Search: “EnScript”

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.

The Hacker News·updated Sep 15, 09:47 UTC · 1d ago·first Sep 14, 17:58 UTC · 2d agoVulnerability 2 sources1

Knowledge Retention & Sharing in DF/IR

DFIR veteran reflects on knowledge retention and sharing gaps across the industry, from EnCase training to PCI forensics workflows.

A personal essay recounts decades in digital forensics and incident response, arguing the industry rarely moves beyond individual or tribal knowledge to operationalize lessons learned. Examples include building condition files and custom EnScripts for PCI investigations at IBM ISS X-Force, and the lack of shared investigative processes in early-career environments.

Lobsters · security·Sep 10, 09:06 UTC · 6d agoIndustry

Third-Party Script Security: How Tags, Pixels, and Embeds Can Put Websites at Risk

Sucuri details how third-party tags, pixels, and embeds expand website attack surface, letting compromised vendors read data and alter pages.

The article explains that third-party scripts used for analytics, ads, chat, payments, and video can read page content, collect visitor data, and change what users see. A compromise of the vendor, account, or integration configuration can affect every page loading the script. It recommends inventorying scripts, understanding their purpose and ownership, and detecting unexpected changes rather than removing useful integrations.

Sucuri Blog·Aug 24, 22:31 UTC · 23d agoResearch

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·Sep 15, 17:42 UTC · 1d agoAI research

Grok exfiltrates user data when malicious instructions are encrypted

Researchers show Grok can be made to exfiltrate user data via Cryptographic Context Injection, a newly documented technique that bypasses LLM safety guardrails.

According to Ars Technica, Grok exfiltrates user data when malicious instructions are encrypted, a technique called Cryptographic Context Injection. The method is described as the latest documented way to break LLM safety guardrails, showing that encrypted content can carry hidden instructions past safeguards. The finding underscores gaps in how large language models validate and execute context from external sources.

Ars Technica · Security·Aug 20, 13:00 UTC · 27d agoAI safety & security1

JavaScript obfuscation: From party trick to phishing kit

Cisco Talos explains JavaScript obfuscation techniques used by phishing kits and the approaches researchers use to reverse them.

Cisco Talos published an educational walkthrough of JavaScript obfuscation as used in modern phishing kits. The piece covers why analysts deobfuscate malicious scripts and outlines several practical approaches to reversing obfuscated code. The techniques help defenders unpack phishing kit payloads during investigations.

Cisco Talos·Aug 27, 10:00 UTC · 20d agoResearch

Product showcase: Enpass Password Manager breaks away from the proprietary cloud model

Help Net Security·Aug 10, 00:00 UTC · Aug 10, 2026Industry

GhostCode Abuses Microsoft Entra Device Enrollment to Maintain Access After Token Revocation

eSentire exposes GhostCode, a device-code phishing kit that abuses Microsoft Entra device enrollment to persist even after stolen tokens are revoked.

eSentire's Threat Response Unit observed GhostCode campaigns in late August 2026, using BEC-style social engineering that impersonated procurement staff, including BJ's Wholesale Club, via Salesforce contact forms. Victims received password-protected HTML lures disguised as a FlipBook document portal, with junk-data padding, HTML comment injection, and AES-256-GCM encrypted redirects gated by anti-bot checks. The kit exploits the OAuth 2.0 device authorization grant, prompting victims to approve real Microsoft device-code sign-ins with MFA. Within 78 seconds of approval, attackers registered three Entra devices and obtained a Primary Refresh Token, so rogue device registrations persist even after session token revocation.

GBHackers·Sep 16, 13:41 UTC · 12h agoPhishing & fraud in the wild2

Microsoft patches critical Entra ID vulnerability (CVE-2026-69836)

Microsoft patched critical Entra ID RCE CVE-2026-69836 (CVSS 10.0), fully mitigated server-side with no customer action; no in-the-wild exploitation confirmed.

Microsoft patched CVE-2026-69836, a critical (maximum CVSS 10.0) unauthenticated remote code execution flaw in Entra ID caused by deserialization of untrusted data over a network. Entra ID, formerly Azure Active Directory, is Microsoft's cloud identity service verifying logins and controlling access to Microsoft 365, Azure, and connected third-party apps. The flaw was discovered by Microsoft Principal Security Engineer Robert Fitzpatrick and fully mitigated server-side, requiring no customer action. Microsoft initially reported the bug as exploited, but later changed the status to 'no' and confirmed the vulnerability was not exploited in the wild.

Help Net Security·Aug 24, 06:16 UTC · 23d agoVulnerabilityCVE-2026-69836

Technical Manual for a Toolkit for Measuring Contextual Individuation in Transformer Language Models

An open methodology toolkit measures whether transformer language models contextualize fixed word forms across domains using bridge forms and layer-wise silhouette analysis.

