Listen to this Post
Smartwatches are supposed to be convenient, personal devices, but researchers have uncovered a shocking vulnerability in a low-cost model that turns its own display into a window into sensitive firmware. By exploiting how custom watch faces are rendered on the screen, hackers demonstrated they could extract the device’s firmware—reviving a near-forgotten “blinkenlights” technique once seen only on networking equipment in the early 2000s. This discovery highlights how even seemingly harmless display features can become powerful exfiltration channels when firmware validation is weak.
From OTA Reversing to Screen-Based Attacks
Initially, researchers focused on extracting the firmware via the device’s over-the-air (OTA) update service over Bluetooth Low Energy (BLE). JieLi’s Android OTA app performs a mutual authentication handshake, generating a 16-byte random challenge and verifying responses using a hardcoded E1 legacy key and static pseudo-address embedded in the firmware library. The team replicated this algorithm in Python and confirmed the handshake, but the OTA service only allowed firmware upgrades, not read-backs, making direct extraction impossible.
Attention then turned to the smartwatch’s custom watch faces, delivered as binary blobs over BLE. Each blob contains a small header with magic bytes, chunk counts, and CRC checks, followed by multiple 16-byte chunks with indexes. By capturing these transfers and analyzing differences between watch faces, researchers mapped the structure: headers, region descriptors, and pixel offsets defining hours, minutes, battery graphics, and images.
Reviving Blinkenlights: Extracting Memory via Pixels
The critical flaw: firmware trusted the offsets in the watch face blobs without proper bounds checking. This allowed a malicious face to reference memory outside its allocated buffer. When displayed, the screen showed what looked like random pixels but were actually raw memory from the SoC. This recreated the classic “blinkenlights” side-channel attacks, but instead of network LEDs, the leakage flowed through a high-resolution smartwatch display.
Capturing the Display Bus
To turn this into a usable firmware dump, researchers first analyzed the TFT display bus by soldering fine wires to the screen connector. Using a Raspberry Pi Pico overclocked to 200 MHz, they captured the serial communication at 100 Msps. By sampling on the rising edge of the 25 MHz display clock and decoding pixel transfer commands, they could identify memory blocks displayed on the screen. Custom dials added sync markers, memory addresses, and delimiters, allowing the extraction of individual memory slices.
Automating Firmware Extraction
A Python toolchain automated the collection process. One script continuously captured hex dumps via USB, extracted pixel payloads, and validated sync markers, saving each slice as firmware-dump files. A second script combined these slices into a contiguous 2 MB firmware image, matching known JieLi layouts. This enabled deep disassembly of fake health measurements and display routines.
Implications for Embedded Security
This research underscores the risks in low-cost microcontrollers, weak parser validation, and legacy cryptographic designs. It demonstrates that even routine display paths can become sensitive attack surfaces. Developers must treat screens as potential exfiltration channels rather than purely cosmetic outputs. Modern embedded devices require careful input validation, bounds checking, and threat modeling for all outputs.
What Undercode Say:
The smartwatch exploit illustrates a larger trend in embedded security where peripheral interfaces, traditionally considered low-risk, are now being leveraged for high-bandwidth data exfiltration. Low-cost microcontrollers often reuse legacy designs with minimal input validation, creating systemic vulnerabilities. In this case, the screen itself became a data leakage vector due to insufficient bounds checking in the firmware’s dial parser.
The methodology highlights the importance of understanding device architectures at a hardware level. By physically probing the display bus, the researchers bypassed cryptographic protections entirely, showing that software-only security assumptions are insufficient. This aligns with historical lessons from networking hardware blinkenlights attacks, where optical signals provided unintended side channels.
From a security engineering perspective, this attack underlines two critical needs: enforcing strict bounds checking and assuming that any output device—screen, LEDs, speakers—can become a side channel. Firmware developers must also avoid fixed keys or static authentication schemes in OTA processes, as these allow predictable interactions exploitable in combination with peripheral manipulations.
Additionally, this research sheds light on a concerning trend: as devices become smaller and more integrated, debugging and analysis tools have become accessible enough to allow such physical attacks without requiring industrial-grade lab equipment. Raspberry Pi Pico devices and inexpensive logic analyzers are sufficient for these exploits, lowering the barrier for attackers.
The implications extend beyond smartwatches. Any low-cost IoT device using similar display or LED outputs could potentially leak sensitive information. Financial, health, and authentication devices are particularly at risk if they use the same approach to display critical data. The attack also emphasizes the need for threat modeling that includes human-readable outputs as potential security liabilities.
This exploit also demonstrates a tradeoff in embedded design: balancing low-cost, lightweight firmware with robust security measures. Overlooked validation in custom protocols can compromise an entire device, even when standard OTA protections are in place. Security testing for embedded devices must therefore include both conventional attack surfaces and unconventional ones like screens or user interfaces.
Finally, the study serves as a wake-up call for vendors relying on legacy cryptography and minimalistic firmware validation. As attackers combine software, protocol, and hardware insights, traditional security assumptions—like the harmlessness of a display—become outdated. Device designers must anticipate adversaries capable of both physical and logical attacks, integrating monitoring, testing, and mitigation strategies accordingly.
Fact Checker Results:
✅ The firmware extraction via smartwatch screen is real and demonstrated in research.
✅ OTA handshake exists but cannot directly dump firmware.
❌ The attack requires physical access and hardware probing, not purely remote execution.
Prediction:
📊 This attack vector is likely to inspire similar research on low-cost IoT devices, particularly wearables and health gadgets. Manufacturers may adopt stricter bounds checking, encryption for screen buffers, and anomaly detection to prevent optical side-channel leaks. Expect a wave of security updates targeting display-driven data leakage in the next 12–18 months.
🕵️📝✔️Let’s dive deep and fact‑check.
References:
Reported By: cyberpress.org
Extra Source Hub (Possible Sources for article):
https://www.instagram.com
Wikipedia
OpenAi & Undercode AI
Image Source:
Unsplash
Undercode AI DI v2
Bing
🔐JOIN OUR CYBER WORLD [ CVE News • HackMonitor • UndercodeNews ]
📢 Follow UndercodeNews & Stay Tuned:
𝕏 formerly Twitter 🐦 | @ Threads | 🔗 Linkedin | 🦋BlueSky | 🐘Mastodon
