Search: “BusyBox”

Honeypot-Omaha and batch.py [Guest Diary], (Wed, Sep 2nd)

A SANS ISC guest diary describes batch.py, a Python tool that consolidates honeypot logs and enriches IOCs with threat intelligence data.

Written by a SANS.edu BACS intern, the diary explains analysis of the DShield Honeypot-Omaha sensor, which uses Cowrie to emulate SSH and Telnet and log attacker activity. The author's batch.py script implements a four-phase pipeline with SHA-256-generated master and guest authentication to consolidate JSON and log files, correlate data via external APIs, and produce MITRE, CVE, geolocation, threat-score and fingerprint enrichment for investigated indicators.

SANS Internet Storm Center·Sep 3, 02:02 UTC · 13d agoTools1

ZDI-26-705: (0Day) BusyBox libarchive Symlink Directory Traversal Arbitrary File Creation Vulnerability

ZDI disclosed an unpatched symlink directory traversal flaw (CVE-2026-92205, CVSS 6.1) in BusyBox libarchive enabling arbitrary file creation.

ZDI-26-705 details an arbitrary file creation vulnerability in BusyBox's libarchive component caused by symlink directory traversal. Remote exploitation requires user interaction, such as visiting a malicious page or opening a malicious file. The flaw is rated CVSS 6.1, tracked as CVE-2026-92205, and published as a 0day advisory.

ZDI Published Advisories·05:00 UTC · 16h agoVulnerabilityCVE-2026-92205

AWS Introduces Pizza Bot: An Open Source Inbox for Background AI Agents

AWS open-sourced Pizza Bot, a self-hosted inbox app for background AI agents with approval gating and multi-provider model support.

AWS released Pizza Bot under Apache 2.0 after earlier versions served over 2,000 Amazon employees for meeting prep, email drafting, and research. The app provides macOS, Windows, and Linux desktop builds plus browser and terminal clients talking to a Hono API server, with LangGraph/DeepAgents checkpoints preserving thread state and approval pauses. It supports Amazon Bedrock, Anthropic, Google Gemini, OpenAI, OpenRouter, and Ollama, exposes external tools via MCP servers, and lets skill authors gate actions behind approve/edit/reject flows.

MarkTechPost·Sep 13, 08:10 UTC · 3d agoAI tools & infra

A Deep Dive Into Attempted Exploitation of CVE-2023

Mirai-like botnet scans exploit TP-Link EOL router flaw CVE-2023-33538 after CISA KEV addition, though observed exploit code is flawed.

Unit 42 observed large-scale automated scans attempting to exploit CVE-2023-33538 in end-of-life TP-Link TL-WR940N, TL-WR740N and TL-WR841N routers after CISA added the flaw to its KEV catalog in June 2025. HTTP GET requests inject commands via the ssid1 parameter at the /userRpm/WlanNetworkRpm endpoint to download and execute an arm7 ELF binary, a Mirai variant related to the Condi IoT botnet. Firmware emulation and reverse engineering showed the observed exploits are flawed and would fail, but the underlying vulnerability is real and successful exploitation requires authentication to the router's web interface. TP-Link confirmed the devices are end-of-life with no patches available and recommends replacing units and eliminating default credentials.

Palo Alto Unit 42·Aug 19, 12:03 UTC · 28d agoExploit / PoC in the wildCVE-2023-335381

I-have-ADHD: A skill to stop your coding agent from burying the answer

Developer releases I-have-ADHD, an open-source skill that stops coding agents from burying direct answers under verbose output.

A GitHub project titled I-have-ADHD packages a 'skill' intended to make AI coding agents answer directly instead of hiding the answer inside lengthy output. It gained traction on Hacker News with 45 points and 42 comments. It targets prompt/agent configuration rather than introducing a new model or infrastructure component.

Hacker News · AI·Sep 8, 14:13 UTC · 8d agoAI tools & infraHN 45↑ · 42 comments1

Your MikroTik Router May Already Be Compromised: Look for SSH User “-2”

MikroTik RouterOS SSH auth-bypass chain MikroTrick (CVE-2026-67276 plus CVE-2026-86060) is actively exploited; patch to 7.24.2/7.23.5/6.49.21.

