Static Analysis Of The DeepSeek Android App

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I conducted a fixed analysis of DeepSeek, a Chinese LLM chatbot, utilizing variation 1.8.0 from the Google Play Store. The goal was to recognize potential security and privacy issues.


I have actually blogged about DeepSeek formerly here.


Additional security and 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 indicates that while the code exists within the app, there is no definitive proof that all of it is performed in practice. Nonetheless, the existence of such code warrants scrutiny, especially offered the growing concerns around data personal privacy, photorum.eclat-mauve.fr monitoring, users.atw.hu the prospective abuse of AI-driven applications, and cyber-espionage dynamics in between global powers.


Key Findings


Suspicious Data Handling & Exfiltration


- Hardcoded URLs direct information to external servers, raising concerns about user activity tracking, such as to ByteDance "volce.com" endpoints. NowSecure determines these in the iPhone app yesterday too.
- Bespoke encryption and information obfuscation methods are present, ai-db.science with indications that they could 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 captures detailed user behavior without clear permission.
- WebView manipulation exists, which might permit for classihub.in the app to gain access to personal external web browser data when links are opened. More details about WebView manipulations is here


Device Fingerprinting & Tracking


A substantial portion of the evaluated code appears to concentrate on gathering device-specific details, which can be utilized for tracking and fingerprinting.


- The app gathers different unique gadget identifiers, including UDID, Android ID, IMEI, IMSI, and provider details.
- System homes, installed bundles, and root detection mechanisms suggest potential anti-tampering steps. E.g. probes for the existence of Magisk, a tool that privacy advocates and security researchers use to root their Android gadgets.
- Geolocation and network profiling exist, showing potential tracking abilities and making it possible for wiki-tb-service.com or disabling of fingerprinting routines by area.
- Hardcoded gadget design lists suggest the application may act differently depending upon the detected hardware.
- Multiple vendor-specific services are utilized to extract extra device details. E.g. if it can not figure out the gadget through basic Android SIM lookup (because permission was not given), it specific extensions to access the same details.


Potential Malware-Like Behavior


While no definitive conclusions can be drawn without dynamic analysis, numerous observed habits line up with recognized spyware and malware patterns:


- The app uses reflection and UI overlays, which might help with unauthorized screen capture or phishing attacks.
- SIM card details, identification numbers, and other device-specific data are aggregated for unidentified purposes.
- The app carries out country-based gain access to constraints and "risk-device" detection, recommending possible security mechanisms.
- The app executes calls to pack Dex modules, where additional code is filled from files with a.so extension at runtime.
- The.so files themselves turn around and make additional calls to dlopen(), which can be utilized to pack additional.so files. This center is not typically examined by Google Play Protect and other static 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 procedure and obscures the complete extent of the app's capabilities. Moreover, native code can be leveraged to more easily escalate benefits, potentially making use of vulnerabilities within the operating system or device hardware.


Remarks


While information collection prevails in contemporary applications for debugging and improving user experience, aggressive fingerprinting raises substantial personal privacy issues. The DeepSeek app needs users to visit with a legitimate email, which need to already supply adequate authentication. There is no valid factor for the app to strongly collect and transfer unique gadget identifiers, IMEI numbers, SIM card details, and other non-resettable system properties.


The degree of tracking observed here surpasses normal analytics practices, possibly allowing persistent user tracking and re-identification throughout gadgets. These behaviors, integrated with obfuscation strategies and network interaction with third-party tracking services, necessitate a greater level of scrutiny from security researchers and wiki.snooze-hotelsoftware.de users alike.


The work of runtime code filling in addition to the bundling of native code suggests that the app could enable the implementation and execution of unreviewed, remotely delivered code. This is a major prospective 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 often warranted in DRM-protected streaming services, where security and content protection are crucial, or in competitive video games to avoid unfaithful. However, there is no clear reasoning for such rigorous procedures in an application of this nature, raising additional concerns about its intent.


Users and companies thinking about installing DeepSeek must understand these possible risks. If this application is being utilized within a business or federal government environment, extra vetting and security controls need to be implemented before allowing its implementation on handled devices.


Disclaimer: The analysis provided in this report is based upon fixed code review and does not indicate that all discovered functions are actively utilized. Further investigation is required for definitive conclusions.

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