---
type: Whitepaper
title: Exposing the Lack of Privacy in File Hosting Services (Paper)
description: Examines download URLs as bearer credentials across file-hosting services. Identifier density, metadata oracles and shared token prefixes undermine privacy despite download delays or CAPTCHAs. Decoy files measure access and credential use; search non-indexing only approximates privacy, and not every access proves identifier guessing.
resource: "https://www.usenix.org/legacy/event/leet11/tech/full_papers/Nikiforakis.pdf"
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    resource: "https://www.usenix.org/legacy/event/leet11/tech/full_papers/Nikiforakis.pdf"
    title: Exposing the Lack of Privacy in File Hosting Services (Paper)
    author: Nick Nikiforakis, Marco Balduzzi, Steven Van Acker, Wouter Joosen, Davide Balzarotti
    last_modified: 2011-03-29
also_at: []
authors:
  - Nick Nikiforakis
  - Marco Balduzzi
  - Steven Van Acker
  - Wouter Joosen
  - Davide Balzarotti
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original_url: "https://www.usenix.org/legacy/event/leet11/tech/full_papers/Nikiforakis.pdf"
published: 2011-03-29
publisher: USENIX
publisher_english: ""
raw_sha256: 4831d4608aceb6fec5e4494ccdbd86a4311e16aba1a34a38867d27b7fe522739
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slug: usenix-exposing-lack-privacy-file-hosting-services-paper
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---

# Exposing the Lack of Privacy in File Hosting Services (Paper)

**Exposing the Lack of Privacy in File Hosting Services (Paper)** - Nick Nikiforakis, Marco Balduzzi, Steven Van Acker, Wouter Joosen, Davide Balzarotti, USENIX.

- Published: 2011-03-29
- Original: <https://www.usenix.org/legacy/event/leet11/tech/full_papers/Nikiforakis.pdf>
- Preserved from: https://www.usenix.org/legacy/event/leet11/tech/full_papers/Nikiforakis.pdf (manual-import) on 2026-09-29
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## Content

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Exposing the Lack of Privacy in File Hosting Services

Nick Nikiforakis1 , Marco Balduzzi2 , Steven Van Acker1 , Wouter Joosen1 , and Davide Balzarotti2
                             1
                                 DistriNet, Katholieke Universiteit Leuven, Belgium
                                   2
                                     Institute Eurecom, Sophia Antipolis, France



                        Abstract                                       One of the first services designed to fill this gap was
                                                                    offered by RapidShare1 , a company founded in 2006.
   File hosting services (FHSs) are used daily by thou-
                                                                    RapidShare provides users the ability to upload large
sands of people as a way of storing and sharing files.
                                                                    files to their servers and then share the links to those files
These services normally rely on a security-through-
                                                                    with other users. RapidShare’s success spawned hun-
obscurity approach to enforce access control: For each
                                                                    dreds of file hosting services that compete against each
uploaded file, the user is given a secret URI that she can
                                                                    other for a share of users. Apart from being used as a way
share with other users of her choice.
                                                                    to share private files, researchers have found that FHSs
   In this paper, we present a study of 100 file hosting ser-
                                                                    are also used as an alternative to peer-to-peer networks
vices and we show that a significant percentage of them
                                                                    [1], since they offer several advantages such as harder
generate secret URIs in a predictable fashion, allowing
                                                                    detection of the user who first uploaded a specific file,
attackers to enumerate their services and access their file
                                                                    always-available downloads and no upload/download ra-
list. Our experiments demonstrate how an attacker can
                                                                    tio 2 measurements.
access hundreds of thousands of files in a short period of
                                                                       In this paper, we present our study on 100 file host-
time, and how this poses a very big risk for the privacy
                                                                    ing services. These services adopt a security-through-
of FHS users. Using a novel approach, we also demon-
                                                                    obscurity mechanism where a user can access the up-
strate that attackers are aware of these vulnerabilities and
                                                                    loaded files only by knowing their correct download
are already exploiting them to get access to other users’
                                                                    URIs. While these services claim that these URIs are
files. Finally we present SecureFS, a client-side protec-
                                                                    secret and cannot be guessed, our study shows that this
tion mechanism which can protect a user’s files when up-
                                                                    is far from being true. A significant percentage of FHSs
loaded to insecure FHSs, even if the files end up in the
                                                                    generate the “secret” URIs in a predictable fashion, al-
possession of attackers.
                                                                    lowing attackers to easily enumerate their files and get
1   Introduction                                                    access to content that was uploaded by other users.
                                                                       We implemented crawlers for different hosting
   In an ever expanding Internet, an increasing number              providers and, using search engines as a privacy classi-
of people utilize online services to share digital content.         fication mechanism, we were able to disclose hundreds
Most of the platforms that support file sharing operate in          of thousands of private files in less than a month. The
a broadcasting way. For example, users of social net-               second contribution of this paper is a technique to mea-
works can upload multimedia files which are then ac-                sure whether attackers are already abusing FHSs to ac-
cessible to their entire friend list. In traditional peer-to-       cess private information. To reach this goal, we cre-
peer networks (e.g., DC++, KaZaa and BitTorrent), users             ated a number of “HoneyFiles”, i.e. fake documents that
share their files with everyone connected to the same net-          promise illegal content, and we uploaded them to many
work.                                                               FHSs. These files were designed to silently contact one
   Sometimes however, users may want to share files                 of our servers once they were opened. Over the period of
only with a limited number of people, such as their co-             a month, more than 270 file accesses from over 80 dif-
workers, spouses, or family members. In these situa-                ferent IP addresses were recorded, showing that private
tions, the all-or-nothing approach of sharing files is not          documents uploaded to file hosting services are in fact
desired. While emailing digital content is still a popular
choice, most email providers do not usually allow attach-             1 RapidShare AG, http://www.rapidshare.com/