Attackers are actively exploiting a chain dubbed MikroTrick that combines CVE-2026-67276 (CVSS 9.2), an SSH authentication bypass in RouterOS RSA public key verification, and CVE-2026-86060, an SSH session privilege escalation, giving full admin control of internet-exposed MikroTik devices without the private key. Exploitation began around September 2, 2026, a day before MikroTik's September 3 patches, with confirmed compromises including creation of an 'ops' account; attacks traced to IPs 82.192.72.4 (Leaseweb) and 103.102.31.18. Fixed versions include 7.25beta3, 7.24.2, 7.23.4, 7.23.5 and 6.49.21. Defenders should check logs for failed logins with username '-2' and inspect /system history for ssh:-2@<IP> entries attached to configuration changes.

Security Affairs·Sep 6, 13:46 UTC · 10d agoExploit / PoC in the wildCVE-2026-67276CVE-2026-860602

Home & Small Office Wireless Routers Exploited to Attack Gaming Servers

Unit 42 details an updated Gafgyt botnet variant exploiting Zyxel, Huawei, and Realtek router vulnerabilities to recruit devices for DoS attacks on gaming servers.

Unit 42 researchers identified an updated Gafgyt variant derived from the JenX botnet that combines three remote code execution exploits: CVE-2017-18368 (Zyxel P660HN-T1A), CVE-2017-17215 (Huawei HG532), and CVE-2014-8361 (Realtek RTL81XX chipset). Shodan scans show more than 32,000 wireless routers worldwide potentially vulnerable to these exploits. The exploits act as droppers, pulling architecture-specific binaries from a malicious server (185.172.110.224), and the botnet performs denial-of-service attacks against gaming servers, most notably Valve Source engine servers.

Palo Alto Unit 42·Aug 18, 04:46 UTC · 29d agoMalware in the wildCVE-2017-18368CVE-2017-17215CVE-2014-83611

Open-source secrets scanning tool Sift hunts credentials in Microsoft 365, Slack, and Jira

Stratus Security open-sourced Sift, a CLI secrets scanner covering Active Directory, SharePoint, Teams, Slack, Jira, and Confluence, outperforming Snaffler in benchmarks.

Stratus Security released Sift, a free open-source command line tool that hunts passwords, API keys, and sensitive data across local disks, Windows shares, Active Directory, SharePoint, OneDrive, Teams, Slack, Jira, and Confluence. In the firm's benchmarks, Sift scanned 250,000 files in 10.61 seconds versus Snaffler's 25.48 and averaged 92 MiB memory versus Snaffler's 337 MiB. Optional false-positive filtering runs through a local language model via Ollama, and scans write checkpoints so interrupted runs resume. The tool found thousands of credentials in Jira ticket comments that prior pentesting had missed.

Help Net Security·Sep 2, 00:00 UTC · 14d agoTools

New KATARU IoT Malware Packs Linux Privilege Escalation Exploits and Mirai-Style DDoS Attacks

Nozomi Networks identified KATARU, a new Mirai-style IoT botnet delivered via Telnet brute force that uses Linux privilege-escalation exploits and encrypted C2 for DDoS floods.

Nozomi Networks identified KATARU in August after a Telnet password-guessing attack against a honeypot retrieved an ARM payload. The malware attempts exploits for CVE-2026-46300 (Fragnesia), CVE-2026-43284 (DirtyFrag), and CVE-2026-31431 (Copy Fail), plus a cgroup v1 release_agent escape, and persists via systemd services, cron tasks, rc scripts, OpenWrt hooks, and Android boot locations. Its C2 uses X25519 key exchange with ChaCha20-Poly1305 encryption and supports TCP, UDP, ICMP, HTTP, QUIC, and DNS floods, plus SSH brute forcing and command execution; embedded exploit shellcode in the ARM build targeted x86, suggesting untested copied code.

Cyber Security News·Sep 11, 14:17 UTC · 5d agoMalware in the wild 2 sourcesCVE-2026-46300CVE-2026-43284CVE-2026-31431

Quoting Calif Research

Calif Research demos WeWorm, an AI-built zero-click worm that spreads via WeChat calls on iOS and Android without user interaction.

Calif Research released a demo of WeWorm, described as the first zero-click worm to spread through WeChat calls across iOS and Android; victims need not answer the call and hear nothing even if they do. The team used AI to find the underlying bug and write a remote code execution exploit in about two days, then spent one more week building the worm. The researchers argue AI can now do most of the exploit-development work, with humans supplying judgment on targeting and safe testing.

