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I carried out a static analysis of DeepSeek, a Chinese LLM chatbot, utilizing version 1.8.0 from the Google Play Store. The objective was to identify potential security and wiki.dulovic.tech personal privacy issues.

I have actually discussed DeepSeek formerly here.

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

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

The findings detailed in this report are based purely on static analysis. This suggests 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 analysis, especially offered the growing issues around data personal privacy, monitoring, the potential misuse of AI-driven applications, and cyber-espionage characteristics between worldwide 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 too.

• Bespoke encryption and data obfuscation methods are present, with signs 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 captures detailed user behavior without clear permission. - WebView adjustment is present, which could enable the app to gain access to personal external web browser data when links are opened. More details about WebView controls is here
  
  Device Fingerprinting & Tracking
  
  A substantial portion of the examined code appears to concentrate on gathering device-specific details, which can be utilized for tracking and fingerprinting.
  
  - The app gathers numerous distinct gadget identifiers, wiki.lafabriquedelalogistique.fr consisting of UDID, Android ID, IMEI, IMSI, and provider details.
• System homes, set up plans, and root detection mechanisms recommend possible anti-tampering steps. E.g. probes for the existence of Magisk, a tool that privacy advocates and security scientists utilize to root their Android gadgets.
• Geolocation and network profiling exist, suggesting prospective tracking abilities and allowing or disabling of fingerprinting programs by region. - Hardcoded gadget design lists recommend the application might behave differently depending on the identified hardware.
• Multiple vendor-specific services are used to extract extra gadget details. E.g. if it can not identify the device through standard Android SIM lookup (because permission was not granted), photorum.eclat-mauve.fr it tries producer specific extensions to access the exact same details.
  
  Potential Malware-Like Behavior
  
  While no conclusive conclusions can be drawn without dynamic analysis, several observed behaviors align with recognized spyware and malware patterns:
  
  - The app utilizes reflection and UI overlays, which could facilitate unapproved screen capture or phishing attacks.
• SIM card details, identification numbers, and other device-specific information are aggregated for unknown functions.
• The app implements country-based gain access to constraints and "risk-device" detection, recommending possible security mechanisms.
• The app carries out calls to pack Dex modules, where additional code is filled from files with a.so at runtime.
• The.so submits themselves turn around and make extra calls to dlopen(), which can be utilized to fill additional.so files. This facility is not usually examined by Google Play Protect and other fixed analysis services.
• The.so files can be carried out in native code, such as C++. The usage 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 easily escalate benefits, possibly exploiting vulnerabilities within the os or gadget hardware.
  
  Remarks
  
  While data collection prevails in modern applications for debugging and enhancing user experience, aggressive fingerprinting raises significant personal privacy concerns. The DeepSeek app needs users to log in with a valid email, which should currently offer sufficient authentication. There is no legitimate factor for iuridictum.pecina.cz the app to aggressively gather and transfer special device identifiers, IMEI numbers, SIM card details, and other non-resettable system properties.
  
  The extent of tracking observed here exceeds typical analytics practices, potentially allowing consistent user tracking and re-identification across gadgets. These habits, integrated with obfuscation strategies and network communication with third-party tracking services, call for a higher level of scrutiny from security scientists and users alike.
  
  The employment of runtime code packing along with the bundling of native code suggests that the app could allow the release and execution of unreviewed, from another location delivered code. This is a major potential attack vector. No proof in this report exists that remotely deployed code execution is being done, just that the facility for this appears present.
  
  Additionally, the app's technique to finding rooted gadgets appears extreme for an AI chatbot. Root detection is frequently warranted in DRM-protected streaming services, where security and trademarketclassifieds.com content security are important, or forum.pinoo.com.tr in competitive video games to avoid unfaithful. However, there is no clear rationale for such stringent steps in an application of this nature, raising further questions about its intent.
  
  Users and companies considering setting up DeepSeek should know these potential dangers. If this application is being used within an enterprise or government environment, additional vetting and security controls should be imposed before allowing its implementation on handled devices.
  
  Disclaimer: The analysis provided in this report is based upon fixed code review and does not imply that all detected functions are actively utilized. Further examination is required for conclusive conclusions.