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Telegram Desktop Flaw Lets Attackers Steal Chat Messages Through Poisoned HTML Exports

Telegram Desktop XSS in bot inline keyboard buttons let attackers steal chat content from exported HTML archives; patched in 7.0.1.

ExPatch researchers Denis and Aleksander Rostilov found a stored cross-site scripting flaw in Telegram Desktop's HTML export feature, present since version 4.15.1 (March 2024). JavaScript hidden in bot inline keyboard button text executes when a user opens an exported chat HTML file with JavaScript enabled, exposing messages, metadata, and enabling DOM manipulation such as fake verification screens. Fixes shipped in Desktop Beta 6.9.4 (July 3, 2026) and Stable 7.0.1 (July 14, 2026), but previously exported HTML files remain unsafe.

Cyber Security News · 1d agoVulnerability 2 sources

Telegram Desktop Flaw Could Turn Old Chat Exports Into Data Theft Traps

ExPatch disclosed stored XSS in Telegram Desktop HTML export letting bot messages steal chat data when exports open in browsers.

ExPatch researchers Denis and Aleksander Rostilov found a stored XSS flaw (CVSS 8.2) where bot inline keyboard button text was written unescaped into HTML chat exports, executing attacker JavaScript in browsers. The payload can persist in chat history for months, exfiltrate messages, metadata, and local file paths, and rewrite the page, spreading via forwarded messages without bot membership. Telegram fixed it by applying SerializeString(), first stable fixed release 7.0.1 shipped July 14, 2026, but HTML exports created with vulnerable versions remain dangerous.

Security Affairs · 1d agoVulnerability1· 1 read

Telegram Desktop XSS Vulnerability Lets Attackers Steal Entire Chat Histories

Stored XSS in Telegram Desktop HTML chat exports (CVSS 8.2) could let attacker-controlled inline keyboard buttons steal full chat histories.

ExPatch researchers Denis and Aleksander Rostilov found a stored XSS in Telegram Desktop's HTML chat export pipeline affecting builds before Beta 6.9.4 and Stable 7.0.1. Unsanitized inline keyboard button text becomes executable JavaScript when a user exports a chat and opens the HTML file in a browser, exposing messages, metadata, and local file paths, and enabling phishing overlays. Telegram patched the issue in commit 8457d13a during July 2026; no CVE had been assigned at disclosure time.

GBHackers · 1d agoVulnerability

Retrofitting Code Using LLMs to Support Exceptional Behavior

EXCODER combines static/dynamic analysis with LLMs to retrofit exception-handling code, achieving 85.92% pass@1 with Qwen 2.5 Coder 32B on Java benchmarks.

The paper introduces the task of retrofitting existing code with Exception Related Code (throw statements, guarding conditions, try/catch blocks) so that given Exceptional Behavior Tests pass. EXCODER performs context engineering by integrating static and dynamic program analysis output with LLMs; it was evaluated on a benchmark built from 304 methods across 75 GitHub Java projects. Combined with Qwen 2.5 Coder 32B, EXCODER achieves pass@1, 5, and 10 rates of 85.92%, 86.18%, and 86.51%, roughly 13 percentage points over baseline, and manual inspection reveals remaining limitations.

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

ExecCritic: Learn to Test, Test to Improve for Coding Agents

ExecCritic separates test generation from patching for coding agents, lifting SWE-bench Verified resolution to 72.6%.

ExecCritic pairs a test-verify-revise scaffold with role-specific reinforcement learning: a Test agent writes repository-native tests and a Repair agent fixes code from execution feedback, both using Qwen-3.5-35B-A3B backbones. Post-trained Qwen agents compose to 72.6% on SWE-bench Verified, an 11.4-point gain over the 61.2% no-test baseline, without stronger-model or oracle feedback at evaluation time. The work shows test quality is the key variable: base-agent tests lowered resolution to 57.3% while GPT-5.6-sol tests raised it to 65.3%.

arXiv cs.AI / cs.LG / cs.CL · 8d agoAI research1

Multi-Vector (Late Interaction) Embedding Models with Sentence Transformers

Hugging Face details building and using multi-vector late-interaction embedding models with Sentence Transformers for retrieval workloads.