ments that exceed a few tens of megabytes.                            2 A user-quality metric used mainly in private BitTorrent trackers




                                                                1
actively downloaded by attackers.                                      unique ID returned by the FHS or by exploiting a soft-
   The rest of our paper is structured as follows. In Sec-             ware bug that will eventually allow access to the up-
tion 2 we present a high-level view of how FHSs operate,               loaded files.
followed by a security and privacy study of the top 100
FHSs in Section 3. Section 4 provides the details and                  3       Privacy study
reports the results of our HoneyFiles experiment. In Sec-                  The first phase of our study consists in comparing
tion 5 we present a possible countermeasure to protect                 the privacy offered by 100 File Hosting Services. The
users of vulnerable FHSs. We then present ethical con-                 list was constructed by merging the information re-
siderations regarding our experiments in Section 6. Sec-               trieved from different sources, such as the Alexa web-
tion 7 explores related work, Section 8 discusses possible             site, Google search engine, and a number of articles and
future work, and finally, Section 9 concludes the paper.               reviews posted on the Web [9, 14].
                                                                           Our final top 100 list includes well-known FHSs
2     Life cycle of files on File Hosting Services                     like RapidShare, FileFactory and Easyshare
   In this section, we describe the typical life cycle of a            as well as less popular and regional websites like
file in relation to file hosting services and we point out             FileSave.me (India), OnlineDisk.ru (Russia)
the privacy-sensitive steps. In order to model this life               and FileXoom.com (Mexico).
cycle we consider a FHS which allows users to upload                       Before starting the experiments we manually screened
files without the need to register an account.                         each website and found that 12 of them provide either a
   A typical user interaction with a FHS usually follows               search functionality (to retrieve the link of a file know-
the following steps:                                                   ing its name) or an online catalogue (to browse part of
                                                                       the uploaded files). Obviously, these services are not in-
    1. Alice decides to share some digital content3 with               tended for storing personal documents, but only as an
       other users by uploading it to her favorite FHS.                easy way to publicly share files between users. There-
    2. The FHS receives and stores the file. It then creates           fore, we removed these FHSs from our privacy study and
       a unique identifier and binds it to the uploaded file.          we focused our testing on the remaining 88 services.
    3. The identifier (ID) is returned to Alice in the form                We began our evaluation by analyzing how the unique
       of a URI that permits her to easily retrieve the up-            file identifiers are generated by each FHS. As we de-
       loaded file.                                                    scribed in the previous section, when a user uploads a
    4. Alice may now distribute the URI according to the               file to a FHS, the server creates an unique identifier (ID)
       nature of her file: If the file is meant to be public,          and binds it to the uploaded file. The identifier acts as a
       she may post the link on publicly accessible forums,            shared secret between the user and the hosting service,
       news-letters or social-networks, otherwise she may              and therefore, it should not be possible for an attacker to
       prefer to share the URI using one-to-one communi-               either guess or enumerate valid IDs.
       cation channels such as e-mails or instant messag-
       ing.                                                            Sequential Identifiers
    5. The public or private recipients use the shared URI
                                                                       For each FHS, we consecutively uploaded a number of
       to access the file that Alice has uploaded.
                                                                       random files and we monitored the download URIs gen-
    6. If the uploaded file violates copyright laws (movies,
                                                                       erated by the hosting service. Surprisingly, we noticed
       music, non-free software) then a third party can pos-
                                                                       that 34 out of the 88 FHSs (38.6%) generated sequential
       sibly report it. In this case the file is deleted and the
                                                                       IDs to identify the uploaded files. Hence, a hypothetical
       unique ID is possibly reused. If the file survives this
                                                                       attacker could easily enumerate all private files hosted
       process, it remains accessible for a limited amount
                                                                       by a vulnerable FHS by repeatedly decreasing a valid ID
       of time (set by the provider) or until Alice voluntar-
                                                                       (that can be easily obtained by uploading a test file).
       ily removes it.                                                    As an example, the following snippet shows how one
                                                                       of the hosting providers (anonymized to vulnerable.com)
   In the context of this paper, we focus on the scenario
                                                                       stored our uploaded files with sequential identifiers:
in which the user uploads a private file to a FHS and uses                                                                    
a one-to-one channel to share the unique ID returned by                    http://vulnerable.com/9996/
                                                                           http://vulnerable.com/9997/
the service with the intended recipients of the file. We                   http://vulnerable.com/9998/
also assume that the trusted recipients will not forward                   http://vulnerable.com/9999/
                                                                           [...]
the URI to other untrusted users.                                                                                             
   In this case, the only way in which the file can be
accessed by a malicious user is either by guessing the                   However, the enumeration attack is possible only
                                                                       when the URI does not contain other non-guessable pa-
    3 In the rest of the paper called “file”                           rameters. In particular, we noticed that out of the 34 FHS