Simon Willison·Sep 10, 00:56 UTC · 6d agoAI safety & security

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·Sep 8, 20:00 UTC · 8d agoAI research

TuxBot v3: Inside an IoT Botnet Framework With LLM

Unit 42 uncovers TuxBot v3, an LLM-assisted IoT botnet framework with 17-architecture builds, Telnet brute-forcing, and DDoS capabilities.

Palo Alto Unit 42 identified TuxBot v3 Evolution, a modular IoT botnet framework derived from AISURU, Wuhan-lineage botnets, and MHDDoS. The C-based bot brute-forces Telnet with 1,496 credential pairs, targets over 30 IoT device families, and communicates with a Go-based C2 over encrypted TCP with multiple fallback mechanisms including DGA, P2P, and DNS TXT. LLM-assisted development left hallucinated crypto implementations and broken exploit modules in the analyzed samples, though roughly 70% of core functionality works. Researchers warn polished production builds likely exist, raising the threat potential.

Palo Alto Unit 42·Aug 19, 12:03 UTC · 28d agoMalware1

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%.

arXiv cs.AI / cs.LG / cs.CL·Sep 9, 16:02 UTC · 7d agoAI tools & infra

Debian 13.7 ships the fixes behind 92 security advisories, updates 106 packages

Debian 13.7 'trixie' point release bundles 92 security advisories and 106 package updates, including kernel, glibc, u-boot and qemu fixes.

Debian shipped version 13.7 of 'trixie', folding in 92 previously published security advisories and corrections to 106 source packages, including six Linux kernel advisories (DSA-6381, DSA-6393, DSA-6405, DSA-6415, DSA-6466, DSA-6477). glibc fixes a buffer overflow (CVE-2026-5928) and buffer underflow (CVE-2026-5450), with 17 packages rebuilt against the updated library; qemu carries 25 CVEs including a secure boot bypass (CVE-2026-16288), imagemagick 24, wolfssl 15 and perl 13. Boot-chain fixes include a u-boot FIT image verification bypass (CVE-2026-46728), a BOOTP/DHCP buffer overread (CVE-2024-42040), and corrected intermediate certificate verification in sbsigntool. The installer was rebuilt with kernel ABI 6.12.107+deb13, and existing systems receive the fixes through normal package mirror updates.

Help Net Security·Sep 14, 07:40 UTC · 2d agoAdvisoryCVE-2026-5928CVE-2026-5450CVE-2026-34873+17 CVEs

CodeTD: Topology of Attention Detects Hallucinations in Code LLMs

CodeTD detects hallucinations in code LLMs before execution by analyzing topological patterns of attention maps, outperforming recent baselines.

CodeTD applies topological data analysis (TDA) to code LLM attention maps to quantify prompt-generation mismatch as a pre-execution correctness signal. Experiments cover HumanEval, MBPP, BigCodeBench, and MultiPL-E across 5 programming languages and 10 code LLMs up to 34B parameters. The method outperforms recent baselines and transfers between coding benchmarks, helping catch code that fails the task or embeds security vulnerabilities.

arXiv cs.AI / cs.LG / cs.CL·Sep 7, 17:26 UTC · 9d agoAI research1

Repeat-After-Me: Black-Box Adaptive Visual Prompt Injection

Researchers unveil Repeat-After-Me, a black-box visual prompt injection achieving over 80% success on Qwen3.6-27B and 47% on GPT-5.5.

Researchers present Repeat-After-Me, a black-box adaptive visual prompt injection that induces frontier VLMs to reveal PII or make malicious tool calls via injected images. It exceeds 80% attack success rate on Qwen3.6-27B and 47% on GPT-5.5 even when the benign user prompt is unrelated and does not authorize the injected task. In a real-world OpenClaw Discord deployment, a minimally injected image can overwrite TOOLS.md, enabling later remote code execution and secret exfiltration.

arXiv cs.CR·Sep 3, 22:44 UTC · 12d agoAI safety & security

JarvisGUI: Towards Cross-Device GUI Agents with Dynamic Task Composition

JarvisGUI benchmark tests GUI agents on cross-device workflows across Android, Windows, and Ubuntu, revealing major gaps in state transfer and long-horizon reasoning.

JarvisGUI is a dynamic benchmark that formulates GUI tasks as input-output transformations under a lightweight type system, automatically composing multi-step cross-device workflows across Android, Windows, and Ubuntu virtual environments. Evaluation shows state-of-the-art open-source GUI agents struggle with state-transfer awareness, cross-platform contextual reasoning, and long-horizon dependency management, exposing a capability gap invisible to existing single-device benchmarks.

arXiv cs.AI / cs.LG / cs.CL·Sep 9, 16:59 UTC · 7d agoAI research1

Bulk AbuseIPDB reporting using command-line tools

A blogger shows how to bulk-report distributed botnet IPs scraping a self-hosted Gitea instance to AbuseIPDB using bash, awk, and jq.

