draft-iab-privsec-confidentiality-threat-03.xml

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<rfc ipr="trust200902" docName="draft-iab-privsec-confidentiality-threat-03" category="info">

  <front>
    <title abbrev="Confidentiality Threat Model">Confidentiality in the Face of Pervasive Surveillance: A Threat Model and Problem Statement</title>

    <author initials="R." surname="Barnes" fullname="Richard Barnes">
      <organization></organization>
      <address>
        <email>rlb@ipv.sx</email>
      </address>
    </author>
    <author initials="B." surname="Schneier" fullname="Bruce Schneier">
      <organization></organization>
      <address>
        <email>schneier@schneier.com</email>
      </address>
    </author>
    <author initials="C." surname="Jennings" fullname="Cullen Jennings">
      <organization></organization>
      <address>
        <email>fluffy@cisco.com</email>
      </address>
    </author>
    <author initials="T." surname="Hardie" fullname="Ted Hardie">
      <organization></organization>
      <address>
        <email>ted.ietf@gmail.com</email>
      </address>
    </author>
    <author initials="B." surname="Trammell" fullname="Brian Trammell">
      <organization></organization>
      <address>
        <email>ietf@trammell.ch</email>
      </address>
    </author>
    <author initials="C." surname="Huitema" fullname="Christian Huitema">
      <organization></organization>
      <address>
        <email>huitema@huitema.net</email>
      </address>
    </author>
    <author initials="D." surname="Borkmann" fullname="Daniel Borkmann">
      <organization></organization>
      <address>
        <email>dborkman@redhat.com</email>
      </address>
    </author>

    <date year="2015" month="February" day="20"/>

    
    
    

    <abstract>


<t>Documents published since initial revelations in 2013 have revealed
several classes of pervasive surveillance attack on Internet
communications.  In this document we develop a threat model that
describes these pervasive attacks. We start by assuming an attacker
with an interest in undetected, indiscriminate eavesdropping, then
expand the threat model with a set of verified attacks that have been
published.</t>



    </abstract>


  </front>

  <middle>


<section anchor="introduction" title="Introduction">

<t>Starting in June 2013, documents released to the press by Edward
Snowden have revealed several operations undertaken by intelligence
agencies to exploit Internet communications for intelligence purposes.
These attacks were largely based on protocol vulnerabilities that were
already known to exist.  The attacks were nonetheless striking in
their pervasive nature, both in terms of the amount of Internet
communications targeted, and in terms of the diversity of attack
techniques employed.</t>

<t>To ensure that the Internet can be trusted by users, it is necessary
for the Internet technical community to address the vulnerabilities
exploited in these attacks <xref target="RFC7258"/>.  The goal of this document is
to describe more precisely the threats posed by these pervasive
attacks, and based on those threats, lay out the problems that need to
be solved in order to secure the Internet in the face of those
threats.</t>

<t>The remainder of this document is structured as follows. In
<xref target="adversary"/>, we describe an idealized flow access attacker, one which
could completely undetectably compromise communications at Internet
scale. In <xref target="reported"/>, we provide a brief summary of some attacks
that have been disclosed, and use these to expand the assumed
capabilities of our idealized attacker.  Note that we do not attempt
to describe all possible attacks, but focus on those which result in
undetected eavesdropping. <xref target="model"/> describes a threat model based on
these attacks, focusing on classes of attack that have not been a
focus of Internet engineering to date.</t>

</section>
<section anchor="terminology" title="Terminology">

<t>This document makes extensive use of standard security and privacy
terminology; see <xref target="RFC4949"/> and <xref target="RFC6973"/>. Terms used from
<xref target="RFC6973"/> include Eavesdropper, Observer, Initiator, Intermediary,
Recipient, Attack (in a privacy context), Correlation, Fingerprint,
Traffic Analysis, and Identifiability (and related terms). In
addition, we use a few terms that are specific to the attacks
discussed here:</t>

