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A 2025 study found that several popular VPN apps were connected through shared providers, code, infrastructure or tunneling protocols—and reported serious weaknesses in some of the versions it tested. Its strongest warning concerns hard-coded Shadowsocks passwords that could let a network eavesdropper decrypt affected traffic. The findings apply to the apps and versions examined for the study, not necessarily to current releases.

What the 2025 VPN study found

In “Hidden Links: Analyzing Secret Families of VPN Apps,” Benjamin Mixon-Baca, Jeffrey Knockel and Jedidiah R. Crandall examined relationships among VPN apps and their providers, then analyzed security issues in selected apps. The paper appeared in Free and Open Communications on the Internet 2025(2), pages 18–27. SecurityWeek published a news summary on August 19, 2025.

The researchers reported three distinct kinds of concern: collection of location-related data not disclosed in privacy policies; attacks that could infer or interfere with active VPN connections; and exposure of traffic in affected Shadowsocks configurations. These findings describe different risks. They do not establish that every VPN app—or every app in an app store—is unsafe.

How the researchers selected and examined apps

The authors started with 100 of the most-downloaded VPN apps in Sensor Tower and AppMagic datasets. They narrowed that pool to 50 providers based outside the United States, then identified 13 providers that appeared potentially related for closer security analysis. The paper’s study table lists 21 analyzed apps.

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The investigation drew on provider and app-store information, websites, business filings, APK static and dynamic analysis, packet captures, code similarities and network observations. Testing used a rooted Google Pixel 7a and the apps available to the researchers at the time. The authors caution that similar code or privacy-policy language can be ambiguous; shared infrastructure and cryptographic credentials offered stronger evidence of links in their analysis.

Which VPN app groups were linked?

The paper describes three provider families and a separate group of apps for which the researchers found no apparent links. The table summarizes the evidence and the limits of what the study established.

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Study group Providers and apps identified Reported evidence or security findings Coverage and limits
Family A Innovative Connecting, Autumn Breeze and Lemon Clove; eight apps: Turbo VPN, Turbo VPN Lite, VPN Monster, VPN Proxy Master, VPN Proxy Master – Lite, Snap VPN, Robot VPN and SuperNet VPN Substantial code and asset overlap, shared infrastructure, and hard-coded Shadowsocks passwords. The researchers also observed collection of a ZIP code derived from a user’s public IP address. The tested apps used a shared Shadowsocks credential that, under the study’s conditions, could let a network eavesdropper decrypt affected traffic.
Family B MATRIX MOBILE PTE LTD, ForeRaya Technology Limited, WILDLOOK TECH PTE LTD, Hong Kong Silence Technology Limited and Yolo Mobile Technology Limited Protocol and code patterns, obfuscation and server infrastructure linked the providers. The researchers reported connection-inference susceptibility and hard-coded or obfuscated Shadowsocks passwords. The paper identifies the five providers but the findings summarized here do not state an app count for this family.
Family C Fast Potato Pte. Ltd and Free Connected Limited, distributing Fast Potato VPN and X-VPN respectively Shared proprietary tunneling implementation and other code signatures; the researchers reported connection-inference susceptibility. The analysis was partial and did not include cryptographic analysis.
Other Apps from VPN Super Inc., Miczon LLC and Secure Signal Inc. The researchers found “no apparent links” among these apps and the identified families. This means no links were found in this study; it does not prove independent ownership or comprehensive security.

What the Shadowsocks password finding means

Shadowsocks is a proxy protocol designed for censorship circumvention, not a guarantee of privacy. For affected apps that used the tested hard-coded credentials, the authors found that someone able to observe network traffic and obtain the shared credentials could decrypt traffic carried through Shadowsocks under the conditions they tested. That is a specific risk tied to the implementation and configuration they analyzed; it is not evidence that every VPN protocol or every app using a VPN label has the same weakness.

The authors’ recommendation is direct: “At a minimum, VPN users who value privacy should avoid using Shadowsocks, including the apps from these developers, as Shadowsocks was not designed to facilitate privacy, merely censorship circumvention.” That advice is the paper’s conclusion about privacy expectations and the studied apps, not a current audit of every release.

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Connection inference and interference are different risks

For Families B and C, the researchers report susceptibility to connection inference. In broad terms, this kind of weakness can allow an observer to infer whether a VPN connection is active or interfere with it. It is distinct from decrypting tunneled traffic: the study’s connection-inference finding should not be read as proof that an attacker could read all data passing through those apps.

What the location-related data finding says

For Family A, researchers observed apps requesting a ZIP code derived from a user’s public IP address from ip-api.com, then uploading it to a Firebase endpoint. They report that this happened even when the app did not request location permission, while the apps’ privacy policies said addresses were not collected. This is the researchers’ observation of the tested apps and methods; it does not establish behavior in later app versions.

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How large was the app group—and what do the download figures mean?

The authors’ study table shows aggregate Google Play download bands of more than 972 million across the 21 listed apps. Separately, the paper’s abstract gives more than 700 million combined Google Play downloads for the three identified provider families. These are research-era store download counts, not a measure of current active users. The initial counts—100 apps, 50 non-US providers and 13 potentially related providers—describe how the sample was selected; they are not estimates of how common these issues are across the VPN market.

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What the study does not establish

  • Current app status: The paper analyzed apps available to the researchers at the time. It does not establish whether each named app is still available, whether later versions fixed a weakness, or what any current build does.
  • Every ownership relationship: The authors say they did not confirm all relationships reported by previous researchers. For example, they confirmed shared infrastructure for the three Family A providers they analyzed, rather than establishing every proposed connection.
  • Why providers used multiple identities: The paper discusses possible cost or management explanations, but does not demonstrate the operators’ motive.
  • A safe alternative: This was not a current comparative audit of VPN services. Its “Other” group is not a security endorsement, and the study does not identify a tested replacement.

What VPN users can take from the findings

A VPN listing or privacy claim alone does not verify who operates an app or how securely it implements a tunnel. The study’s evidence came from combining ownership clues with technical analysis, and its most severe reported issue was tied to hard-coded Shadowsocks credentials in affected configurations. Connection inference and undisclosed location-related data collection are separate concerns with different consequences.

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For users who value privacy, the authors’ specific advice is to avoid Shadowsocks, including in the apps from the developers they studied. Anyone evaluating a particular VPN should distinguish this 2025 analysis from a current, version-specific security assessment: the paper does not verify present-day listings, updates or fixes.

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