I performed a static analysis of DeepSeek, a Chinese LLM chatbot, using variation 1.8.0 from the Google Play Store. The objective was to determine possible security and privacy concerns.

I've discussed DeepSeek previously here.

Additional security and privacy issues 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 simply on static analysis. This implies that while the code exists within the app, there is no definitive evidence that all of it is carried out in practice. Nonetheless, the presence of such code warrants scrutiny, specifically provided the growing issues around information personal privacy, monitoring, larsaluarna.se the prospective abuse of AI-driven applications, and cyber-espionage characteristics between global powers.

Key Findings

Suspicious Data Handling & Exfiltration

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

• Bespoke encryption and information obfuscation techniques are present, with indicators that they could be used to exfiltrate user details.
• The app contains hard-coded public secrets, instead of counting on the user gadget's chain of trust.
• UI interaction tracking catches detailed user behavior without clear authorization. - WebView adjustment exists, which could enable the app to gain access to private external internet browser information when links are opened. More details about WebView manipulations is here
  
  Device Fingerprinting & Tracking
  
  A significant portion of the analyzed code appears to focus on gathering device-specific details, which can be used for tracking and fingerprinting.
  
  - The app gathers different special device identifiers, consisting of UDID, Android ID, IMEI, IMSI, and carrier details.
• System homes, installed packages, and root detection mechanisms suggest prospective anti-tampering measures. E.g. probes for the presence of Magisk, a tool that personal privacy advocates and security scientists use to root their Android gadgets.
• Geolocation and network profiling are present, indicating potential tracking abilities and allowing or disabling of fingerprinting routines by area.
• Hardcoded gadget model lists suggest the application may act differently depending upon the found hardware. - Multiple vendor-specific services are utilized to draw out extra device details. E.g. if it can not identify the gadget through basic Android SIM lookup (since approval was not approved), it attempts manufacturer particular extensions to access the exact 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 utilizes reflection and wiki.philipphudek.de UI overlays, which could assist in unapproved screen capture or phishing attacks.
• SIM card details, identification numbers, and other device-specific data are aggregated for unknown purposes.
• The app carries out country-based gain access to constraints and "risk-device" detection, recommending possible monitoring systems.
• The app executes calls to load Dex modules, where code is filled from files with a.so extension at runtime.
• The.so submits themselves turn around and make additional calls to dlopen(), larsaluarna.se which can be utilized to fill additional.so files. This facility is not typically checked by Google Play Protect and trademarketclassifieds.com other fixed analysis services.
• The.so files can be executed in native code, such as C++. Using native code includes a layer of complexity to the analysis process and obscures the full level of the app's abilities. Moreover, native code can be leveraged to more easily escalate benefits, potentially exploiting vulnerabilities within the operating system or gadget hardware.
  
  Remarks
  
  While information collection prevails in modern-day applications for debugging and improving user experience, aggressive fingerprinting raises considerable privacy issues. The DeepSeek app needs users to visit with a valid email, which ought to currently offer sufficient authentication. There is no valid reason for the app to strongly collect and transfer unique gadget identifiers, links.gtanet.com.br IMEI numbers, SIM card details, and other non-resettable system residential or commercial properties.
  
  The extent of tracking observed here exceeds normal analytics practices, potentially making it possible for links.gtanet.com.br consistent user tracking and re-identification across gadgets. These habits, integrated with obfuscation strategies and network interaction with third-party tracking services, require a greater level of analysis from security researchers and users alike.
  
  The employment of runtime code filling along with the bundling of native code suggests that the app could permit the release and execution of unreviewed, remotely delivered code. This is a serious possible attack vector. No evidence in this report is provided that remotely released code execution is being done, wikibase.imfd.cl just that the facility for this appears present.
  
  Additionally, the app's method to finding rooted gadgets appears extreme for an AI chatbot. Root detection is frequently justified in DRM-protected streaming services, where security and material security are crucial, or in competitive computer game to prevent unfaithful. However, there is no clear reasoning for such strict measures in an application of this nature, raising more concerns about its intent.
  
  Users and companies considering setting up DeepSeek needs to know these possible dangers. If this application is being used within an enterprise or government environment, extra vetting and security controls should be enforced before permitting its implementation on managed devices.
  
  Disclaimer: The analysis presented in this report is based upon fixed code evaluation and does not imply that all detected functions are actively utilized. Further examination is required for conclusive conclusions.