<t><list style="hanging">
  <t hangText='Flow Access Attack:  '>
  An eavesdropping attack in which the packets
in a traffic stream between two endpoints are eavesdropped upon, but
in which the attacker does not modify the packets in the traffic
stream between two endpoints, modify the treatment of packets in the
traffic stream (e.g. delay, routing), or add or remove packets in the
traffic stream. Flow access attacks are undetectable from the
endpoints.</t>
  <t hangText='Flow Modification Attack: '>
  An attack which includes both eavesdropping (as in a
flow access attack) as well as modification, addition, or removal of
packets in a traffic stream, or modification of treatment of packets
in the traffic stream. Flow modification attacks provide more
capabilities to the attacker at the cost of possible detection at the 
endpoints.</t>
  <t hangText='Pervasive Attack: '>
  An attack on Internet communications that makes
use of access at a large number of points in the network, or otherwise
provides the attacker with access to a large amount of Internet
traffic; see <xref target="RFC7258"/></t>
  <t hangText='Observation:'>
  Information collected directly from communications by an
eavesdropper or observer. For example, the knowledge that
&lt;alice@example.com&gt; sent a message to &lt;bob@example.com&gt;
via SMTP taken from the headers of an observed SMTP message would be
an observation.</t>
  <t hangText='Inference:'>
  Information extracted from analysis of information collected
directly from communications by an eavesdropper or observer. For
example, the knowledge that a given web page was accessed by a given
IP address, by comparing the size in octets of measured network flow
records to fingerprints derived from known sizes of linked resources
on the web servers involved, would be an inference.</t>
  <t hangText='Collaborator:'>
  An entity that is a legitimate participant in a communication, but
who deliberately provides information about that interaction to an
attacker.</t>
  <t hangText='Unwitting Collaborator:'>
  An entity that is a legitimate participant in a communication, and
who is the source of information obtained by the attacker without the
entity’s consent or intention, because the attacker has exploited some
technology used by the entity.</t>
  <t hangText='Key Exfiltration:'>
  The transmission of keying material for an encrypted communication
from a collaborator, deliberately or unwittingly, to an attacker</t>
  <t hangText='Content Exfiltration:'>
  The transmission of the content of a communication from a collaborator, deliberately or unwittingly, to an attacker</t>
</list></t>

</section>
<section anchor="adversary" title="An Idealized Pervasive Flow Access Attacker">

<t>In considering the threat posed by pervasive surveillance, we begin by
defining an idealized pervasive flow access attacker. While this attacker
is less capable than those which we now know to have compromised the
Internet from press reports, as elaborated in <xref target="reported"/>, it does
set a lower bound on the capabilities of an attacker interested in
indiscriminate passive surveillance while interested in remaining
undetectable. We note that, prior to the Snowden revelations in 2013,
the assumptions of attacker capability presented here would be
considered on the border of paranoia outside the network security
community.</t>

<t>Our idealized attacker is an indiscriminate eavesdropper on an Internet-attached computer network that:</t>

<t><list style="symbols">
  <t>can observe every packet of all communications at any hop in any network path between an initiator and a recipient; </t>
  <t>can observe data at rest in any intermediate system between the endpoints controlled by the initiator and recipient; and</t>
  <t>can share information with other such attackers; but</t>
  <t>takes no other action with respect to these communications (i.e., blocking, modification, injection, etc.).</t>
</list></t>

<t>The techniques available to our ideal attacker are direct observation
and inference. Direct observation involves taking information directly
from eavesdropped communications - e.g., URLs identifying content or
email addresses identifying individuals from application-layer
headers. Inference, on the other hand, involves analyzing eavesdropped
information to derive new information from it; e.g., searching for
application or behavioral fingerprints in observed traffic to derive
information about the observed individual from them, in absence of
directly-observed sources of the same information. The use of
encryption to protect confidentiality is generally enough to prevent
direct observation of unencrypted content, assuming uncompromised
encryption implementations and key material. However, it provides less
complete protection against inference, especially inference based only
on unprotected portions of communications (e.g. IP and TCP headers for
TLS <xref target="RFC5246"/>).</t>

<section anchor="information-subject-to-direct-observation" title="Information subject to direct observation">

<t>Protocols which do not encrypt their payload make the entire content
of the communication available to the idealized attacker along their
path. Following the advice in <xref target="RFC3365"/>, most such protocols have a
secure variant which encrypts payload for confidentiality, and these
secure variants are seeing ever-wider deployment. A noteworthy
exception is DNS <xref target="RFC1035"/>, as DNSSEC <xref target="RFC4033"/> does not have
confidentiality as a requirement. This implies that, in the absence of
changes to the protocol as presently under development in the DPRIVE
working group, all DNS queries and answers generated by the activities
of any protocol are available to the attacker.</t>

<t>Protocols which imply the storage of some data at rest in
intermediaries (e.g. SMTP <xref target="RFC5321"/>) leave this data subject to
observation by an attacker that has compromised these intermediaries,
unless the data is encrypted end-to-end by the application layer
protocol, or the implementation uses an encrypted store for this data.</t>

</section>
<section anchor="information-useful-for-inference" title="Information useful for inference">

<t>Inference is information extracted from later analysis of an observed
or eavesdropped communication, and/or correlation of observed or
eavesdropped information with information available from other
sources. Indeed, most useful inference performed by the attacker falls
under the rubric of correlation. The simplest example of this is the
observation of DNS queries and answers from and to a source and
correlating those with IP addresses with which that source
communicates. This can give access to information otherwise not
available from encrypted application payloads (e.g., the Host:
HTTP/1.1 request header when HTTP is used with TLS).</t>