The author's self-hosted Gitea instance was scraped by distributed bots using random IPs worldwide and randomized, often nonexistent User-Agent strings, generating heavy request load for days. The write-up demonstrates filtering Traefik access logs (CLF and JSON) with grep, awk, and jq to extract offending IPs, tagging them with AbuseIPDB category 19 (Bad Web Bot), deduplicating them, and building a CSV for the Bulk Reporter tool. Reports can then be submitted through the AbuseIPDB bulk-report API, respecting the 5,000-report daily limit.

Lobsters · security·Sep 9, 20:26 UTC · 7d agoTools1

A Three-Layer Caching Architecture for Low-Latency LLM Web Search on Commodity CPU Hardware

OreoLook's three-layer Redis caching architecture cuts redundant LLM calls and embedding work for CPU-hosted web-search answer generation.

The paper describes a three-layer caching architecture for OreoLook (formerly lixSearch), an open-source LLM answer engine: a Redis session context window with Huffman-compressed disk overflow, a semantic query cache matching rephrasings via embedding cosine similarity, and a URL embedding cache deduplicating embedding computations. Deployed on a single 8-vCPU Intel Cascade Lake server with 30 Hypercorn workers across three containerized replicas, it achieved an 89.3% aggregate Redis keyspace hit rate, 0.1 ms read latency, and 1.38 MB memory overhead. An LRU eviction daemon migrates idle sessions to disk and rehydrates them for resumption hours or days later.

Hugging Face daily papers·Aug 11, 20:00 UTC · Aug 11, 2026AI tools & infra1

WeChat worm could pwn a friend before they even answered the call

Calif researchers demoed WeWorm, a zero-click WeChat VoIP memory-corruption worm enabling account takeover; Tencent patched it August 21.

Security firm Calif found a memory corruption bug in WeChat's VoIP stack that let a trusted contact take over a user's account simply by calling them, without the call being answered. The demo worm then called the victim's contacts to self-propagate across iOS and Android; declining the call prevented infection. Tencent pushed fixes on August 21, and Calif said chaining the bug with other Android and iOS flaws could yield full device control. Calif used AI to find the vulnerability and build its first RCE exploit in about two days.

The Register · Security·Sep 9, 12:45 UTC · 7d agoExploit / PoC

The VMs Powering Mobile Agents (Instinct, Claude Code)

A teardown reveals Claude Code runs in Firecracker microVMs with a Rust PID 1 and MITM'd egress, while Instinct rents E2B sandboxes with git-based memory.

The author inspects the virtual machines hosting cloud agents: Claude Code runs in a Firecracker microVM with a custom Rust init (process_api) as PID 1, a 324 MB Bun harness on a read-only disk, and 443-only MITM'd SSE egress to api.anthropic.com with host-rotated OAuth tokens and no inbound access. Instinct rents E2B sandbox-as-a-service Firecracker microVMs (Ubuntu 22.04, 2 vCPU, 1.9 GB RAM) where agent memory is a git repo of Markdown committed by the agent and pushed to S3 as a single bundle, using short-lived STS credentials. Both platforms rely on Firecracker, differing mainly in fleet operator and guest boot configuration.

Hacker News · AI·Sep 8, 04:36 UTC · 8d agoAI tools & infraHN 58↑ · 19 comments1

Show HN: LLM Attention Visualization

A developer released a browser-based tool that visualizes which past tokens influence each LLM output token using aggregated, value-weighted attention scores.

A Show HN project presents a React application built on Transformers.js that renders per-token attention influence by aggregating attention weights scaled by value-vector magnitudes across all attention heads and layers. To expose internal tensors, the author instrumented the ONNX computation graph, hosted a modified model on Hugging Face, and pre-generated prompts to avoid long model downloads in the browser. Demos with a 600-million-parameter model show how verbatim copying draws heavily on source tokens and how single outputs blend information from multiple phrases.

Hacker News · AI·Sep 8, 16:59 UTC · 8d agoAI tools & infraHN 41↑ · 9 comments

WeWorm – First 0-Click Worm Spreading Through WeChat Calls Across iOS and Android

Researchers demonstrated WeWorm, a zero-click worm exploiting a memory-corruption flaw in WeChat's VoIP stack to spread via calls across iOS and Android.

