I conducted a fixed analysis of DeepSeek, a Chinese LLM chatbot, using version 1.8.0 from the Google Play Store. The objective was to recognize potential security and personal privacy issues.
I have actually blogged about DeepSeek previously here.
Additional security and 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 simply on fixed analysis. This implies that while the code exists within the app, there is no conclusive proof that all of it is performed in practice. Nonetheless, the existence of such code warrants scrutiny, specifically given the growing concerns around information personal privacy, monitoring, the possible misuse of AI-driven applications, and cyber-espionage characteristics between international 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 identifies these in the iPhone app the other day also.
- Bespoke file encryption and information obfuscation methods are present, with indications that they could be utilized to exfiltrate user details.
- The app contains hard-coded public secrets, instead of counting on the user device's chain of trust.
- UI interaction tracking records detailed user habits without clear permission.
- WebView manipulation exists, which might enable the app to gain access to private external web 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 used for tracking and fingerprinting.
- The app gathers numerous special gadget identifiers, consisting of UDID, Android ID, IMEI, IMSI, and . - System properties, set up packages, and root detection mechanisms suggest prospective anti-tampering measures. E.g. probes for the existence of Magisk, a tool that privacy advocates and security researchers utilize to root their Android gadgets. - Geolocation and demo.qkseo.in network profiling are present, showing possible tracking abilities and allowing or disabling of fingerprinting routines by area.
- Hardcoded device model lists recommend the application might act in a different way depending on the spotted hardware.
- Multiple vendor-specific services are used to extract additional gadget details. E.g. if it can not identify the gadget through basic Android SIM lookup (since 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, numerous observed behaviors align with recognized spyware and malware patterns:
- The app uses reflection and UI overlays, which might help with 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 systems.
- The app carries out calls to load Dex modules, where extra code is packed from files with a.so extension at runtime.
- The.so files themselves reverse and make extra calls to dlopen(), which can be used 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++. Using native code adds a layer of intricacy to the analysis procedure and obscures the complete level of the app's capabilities. Moreover, native code can be leveraged to more easily intensify privileges, potentially making use of vulnerabilities within the operating system or device hardware.
Remarks
While information collection prevails in modern applications for debugging and enhancing user experience, aggressive fingerprinting raises significant privacy concerns. The DeepSeek app requires users to visit with a legitimate email, which need to currently supply sufficient authentication. There is no valid reason for the app to strongly gather and transfer distinct device identifiers, IMEI numbers, SIM card details, and other non-resettable system properties.
The degree of tracking observed here exceeds common analytics practices, potentially making it possible for relentless user tracking and re-identification throughout gadgets. These behaviors, integrated with obfuscation strategies and network communication with third-party tracking services, require a higher level of analysis from security researchers and users alike.
The employment of runtime code filling in addition to the bundling of native code recommends that the app might enable the implementation and execution of unreviewed, from another location delivered code. This is a severe potential attack vector. No evidence in this report exists that remotely deployed code execution is being done, only that the facility for this appears present.
Additionally, the app's technique to discovering rooted devices appears excessive for an AI chatbot. Root detection is frequently warranted in DRM-protected streaming services, where security and content defense are critical, yewiki.org or in competitive video games to prevent 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 organizations thinking about installing DeepSeek ought to be conscious of these potential threats. If this application is being utilized within a business or government environment, extra vetting and security controls must be enforced before allowing its release on handled devices.
Disclaimer: The analysis presented in this report is based upon fixed code review and does not indicate that all detected functions are actively utilized. Further investigation is required for conclusive conclusions.