Hugging Face published a guide on multi-vector, late-interaction embedding models (ColBERT-style) supported through Sentence Transformers. The post covers how practitioners can build and use these models for retrieval and RAG pipelines. It is a developer tooling and technique write-up, not a security advisory.

Hugging Face Blog · 29d agoAI tools & infra1

Update modules/auxiliary/scanner/http/elasticsearch_tika_xfa_xxe.rb

Rapid7 updated a Metasploit auxiliary scanner module that detects XML external entity injection in Elasticsearch via Apache Tika.

A commit in the Metasploit Framework updated modules/auxiliary/scanner/http/elasticsearch_tika_xfa_xxe.rb, an auxiliary scanner module. The module targets XML external entity (XXE) injection in Elasticsearch through Apache Tika, and was co-authored by jheysel-r7. The terse commit message contains no additional details, CVE references, or exploitation notes.

Metasploit Framework commits · 8d agoTools

Rosetta at AlexandriaX-2026: LoRA-Adapted NileChat for Context-Aware Dialectal Arabic Dialogue Translation

Rosetta ranks 4th and 5th in AlexandriaX-2026 dialectal Arabic dialogue translation using a LoRA adapter on NileChat-3B, finding limited pretraining benefit.

The Rosetta system for the AlexandriaX-2026 shared task fine-tunes a LoRA adapter on NileChat-3B for context-aware English-to-dialectal Arabic dialogue translation. The adapter was additionally pretrained on MADAR and PADIC dialect corpora for the unconstrained track. It achieved spBLEU 26.10 (4th, constrained) and 25.09 (5th, unconstrained). External dialect pretraining improved only two of thirteen dialects while slightly degrading overall performance, indicating negative transfer.

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

ENCP: Episode-Normalized Conformal Prediction for Vision-and-Language Navigation

ENCP calibrates conformal prediction per navigation episode, giving step-level coverage guarantees for vision-language navigation agents despite within-episode dependence.

Episode-Normalized Conformal Prediction (ENCP) rescales a nonconformity score by a VLN policy's residual confidence and calibrates one maximum score per episode, preserving step-level coverage of at least 1−α despite dependence among steps within an episode. Across four VLN policies and three nonconformity scores on R2R and REVERIE, ENCP meets all reported empirical step-coverage targets in seen-to-unseen evaluation. The model-agnostic uncertainty estimates can signal when an agent should defer to a stronger predictor or human assistance.

arXiv cs.AI / cs.LG / cs.CL · 1d agoAI research

PACE: Perceived-Latency-Aware Cascading Service Routing and Filler Control for QoE-Efficient Retrieval-Augmented Dialogue Serving

PACE cuts perceived latency in retrieval-augmented dialogue serving via cascading routing and filler control, reaching 0.41s P95 under load.

PACE is a serving framework for retrieval-augmented dialogue that optimizes Perceived Time-to-First-Response (PTFR) under quality and cost constraints. It combines a load-adaptive cascading router, a joint path-filler controller, and volatility-aware cache admission, deployed on a humanoid-robot sales service. On 75k CarQA requests, the cascade halved pure-LLM P95 PTFR (0.29s vs 0.53s) and the adaptive controller reached 0.41s P95, 2.4x better than RAG at high load; filler calls dropped 94% and stale answers fell from 86% to 0%.

StyleSmuggler: Unpatched Magento and Adobe Commerce Zero-Day Exploited

Attackers are actively exploiting an unpatched zero-day dubbed StyleSmuggler in Magento Open Source and Adobe Commerce for unauthenticated remote code execution.

A zero-day vulnerability tracked as StyleSmuggler affects Magento Open Source and Adobe Commerce and permits unauthenticated remote code execution. The flaw is unpatched and exploitation is ongoing in the wild. E-commerce stores running these platforms are at direct risk of compromise until a fix is released.

