV heads, relu-squared MLPs, QK-norm, and ResFormer-style value embeddings that account for 19% of parameters. Key wins included the Muon optimizer for matrix parameters, a trapezoidal learning-rate schedule with linear cooldown, FP8 training plus vocabulary padding for roughly 33% throughput gains, and the ClimMix dataset over FineWeb-Edu. The project, inspired by Karpathy's nanochat, was built as a config-driven YAML framework for small LLM training.
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