                                                                   2
                   Sequential ID   Non-Sequential ID      Tot             File Type                             # Enumerated Files
 Filename:                                                                Images (JPG, GIF, BMP)                           27,771
    Required            14                6               20              Archives (ZIP)                                   13,354
    Not required        20                48              68
 Total                  34                54              88
                                                                          Portable Document Format (PDF)                    7,137
                                                                          MS Office Word Documents                          3,686
     Table 1: Analysis of the Download URI’s identifier                   MS Office Excel Sheets                            1,182
                                                                          MS PowerPoint                                       967
that use sequential identifiers, 14 also required the proper            Table 2: Number of files with sensitive types reported as private
filename to be provided with the secret identifier. For ex-             by our privacy-classification mechanism
ample, the URI was sometimes constructed by appending
                                                                        download URI on websites, blogs, and/or public forums,
the filename as shown in the following example:
                                                                      depending on the target audience of the file. On the
  http://site-one.com/9996/foo.pdf                                      other hand, if a file is intended to be kept private, the
  http://site-one.com/9997/bar.xls                                      link would probably be shared in a one-to-one fashion,
  http://site-one.com/9998/password.txt
  [...]                                                                 e.g., through personal emails and instant messaging. We
                                                                      decided to exploit this difference to roughly characterize
   Since the filenames associated to each ID are, in gen-               a file as public or private. In particular, we queried for
eral, unknown to the attacker, this feature acts as an                  each file name on Bing, Microsoft’s search engine, and
effective mitigation against enumeration attacks. Even                  we flagged as “public” any file whose link was found on
though it would still be possible for an attacker to nar-               the Web. If Bing did not return any results for our query,
row down his research to a particular filename, we did                  we considered the file as private.
not investigate this type of targeted attacks in our study.                Out of the 310,735 unique filenames extracted with
   Table 1 provides an overview of the techniques                       our enumeration tool, Bing returned no search results
adopted by the various FHSs to generate the download                    for 168,320, thus classifying 54.16% of files as private.
URIs. The privacy provided by 20 service providers was                  This classification is quite approximate as the list of pri-
extremely weak, relying only on a sequential ID to pro-                 vate files also contains data exchanged in closed “pi-
tect the users’ uploaded data. Unfortunately, the problem               rate” communities, beyond the reach of search engines’
is extremely serious since the list of insecure FHSs using              crawlers [1, 8]. Nevertheless, this technique still pro-
sequential IDs also includes some of the most popular                   vides a useful estimation of the impact of this kind of
names, often highly ranked by Alexa in the list of the top              attack on the privacy of FHS users.
Internet websites.                                                         Table 2 shows the number of unique private files
   To further prove that our concerns have a practical se-              crawled by our tool, grouped by common filetypes. In
curity impact, we implemented an automatic enumerator                   addition to the major extensions reported in the Table,
for the 20 FHSs that use sequential IDs and do not re-                  we also found several files ending with a .sql exten-
quire the knowledge of the associated filename. Our tool                sion. These files are probably database dumps that at-
inserted a random delay after each request to reduce the                tackers may use to gain a detailed view of the content of
impact on the performance of the file hosting providers.                the victim’s database.
As a result, our crawler requests were interleaved with                    Even though we believe that the majority of these files
many legitimate user requests, a fact which allowed us to               contain private information, for ethical reasons we de-
conduct our experiment for over a month without being                   cided not to verify our hypothesis. In fact, to preserve
blacklisted by any service provider.                                    the users’ privacy, our crawler was designed to extract
   When a user requests a file by providing a valid URI,                only the name and size of the files from the information
the FHS usually returns a page containing some informa-                 page, without downloading the actual content.
tion about the document (e.g., filename, size, and number
of times it was downloaded), followed by a series of links              Random Identifiers
which a user must follow to download the real file. This
feature is extremely convenient for an attacker that can                In a second experiment we focused on the 54 FHSs that
initially scrape the name of each file, and then download               adopt non sequential identifiers (ref. Table 1).
only those files that look more interesting.                               In these cases, the identifiers were randomly generated
   By enumerating sequential IDs, our crawler was able                  for each uploaded file, forcing a malicious user to guess
to retrieve information about 310,735 unique files in a                 a valid random value to get access to a single file. The
period of 30 days. While this list is “per se” sensitive                complexity of this operation depends on the length (i.e.,
information, we tried to estimate how many files corre-                 number of characters) of the secret and on the charac-
spond to private users’ documents.                                      ter set (i.e., number of possible values for each charac-
   It is reasonable to assume that if the user wants to                 ter) that is used to generate the identifier. As shown in
make her file publicly accessible, she would post the                   Figure 1 and Figure 2, different FHSs use different tech-