<t>Protocols which encrypt their payload using an application- or
transport-layer encryption scheme (e.g. TLS) still expose all the
information in their network and transport layer headers to the
attacker, including source and destination addresses and ports. IPsec
ESP<xref target="RFC4303"/> further encrypts the transport-layer headers, but still
leaves IP address information unencrypted; in tunnel mode, these
addresses correspond to the tunnel endpoints. Features of the
cryptographic protocols themselves, e.g. the TLS session identifier,
may leak information that can be used for correlation and
inference. While this information is much less semantically rich than
the application payload, it can still be useful for the inferring an
individual’s activities.</t>

<t>Inference can also leverage information obtained from sources other
than direct traffic observation. Geolocation databases, for example,
have been developed map IP addresses to a location, in order to
provide location-aware services such as targeted advertising. This
location information is often of sufficient resolution that it can be
used to draw further inferences toward identifying or profiling an
individual.</t>

<t>Social media provide another source of more or less publicly
accessible information. This information can be extremely semantically
rich, including information about an individual’s location,
associations with other individuals and groups, and
activities. Further, this information is generally contributed and
curated voluntarily by the individuals themselves: it represents
information which the individuals are not necessarily interested in
protecting for privacy reasons. However, correlation of this social
networking data with information available from direct observation of
network traffic allows the creation of a much richer picture of an
individual’s activities than either alone.</t>

<t>We note with some alarm that there is little that can be done at
protocol design time to limit such correlation by the attacker, and
that the existence of such data sources in many cases greatly
complicates the problem of protecting privacy by hardening protocols
alone.</t>

</section>
<section anchor="an-illustration-of-an-ideal-flow-access-attack" title="An illustration of an ideal flow access attack">

<t>To illustrate how capable the idealized attacker is even given its
limitations, we explore the non-anonymity of encrypted IP traffic in
this section. Here we examine in detail some inference techniques for
associating a set of addresses with an individual, in order to
illustrate the difficulty of defending communications against our
idealized attacker. Here, the basic problem is that information
radiated even from protocols which have no obvious connection with
personal data can be correlated with other information which can paint
a very rich behavioral picture, that only takes one unprotected link
in the chain to associate with an identity.</t>

<section anchor="analysis-of-ip-headers" title="Analysis of IP headers">

<t>Internet traffic can be monitored by tapping Internet links, or by
installing monitoring tools in Internet routers. Of course, a single
link or a single router only provides access to a fraction of the
global Internet traffic. However, monitoring a number of high capacity
links or a set of routers placed at strategic locations provides
access to a good sampling of Internet traffic.</t>

<t>Tools like IPFIX <xref target="RFC7011"/> allow administrators to acquire
statistics about sequences of packets with some common properties that
pass through a network device. The most common set of properties used
in flow measurement is the “five-tuple”of source and destination
addresses, protocol type, and source and destination ports. These
statistics are commonly used for network engineering, but could
certainly be used for other purposes.</t>

<t>Let’s assume for a moment that IP addresses can be correlated to
specific services or specific users. Analysis of the sequences of
packets will quickly reveal which users use what services, and also
which users engage in peer-to-peer connections with other
users. Analysis of traffic variations over time can be used to detect
increased activity by particular users, or in the case of peer-to-peer
connections increased activity within groups of users.</t>

</section>
<section anchor="correlation-of-ip-addresses-to-user-identities" title="Correlation of IP addresses to user identities">

<t>The correlation of IP addresses with specific users can be done in
various ways. For example, tools like reverse DNS lookup can be used
to retrieve the DNS names of servers. Since the addresses of servers
tend to be quite stable and since servers are relatively less numerous
than users, an attacker could easily maintain its own copy of the DNS
for well-known or popular servers, to accelerate such lookups.</t>

<t>On the other hand, the reverse lookup of IP addresses of users is
generally less informative. For example, a lookup of the address
currently used by one author’s home network returns a name of the form
“c-192-000-002-033.hsd1.wa.comcast.net”. This particular type of
reverse DNS lookup generally reveals only coarse-grained location or
provider information, equivalent to that available from geolocation
databases.</t>

<t>In many jurisdictions, Internet Service Providers (ISPs) are required
to provide identification on a case by case basis of the “owner” of a
specific IP address for law enforcement purposes. This is a reasonably
expedient process for targeted investigations, but pervasive
surveillance requires something more efficient. This provides an
incentive for the attacker to secure the cooperation of the ISP in
order to automate this correlation.</t>

