Static Analysis Of The DeepSeek Android App

I carried out a static analysis of DeepSeek, a Chinese LLM chatbot, using version 1.8.0 from the Google Play Store. The goal was to identify prospective security and personal privacy issues.


I have actually blogged about DeepSeek previously here.


Additional security and privacy concerns 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 purely on fixed analysis. This indicates that while the code exists within the app, there is no conclusive evidence that all of it is performed in practice. Nonetheless, the presence of such code warrants analysis, specifically given the growing issues around information privacy, surveillance, the prospective abuse of AI-driven applications, and cyber-espionage characteristics in between international 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 recognizes these in the iPhone app the other day too.
- Bespoke encryption and data obfuscation methods are present, with indications that they might be utilized to exfiltrate user details.
- The app contains hard-coded public keys, rather than depending on the user device's chain of trust.
- UI interaction tracking records detailed user habits without clear approval.
- WebView adjustment exists, wiki.myamens.com which could allow for 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 substantial portion of the evaluated code appears to focus on gathering device-specific details, which can be utilized for tracking and fingerprinting.


- The app gathers various unique device identifiers, consisting of UDID, Android ID, IMEI, IMSI, and carrier details.
- System homes, securityholes.science set up plans, and root detection mechanisms suggest potential anti-tampering procedures. E.g. probes for kenpoguy.com the existence of Magisk, a tool that privacy supporters and security researchers utilize to root their Android gadgets.
- Geolocation and network profiling exist, indicating potential tracking capabilities and enabling or disabling of fingerprinting regimes by region.
- Hardcoded gadget model lists suggest the application may act in a different way depending on the discovered hardware.
- Multiple vendor-specific services are used to draw out extra gadget details. E.g. if it can not figure out the device through standard Android SIM lookup (due to the fact that permission was not given), it attempts manufacturer specific extensions to access the exact same details.


Potential Malware-Like Behavior


While no conclusive conclusions can be drawn without dynamic analysis, several observed habits align with recognized spyware and malware patterns:


- The app uses reflection and UI overlays, which could facilitate unauthorized screen capture or phishing attacks.
- SIM card details, identification numbers, and other device-specific data are aggregated for unidentified purposes.
- The app implements country-based gain access to constraints and "risk-device" detection, recommending possible monitoring mechanisms.
- The app implements calls to pack Dex modules, where extra code is loaded from files with a.so extension at runtime.
- The.so files themselves turn around and make extra calls to dlopen(), which can be utilized to fill additional.so files. This facility is not normally examined by Google Play Protect and other fixed analysis services.
- The.so files can be implemented in native code, ai-db.science such as C++. Using native code includes a layer of complexity to the analysis process and obscures the complete level of the app's abilities. Moreover, native code can be leveraged to more quickly escalate opportunities, possibly exploiting vulnerabilities within the operating system or device hardware.


Remarks


While information collection in modern applications for debugging and enhancing user experience, aggressive fingerprinting raises considerable privacy concerns. The DeepSeek app requires users to log in with a valid email, which must already supply enough authentication. There is no legitimate factor for the app to aggressively collect and transmit distinct gadget identifiers, IMEI numbers, SIM card details, and other non-resettable system residential or commercial properties.


The extent of tracking observed here exceeds typical analytics practices, potentially allowing relentless user tracking and re-identification throughout devices. These habits, combined with obfuscation strategies and network interaction with third-party tracking services, call for a higher level of analysis from security scientists and users alike.


The work of runtime code packing as well as the bundling of native code suggests that the app could enable the deployment and execution of unreviewed, from another location delivered code. This is a severe possible attack vector. No proof in this report is presented that from another location deployed code execution is being done, only that the center for this appears present.


Additionally, the app's method to identifying rooted devices appears extreme for an AI chatbot. Root detection is often justified in DRM-protected streaming services, where security and content protection are important, or in competitive video games to prevent unfaithful. However, there is no clear rationale for such rigorous procedures in an application of this nature, raising further questions about its intent.


Users and companies thinking about setting up DeepSeek ought to understand these potential risks. If this application is being used within a business or government environment, extra vetting and security controls must be imposed before permitting its release on handled devices.


Disclaimer: niaskywalk.com The analysis presented in this report is based upon static code evaluation and does not suggest that all identified functions are actively utilized. Further investigation is required for definitive conclusions.