Secluso is an open-source DIY home security camera system built around the Raspberry Pi Zero 2 W. It focuses on privacy by using true end-to-end encryption (E2EE) via Messaging Layer Security (MLS), ensuring that even untrusted relays cannot decrypt video feeds. The system features on-device AI for detecting humans, pets, and vehicles. To enhance security, the core software is written in Rust to prevent memory-related bugs and includes post-quantum encryption to protect data against future threats.
- Raspberry Pi Zero 2W based hardware architecture
- End-to-end encryption using MLS (RFC 9420)
- On-device AI for human, pet, and vehicle detection
- Memory-safe software core written in Rust
- Post-quantum encryption support
- Minimal Yocto-based Secluso OS
- Support for self-hosted relays or official beta services
- Raspberry Pi Zero 2W based hardware architecture
- End-to-end encryption using MLS (RFC 9420)
- On-device AI for human, pet, and vehicle detection
- Memory-safe software core written in Rust
- Post-quantum encryption support
- Minimal Yocto-based Secluso OS
- Support for self-hosted relays or official beta services
An overview of ESPConnect, a free self-hosted web utility used to manage and flash ESP32 microcontrollers. The tool provides detailed hardware profiling for various MCU models, allows for advanced partition management, and enables flashing firmware or creating system backups through filesystem access. It also includes essential debugging features like an NVS Inspector and a Serial Monitor.
- Detailed hardware profile generation (MAC address, memory, clock speeds)
- Partition layout modification and flash backup capabilities
- File system support including SPIFFS, LittleFS, and FATFS
- Debugging via UART logs and session history tracking
- Easy deployment on Proxmox using LXC scripts
- Detailed hardware profile generation (MAC address, memory, clock speeds)
- Partition layout modification and flash backup capabilities
- File system support including SPIFFS, LittleFS, and FATFS
- Debugging via UART logs and session history tracking
- Easy deployment on Proxmox using LXC scripts
An exploration of high-performing small language models with under 7 billion parameters that can run locally on consumer hardware like laptops and smartphones. The article explains how advancements in training data quality, model distillation from larger frontier models, and architectural improvements like Mixture-of-Experts have enabled these compact models to compete with much larger versions on reasoning benchmarks. It provides a curated guide of top available models on Hugging Face, detailing their specific strengths, benchmark performance, and providing Python code for implementation.
Key models covered:
- Qwen3.5-4B for multilingual tasks and long context windows
- Microsoft Phi-4-mini-instruct for reasoning-heavy English workloads
- Google Gemma 3 4B IT for coding and mathematics
- Google Gemma 3n E4B for efficient mobile and on-device deployment
- Meta Llama 3.2 3B Instruct for tool calling and community support
- SmolLM3-3B for research transparency and open-source projects
- DeepSeek-R1-Distill-Qwen-1.5B for lightweight reasoning on edge devices
- Qwen3-0.6B for ultra-constrained hardware and text classification
Key models covered:
- Qwen3.5-4B for multilingual tasks and long context windows
- Microsoft Phi-4-mini-instruct for reasoning-heavy English workloads
- Google Gemma 3 4B IT for coding and mathematics
- Google Gemma 3n E4B for efficient mobile and on-device deployment
- Meta Llama 3.2 3B Instruct for tool calling and community support
- SmolLM3-3B for research transparency and open-source projects
- DeepSeek-R1-Distill-Qwen-1.5B for lightweight reasoning on edge devices
- Qwen3-0.6B for ultra-constrained hardware and text classification
Clawdmeter is a custom-built desk dashboard powered by the ESP32-S3 that provides real-time monitoring of Claude Code token usage. Utilizing a 2.16-inch AMOLED screen and Bluetooth LE connectivity, the device displays animated pixel art that reacts to usage rates and acts as a HID keyboard for quick command shortcuts via BLE.
This advisory details a significant tactical shift by China-nexus cyber actors toward using large-scale networks of compromised devices, known as covert networks or botnets, to route malicious activity. These networks primarily consist of vulnerable Small Office Home Office (SOHO) routers and Internet of Things (IoT) devices, allowing threat actors to disguise their origins and conduct reconnaissance, malware delivery, and data exfiltration with high deniability.
Key points include:
- The transition from individually procured infrastructure to externally provisioned botnets managed by Chinese information security companies.
- Use of compromised edge devices like Cisco and NetGear routers that are often end-of-life or unpatched.
- Challenges for defenders due to indicator of compromise (IOC) extinction, making static IP block lists less effective.
- Recommended defensive strategies ranging from basic asset mapping and multi-factor authentication to advanced zero trust policies and active threat hunting.
Key points include:
- The transition from individually procured infrastructure to externally provisioned botnets managed by Chinese information security companies.
- Use of compromised edge devices like Cisco and NetGear routers that are often end-of-life or unpatched.
- Challenges for defenders due to indicator of compromise (IOC) extinction, making static IP block lists less effective.
- Recommended defensive strategies ranging from basic asset mapping and multi-factor authentication to advanced zero trust policies and active threat hunting.
The Orange Pi Zero 3W is a new compact single-board computer measuring 65 x 32 mm. It features the Allwinner A733 octa-core processor, combining Cortex-A76 and Cortex-A55 cores with an integrated NPU for AI workloads and a RISC-V coprocessor for real-time tasks. The board supports up to 16GB of LPDDR5 memory and offers versatile display options including Mini HDMI, MIPI-DSI, and DisplayPort via USB-C.