SOCRadar · 9d agoExploit / PoC in the wild

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.

arXiv cs.AI / cs.LG / cs.CL · 6d agoAI research1

Flextype v1.0.0-alpha.3 Stored Fetch Shortcode Allows Server-Side Request Forgery

Flextype CMS v1.0.0-alpha.3's stored fetch shortcode enables server-side request forgery via attacker-controlled entry fields passed to fetch().

Flextype CMS v1.0.0-alpha.3 automatically processes attacker-controlled entry fields through its shortcode parser when global shortcode processing is enabled. The built-in fetch shortcode passes attacker-controlled resources to the server-side fetch() helper without sufficient destination restrictions. This enables stored server-side request forgery initiated from saved entry content. The issue was disclosed on the Full Disclosure mailing list on September 3, 2026.

Full Disclosure · 12d agoVulnerability 8 sources

[webapps] Bludit CMS 3.20.0 - Reflected Cross-Site Scripting

A reflected cross-site scripting flaw in Bludit CMS 3.20.0 is documented with a public proof-of-concept exploit on Exploit-DB.

Exploit-DB published exploit ID 52678 targeting Bludit CMS 3.20.0, a web application affected by reflected cross-site scripting. The listing contains a proof-of-concept but includes no CVE identifier or evidence of active exploitation.

Exploit-DB · 14d agoExploit / PoC1

The Shared Clipboard Inside the Sandbox: Cross-Account Data Leakage in ChatGPT

Check Point discovers cross-account data leakage in ChatGPT: isolated code-execution containers communicate via shared JFrog Artifactory, enabling covert Gmail exfiltration.

Check Point Research found a covert bidirectional channel between ChatGPT code-execution containers belonging to different accounts, which were supposed to be isolated from each other and the public internet. Both could reach the same internal JFrog Artifactory instance used for package delivery, whose exposed Item Management API allowed a 'shared clipboard' between containers. In a proof of concept, a hidden instruction in a shared conversation made ChatGPT retrieve email data from the victim's connected Gmail account and send it to the attacker's account while the victim received a normal answer. The same channel could exfiltrate conversation history and session files; OpenAI recently described a similar isolation weakness in its postmortem of the Hugging Face incident.

Check Point Research · 8d agoAI safety & security1

NeoMME: an efficient Multimodal-native and Multilingual Encoder

H Company released NeoMME, an efficient multimodal-native and multilingual encoder, via a post on the Hugging Face blog.

H Company published a Hugging Face blog post introducing NeoMME, described as an efficient multimodal-native and multilingual encoder. The article body was unavailable in the feed, so architecture, benchmarks, and licensing details could not be verified. The post suggests a new encoder release relevant to multilingual multimodal model development.

Hugging Face Blog · 13d agoModel release

Meet Redis LangCache: A Managed Semantic Cache That Cuts LLM API Costs by Up to 90% and Returns Cache Hits Up to 15x Faster

Redis launches LangCache, a managed semantic cache matching LLM prompts by meaning, cutting API costs up to 90% and returning hits up to 15x faster.

Redis LangCache is a fully managed semantic caching service in public preview on Redis Cloud, accessed via a REST API with Python and JavaScript SDKs. It embeds incoming prompts, vector-searches stored entries, and returns a cached response when similarity clears a configured threshold, skipping the LLM call entirely. Redis claims up to 90% cost savings and up to 15x faster cache hits; a demo run showed 0.37 seconds versus 2.232 seconds direct inference (about 6x) with zero LLM tokens. Customer Mangoes.ai reports a 70% hit rate, 70% lower LLM spend, and 4x faster responses on a patient-care voice app.

MarkTechPost · 6d agoAI tools & infra1

Diffs vs. Whole Files: An Empirical Comparison of Iterative Edit-Based and Direct Generation for Flutter/Dart Code Models

Empirical study finds direct whole-file generation beats iterative diff-based editing for Flutter/Dart code models on about 1,790 held-out tasks.

Researchers trained Rainbow-Pony-100M from scratch and fine-tuned Qwen2.5-Coder-0.5B in both direct-generation and diff-based regimes, then evaluated four resulting models on roughly 1,790 Flutter/Dart tasks. Direct generation outperformed diff-based generation on compilation pass rate, bits-per-byte, character-level similarity, and blinded LLM-judge ratings. Diff-based editing is competitive only on short, localized edits in refactoring and error-handling tasks, a property the authors call task locality.