Security firm Calif published WeWorm, a proof-of-concept zero-click worm exploiting a memory-corruption bug in WeChat's VoIP stack to spread through voice calls on iOS and Android without the victim answering. The demo chained a Pixel 10a, an iPhone 17e, and a second Pixel 10a, compromising each device while the call was still ringing and giving full control of the WeChat account. The attacker must already be on the victim's friend list, but compromised contacts become the propagation layer across a platform with over 1.4 billion monthly users. Calif reported the bug to Tencent in July 2026, and Tencent has since mitigated it; full technical details are withheld for a later conference presentation.

Cyber Security News·Sep 8, 12:09 UTC · 8d agoExploit / PoC

Context Engineering Inside the Harness: 4 Mechanisms That Beat Context Overflow and Goal Loss on Long-Horizon Tasks

Survey of four harness mechanisms—context budgeting, compaction, todo-state, and memory—that keep long-horizon LLM agents on task across 200+ tool calls.

The article details how agent harnesses, not larger context windows, solve context overflow and goal loss on long-horizon tasks, citing Chroma's Context Rot report showing 18 LLMs (GPT-4.1, Claude 4, Gemini 2.5, Qwen3) degrade on long inputs. Concrete implementations include LangChain Deep Agents offloading tool responses over 20,000 tokens to the filesystem and truncating old tool calls at 85% window usage, and Claude Code capping auto memory at 25KB while re-reading the 5 most recently modified files after compaction. OpenAI's Responses API now offers server-side compaction via context_management with a standalone /responses/compact endpoint, which Codex uses for long-running coding tasks. Manus reports a roughly 100:1 input-to-output token ratio per ~50-tool-call task, motivating todo.md state recitation to prevent goal drift.

MarkTechPost·Sep 13, 05:56 UTC · 3d agoAI research1

“Zero-click” WeChat worm could hijack accounts and spread via a single call

Researchers discovered a critical memory corruption flaw in WeChat's VoIP stack enabling a zero-click worm, WeWorm, that hijacks accounts via calls; Tencent patched it.

Calif researchers weaponized a memory corruption issue in WeChat's VoIP stack into "WeWorm", a worm that spreads through WeChat calls without user interaction, hijacks each victim's account, and propagates via saved contacts across iOS and Android, potentially reaching millions of devices within hours. Exploitation takes seconds and grants full account control, and chaining with other reported Android/iOS bugs could lead to full device control. Tencent issued updated WeChat versions for iOS and Android and applied server-side mitigations; technical details remain withheld. WeChat has over a billion users, overwhelmingly in China.

Help Net Security·Sep 8, 13:40 UTC · 8d agoVulnerability

Aggah Campaign: Bit.ly, BlogSpot, and Pastebin Used for C2 in Large Scale Campaign

Aggah campaign abuses Bit.ly, BlogSpot, and Pastebin as multi-hop C2 to deliver RevengeRAT across the Middle East, US, Europe, and Asia.

Unit 42 details the Aggah campaign, which began with spearphishing emails in March 2019 spoofing a large financial institution and targeting education, media/marketing, and government organizations in the Middle East, later expanding to the US, Europe, and Asia. Delivery documents use Template Injection to load a remote OLE file whose macro runs mshta against a Bit.ly link redirecting to a BlogSpot post, which then uses Pastebin pastes to download RevengeRAT configured with a duckdns[.]org C2 domain. The embedded script also deletes Microsoft Defender signatures and kills Defender and Office processes, and modifies registry keys to enable macros. High-level TTPs resemble the Gorgon Group, but Unit 42 could not confirm attribution.

Palo Alto Unit 42·Aug 17, 13:21 UTC · Aug 17, 2026Threat actor

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·Sep 9, 16:31 UTC · 7d agoAI research

microsoft/VibeVoice-ASR-Streaming-7B — new model trending #27 on Hugging Face

Microsoft released VibeVoice-ASR-Streaming-7B, an open streaming ASR model with speaker attribution, custom hotwords, and support for 10 languages under MIT license.

Microsoft Research released VibeVoice-ASR-Streaming-7B on Hugging Face, a unified streaming speech recognition model that continuously transcribes who said what as speech arrives. The 7B model supports customized hotwords for domain-specific terms and 10 languages including Chinese, English, French, German, Italian, Japanese, Korean, Portuguese, Russian, and Spanish. Code is available at github.com/microsoft/VibeVoice with a live demo, and a technical report is on arXiv (2609.02812). The model is licensed under MIT.

