AI Weekly Malaysia

Needle 2 is a 45M-parameter agentic LLM compressed to a 14MB binary that runs in 28MB of RAM, designed for tool calling, device control, and structured extraction on sub-$200 hardware. It hits 500 tokens/sec decode on a Raspberry Pi 5, 300–700 on budget Samsung A-Series phones, and even runs on ESP32-S3 microcontrollers. It trades benchmark wins with models 5×–70× larger (FunctionGemma 270M, LFM2.5 230M, Apple FM) on mobile device-use tasks, and is released under Apache 2.0 with weights on Hugging Face.

Why: If you are building IoT, smart home, wearable, or robotics products targeting the Malaysian or broader SEA market where most phones ship under $200, Needle 2 lets you run on-device function calling without a GPU, NPU, or cloud dependency. The 28MB RAM footprint means you can prototype agent-based device control on hardware you already have—Raspberry Pi, ESP32-S3, or budget Android phones—today, with the repo and sandbox available to test immediately.

Researchers from the University of Birmingham and Fuzzware found that a malicious SIM card can execute attacker-chosen code on cellular modems via a 'RUN AT' interface, present in 9 of 26 devices tested. Six of eight cellular modules accepted the command—including five Quectel parts pulled from an EV charger, industrial router, and car telematics unit—while only 3 of 18 phones did (OPPO Find X5, OPPO Reno 14 F 5G, ASUS Zenfone 9). All nine vulnerable devices run Qualcomm communication processors; Qualcomm has built a hardened config that disables the interface by default for future devices, but neither Qualcomm nor Quectel has published a public advisory.

Why: If you ship or operate cellular IoT fleets—EV chargers, industrial routers, telematics—ask your module supplier today whether RUN AT is enabled in the firmware they ship, since there is no central patch and Quectel's vulnerability portal is login-walled. The attack requires physical SIM access, so unattended devices with accessible SIM trays and few other interfaces are the highest-risk targets.

Researchers from the University of Birmingham and Fuzzware presented a toolkit called CATANA at USENIX WOOT that exploits proactive SIM functionality—specifically the RUN AT command—to hijack cellular modems. Testing 26 devices (18 smartphones, 8 IoT modems), they found 9 exposed an AT command interface to the SIM, enabling code execution, file theft, denial of service, and forced 2G downgrades. Demonstrated attacks include code execution on an Autel EV charger via a Quectel EC25-AFX module and 198 AT commands accessible on an Oppo Reno14 F 5G, including one that forced a stubborn downgrade to 2G that couldn't be reversed by toggling airplane mode or changing network settings.

Why: If you ship IoT devices with cellular modules (especially Quectel modems, which are common in Malaysian IoT and fleet deployments), audit whether your modem exposes the AT command interface to the SIM and whether you can disable proactive SIM commands. The Oppo Reno14 F 5G is a consumer device sold in Malaysia, so the 2G-downgrade and shutdown attacks are directly relevant to local mobile users—worth flagging if you build mobile apps or advise on device security.

A routine cyber vulnerability assessment found cameras aboard Royal Navy Kraken Unmanned Surface Vessels transmitting heartbeat signals to an IP address in China. The UK MoD confirmed no classified data was compromised, and the cameras were sourced by Kraken from a third-party supplier. The incident underscores that even benign telemetry transmissions from unvetted supply chain components can surface as serious security incidents.

Why: If you ship IoT or edge devices, or build systems that incorporate third-party hardware, this is a concrete reminder to network-monitor your own components for unexpected outbound traffic before a customer or auditor finds it. The failure here wasn't malware—it was an unexamined camera phoning home. Builders integrating hardware from opaque supply chains should demand component-level network behavior documentation and run passive traffic capture during staging, not trust supplier assurances.

The UK Royal Navy discovered that components in its sea drones were secretly transmitting data to China, prompting the government to cut camera connectivity. Officials downplayed the incident, claiming the transmissions were only non-sensitive 'heartbeat communications.'

Why: If you build IoT, robotics, or drone systems using third-party hardware modules, this is a concrete reminder that components can exfiltrate data without your knowledge. Audit your bill of materials for any sub-module with its own network stack, and network-segregate sensors that don't need outbound connectivity—especially when sourcing from opaque supply chains.

Attackers shut down a steam turbine and water treatment system at a Polish CHP plant by pivoting through a private cellular APN from a compromised wind farm to a WAGO controller with default admin credentials. CERT Polska, disclosing the December 2025 incident on August 8, called it the first real-world observed use of a private APN as an attack vector into industrial control networks. No CVE was identified and no single patch exists; the root causes were permissive client-to-client APN traffic, default credentials, and exposed management interfaces.

Why: If you build or manage anything behind a private APN or cellular IoT network, audit whether client isolation is enabled and whether devices can reach each other laterally—CERT found this misconfiguration is common across countries. The incident also reinforces that default credentials on reachable controllers remain a live attack path, but there is no specific software patch to apply here.

Ars Technica reports that pet owners claim a smart pet feeder outage left their animals unfed, but the article body retrieved is entirely cookie consent/privacy policy boilerplate with no substantive content about the incident, the vendor, the outage duration, or the affected product.

Why: No actionable detail is available from the retrieved text. The headline alone hints at a familiar IoT failure pattern—cloud-dependent consumer devices that brick core functionality when the backend goes down—but without the article content there is nothing concrete to discuss or decide on.