                                                                    3
                                                                   Filename          Filename                      Feature                                Number of FHSs
           Number of File Hosting Services
                                                                   not required      required                      CAPTCHA                                           30%
                                              14                                                                   Delay                                             49%
                                              12                                                                   Password                                          26%
                                              10                                                                   PRO Version                                       53%
                                                  8                                                                Automated File Trashing (2-360 days)              54%
                                                  6                                                                               Table 4: Security features
                                                  4                                                             This shows that the size of the space to explore is not the
                                                  2
                                                                                                                only variable in the process and that the important fac-
                                                  0
                                                      5    6   7    8   9   10 11 12 13 15 16 20 32 36
                                                                                                                tor is the ratio between the number of possible identifiers
                                                                                                                and the total number of uploaded files.
                                                          Figure 1: Length of the Identifier

                                                                   Filename         Filename                    Existing Mitigations
  Number of File Hosting Services




                                                                   not required     required
                                             20
                                                                                                                We have shown that different hosting providers, by
                                             18                                                                 adopting download URIs that are either sequential or eas-
                                             16                                                                 ily predictable, can be abused by malicious users to ac-
                                             14
                                             12                                                                 cess a large amount of private user data. However, some
                                             10                                                                 hosting providers implement a number of mechanisms
                                              8
                                              6
                                                                                                                that mitigate the possible attacks and make automated
                                              4                                                                 enumeration more difficult to realize.
                                              2                                                                    From a manual analysis of the FHSs in our list we
                                              0
                                                      10           16       26       36         62   > 62       identified two techniques commonly used to prevent au-
                                              Figure 2: Size of the Identifier’s Character Set
                                                                                                                tomated downloads. As summarized in Table 4, 30%
                                                                                                                of websites use CAPTCHA and 49% force the user to
                                    Length                  Chars Set             # Tries   Files Found         wait (between 10 to 60 seconds) before the download
                                      6                      Numeric              617,169       728             starts. However, note that both techniques only increase
                                      6                    Alphanumeric           526,650       586             the difficulty of downloading files, and not the process
                                      8                      Numeric              920,631       332             of guessing the right identifier. As a consequence, our
                         Table 3: Experiment on the non-sequential identifiers                                  tool was not restricted in any way by these protection
                                                                                                                mechanisms. In addition, we noticed that a large number
                                                                                                                of sites offer a PRO version of their service where these
niques, varying in length from 6 to 36 bytes and adopting
                                                                                                                “limitations” are removed by paying a small monthly fee.
different character sets.
                                                                                                                   A much safer solution consists in adding an online
   The three peaks in Figure 1 correspond to identifier
                                                                                                                password to protect a file. Unfortunately, as shown in
length of six, eight, and twelve characters respectively.
                                                                                                                Table 4, only a small percentage of the tested FHSs pro-
The second graph shows instead that the most common
                                                                                                                vided this functionality.
approach consists in using alphanumeric characters. Un-
fortunately, a fairly large number of FHSs are still adopt-
ing easily guessable identifiers composed only of deci-                                                         Other Design and Implementation Errors
mal or hexadecimal digits.                                                                                      According to the results of our experiments, many FHSs
   To show the limited security offered by some of the                                                          are either vulnerable to sequential enumeration or they
existing solutions we conducted another simple experi-                                                          generate short identifiers that can be easily guessed by
ment. We modified our enumerator tool to bruteforce the                                                         an attacker. In the rest of this section, we show that, even
file identifiers of three different non sequential FHSs that                                                    when the identifiers are strong enough to resist a direct
did not require the filename in the URI. In particular, we                                                      attack, other weaknesses or vulnerabilities in the FHS’s
selected a FHS with numeric IDs of 6 digits, one with                                                           software may allow an attacker to access or manipulate
numeric IDs of 8 digits, and one with alphanumeric IDs                                                          private files.
of 6 characters. Our tool ran for five days, from a sin-                                                           While performing our study, we noticed that 13% of
gle machine on a single IP address. The results, shown                                                          hosting services use the same, publicly available, soft-
in Table 3, confirm that if the random identifiers are too                                                      ware to provide their services. To verify our concern
weak, an attacker can easily gain access to thousands of                                                        about the security of these systems, we downloaded and
third-party files in a reasonable amount of time.                                                               audited the free version of that platform. Through a man-
   It is also interesting to note that the success rate of                                                      ual investigation we were able to discover serious design
guessing both numeric and alphanumeric IDs of six dig-                                                          and implementation errors. For instance, the software
its was about the same (1.1 hit every thousand attempts).                                                       contained a directory traversal vulnerability that allows