The manual documents an open toolkit built around 'bridge forms' - identical written words recurring across two or more subject domains with a different sense in each - to test whether transformer language models individuate word occurrences by context beyond the embedding layer. It covers declarative specification of bridge forms, Wikipedia corpus acquisition, occurrence localization, layer-wise representation extraction, domain-pairwise silhouette measurement, and visualization, justifying each choice against failure modes such as sense contamination and subword-tokenization misalignment. It is a methodological and implementation reference and reports no empirical results.

arXiv cs.AI / cs.LG / cs.CL·Sep 4, 16:38 UTC · 12d agoAI research

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·Sep 8, 19:22 UTC · 8d agoTools

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·Sep 4, 17:32 UTC · 12d agoAI research1

[20260809] - Core - Improper ACL checks when injection schema.org contact data

Joomla fixed CVE-2026-73372, an improper ACL check that leaks inaccessible contact items' data into schema.org snippets, affecting CMS 5.1.0-5.4.7 and 6.0.0-6.1.2.

Joomla security advisory 20260809 describes CVE-2026-73372, an incorrect access control issue when injecting schema.org contact data. Improper access checks inject contact information for inaccessible contact items into schema.org snippets, exposing restricted data. 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 Stefan Wendhausen on 2026-07-31.

Joomla Security Centre·Aug 17, 14:00 UTC · Aug 17, 2026AdvisoryCVE-2026-73372

[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.

Joomla Security Centre·Aug 17, 14:00 UTC · Aug 17, 2026AdvisoryCVE-2026-73336

Right Tool, Right Job: Native-Language Evaluation, Tokenizer Sensitivity, and Methodological Findings from a French-Only BabyLM

French BabyLM entry METRON-FR (125M GPT-2, 92.47M words) shows tokenizer artifacts dominate child-scale zero-shot evaluation; proposes standard diagnostics.

METRON-FR is a 125M-parameter GPT-2 pretrained on 92.47M French words, submitted to the BabyLM 2026 Strict track, scoring 85.97% on the native Quebec-French QFrBLiMP benchmark and 62.80% on the BabyLM-weighted leaderboard. A cross-lingual GLUE protocol combining French task-data translation with rank-16 LoRA shows relational tasks gain while world-knowledge tasks regress. Bilingual Lexicon Induction reaches p@1 of 68.84%, 18x above chance, and ablations show single-token zero-shot scoring is dominated by tokenizer and template artifacts at child scale.

arXiv cs.AI / cs.LG / cs.CL·Sep 15, 16:43 UTC · 1d agoAI research

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·Sep 9, 16:18 UTC · 7d agoAI research1

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.

CISA Advisories·Sep 15, 12:00 UTC · 1d agoAdvisoryCVE-2026-58113

[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·Aug 31, 00:00 UTC · 17d agoExploit / PoC1

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.

arXiv cs.AI / cs.LG / cs.CL·Sep 7, 17:41 UTC · 9d agoAI research

Describing attacks with crime script analysis

Cisco Talos researcher Martin explains how crime script analysis describes attacks in everyday language, aiding communication and identifying disruption points.

Cisco Talos published a methodology piece on applying crime script analysis to cybersecurity incidents. The approach describes each stage of an attack in everyday language, making technical incidents accessible to non-technical audiences. It also helps defenders identify points in the attack chain where the crime can be disrupted.

Cisco Talos·Aug 19, 10:00 UTC · 28d agoResearch

Cisco Identity Services Engine Cross-Site Scripting Vulnerability

Cisco patched a reflected XSS in the ISE management interface allowing unauthenticated attackers to execute script via crafted links.

A reflected cross-site scripting vulnerability in the web-based management interface of Cisco Identity Services Engine lets an unauthenticated remote attacker execute arbitrary script in the context of the interface. Exploitation requires persuading a user to click a crafted link due to improper input validation. Cisco has released software updates.

Cisco Security Advisories·Sep 16, 16:00 UTC · 10h agoAdvisory 15 sources

AuK Technical Report: An Open-Source Foundational Model for Speech Generation and Editing

Open-source speech foundation model AuK unifies generation and editing, trained on 1.95 million hours, with distilled AuK-Flash achieving 4.5x speedup.