Hugging Face daily papers · 12d agoAI research1

Expert-Space Exploration in MoE Reinforcement Learning

ESRL explores MoE expert-routing space during RL, lifting Qwen3-30B-A3B Pass@1 by 3.2 points over GRPO at no extra cost.

ESRL (Expert-Space Exploration Reinforcement Learning) is an architecture-aware framework that treats expert routing in Mixture-of-Experts models as an additional source of rollout diversity. It preserves high-confidence experts as anchors, restricts stochastic routing to a plausible candidate pool, adapts perturbation strength to router entropy, and replays recorded expert paths during policy optimization. ESRL achieves the best performance across top-K, top-1, and shared-expert routing backbones on mathematics, science, and code tasks; on Qwen3-30B-A3B it improves average Pass@1 and Pass@8 over GRPO by 3.2 and 4.5 percentage points respectively, without additional sampling or compute.

PEEP Turns Chrome and Edge Into Post-Compromise Backdoors for Host Command Execution

SOCRadar disclosed PEEP, a post-exploitation Chromium extension toolkit that turns Chrome and Edge into host-level backdoors via native messaging and C2 polling.

SOCRadar researchers detailed PEEP, a Chromium-based post-exploitation toolkit masquerading as a 'Smart Bookmarks' extension injected directly into Chrome and Edge profiles by forging Secure Preferences integrity values, bypassing Web Store checks. A native-messaging host binary (nm_host.exe) extends the browser agent to host-level command execution, file management, credential theft, and session hijacking, while the extension polls C2 endpoints at 206.237.30.232 or xfjcc.fun every 30 seconds over plaintext HTTP and exfiltrates browsing history, cookies, and tab metadata. PEEP is derived from the open-source RedExt red teaming framework, adds PowerShell persistence scripts, and includes a Linux-targeting Python script, suggesting cross-platform intent. The activity is unattributed but contains Chinese-language artifacts; a C2 /health endpoint showed 34 agent entries and 10 active sessions.

The Hacker News · 9d agoMalware in the wild1

CrossLink: Breaking Location Privacy by Linking Device Identifiers Across Protocols

Researchers present CrossLink, a passive tracing algorithm linking temporary device identifiers across LTE, WiFi, and BLE, reconstructing full traces for 83% of simulated users.

Smartphones emit temporary identifiers simultaneously over LTE, WiFi, and BLE, and per-protocol randomization defenses implicitly assume their protections compose across protocols. CrossLink is an uncertainty-aware tracing algorithm that stitches device identifiers across time, space, and protocols even when the adversary is fully passive and rotations are unsynchronized. In large-scale mobility simulation it reconstructs full traces for 83% of users versus 22% for the best single-protocol baseline. It remains effective under partial sniffer coverage, including strategically placed sniffers near LTE handover regions, mobile sniffers, and limited high-coverage subregions.

arXiv cs.CR · 7d agoResearch

Unpatched Magento and Adobe Commerce Zero-Day Exploited to Backdoor Online Stores

Sansec reports active exploitation of an unpatched zero-day, dubbed StyleSmuggler, in Magento and Adobe Commerce, letting attackers backdoor online store servers without authentication.

Sansec disclosed on September 5 that attackers are exploiting an unpatched vulnerability, named StyleSmuggler, in Magento Open Source and Adobe Commerce to achieve unauthenticated remote code execution, with attacks observed starting September 4. All current versions including 2.4.9 are affected, and Adobe has published no advisory, CVE, patch, or workaround, with the next scheduled security release on September 8. Hosting firm Disrex Group independently confirmed two compromised stores (running 2.4.8 and 2.4.7-p2), both breached within the roughly eight-hour window before Sansec's blocking rules went live. The implant is a ~1.9 MB statically linked Rust binary disguised as a Linux kworker process, re-adding a cron entry every five minutes and in one case reading Magento sessions directly from Redis with no outbound traffic.

