I carried out a fixed analysis of DeepSeek, a Chinese LLM chatbot, using version 1.8.0 from the Google Play Store. The objective was to determine potential security and personal privacy problems.

I have actually discussed DeepSeek formerly here.

Additional security and personal privacy issues about DeepSeek have actually 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 means that while the code exists within the app, there is no conclusive proof that all of it is carried out in practice. Nonetheless, the presence of such code warrants examination, especially offered the growing concerns around information personal privacy, security, the possible abuse of AI-driven applications, and cyber-espionage characteristics in between international powers.

Key Findings

Suspicious Data Handling & Exfiltration

- Hardcoded URLs direct information to external servers, raising concerns about user activity monitoring, such as to ByteDance "volce.com" endpoints. NowSecure determines these in the iPhone app the other day as well. - Bespoke file encryption and information obfuscation techniques are present, with indicators that they might be utilized to exfiltrate user details.

• The app contains hard-coded public secrets, rather than relying on the user device's chain of trust.
• UI interaction tracking captures detailed user habits without clear authorization. - WebView control exists, which might enable the app to gain access to personal external browser information when links are opened. More details about WebView manipulations is here
  
  Device Fingerprinting & Tracking
  
  A substantial portion of the analyzed code appears to focus on gathering device-specific details, which can be used for tracking and fingerprinting.
  
  - The app gathers numerous distinct device identifiers, including UDID, Android ID, IMEI, IMSI, and carrier details.
• System residential or commercial properties, set up bundles, and root detection systems suggest prospective anti-tampering procedures. E.g. probes for dokuwiki.stream 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 enabling or disabling of fingerprinting regimes by region. - Hardcoded gadget design lists suggest the application might behave in a different way depending on the spotted hardware.
• Multiple vendor-specific services are utilized to draw out extra gadget details. E.g. if it can not figure out the device through standard Android SIM lookup (since authorization was not approved), it attempts maker specific extensions to access the very same details.
  
  Potential Malware-Like Behavior
  
  While no conclusive can be drawn without dynamic analysis, several observed habits line up with recognized spyware and malware patterns:
  
  - The app utilizes reflection and UI overlays, which might assist in unapproved screen capture or phishing attacks.
• SIM card details, serial numbers, and other device-specific data are aggregated for unidentified functions.
• The app executes country-based gain access to constraints and "risk-device" detection, recommending possible security mechanisms.
• The app executes calls to fill Dex modules, where extra code is filled from files with a.so extension at runtime.
• The.so files themselves turn around and make extra calls to dlopen(), akropolistravel.com which can be utilized to pack additional.so files. This center is not typically examined by Google Play Protect and other fixed analysis services.
• The.so files can be carried out in native code, such as C++. Making use of native code adds a layer of intricacy to the analysis process and obscures the complete level of the app's capabilities. Moreover, native code can be leveraged to more quickly escalate benefits, potentially exploiting vulnerabilities within the os or gadget hardware.
  
  Remarks
  
  While data collection prevails in modern-day applications for debugging and improving user experience, aggressive fingerprinting raises considerable privacy concerns. The DeepSeek app requires users to visit with a legitimate email, which need to currently offer enough authentication. There is no legitimate factor for the app to strongly collect and transmit special device identifiers, IMEI numbers, SIM card details, and other non-resettable system homes.
  
  The extent of tracking observed here exceeds typical analytics practices, possibly enabling relentless user tracking and re-identification throughout devices. These behaviors, combined with obfuscation methods and network interaction with third-party tracking services, koha-community.cz call for bphomesteading.com a greater level of examination from security researchers and users alike.
  
  The work of runtime code filling as well as the bundling of native code suggests that the app could enable the implementation and execution of unreviewed, remotely provided code. This is a serious prospective attack vector. No proof in this report exists that from another location deployed code execution is being done, just that the facility for this appears present.
  
  Additionally, the app's method to detecting rooted devices appears extreme for an AI chatbot. Root detection is typically warranted in DRM-protected streaming services, where security and material protection are important, akropolistravel.com or in competitive computer game to prevent unfaithful. However, there is no clear reasoning for such strict procedures in an application of this nature, raising further questions about its intent.
  
  Users and companies thinking about setting up DeepSeek needs to know these possible risks. If this application is being used within an enterprise or federal government environment, extra vetting and security controls must be imposed before enabling its deployment on handled gadgets.
  
  Disclaimer: The analysis provided in this report is based upon fixed code review and does not imply that all found functions are actively utilized. Further examination is required for definitive conclusions.