I carried out a static analysis of DeepSeek, a Chinese LLM chatbot, using version 1.8.0 from the Google Play Store. The objective was to determine possible security and personal privacy issues.
I have actually blogged about DeepSeek previously here.
Additional security and kenpoguy.com privacy issues about DeepSeek have been raised.
See also this analysis by NowSecure of the iPhone version of DeepSeek
The findings detailed in this report are based purely on fixed analysis. This means that while the code exists within the app, genbecle.com there is no definitive evidence that all of it is in practice. Nonetheless, fakenews.win the existence of such code warrants analysis, especially given the growing concerns around information privacy, surveillance, the potential misuse of AI-driven applications, and cyber-espionage dynamics between international 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 identifies these in the iPhone app yesterday as well.
- Bespoke file encryption and information obfuscation methods are present, with indications that they might be used to exfiltrate user details.
- The app contains hard-coded public secrets, instead of relying on the user gadget's chain of trust.
- UI interaction tracking catches detailed user habits without clear permission.
- WebView adjustment exists, which could enable the app to gain access to private external web browser information when links are opened. More details about WebView controls is here
Device Fingerprinting & Tracking
A substantial part of the evaluated code appears to concentrate on event device-specific details, which can be used for tracking and fingerprinting.
- The app gathers various special device identifiers, including UDID, Android ID, IMEI, IMSI, and provider details. - System homes, set up bundles, and root detection systems recommend potential anti-tampering measures. E.g. probes for the existence of Magisk, a tool that personal privacy advocates and security scientists utilize to root their Android devices. - Geolocation and network profiling are present, suggesting prospective tracking abilities and allowing or disabling of fingerprinting regimes by area. - Hardcoded device model lists recommend the application may act in a different way depending on the discovered hardware.
- Multiple vendor-specific services are utilized to extract additional device details. E.g. if it can not determine the device through standard Android SIM lookup (because consent was not given), it attempts producer specific extensions to access the exact same details.
Potential Malware-Like Behavior
While no conclusive conclusions can be drawn without dynamic analysis, numerous observed habits align with known spyware and malware patterns:
- The app utilizes reflection and UI overlays, which might assist in unauthorized screen capture or phishing attacks. - SIM card details, serial numbers, and other device-specific information are aggregated for unknown functions.
- The app implements country-based gain access to constraints and "risk-device" detection, recommending possible security systems.
- The app implements calls to load Dex modules, where extra code is loaded from files with a.so extension at runtime.
- The.so files themselves turn around and make extra calls to dlopen(), which can be utilized to pack additional.so files. This facility is not normally checked by Google Play Protect and other fixed analysis services.
- The.so files can be implemented in native code, such as C++. Using native code adds a layer of complexity to the analysis process and obscures the complete extent of the app's abilities. Moreover, native code can be leveraged to more quickly intensify benefits, possibly exploiting vulnerabilities within the operating system or device hardware.
Remarks
While data collection prevails in modern-day applications for debugging and improving user experience, aggressive fingerprinting raises significant privacy concerns. The DeepSeek app needs users to visit with a legitimate email, which must currently provide adequate authentication. There is no legitimate reason for the app to aggressively gather and funsilo.date send distinct gadget identifiers, IMEI numbers, SIM card details, and other non-resettable system homes.
The level of tracking observed here goes beyond normal analytics practices, potentially making it possible for surgiteams.com persistent user tracking and re-identification across devices. These behaviors, integrated with obfuscation techniques and network communication with third-party tracking services, call for a greater level of examination from security scientists and users alike.
The work of runtime code filling along with the bundling of native code recommends that the app might allow the implementation and execution of unreviewed, remotely delivered code. This is a major potential attack vector. No evidence in this report exists that remotely released code execution is being done, just 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 typically justified in DRM-protected streaming services, where security and content security are vital, or in competitive computer game to avoid unfaithful. However, there is no clear rationale for such strict measures in an application of this nature, raising additional questions about its intent.
Users and annunciogratis.net organizations considering setting up DeepSeek should know these possible dangers. If this application is being used within a business or federal government environment, additional vetting and security controls should be enforced before enabling its release on managed devices.
Disclaimer: The analysis provided in this report is based upon static code evaluation and does not imply that all detected functions are actively utilized. Further examination is required for conclusive conclusions.