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I conducted a static analysis of DeepSeek, a Chinese LLM chatbot, utilizing version 1.8.0 from the Google Play Store. The objective was to identify potential security and privacy concerns.

I've discussed DeepSeek formerly here.

Additional security and personal privacy issues about DeepSeek have been raised.

See likewise this analysis by NowSecure of the iPhone variation of DeepSeek

The findings detailed in this report are based simply on fixed analysis. This means 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 examination, particularly given the growing issues around information personal privacy, security, the possible abuse 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 concerns about user activity tracking, such as to ByteDance "volce.com" endpoints. NowSecure determines these in the iPhone app yesterday as well.

Bespoke encryption and data obfuscation methods exist, with signs that they might be utilized to exfiltrate user details.
The app contains hard-coded public secrets, rather than relying on the user gadget's chain of trust.
UI interaction tracking catches detailed user behavior without clear permission. - WebView manipulation is present, which might enable for the app to gain access to private external browser data when links are opened. More details about WebView manipulations is here

Device Fingerprinting & Tracking

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

- The app gathers different special device identifiers, consisting of UDID, Android ID, IMEI, IMSI, and provider details.
System properties, installed bundles, garagesale.es and root detection mechanisms recommend possible anti-tampering measures. E.g. probes for the presence of Magisk, a tool that privacy supporters and security researchers utilize to root their Android devices. - Geolocation and network profiling are present, suggesting prospective tracking abilities and making it possible for or disabling of fingerprinting programs by area.
Hardcoded gadget model lists recommend the application might act in a different way depending upon the identified hardware. - Multiple vendor-specific services are utilized to draw out additional device details. E.g. if it can not identify the device through standard Android SIM lookup (due to the fact that consent was not given), it tries manufacturer specific extensions to access the very same .

Potential Malware-Like Behavior

While no definitive conclusions can be drawn without vibrant analysis, several observed behaviors align with recognized spyware and malware patterns:

- The app uses reflection and UI overlays, which could facilitate unapproved screen capture or phishing attacks.
SIM card details, identification numbers, and other device-specific data are aggregated for unidentified functions.
The app implements country-based gain access to constraints and "risk-device" detection, recommending possible monitoring mechanisms.
The app implements calls to load Dex modules, where additional 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 used to fill additional.so files. This center is not typically 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 complexity to the analysis process and obscures the complete degree of the app's abilities. Moreover, native code can be leveraged to more easily intensify 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 significant personal privacy issues. The DeepSeek app requires users to visit with a legitimate email, which ought to already supply sufficient authentication. There is no valid factor for the app to aggressively gather and transmit special gadget identifiers, IMEI numbers, SIM card details, and iuridictum.pecina.cz other non-resettable system homes.

The level of tracking observed here exceeds common analytics practices, potentially allowing persistent user tracking and re-identification across gadgets. These behaviors, integrated with obfuscation methods and network interaction with third-party tracking services, require a greater level of analysis from security researchers and users alike.

The employment of runtime code loading as well as the bundling of native code recommends that the app might allow the release and execution of unreviewed, remotely delivered code. This is a severe possible attack vector. No evidence in this report is presented that from another location deployed code execution is being done, just that the facility for this appears present.

Additionally, the app's technique to spotting rooted devices appears excessive for an AI chatbot. Root detection is typically warranted in DRM-protected streaming services, where security and material defense are critical, or in competitive computer game to prevent unfaithful. However, there is no clear rationale for such stringent steps in an application of this nature, raising further questions about its intent.

Users and companies considering installing DeepSeek should understand these prospective threats. If this application is being used within an enterprise or federal government environment, wiki.vst.hs-furtwangen.de extra vetting and security controls should be implemented before permitting its implementation on managed gadgets.

Disclaimer: The analysis provided in this report is based upon static code review and does not indicate that all spotted functions are actively utilized. Further investigation is needed for conclusive conclusions.