The Hacker News · 11d agoExploit / PoC in the wild

[webapps] CubeCart 6.7.4 - Stored XSS

A proof-of-concept stored cross-site scripting exploit targeting CubeCart 6.7.4 was published on Exploit-DB.

Exploit-DB lists a proof-of-concept exploit for a stored cross-site scripting (XSS) vulnerability in CubeCart 6.7.4, a PHP-based e-commerce web application. The listing demonstrates injection of attacker-controlled script that persists in the application, but no exploitation in the wild or CVE assignment is reported in the provided text.

Exploit-DB · 16d agoExploit / PoC1

What Good Identity Hardening Looks Like

Huntress guidance defines mature identity hardening beyond baseline MFA, covering exception cleanup and detecting identity configuration drift before attackers do.

Huntress argues MFA is only a starting point and outlines what mature identity hardening actually looks like in practice. The guidance covers closing MFA exceptions and coverage gaps that create unauthenticated attack paths. It also stresses catching identity configuration drift before attackers can exploit it.

Huntress · 22d agoResearch

XHToken/Spark-X2.5-4B-GGUF — new model trending #30 on Hugging Face

XHToken released GGUF weights of Spark-X2.5-4B, a compact model with 1M-token context and 200+ language support, under Apache 2.0.

The Hugging Face repository provides BF16 GGUF conversions of Spark-X2.5-4B, a compact general-purpose language model for conversation, writing, translation, reasoning, coding, tool use, and agentic workflows. The model uses a hybrid attention architecture, supports a native context length up to 1M tokens, and covers more than 200 languages. Local inference is supported through Ollama and LM Studio via an XHToken llama.cpp fork, with a --think=false flag to disable thinking mode for faster responses. Released under Apache License 2.0; it was trending #30 on Hugging Face at publication.

Hugging Face trending models · 19d agoModel release

ECHO: A Matched-Contrast Benchmark for Context-Sensitive Turn-Taking in Full-Duplex Dialogue

ECHO benchmark pairs identical-overlap Chinese dialogue examples with contrasting contexts, revealing most full-duplex systems bias toward yielding the floor.

ECHO is a paired diagnostic benchmark for Chinese full-duplex turn-taking that matches examples with identical overlap transcripts but contrasting preceding multi-turn contexts, one requiring Yield and the other Keep. It also includes off-talk examples for diagnosing unnecessary yielding and introduces pair accuracy, which grants no credit to constant-action policies. Experiments across multiple full-duplex systems show most exhibit a pronounced Yield bias, performing substantially better on interruptions than backchannels. The benchmark and metadata will be publicly released.

arXiv cs.AI / cs.LG / cs.CL · 1d agoAI research

Hackers Are Probing PaperCut Servers, and 47% Still Have No Patch

PaperCut pre-auth RCE CVE-2026-81578 actively exploited; 47% of tracked installs unpatched and exposed to remote code execution.

Huntress confirmed active exploitation of a pre-authentication RCE flaw in PaperCut (CVE-2026-81578), chainable with CVE-2026-82078 to achieve SYSTEM-level code execution via PaperCut's Application Server. Observed attacks focused on short reconnaissance (whoami, ver, tasklist) with no persistence, but a malicious Java class dropping into the installation directory leaves the jdbc:derby:memory:pwn breadcrumb. Roughly 47% of ~2,500 tracked installations run version 23 or earlier with no patch yet available.

Security Affairs · 10d agoExploit / PoC in the wildCVE-2026-81578CVE-2026-82078

Next.js 16.4.0-canary.13 Image Optimizer DNS Rebinding TOCTOU SSRF Still Exists

Next.js 16.4.0-canary.13 Image Optimizer retains a DNS rebinding TOCTOU SSRF in fetchExternalImage() allowing requests to private network resources.

Next.js 16.4.0-canary.13 contains a DNS rebinding time-of-check-to-time-of-use Server-Side Request Forgery vulnerability in the Image Optimizer's fetchExternalImage() function. The code resolves the supplied hostname and checks the resulting addresses with isPrivateIp(), but a TOCTOU gap between resolution and the actual fetch allows an attacker-controlled DNS record to change and reach private network resources.

Full Disclosure · 12d agoVulnerability