Hugging Face trending models·Sep 2, 15:46 UTC · 14d agoModel release1

ChainDrop Worm Hits 400 npm Packages with Two Billion Monthly Installs

Infosecurity Magazine·Aug 5, 10:00 UTC · Aug 5, 2026Malware

Give Your Coding Agents a Memory You Own

Hugging Face introduces Funes, a tool that gives coding agents persistent, self-owned memory outside vendor clouds.

A Hugging Face blog post presents Funes, an approach for giving coding agents a persistent memory that developers own and control. The piece targets agent workflows where context must survive across sessions without ceding data to third-party services. No article body was available in the feed, so specifics beyond the title are limited.

Hugging Face Blog·Sep 3, 00:00 UTC · 13d agoAI tools & infra1

Researchers Build WeChat Zero-Click Worm Hijacking Phones via Calls

Calif researchers built WeWorm, a zero-click worm exploiting a WeChat VoIP memory-corruption RCE that Tencent has now patched.

Calif researchers found a memory corruption flaw in WeChat's VoIP stack in July using LLM-assisted analysis and built working exploits within two days, then integrated them into WeWorm, which they call the first zero-click worm spreading through WeChat calls on iOS and Android. A crafted incoming call yields remote code execution with no user interaction, giving full control of the victim's WeChat account; the attacker only needs to be on the victim's friend list, easily achieved by compromising a contact first. Tencent confirmed the bug and shipped patches in WeChat Android 8.0.77 and iOS 8.0.76, and chaining with other OS bugs could yield full device control.

Infosecurity Magazine·Sep 9, 15:00 UTC · 7d agoExploit / PoC

JustFit: 200K-Token LLM Serving on a 24 GiB Laptop with Just-in-Time State Management

JustFit MLX runtime serves 200K-token contexts for Qwen3.8-27B on a 24 GiB MacBook via just-in-time state management.

JustFit is an MLX-based inference runtime combining KVExec for compressed KV execution, PhaseSwap for component residency, and StateTrans for state-preserving serving transitions, independent of weight quantization. On a 24 GiB M4 Pro MacBook running Qwen3.8-27B MXFP4, it completed 196,608 input and 16,384 output tokens, raising single-request context from the mlx-vlm baseline's 30,720 positions to 212,992 (6.93x). Performance tests show 19.11 tokens/s on a 32K-input probe with a 16,374 MiB median peak footprint, and the runtime answered 29 of 30 AIME 2026 problems correctly.

arXiv cs.AI / cs.LG / cs.CL·Sep 15, 17:15 UTC · 1d agoAI research

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·Sep 10, 17:39 UTC · 6d agoAI research1

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·Sep 8, 13:00 UTC · 8d agoAI safety & security1

Grouped Value Attention: Efficient KV Caching via On-Demand Key Reconstruction

Grouped Value Attention stores grouped values and reconstructs content keys via a learned linear map, cutting KV-cache size about 45-47% versus GQA.

GVA stores only grouped values and reconstructs content keys with a learned linear map absorbed into the query at decode time, while a small shared decoupled RoPE channel preserves positional information via a separately cached positional key. At 350M parameters trained on 30B FineWeb-Edu tokens, the 16-dimensional positional variant scores 44.18 average accuracy across five tasks versus 44.36 for GQA and 43.88 for MLA. Custom decoding kernels are in development with an open-source release planned.

Hugging Face daily papers·Sep 7, 20:00 UTC · 9d agoAI research

BreezeBlue/Breeze-TTS-2 — new model trending #19 on Hugging Face

BreezeBlue open-weights Breeze TTS 2, a bilingual text-to-speech model it ranks #1 among open-weight models on the Artificial Analysis TTS leaderboard.

BreezeBlue released open weights and Apache 2.0-licensed PyTorch inference code for Breeze TTS 2 on 2026-08-25. The text-to-speech model supports English and Chinese, voice cloning, reference-free voice design, voice direction, and inline vocal events like (laugh) and (sigh). Reported performance includes #1 open-weight ranking on the Artificial Analysis Elo leaderboard, under 40 ms time-to-first-audio, a 0.32 real-time factor on an NVIDIA H100, and about 7.7 GiB GPU memory for eager inference.

Hugging Face trending models·Aug 25, 16:39 UTC · 22d agoModel release

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