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Static Analysis of The DeepSeek Android App
Adela Elmer edited this page 4 months ago
I performed a static analysis of DeepSeek, a Chinese LLM chatbot, utilizing variation 1.8.0 from the Google Play Store. The goal was to identify potential security and personal privacy concerns.
I have actually written about DeepSeek previously 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 simply on static analysis. This implies that while the code exists within the app, there is no definitive evidence that all of it is performed in practice. Nonetheless, the presence of such code warrants scrutiny, especially offered the growing concerns around data personal privacy, surveillance, the potential abuse of AI-driven applications, and cyber-espionage characteristics in between worldwide powers.
Key Findings
Suspicious Data Handling & Exfiltration
- Hardcoded URLs direct data to external servers, raising concerns about user activity tracking, such as to ByteDance "volce.com" endpoints. NowSecure determines these in the iPhone app yesterday also.
- Bespoke file encryption and data obfuscation methods are present, with indicators that they could be 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 manipulation is present, which could enable the app to gain access to personal external internet browser data when links are opened. More details about WebView controls is here
Device Fingerprinting & Tracking
A significant portion of the analyzed code appears to concentrate on event device-specific details, which can be utilized for tracking and fingerprinting.
- The app collects different unique gadget identifiers, including UDID, Android ID, IMEI, IMSI, and provider details. - System properties, set up packages, and root detection systems recommend possible anti-tampering measures. E.g. probes for the presence of Magisk, a tool that personal privacy advocates and security researchers utilize to root their Android devices.
- Geolocation and network profiling are present, showing prospective tracking abilities and wiki.snooze-hotelsoftware.de making it possible for or disabling of fingerprinting regimes by region. - Hardcoded gadget design lists recommend the application may behave differently depending on the identified hardware.
- Multiple vendor-specific services are used to extract extra device details. E.g. if it can not figure out the device through basic Android SIM lookup (because approval was not approved), it attempts maker particular extensions to access the exact same details.
Potential Malware-Like Behavior
While no conclusive conclusions can be drawn without vibrant analysis, honkaistarrail.wiki a number of observed habits align with recognized spyware and malware patterns:
- The app uses reflection and UI overlays, shiapedia.1god.org which could assist in unapproved screen capture or phishing attacks. - SIM card details, serial numbers, and other device-specific information are aggregated for unknown purposes.
- The app executes country-based gain access to constraints and "risk-device" detection, suggesting possible monitoring mechanisms.
- The app carries out calls to load Dex modules, where extra code is loaded from files with a.so extension at runtime.
- The.so submits themselves reverse and make extra calls to dlopen(), which can be utilized to fill additional.so files. This facility is not generally inspected by Google Play Protect and other fixed analysis services.
- The.so files can be implemented in native code, such as C++. The use of native code includes a layer of complexity to the analysis process and obscures the complete degree of the app's capabilities. Moreover, native code can be leveraged to more quickly intensify opportunities, championsleage.review potentially making use of vulnerabilities within the operating system or device hardware.
Remarks
While data collection prevails in contemporary applications for debugging and improving user experience, aggressive fingerprinting raises substantial personal privacy concerns. The DeepSeek app requires users to log in with a valid email, which ought to currently supply sufficient authentication. There is no valid reason for the app to aggressively collect and transfer distinct gadget identifiers, IMEI numbers, SIM card details, and other non-resettable system residential or commercial properties.
The extent of tracking observed here surpasses normal analytics practices, potentially making it possible for consistent user tracking and re-identification across devices. These behaviors, combined with obfuscation methods and network communication with third-party tracking services, require a higher level of scrutiny from security scientists and users alike.
The employment of runtime code loading as well as the bundling of native code suggests that the app could permit the implementation and execution of unreviewed, from another location delivered code. This is a severe prospective attack vector. No evidence in this report is presented that from another location released code execution is being done, only that the center for this appears present.
Additionally, the app's technique to spotting rooted devices appears excessive for an AI chatbot. Root detection is frequently warranted in DRM-protected streaming services, where security and material protection are vital, or in competitive video games to prevent unfaithful. However, there is no clear reasoning for such rigorous measures in an application of this nature, raising additional concerns about its intent.
Users and companies considering setting up DeepSeek must know these potential risks. If this application is being utilized within a business or government environment, additional vetting and security controls need to be implemented before enabling its implementation on handled devices.
Disclaimer: The analysis presented in this report is based upon fixed code evaluation and does not imply that all identified functions are actively utilized. Further examination is required for conclusive conclusions.