Static Analysis of The DeepSeek Android App

I conducted a static analysis of DeepSeek, a Chinese LLM chatbot, using variation 1.8.0 from the Google Play Store. The objective was to determine possible security and personal privacy problems.

I have actually blogged about DeepSeek formerly here.

Additional security and personal privacy issues about DeepSeek have 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 implies that while the code exists within the app, there is no definitive evidence that all of it is carried out in practice. Nonetheless, online-learning-initiative.org the presence of such code warrants analysis, specifically given the growing concerns around data privacy, surveillance, the prospective misuse 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 issues about user activity monitoring, such as to ByteDance „volce.com“ endpoints. NowSecure determines these in the iPhone app the other day as well.
– Bespoke encryption and information obfuscation techniques are present, with indicators that they could be used to exfiltrate user details.
– The app contains hard-coded public secrets, instead of depending on the user device’s chain of trust.
– UI interaction tracking catches detailed user habits without clear permission.
– WebView control is present, which could enable the app to gain access to private external browser information when links are opened. More details about WebView adjustments is here

Device Fingerprinting & Tracking

A significant part of the analyzed code appears to focus on gathering device-specific details, which can be utilized for tracking and fingerprinting.

– The app collects various distinct gadget identifiers, including UDID, Android ID, oke.zone IMEI, IMSI, and carrier details.
– System residential or commercial properties, set up plans, and oke.zone root detection systems recommend prospective anti-tampering procedures. E.g. probes for higgledy-piggledy.xyz the presence of Magisk, a tool that personal privacy supporters and security scientists utilize to root their Android gadgets.
– Geolocation and network profiling are present, showing possible tracking abilities and making it possible for or disabling of fingerprinting regimes by area.
– Hardcoded device design lists recommend the application may act differently depending upon the discovered hardware.
– Multiple vendor-specific services are utilized to extract additional gadget details. E.g. if it can not determine the device through standard Android SIM lookup (due to the fact that approval was not approved), it tries manufacturer particular extensions to access the same details.

Potential Malware-Like Behavior

While no conclusive conclusions can be drawn without vibrant analysis, a number of observed behaviors line up with recognized spyware and malware patterns:

– The app uses reflection and UI overlays, which might facilitate unauthorized screen capture or phishing attacks.
– SIM card details, serial numbers, and classicrock.awardspace.biz other device-specific information are aggregated for unidentified 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 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 used to fill additional.so files. This facility is not generally examined by Google Play Protect and other fixed analysis services.
– The.so files can be implemented in native code, such as C++. Making use of native code includes a layer of intricacy to the analysis procedure and obscures the full degree of the app’s abilities. Moreover, native code can be leveraged to more quickly intensify benefits, possibly making use of vulnerabilities within the operating system or device hardware.

Remarks

While data collection prevails in contemporary applications for debugging and enhancing user experience, lespoetesbizarres.free.fr aggressive fingerprinting raises significant privacy concerns. The DeepSeek app needs users to log in with a valid email, which should already authentication. There is no legitimate reason for the app to aggressively collect and transmit unique device identifiers, IMEI numbers, SIM card details, and other non-resettable system homes.

The level of tracking observed here surpasses normal analytics practices, potentially allowing persistent user tracking and re-identification across gadgets. These habits, integrated with obfuscation methods and network communication with third-party tracking services, necessitate a greater level of analysis from security researchers and users alike.

The employment of runtime code loading in addition to the bundling of native code suggests that the app might permit the implementation and execution of unreviewed, from another location provided code. This is a major potential attack vector. No evidence in this report is presented that remotely released code execution is being done, only that the facility for this appears present.

Additionally, the app’s approach to spotting rooted gadgets appears extreme for an AI chatbot. Root detection is typically warranted in DRM-protected streaming services, where security and material protection are crucial, or in competitive video games to avoid unfaithful. However, there is no clear reasoning for such rigorous measures in an application of this nature, raising additional questions about its intent.

Users and organizations thinking about installing DeepSeek should understand these prospective risks. If this application is being used within an enterprise or government environment, additional vetting and security controls ought to be imposed before enabling its release on handled devices.

Disclaimer: The analysis presented in this report is based on fixed code review and does not indicate that all identified functions are actively used. Further examination is needed for conclusive conclusions.