                                                                                                            4
an attacker to list the URIs of all the recently uploaded                         of Table 5 list the names and descriptions of each file.
files.                                                                            The most important characteristic of these files is the
   In addition, the software provides to the user a delete                        fact that, once they are open, they automatically connect
URI for each uploaded file. The delete URI can be used                            back to our monitor running on the card3rz.co.cc server.
by the user at any time to delete her uploaded files from                         This was implemented in different ways, depending on
the service’s database. This feature can improve the                              the type of the document. For example, the HTML files
user’s privacy since the file can be deleted when it is no                        included an <img/> tag to fetch some content from our
longer needed. The deletion ID generated by this soft-                            webpage, the exe file opened a TCP connection upon its
ware was 14 characters long, with hexadecimal charac-                             execution, and the PDF documents asked the user per-
ters. This provides 1614 valid combinations which make                            mission to open a webpage. For Microsoft’s DOC for-
any attack practically impossible. However, we noticed                            mat, the most straightforward way we found was to em-
that the “report file” link, a per file automatically gener-                      bed an HTML file inside the document. In cases where
ated link to report copyright violations, consisted of the                        user action was required (e.g., the acceptance of a warn-
first 10 characters of the deletion code.                                         ing dialog or the double-click of the HTML object in the
   Since the “report file” link (used to report a copyright                       DOC file) we employed social engineering to convince
violation) is publicly available to everybody, an attacker                        the malicious user to authorize the action.
can use it to retrieve the first 10 digits of the delete URI,                        In addition to the connect-back functionality, one of
thus lowering the number of combinations to bruteforce                            the files contained valid credentials for logging into our
to only 164 = 65, 536.                                                            fake carding website. We did this to investigate whether
                                                                                  attackers would not only access illegally obtained data
   To conclude, it is evident that even if end-users only                         but also take action on the information found inside the
share the download-link with their intended audience,                             downloaded files.
they can not be certain that their files will not reach unin-                        The last step of our experiment consisted in writing
tended recipients. In Section 5, we will discuss a client-                        a number of tools to automatically upload the Honey-
side solution that can protect a user’s files without chang-                      Files to the various FHSs. Since the links to our files
ing his file-uploading and file-sharing habits.                                   were not shared with anyone, any file access recorded
                                                                                  by our monitor was the consequence of a malicious user
4     HoneyFiles                                                                  that was able to download and open our HoneyFiles, thus
   In Section 3 we showed that a significant percentage of                        triggering the hidden connect-back functionality.
file hosting services use a URI generation algorithm that
produces sequential identifiers, allowing a potential at-                         Monitoring Sequential FHSs
tacker to enumerate all the files uploaded by other users.
                                                                                  In our first experiment we used our tools to upload the
In addition, our experiments also showed that some of
                                                                                  HoneyFiles 4 times a day to all the FHSs adopting se-
the FHSs which use a more secure random algorithm, of-
                                                                                  quential identifiers. We also included the ones that
ten rely on weak identifiers that can easily be bruteforced
                                                                                  have Search/Catalogue functionality in order to find out
in a short amount of time.
   In summary, a large amount of the top 100 file hosting                         whether attackers search for illegal content in FHSs.
                                                                                     While we were initially skeptical of whether our ex-
services are not able to guarantee to the user the privacy
                                                                                  periment would provide positive results, the activity
of her documents. The next question we investigate is
                                                                                  recorded on our monitor quickly proved us wrong. Over
whether (and to what extent) the lack of security of these
                                                                                  the span of one month, users from over 80 unique IP ad-
websites is already exploited by malicious users. In order
                                                                                  dresses accessed the HoneyFiles we uploaded on 7 dif-
to answer this question we designed a new experiment in-
                                                                                  ferent FHSs for a total of 275 times. Table 6 shows the
spired by the work of Bowen et al. [3] and Yuill et al. [18]
                                                                                  categorization of the attackers by their country of origin
on the use of decoy documents to identify insider threats
                                                                                  using geolocation on their IP addresses. While most of
and detect unauthorized access.
   First, we registered the card3rz.co.cc domain and cre-                         the attacks originated from Russia, we also recorded ac-
ated a fake login page to a supposedly exclusive under-                           cesses from 16 other countries from Europe, the United
ground “carding”4 community. Second, we created a                                 States and the Middle East, showing that this attack tech-
number of decoy documents that promised illegal/stolen                            nique is used globally and it is not confined to a small
data to the people that accessed them. Each file contained                        group of attackers in a single location.
                                                                                     The third column of Table 5 presents the download ra-
a set of fake sensitive data and some text to make the
                                                                                  tio of each HoneyFile. It is evident that attackers favor
data convincing when necessary. The first two columns
                                                                                  content that will give them immediate monetary compen-
    4 Carding is a term used for a process to verify the validity of stolen       sation (such as PayPal accounts and credentials for our
credit card data.                                                                 carding forum) than other data (e.g., email addresses and


