I conducted a fixed analysis of DeepSeek, a Chinese LLM chatbot, using version 1.8.0 from the Google Play Store. The goal was to identify possible security and privacy problems.

I've blogged about DeepSeek previously here.

Additional security and personal privacy issues 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 purely on fixed analysis. This implies that while the code exists within the app, there is no conclusive evidence that all of it is executed in practice. Nonetheless, the existence of such code warrants examination, especially provided the growing issues around data personal privacy, surveillance, the prospective misuse 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 issues about user activity monitoring, such as to ByteDance "volce.com" endpoints. NowSecure recognizes these in the iPhone app yesterday as well.

• Bespoke file encryption and data obfuscation approaches are present, with signs that they might be used to exfiltrate user details.
• The app contains hard-coded public secrets, instead of relying on the user gadget's chain of trust.
• UI interaction tracking captures detailed user habits without clear approval.
• WebView control is present, which might enable the app to gain access to private external internet browser information when links are opened. More details about WebView controls is here
  
  Device Fingerprinting & Tracking
  
  A substantial portion of the analyzed code appears to concentrate on event device-specific details, which can be utilized for tracking and fingerprinting.
  
  - The app gathers different special device identifiers, consisting of UDID, Android ID, IMEI, IMSI, and carrier details.
• System properties, townshipmarket.co.za installed packages, and root detection systems suggest potential anti-tampering steps. E.g. probes for the presence of Magisk, a tool that privacy advocates and security scientists utilize to root their Android devices.
• Geolocation and network profiling are present, suggesting prospective tracking capabilities and allowing or disabling of fingerprinting programs by area. - Hardcoded device design lists recommend the application might act differently depending upon the discovered hardware.
• Multiple vendor-specific services are used to draw out extra device details. E.g. if it can not figure out the device through standard Android SIM lookup (because consent was not approved), it attempts producer specific extensions to access the very same details.
  
  Potential Malware-Like Behavior
  
  While no conclusive conclusions can be drawn without vibrant analysis, several observed behaviors line up with recognized spyware and malware patterns:
  
  - The app uses reflection and UI overlays, which might facilitate unapproved screen capture or phishing attacks.
• SIM card details, identification numbers, and other device-specific information are aggregated for unknown functions.
• The app executes country-based gain access to constraints and "risk-device" detection, suggesting possible security systems.
• The app executes calls to load Dex modules, where additional code is packed from files with a.so extension at runtime.
• The.so submits themselves reverse and make extra calls to dlopen(), which can be utilized to pack additional.so files. This facility is not typically inspected by Google Play Protect and other static analysis services.
• The.so files can be implemented in native code, such as C++. Using native code includes a layer of complexity to the analysis procedure and obscures the full level of the app's capabilities. Moreover, native code can be leveraged to more easily escalate privileges, potentially exploiting vulnerabilities within the os or gadget hardware.
  
  Remarks
  
  While data collection prevails in contemporary applications for debugging and improving user experience, aggressive fingerprinting raises significant privacy issues. The DeepSeek app needs users to visit with a legitimate email, which ought to already offer sufficient authentication. There is no valid factor for the app to aggressively collect and transfer special device identifiers, IMEI numbers, SIM card details, and other non-resettable system residential or .
  
  The level of tracking observed here exceeds common analytics practices, possibly making it possible for relentless user tracking and re-identification throughout gadgets. These habits, photorum.eclat-mauve.fr combined with obfuscation methods and network communication with third-party tracking services, necessitate a higher level of analysis from security scientists and users alike.
  
  The employment of runtime code packing in addition to the bundling of native code suggests that the app could allow the implementation and execution of unreviewed, remotely provided code. This is a serious potential attack vector. No proof in this report exists that from another location released code execution is being done, just that the facility for this appears present.
  
  Additionally, the app's method to spotting rooted gadgets appears excessive for an AI chatbot. Root detection is typically warranted in DRM-protected streaming services, where security and material protection are vital, or in competitive video games to prevent 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 setting up DeepSeek ought to know these possible threats. If this application is being used within a business or federal government environment, extra vetting and security controls should be implemented before enabling its deployment on managed devices.
  
  Disclaimer: The analysis provided in this report is based upon static code evaluation and does not indicate that all detected functions are actively used. Further examination is needed for conclusive conclusions.