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I performed a static analysis of DeepSeek, a Chinese LLM chatbot, utilizing version 1.8.0 from the Google Play Store. The goal was to determine possible security and privacy problems.

I've composed about DeepSeek formerly here.

Additional security and privacy issues about DeepSeek have been raised.

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

The findings detailed in this report are based simply on static analysis. This suggests that while the code exists within the app, there is no definitive proof that all of it is executed in practice. Nonetheless, the existence of such code warrants analysis, particularly provided the growing concerns around data privacy, monitoring, the potential abuse of AI-driven applications, and cyber-espionage characteristics in between global powers.

Key Findings

Suspicious Data Handling & Exfiltration

- Hardcoded URLs direct information to external servers, raising issues about user activity tracking, such as to ByteDance "volce.com" endpoints. NowSecure determines these in the iPhone app yesterday as well.

• Bespoke file encryption and data obfuscation techniques are present, with indications that they might be used to exfiltrate user details.
• The app contains hard-coded public keys, instead of relying on the user gadget's chain of trust.
• UI interaction tracking records detailed user habits without clear permission. - WebView adjustment exists, which might permit the app to gain access to personal external internet browser information when links are opened. More details about WebView adjustments is here
  
  Device Fingerprinting & Tracking
  
  A substantial portion of the examined code appears to concentrate on event device-specific details, which can be utilized for tracking and fingerprinting.
  
  - The app gathers various unique gadget identifiers, consisting of UDID, Android ID, IMEI, IMSI, and provider details.
• System homes, set up bundles, 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 use to root their Android gadgets.
• Geolocation and network profiling exist, indicating prospective tracking abilities and allowing or disabling of fingerprinting programs by area. - Hardcoded gadget design lists suggest the application might act differently depending on the detected hardware.
• Multiple vendor-specific services are utilized to extract extra gadget details. E.g. if it can not figure out the device through standard Android SIM lookup (due to the fact that consent was not approved), it attempts producer specific extensions to access the exact same details.
  
  Potential Malware-Like Behavior
  
  While no definitive conclusions can be drawn without dynamic analysis, several observed behaviors align with known spyware and malware patterns:
  
  - The app utilizes reflection and UI overlays, which could assist in unauthorized screen capture or phishing attacks.
• SIM card details, serial numbers, and forum.tinycircuits.com other device-specific data are aggregated for unknown functions.
• The app executes country-based gain access to constraints and "risk-device" detection, suggesting possible monitoring systems.
• The app implements calls to pack Dex modules, where additional code is filled from files with a.so extension at runtime.
• The.so files themselves reverse and make additional calls to dlopen(), which can be utilized to load additional.so files. This center is not usually checked by Google Play Protect and other static analysis services.
• The.so files can be carried out in native code, such as C++. The use of native code includes a layer of complexity to the analysis process and obscures the complete extent of the app's capabilities. Moreover, native code can be leveraged to more easily escalate privileges, possibly making use of vulnerabilities within the operating system or device hardware.
  
  Remarks
  
  While data collection prevails in modern-day applications for debugging and enhancing user experience, aggressive fingerprinting raises significant personal privacy issues. The DeepSeek app needs users to visit with a valid email, which must currently offer sufficient authentication. There is no valid factor for the app to aggressively collect and transfer special gadget identifiers, IMEI numbers, SIM card details, and other non-resettable system residential or commercial properties.
  
  The level of tracking observed here surpasses typical analytics practices, potentially making it possible for persistent user tracking and re-identification across devices. These habits, combined with obfuscation techniques and network interaction with third-party tracking services, call for a greater level of scrutiny from security researchers and users alike.
  
  The employment of runtime code filling along with the bundling of native code suggests that the app could allow the release and execution of unreviewed, from another location provided code. This is a serious possible attack vector. No evidence in this report is presented that remotely deployed code execution is being done, just that the facility for this appears present.
  
  Additionally, the app's method to discovering rooted devices appears excessive for an AI chatbot. Root detection is frequently 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 strict measures in an application of this nature, raising more questions about its intent.
  
  Users and organizations considering installing DeepSeek should know these prospective threats. If this application is being used within an enterprise or government environment, additional vetting and security controls should be implemented before allowing its implementation on handled devices.
  
  Disclaimer: The analysis presented in this report is based on fixed code evaluation and does not indicate that all found functions are actively utilized. Further investigation is needed for definitive conclusions.