                                                                              5
      Filename                       Claimed Content                                                     Access Percentage
      phished paypal details.html    Credentials to PayPal accounts                                           40.36%
      card3rz reg details.html       Welcoming text to our fake carding forum and valid credentials           21.81%
      Paypal account gen.exe         Application which generates PayPal accounts                              17.45%
      customer list 2010.html        Leaked customer list from a known law firm                                9.09%
      Sniffed email1.doc             Document with an embedded customer list of a known law firm               6.81%
      SPAM list.pdf                  List of email addresses for spamming purposes                             5.09%
Table 5: Set of files containing fake data that were used as bait in our HoneyFiles experiment. The third column shows the resulting
download ratio of each file by attackers

    Countries                                  Accesses              tifiers. Interestingly, our monitor recorded 24 file ac-
    Russia                                     50.06%                cesses from 13 unique IP addresses originating from de-
    Ukraine                                    24.09%                coy documents placed in three separate FHSs over a pe-
    United States, United Kingdom, Nether-     2.40% each            riod of 10 days. Upon examination, two of them were
    lands, Kazakhstan, Germany
                                                                     offering search functionality. While the third FHS stated
    Sweden, Moldova, Latvia, India, France,    1.20% each
    Finland, Egypt, Canada, Belarus, Austria                         specifically that all files are private and no search op-
Table 6: Attack geolocation recorded by our HoneyFile moni-
                                                                     tion is given, we discovered two websites that adver-
tor                                                                  tised as search engines for that FHS. Since our Honey-
                                                                     files could be found through these search engines and
customer lists). Out of the 7 reported FHSs, one had a               we never posted our links in any other website, the only
catalog functionality (listing all the uploaded files), two          logical conclusion is that the owners of that FHS part-
of them had a search option and the remaining four had               nered with other companies, directly violating their pri-
neither catalog nor search functionality. Interestingly,             vacy statement.
one of the FHSs providing a search functionality did so                  We believe that the above experiments show, beyond
through a different website, violating its stated Terms of           doubt, that FHSs are actively exploited by attackers who
Service (ToS). This shows that apart from abusing se-                abuse them to access files uploaded by other users. Un-
quential identifiers attackers are also searching for sensi-         fortunately, since FHSs are server-side applications, the
tive keywords in FHSs that support searching.                        users have little-to-no control over the way their data
   Our monitor also recorded 93 successful logins from
                                                                     is handled once it has been uploaded to the hosting
43 different IP addresses at our fake carding website us-
                                                                     provider.
ing the credentials that we included inside our Honey-
Files. When a valid username and password combination                5   Countermeasures
was entered, the carding website informed the user that
the website was under maintenance and that she should                   In previous sections, we showed that not only many
have retried later. Fourteen out of the 43 attackers did so          file hosting services are insecure and exploitable, but also
with the notable example of an attacker that returned to             that they are in fact being exploited by attackers to gain
the website and logged in 14 times in a single day. The              access to files uploaded by other users. This introduces
multiple successful logins show that attackers do not hes-           significant privacy risks since the content that users up-
itate to make use of the data they find on FHSs. We as-              loaded, and that was meant to be privately shared, is now
sume that the fake PayPal credentials were also tried but            in the hands of people who can use it for a variety of
we have no direct way to confirm our hypothesis.                     purposes, ranging from blackmailing and scamming to
   In addition to login attempts, we also logged several             identity theft.
attempts of SQL injection and file inclusion attacks con-               We notified 25 file hosting providers about the prob-
ducted against the login page of our fake carding web-               lems we found in our experiments. Some of them al-
site and against our monitoring component. This shows                ready released a patch to their system, for instance by
that the attackers who downloaded the files from the vul-            replacing sequential IDs with random values. Others ac-
nerable FHSs had at least some basic knowledge of web                knowledged the problem but, at the time of writing, they
hacking techniques and were not plain users that some-               are still in the process of implementing a solution. Un-
how stumbled upon our HoneyFiles. We were also able                  fortunately, not all the vendors reacted in the same way.
to locate a post in an underground Russian forum that                In one case, the provider refused to adopt random identi-
listed our fake carding website.                                     fiers because it would negatively affect the performance
                                                                     of the database server, while another provider “solved”
                                                                     the problem by changing the Term of Service (ToS) to
Monitoring Non-Sequential FHSs
                                                                     state that his system does not guarantee the privacy of
For completeness, we decided to repeat the HoneyFiles                the uploaded files.
experiment on 20 FHSs that adopt non-sequential iden-                   Therefore, even though it is important to improve the


