bjewaytek

andreskovar80/bjewaytek

I carried out a static analysis of DeepSeek, a Chinese LLM chatbot, utilizing version 1.8.0 from the Google Play Store. The objective was to determine prospective security and privacy issues.

I have actually discussed DeepSeek previously here.

Additional security and privacy concerns about DeepSeek have been raised.

See also this analysis by NowSecure of the iPhone version of DeepSeek

The findings detailed in this report are based purely on static analysis. This means that while the code exists within the app, there is no definitive proof that all of it is performed in practice. Nonetheless, the presence of such code warrants analysis, especially provided the growing concerns around data personal privacy, security, the potential misuse of AI-driven applications, and cyber-espionage dynamics between worldwide powers.

Key Findings

Suspicious Data Handling & Exfiltration

- Hardcoded URLs direct data to external servers, raising concerns about user activity tracking, such as to ByteDance "volce.com" endpoints. NowSecure identifies these in the iPhone app yesterday too. - Bespoke file encryption and data obfuscation methods exist, with indicators that they might be utilized to exfiltrate user details.

The app contains hard-coded public keys, rather than relying on the user gadget's chain of trust.
UI interaction tracking records detailed user habits without clear authorization. - WebView adjustment exists, which might enable the app to gain access to private external web browser information when links are opened. More details about WebView adjustments is here

Device Fingerprinting & Tracking

A significant portion of the examined code appears to concentrate on event device-specific details, which can be utilized for tracking and fingerprinting.

- The app collects different special device identifiers, including UDID, equipifieds.com Android ID, IMEI, IMSI, and provider details.
System properties, installed packages, and root detection systems suggest prospective anti-tampering measures. E.g. probes for the presence of Magisk, a tool that privacy supporters and security researchers utilize to root their Android gadgets.
Geolocation and network profiling are present, indicating potential tracking capabilities and allowing or disabling of fingerprinting routines by area.
Hardcoded device model lists recommend the application might act differently depending upon the spotted hardware.
Multiple vendor-specific services are utilized to draw out additional gadget details. E.g. if it can not identify the device through basic Android SIM lookup (because authorization was not granted), it attempts manufacturer particular extensions to access the same details.

Potential Malware-Like Behavior

While no definitive conclusions can be drawn without vibrant analysis, numerous observed habits line up with known spyware and malware patterns:

- The app uses reflection and UI overlays, which could help with unauthorized screen capture or phishing attacks.
SIM card details, identification numbers, and other device-specific data are aggregated for unknown functions.
The app executes country-based gain access to constraints and "risk-device" detection, recommending possible surveillance mechanisms.
The app executes calls to load Dex modules, where extra code is loaded from files with a.so extension at runtime.
The.so submits themselves reverse and make additional calls to dlopen(), which can be used to pack additional.so files. This facility is not normally inspected by Google Play Protect and other static analysis services.
The.so files can be executed in native code, such as C++. Using native code includes a layer of intricacy to the analysis procedure and obscures the complete degree of the app's abilities. Moreover, native code can be leveraged to more easily intensify privileges, possibly making use of vulnerabilities within the os or gadget hardware.

Remarks

While data collection prevails in contemporary applications for debugging and improving user experience, aggressive fingerprinting raises considerable privacy concerns. The DeepSeek app needs users to visit with a legitimate email, which should currently offer sufficient authentication. There is no legitimate factor for the app to strongly gather and send special device identifiers, IMEI numbers, SIM card details, and other non-resettable system homes.

The degree of tracking observed here surpasses common analytics practices, potentially making it possible for persistent user tracking and re-identification across devices. These behaviors, integrated with obfuscation strategies and network communication with third-party tracking services, call for akropolistravel.com a greater level of analysis from security scientists and users alike.

The work of runtime code filling in addition to the bundling of native code recommends that the app might permit the implementation and execution of unreviewed, remotely delivered code. This is a serious prospective attack vector. No evidence in this report exists that from another location released code execution is being done, only that the facility for this appears present.

Additionally, the app's technique to identifying rooted gadgets appears extreme for an AI chatbot. Root detection is often justified in DRM-protected streaming services, where security and content security are vital, or in games to prevent unfaithful. However, there is no clear reasoning for such rigorous measures in an application of this nature, raising further questions about its intent.

Users and companies considering installing DeepSeek ought to know these potential dangers. If this application is being used within a business or federal government environment, additional vetting and security controls need to be implemented before allowing its release on managed devices.

Disclaimer: The analysis presented in this report is based on static code review and does not suggest that all detected functions are actively utilized. Further examination is required for conclusive conclusions.