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I conducted a static analysis of DeepSeek, a Chinese LLM chatbot, utilizing version 1.8.0 from the Google Play Store. The objective was to identify possible security and personal privacy issues.

I have actually blogged 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 fixed analysis. This implies that while the code exists within the app, there is no conclusive evidence that all of it is performed in practice. Nonetheless, the existence of such code warrants scrutiny, historydb.date particularly provided the growing concerns around data privacy, forum.batman.gainedge.org surveillance, the prospective abuse of AI-driven applications, and cyber-espionage dynamics in between international powers.

Key Findings

Suspicious Data Handling & Exfiltration

- Hardcoded URLs direct data to external servers, raising concerns about user activity monitoring, such as to ByteDance "volce.com" endpoints. NowSecure identifies these in the iPhone app the other day as well.

• Bespoke encryption and information obfuscation approaches are present, with signs that they could be used to exfiltrate user details.
• The app contains hard-coded public secrets, rather than counting on the user gadget's chain of trust.
• UI interaction tracking captures detailed user behavior without clear authorization.
• WebView adjustment exists, which could permit the app to gain access to private external internet browser data when links are opened. More details about WebView controls is here
  
  Device Fingerprinting & Tracking
  
  A considerable portion of the examined code appears to focus on event device-specific details, which can be utilized for tracking and fingerprinting.
  
  - The app collects numerous unique device identifiers, including UDID, Android ID, IMEI, IMSI, and carrier details.
• System homes, set up plans, and disgaeawiki.info root detection systems suggest potential anti-tampering measures. E.g. probes for the existence of Magisk, a tool that privacy advocates and security scientists utilize to root their Android devices.
• Geolocation and network profiling exist, indicating prospective tracking capabilities and enabling or disabling of fingerprinting programs by region.
• Hardcoded gadget model lists suggest the application might act in a different way depending upon the spotted hardware.
• Multiple vendor-specific services are utilized to draw out extra device details. E.g. if it can not figure out the gadget through basic Android SIM lookup (due to the fact that consent was not granted), it attempts producer particular extensions to access the exact same details.
  
  Potential Malware-Like Behavior
  
  While no definitive conclusions can be drawn without dynamic analysis, several observed habits align with recognized spyware and malware patterns:
  
  - The app utilizes reflection and 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 users.atw.hu unidentified purposes.
• The app implements country-based gain access to constraints and "risk-device" detection, suggesting possible monitoring systems.
• The app carries out calls to fill Dex modules, parentingliteracy.com 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 load additional.so files. This facility is not typically inspected by Google Play Protect and other static analysis services.
• The.so files can be executed in native code, such as C++. The use of 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 quickly intensify advantages, possibly exploiting vulnerabilities within the os or device hardware.
  
  Remarks
  
  While information collection prevails in modern-day applications for debugging and improving user experience, aggressive fingerprinting raises substantial personal privacy concerns. The DeepSeek app needs users to visit with a valid email, which ought to currently supply adequate authentication. There is no valid reason for the app to aggressively collect and send unique device identifiers, IMEI numbers, SIM card details, and other non-resettable system residential or commercial properties.
  
  The degree of tracking observed here exceeds normal analytics practices, potentially allowing persistent user tracking and re-identification throughout gadgets. These behaviors, combined with obfuscation techniques and network interaction with third-party tracking services, warrant a greater level of analysis from security researchers and users alike.
  
  The employment of runtime code packing as well as the bundling of native code suggests that the app might permit the release and execution of unreviewed, remotely delivered code. This is a major possible attack vector. No proof in this report is presented that remotely released code execution is being done, only that the facility for this appears present.
  
  Additionally, the app's technique to detecting rooted devices appears excessive for an AI chatbot. Root detection is typically warranted in DRM-protected streaming services, where security and material protection are crucial, or in competitive computer game to avoid unfaithful. However, setiathome.berkeley.edu there is no clear reasoning for such stringent measures in an application of this nature, raising more concerns about its intent.
  
  Users and organizations thinking about setting up DeepSeek needs to know these . If this application is being utilized within a business or government environment, additional vetting and security controls need to be enforced before allowing its release on handled devices.
  
  Disclaimer: The analysis presented in this report is based on fixed code evaluation and does not suggest that all spotted functions are actively utilized. Further examination is needed for definitive conclusions.