                                                                 6
security on the server side, countermeasures must also               • The enumerator tools employed a random delay be-
be applied on the client side to protect the user’s privacy            tween each requests to avoid possible impacts on the
even if her files end up in the hands of malicious users.              performance of the file hosting providers.
   An effective way of securing information against                  • We did not break into any systems and we immedi-
eavesdroppers is through encryption, for example by us-                ately informed the security department of the vulner-
ing password-protected archives. In some cases, how-                   able sites of the problems we discovered.
ever, the default utilities present in operating systems
                                                                     • The HoneyFiles were designed to not harm the user’s
cannot correctly handle encrypted archive files5 . There-
                                                                       computer in any way. Moreover, we did not distribute
fore, we decided to design and implement a client-
                                                                       these files on public sites, but only uploaded them (as
side security mechanism, SecureFS, which automatically
                                                                       private documents) to the various FHSs.
encrypts/decrypts files upon upload/download and uses
steganographic techniques to conceal the encrypted files
and to present a fake one to the possible attackers. The            7   Related Work
motivation behind SecureFS is to transparently protect
the user’s files as well as providing a platform for de-              Different studies have recently been conducted on the
tecting attackers and insecure file hosting services in the         security and privacy of online services. For example,
future (see Section 8).                                             Balduzzi et al. [2] and Gilbert et al. [16] analyze the im-
   SecureFS is implemented as a Firefox extension that              pact of social-networks on the privacy of Internet users,
constantly monitors file uploads and downloads to FHSs              while Narayanan et al. [10] showed that by combining
through the browser. When SecureFS detects that the                 public data with background knowledge, an attacker is
user is about to upload a file, it creates an encrypted copy        capable of revealing the identify of subscribers to online
of the document and combines it with a ZIP file contain-            movie rental services. Other studies (e.g., [13, 17]) fo-
ing fake data. Due to the fact that ZIP archives place              cused on the security and privacy trends in mass-market
their metadata at the end of the file, a possible attacker          ubiquitous devices and cloud-computing providers [11].
who downloads the protected file will decompress it and
access the fake data without realizing that he is being                However, to the best of our knowledge, no prior stud-
mislead. Even if the attacker notices that something is             ies have been conducted on the privacy of FHSs. In
wrong (e.g., by noticing the size difference between the            this paper we reported the insecurity of many hosting
ZIP file and the resulting file) the user’s file is still en-       providers by experimentally proving that these services
crypted and thus protected. On the other hand, when a               are actually exploited by attackers. There are, how-
legitimate user downloads the file, SecureFS recognizes             ever, a number of cases where sequential identifiers of
its internal structure and automatically extracts and de-           various services have been exploited. For example, re-
crypts the original file.                                           searchers investigated how session IDs are constructed
   Most of the described process is automatic, transpar-            and in which cases they can be bruteforced [4]. The
ent and performed without the user’s assistance. The de-            study is not restricted to IDs stored in cookies, but also
tails of SecureFS and our prototype are publicly avail-             analyzes the sequential and non-sequential IDs present
able6 .                                                             inside URIs. Recently, researchers also identified issues
                                                                    with sequential identifiers in cash-back systems [15].
6   Ethical Considerations                                             Antoniades et al. [1] notice that the recent increase of
   Testing the security of one hundred file hosting                 FHSs is threatening the dominance of peer-to-peer net-
providers and extracting information for thousands of               works for file sharing. FHSs are found to have better per-
user files may raise ethical concerns. However, analo-              formance, more content and that this content persists for
gous to the real-world experiments conducted by Jakob-              a longer time than on peer-to-peer networks like BitTor-
sson et al. [5, 6], we believe that realistic experiments           rent. Researchers have also used FHSs as a distributed
are the only way to reliably estimate success rates of at-          mechanism to store encrypted filecaches that can be used
tacks in the real world. Moreover, we believe that our ex-          by a collaborating group of people [7].
periments helped some file hosting providers to improve
their security. In particular, note that:                              Honeypots [12] have been traditionally used to study
                                                                    attacking techniques and post-exploitation trends. Yuil
 • The enumerator tools accessed only partial informa-              et al. [18] introduce Honeyfiles as an intrusion detection
    tion of the crawled files (the file’s name and size) and        tool to identify attackers. Honeyfiles are bait files that
    did not download any file content.                              are stored on, and monitored by, a server. These files are
  5 How to open password-protected ZIP in Mac OS X, http://         intended to be opened by attackers and when they do so,
www.techiecorner.com/833/                                           the server emits an alert. Similarly, Bowen et al. [3] use
  6 http://www.securitee.org/sfs/                                   files with “stealthy beacons” to identify insider threats.