AuK is an open-source foundational model that unifies speech generation and editing through natural-language instructions and audio context, trained on approximately 3.03 billion instruction-audio instances and 1.95 million hours of supervision across five task families including generation, content editing, and acoustic editing. It combines a multimodal LLM for semantic conditioning, a VAE jointly trained on speech, general audio, and music, and a hybrid rectified-flow Transformer using dual-stream MMDiT blocks followed by unified single-stream DiT blocks. Post-training applies human-feedback preference optimization for editing and reward-based reinforcement learning for generation, and the distilled AuK-Flash performs 4-step inference without classifier-free guidance at a 4.5x wall-clock speedup. Source code and model weights are released.

Hugging Face daily papers·Sep 7, 20:00 UTC · 9d agoModel release2

[0day-rubbish] core-admin 1.0.164 (build 16468) Systemic shell command injection via ineffective quote escaping (8.8)

0day Rubbish discloses a CVSS 8.8 shell command injection in core-admin 1.0.164 via ineffective quote escaping, enabling authenticated remote code execution.

0day Rubbish Research Team publicly disclosed a systemic shell command injection (CWE-78) in core-admin 1.0.164 (build 16468). The flaw stems from ineffective quote escaping and scores 8.8 (AV:N/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H). The disclosure does not mention a CVE identifier or observed exploitation in the wild.

Full Disclosure·Sep 8, 17:31 UTC · 8d agoVulnerability1

ENEAS: Embedding-guided Neural Ensemble for Adaptive Segmentation

ENEAS adds text prompting and semantic verification to video segmentation to keep tracking targets through occlusion and reject lookalike distractors.

ENEAS is a unified text-promptable method for instance tracking and open-concept semantic discovery in video, designed to fix temporal hallucinations, spatial fragmentation, and semantic misclassification seen in SAM 3-class foundation models. It extends the geometrically robust SeC architecture with a text-prompting adapter and temporal memory, and uses a verification layer combining fast visual embedding matching with conditional VLM refinement for ambiguous candidates. It targets 3D reconstruction pipelines where a single misclassified distractor corrupts the asset. Code and models are open-sourced.

Hugging Face daily papers·Sep 2, 20:00 UTC · 14d agoAI research

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·Sep 15, 07:48 UTC · 1d agoVulnerability1· 1 read

CVE-2026-52307: Stored XSS in 1CMS v5.6

CVE-2026-52307: authenticated stored XSS in 1CMS (ClassCMS) v5.6 Column Management lets attackers inject scripts via the title field.

ClassCMS 1CMS v5.6 contains an authenticated stored cross-site scripting vulnerability, CVE-2026-52307, in the Column Management component. Attackers can execute arbitrary web scripts or HTML by injecting a crafted payload into the title field. No CVSS score, patch information, or exploitation evidence was provided in the disclosure.

Full Disclosure·Sep 8, 17:24 UTC · 8d agoVulnerabilityCVE-2026-52307

How to Spot and Stop Rogue Device Joins

Wiz details how adversaries use realistic device names in Entra ID registrations to evade detection and which behavioral signals still expose them.

Wiz researchers describe how adversaries generate realistic device names during Entra ID device registration instead of leaving recognizable fingerprints from public tooling, making rogue device joins blend into enterprise environments. The post explains how this trend changes Entra ID detection approaches. It also identifies behavioral signals that still expose these attacks. No specific CVE or victim was named.

Wiz Blog·Aug 18, 16:24 UTC · 29d agoResearch in the wild

LexFlip: A Dissociation Diagnostic for Legal Meaning Preservation Metrics

LexFlip releases 373 minimal perturbations of Quebec statutory French that reverse legal force while preserving tokens, exposing weaknesses in embedding-based meaning preservation metrics.

LexFlip provides 373 minimal perturbations of Quebec statutory French that reverse legal force while preserving 0.93 of tokens, creating dissociation items that break monotone token-overlap metric validation. The seven embedding and BERTScore metrics tested register only 0.022-0.039 of their identical-to-unrelated range on these edits, versus 0.670 for bidirectional NLI. Against FrJudge, with a measured human ceiling of r=0.597, a bare length feature outscores every semantic metric tested.

arXiv cs.AI / cs.LG / cs.CL·Sep 4, 15:49 UTC · 12d agoAI research

[webapps] Bludit CMS - Stored XSS

A stored cross-site scripting (XSS) vulnerability in Bludit CMS was disclosed through a public proof-of-concept published on Exploit-DB.

Exploit-DB published a webapps entry for a stored XSS flaw in Bludit CMS, an open-source flat-file content management system. Stored XSS allows an attacker to persist malicious scripts that execute in other users' browsers, potentially enabling session theft or unauthorized actions. The listing did not include a CVE identifier or affected version range.

Exploit-DB·Sep 1, 00:00 UTC · 16d agoExploit / PoC1

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·Sep 8, 17:53 UTC · 8d agoAI research1