I carried out a fixed analysis of DeepSeek, a Chinese LLM chatbot, utilizing version 1.8.0 from the Google Play Store. The goal was to identify prospective security and personal privacy concerns.

I have actually composed about DeepSeek previously here.

Additional security and personal privacy concerns about DeepSeek have been raised.

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

The findings detailed in this report are based simply on fixed analysis. This means that while the code exists within the app, there is no conclusive proof that all of it is performed in practice. Nonetheless, the existence of such code warrants analysis, especially provided the growing issues around information privacy, security, the potential abuse of AI-driven applications, and cyber-espionage dynamics between global powers.

Key Findings

Suspicious Data Handling & Exfiltration

- Hardcoded URLs direct information to external servers, raising concerns about user activity tracking, such as to ByteDance "volce.com" endpoints. NowSecure recognizes these in the iPhone app yesterday too.
- Bespoke encryption and smfsimple.com data obfuscation techniques exist, with indicators that they could be utilized to exfiltrate user details.
- The app contains hard-coded public keys, rather than counting on the user device's chain of trust.
- UI interaction tracking records detailed user behavior without clear permission.
- WebView control is present, which might enable the app to gain access to personal external internet browser data when links are opened. More details about WebView adjustments is here

Device Fingerprinting & Tracking

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

- The app gathers different distinct device identifiers, consisting of UDID, Android ID, IMEI, IMSI, and provider details.
- System homes, set up plans, and root detection systems suggest prospective anti-tampering measures. E.g. probes for the presence of Magisk, a tool that personal privacy advocates and security researchers use to root their Android gadgets.
- Geolocation and network profiling exist, suggesting possible tracking abilities and allowing or disabling of fingerprinting programs by area.
- Hardcoded device design lists suggest the application might behave in a different way depending upon the detected hardware.
- Multiple vendor-specific services are used to extract extra device details. E.g. if it can not identify the gadget through standard Android SIM lookup (because approval was not given), it attempts manufacturer specific extensions to access the same details.

Potential Malware-Like Behavior

While no definitive conclusions can be drawn without vibrant analysis, a number of observed habits line up with recognized spyware and malware patterns:

- The app uses reflection and UI overlays, which might assist in 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 systems.
- The app executes calls to pack Dex modules, where additional code is loaded from files with a.so extension at runtime.
- The.so files themselves reverse and make additional calls to dlopen(), which can be used to fill additional.so files. This center is not generally inspected by Google Play Protect and other static analysis services.
- The.so files can be carried out in native code, such as C++. Making use of native code adds a layer of complexity to the analysis procedure and obscures the full degree of the app's abilities. Moreover, native code can be leveraged to more easily intensify benefits, potentially exploiting vulnerabilities within the operating system or gadget hardware.

Remarks

While information collection prevails in modern applications for debugging and enhancing user experience, aggressive fingerprinting raises significant personal privacy concerns. The DeepSeek app requires users to log in with a legitimate email, which must already supply sufficient authentication. There is no valid factor for the app to strongly gather and send unique device identifiers, IMEI numbers, SIM card details, and other non-resettable system properties.

The extent of tracking observed here exceeds common analytics practices, possibly allowing persistent user tracking and re-identification across gadgets. These behaviors, integrated with obfuscation techniques and network communication with third-party tracking services, require a greater level of analysis from security scientists and users alike.

The work of runtime code packing as well as the bundling of native code recommends that the app might permit the implementation and execution of unreviewed, remotely delivered code. This is a severe possible attack vector. No evidence in this report is presented that remotely released code execution is being done, only that the center for forum.batman.gainedge.org this appears present.

Additionally, the app's approach to detecting rooted devices appears extreme for an AI chatbot. Root detection is typically justified in DRM-protected streaming services, where security and material security are critical, or in competitive video games to avoid unfaithful. However, there is no clear rationale for such rigorous measures in an application of this nature, raising additional questions about its intent.

Users and companies considering installing DeepSeek needs to know these possible risks. If this application is being utilized within an enterprise or government environment, extra vetting and security controls need to be implemented before enabling its deployment on managed devices.

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