                                                                7
                                                                               for automated user profiling. In Proceedings of the 13th inter-
8    Future Work                                                               national conference on Recent advances in intrusion detection
   In Section 5 we presented our design for a client-side                      (Berlin, Heidelberg, 2010), RAID’10, Springer-Verlag, pp. 422–
protection mechanism for files uploaded to FHSs. We                            441.
described the process of appending a ZIP archive with                      [3] B OWEN , B., H ERSHKOP, S., K EROMYTIS , A., AND S TOLFO ,
                                                                               S. Baiting inside attackers using decoy documents. Security and
fake data to each uploaded file.                                               Privacy in Communication Networks (2009), 51–70.
   While at the moment the fake document is a simple
                                                                           [4] E NDLER , D. Brute-Force Exploitation of Web Application Ses-
text file that informs the attacker of his wrong doings,                       sion IDs. Retrieved from http://www. cgisecurity. com (2001).
we are currently investigating alternative uses. For ex-                   [5] JAKOBSSON , M., F INN , P., AND J OHNSON , N. Why and How
ample, the ZIP archive could contain a file that, when                         to Perform Fraud Experiments. Security & Privacy, IEEE 6, 2
opened, “calls home” (see Section 4) and informs the file                      (March-April 2008), 66–68.
owner of the illegitimate file access. In order to pre-                    [6] JAKOBSSON , M., AND R ATKIEWICZ , J. Designing ethical
serve the user privacy, “home” can be a separate web                           phishing experiments: a study of (ROT13) rOnl query features.
                                                                               In 15th International Conference on World Wide Web (WWW)
service that will in turn report to users which file was                       (2006).
maliciously downloaded and when. The service itself
                                                                           [7] J ENSEN , C. Cryptocache: a secure sharable file cache for roam-
can also be adopted as a FHS monitor which will inform                         ing users. In Proceedings of the 9th workshop on ACM SIGOPS
the users about vulnerable FHSs that should be avoided.                        European workshop: beyond the PC: new challenges for the op-
This privacy-rating functionality can be beneficial to the                     erating system (2000), vol. 54, ACM, pp. 73–78.
community by allowing non-security inclined users to                       [8] L AI , E. What’s replacing P2P, BitTorrent as pirate hang-
choose a secure FHS and by pushing the developers of                           outs? http://www.computerworld.com/s/article/
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the insecure FHSs to correct their privacy issues.
                                                                           [9] M UELLER , W.  Top free file hosts to store your
                                                                               files online. http://www.makeuseof.com/tag/
9    Conclusion                                                                top-free-file-hosts/.
    In this paper, we investigated the privacy of 100 file                [10] NARAYANAN , A., AND S HMATIKOV, V.               Robust de-
hosting services and discovered that a large percentage                        anonymization of large sparse datasets. In Proceedings of the
of them generate download URIs in a predictable fash-                          2008 IEEE Symposium on Security and Privacy (Washington,
                                                                               DC, USA, 2008), IEEE Computer Society, pp. 111–125.
ion. Specifically, many FHSs are either vulnerable to
                                                                          [11] P EARSON , S. Taking account of privacy when designing cloud
sequential enumeration or they generate short identifiers                      computing services. In Proceedings of the 2009 ICSE Workshop
that can be easily guessed by an attacker. Using differ-                       on Software Engineering Challenges of Cloud Computing (Wash-
ent FHS enumerators that we implemented, we crawled                            ington, DC, USA, 2009), CLOUD ’09, IEEE Computer Society,
information for more than 310,000 unique files. Using                          pp. 44–52.
the Bing search engine as a privacy-classification mech-                  [12] P ROVOS , N. A virtual honeypot framework. In Proceedings of
                                                                               the 13th conference on USENIX Security Symposium - Volume 13
anism, we showed that 54% of them were likely private                          (Berkeley, CA, USA, 2004), SSYM’04, USENIX Association,
documents since they were not indexed by the search en-                        pp. 1–1.
gine. We also conducted a second experiment to demon-                     [13] S APONAS , T. S., L ESTER , J., H ARTUNG , C., AGARWAL , S.,
strate that attackers are aware of these vulnerabilities and                   AND KOHNO , T. Devices that tell on you: privacy trends in con-
they are already exploiting them to gain access to files                       sumer ubiquitous computing. In Proceedings of 16th USENIX
                                                                               Security Symposium on USENIX Security Symposium (Berkeley,
uploaded by other users. Finally we presented SecureFS,                        CA, USA, 2007), USENIX Association, pp. 5:1–5:16.
a client-side protection mechanism which is able to pro-                  [14] S HARKY. 100 of the best free file hosting upload sites.
tect a user’s files when uploaded to insecure FHSs, even                       http://filesharefreak.com/2009/08/26/
if the documents ends up in the possession of attackers.                       100-of-the-best-free-file-hosting-upload-sites/.
                                                                          [15] T HIERRY Z OLLER. How NOT to implement a Payback/Cash-
Acknowledgements: This research is partially funded                            back System. In OWASP BeNeLux (2010).
by the Interuniversity Attraction Poles Programme Bel-                    [16] W ONDRACEK , G., H OLZ , T., K IRDA , E., AND K RUEGEL , C.
                                                                               A practical attack to de-anonymize social network users. In Pro-
gian State, Belgian Science Policy, the IBBT, the Re-                          ceedings of the 2010 IEEE Symposium on Security and Privacy
search Fund K.U.Leuven and from the European Union                             (Washington, DC, USA, 2010), SP ’10, IEEE Computer Society,
Seventh Framework Programme (FP7/2007-2013) under                              pp. 223–238.
grant agreement n. 257007.                                                [17] W RIGHT, C. V., BALLARD , L., C OULL , S. E., M ONROSE , F.,
                                                                               AND M ASSON , G. M. Spot me if you can: Uncovering spo-
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