* Allwinner A733 SoC with octa-core CPU and 3 TOPS NPU
* Up to 16GB LPDDR5 RAM support
* Connectivity includes Wi-Fi 6, Bluetooth 5.4, and PCIe 3.0
* Multiple display outputs supporting up to 4K resolution
* Support for Android, Debian, Ubuntu, and OpenHarmony
* Allwinner A733 SoC with octa-core CPU and 3 TOPS NPU
* Up to 16GB LPDDR5 RAM support
* Connectivity includes Wi-Fi 6, Bluetooth 5.4, and PCIe 3.0
* Multiple display outputs supporting up to 4K resolution
* Support for Android, Debian, Ubuntu, and OpenHarmony
A clean-room, header-only C/C++ implementation of the Meshtastic LoRa mesh protocol designed for embedded systems. This standalone library allows devices to interoperate with the Meshtastic network without requiring heavy dependencies like Arduino, RadioLib, or FreeRTOS. It handles everything from raw LoRa byte processing to decoded messages including text, position, and telemetry data.
Key features include:
- Packet parsing and AES-256-CTR encryption/decryption
- PKI direct messages using x25519 key exchange
- Channel management and PSK expansion
- Protobuf decoding for various message types without Nanopb dependency
- Radio configuration including regional settings and modem presets
- CSMA/CA implementation for MAC protocol compliance
Key features include:
- Packet parsing and AES-256-CTR encryption/decryption
- PKI direct messages using x25519 key exchange
- Channel management and PSK expansion
- Protobuf decoding for various message types without Nanopb dependency
- Radio configuration including regional settings and modem presets
- CSMA/CA implementation for MAC protocol compliance
The Orange Pi Zero 2W is a compact and powerful single-board computer designed for efficiency and versatility in IoT, smart home, and media applications. Powered by the Allwinner H618 quad-core Cortex-A53 processor, it offers high performance with low power consumption and supports various memory configurations to suit different project needs.
Key features include:
- Quad-core Cortex-A53 processor up to 1.5GHz with Mali G31 MP2 graphics.
- LPDDR4 memory options of 1GB, 1.5GB, 2GB, or 4GB.
- Integrated Wi-Fi 5 and Bluetooth 5.0 for seamless connectivity.
- Compact PCB size of 30mm x 65mm.
- Extensive expansion capabilities via a 24-pin connector and a 40-pin GPIO port.
- Support for multiple operating systems including Android 12 TV, Debian, Ubuntu, and Orange Pi OS (Arch).
Key features include:
- Quad-core Cortex-A53 processor up to 1.5GHz with Mali G31 MP2 graphics.
- LPDDR4 memory options of 1GB, 1.5GB, 2GB, or 4GB.
- Integrated Wi-Fi 5 and Bluetooth 5.0 for seamless connectivity.
- Compact PCB size of 30mm x 65mm.
- Extensive expansion capabilities via a 24-pin connector and a 40-pin GPIO port.
- Support for multiple operating systems including Android 12 TV, Debian, Ubuntu, and Orange Pi OS (Arch).
Banana Pi has announced the BPI-SM10, a compact computing system powered by the SpacemiT K3 RISC-V processor. This hardware is designed for users interested in exploring RISC-V architecture and high-performance AI tasks at the edge. The system features an 8-core AI accelerator capable of delivering up to 60 TOPS, which is sufficient to run 30 billion parameter AI models.
Key details include:
* BPI-SM10 consists of a SpacemiT K3 compute module and a versatile carrier board.
* The processor features an octa-core design at 2.4 GHz with support for up to 32GB LPDDR5 RAM.
* Carrier board I/O includes M.2 PCIe Gen 4 slots, USB 3.2 ports, DisplayPort, and Gigabit Ethernet.
* A forthcoming K3 Pico-ITX single-unit mini PC will also be released featuring a 10-gigabit Ethernet port.
Key details include:
* BPI-SM10 consists of a SpacemiT K3 compute module and a versatile carrier board.
* The processor features an octa-core design at 2.4 GHz with support for up to 32GB LPDDR5 RAM.
* Carrier board I/O includes M.2 PCIe Gen 4 slots, USB 3.2 ports, DisplayPort, and Gigabit Ethernet.
* A forthcoming K3 Pico-ITX single-unit mini PC will also be released featuring a 10-gigabit Ethernet port.
The MeshCore development team announces a formal split within the project following internal disputes regarding brand ownership and the use of AI-generated code.
A former team member is accused of attempting to claim the MeshCore trademark and rebranding components using "vibe coded" AI tools without team consensus. The core team clarifies that the only official source of truth remains the GitHub repository and has launched meshcore.io to serve as the new central hub for firmware, documentation, and community engagement.
Main points:
- Internal conflict regarding trademark filings and brand control.
- Dispute over the use of AI-generated code versus human-crafted software.
- Transition of official resources to the meshcore.io domain.
- Introduction of the core development team members responsible for future updates.
A former team member is accused of attempting to claim the MeshCore trademark and rebranding components using "vibe coded" AI tools without team consensus. The core team clarifies that the only official source of truth remains the GitHub repository and has launched meshcore.io to serve as the new central hub for firmware, documentation, and community engagement.
Main points:
- Internal conflict regarding trademark filings and brand control.
- Dispute over the use of AI-generated code versus human-crafted software.
- Transition of official resources to the meshcore.io domain.
- Introduction of the core development team members responsible for future updates.