</section>
<section anchor="monitoring-messaging-clients-for-ip-address-correlation" title="Monitoring messaging clients for IP address correlation">

<t>Even if the ISP does not cooperate, user identity can often be
obtained via inference. POP3 <xref target="RFC1939"/> and IMAP <xref target="RFC3501"/> are used
to retrieve mail from mail servers, while a variant of SMTP is used to
submit messages through mail servers. IMAP connections originate from
the client, and typically start with an authentication exchange in
which the client proves its identity by answering a password
challenge. The same holds for the SIP protocol <xref target="RFC3261"/> and many
instant messaging services operating over the Internet using
proprietary protocols.</t>

<t>The username is directly observable if any of these protocols operate
in cleartext; the username can then be directly associated with the
source address.</t>

</section>
<section anchor="retrieving-ip-addresses-from-mail-headers" title="Retrieving IP addresses from mail headers">

<t>SMTP <xref target="RFC5321"/> requires that each successive SMTP relay adds a
“Received” header to the mail headers. The purpose of these headers is
to enable audit of mail transmission, and perhaps to distinguish
between regular mail and spam. Here is an extract from the headers of
a message recently received from the “perpass” mailing list:</t>

<t><spanx style="verb">
   Received: from 192-000-002-044.zone13.example.org (HELO ?192.168.1.100?)
   (xxx.xxx.xxx.xxx) by lvps192-000-002-219.example.net with ESMTPSA
   (DHE-RSA-AES256-SHA encrypted, authenticated); 27 Oct 2013 21:47:14 +0100
   Message-ID: &lt;526D7BD2.7070908@example.org&gt;
   Date: Sun, 27 Oct 2013 20:47:14 +0000
   From: Some One &lt;some.one@example.org&gt;
</spanx></t>

<t>This is the first “Received” header attached to the message by the
first SMTP relay; for privacy reasons, the field values have been
anonymized. We learn here that the message was submitted by “Some One”
on October 27, from a host behind a NAT (192.168.1.100) <xref target="RFC1918"/>
that used the IP address 192.0.2.44. The information remained in the
message, and is accessible by all recipients of the “perpass” mailing
list, or indeed by any attacker that sees at least one copy of the
message.</t>

<t>An attacker that can observe sufficient email traffic can regularly
update the mapping between public IP addresses and individual email
identities. Even if the SMTP traffic was encrypted on submission and
relaying, the attacker can still receive a copy of public mailing
lists like “perpass”.</t>

</section>
<section anchor="tracking-address-usage-with-web-cookies" title="Tracking address usage with web cookies">

<t>Many web sites only encrypt a small fraction of their transactions. A
popular pattern is to use HTTPS for the login information, and then
use a “cookie” to associate following clear-text transactions with the
user’s identity. Cookies are also used by various advertisement
services to quickly identify the users and serve them with
“personalized” advertisements. Such cookies are particularly useful if
the advertisement services want to keep tracking the user across
multiple sessions that may use different IP addresses.</t>

<t>As cookies are sent in clear text, an attacker can build a database
that associates cookies to IP addresses for non-HTTPS traffic. If the
IP address is already identified, the cookie can be linked to the user
identify. After that, if the same cookie appears on a new IP address,
the new IP address can be immediately associated with the
pre-determined identity.</t>

</section>
<section anchor="graph-based-approaches-to-address-correlation" title="Graph-based approaches to address correlation">

<t>An attacker can track traffic from an IP address not yet associated
with an individual to various public services (e.g. websites, mail
servers, game servers), and exploit patterns in the observed traffic
to correlate this address with other addresses that show similar
patterns. For example, any two addresses that show connections to the
same IMAP or webmail services, the same set of favorite websites, and
game servers at similar times of day may be associated with the same
individual. Correlated addresses can then be tied to an individual
through one of the techniques above, walking the “network graph” to
expand the set of attributable traffic.</t>

</section>
<section anchor="tracking-of-mac-addresses" title="Tracking of MAC Addresses">

<t>Moving back down the stack, technologies like Ethernet or Wi-Fi use
MAC Addresses to identify link-level destinations. MAC Addresses
assigned according to IEEE-802 standards are unique to the device. If
the link is publicly accessible, an attacker can track it. For
example, the attacker can track the wireless traffic at public Wi-Fi
networks. Simple devices can monitor the traffic, and reveal which MAC
Addresses are present. If the network does not use some form of Wi-Fi
encryption, or if the attacker can access the decrypted traffic, the
analysis will also provide the correlation between MAC Addresses and
IP addresses. Additional monitoring using techniques exposed in the
previous sections will reveal the correlation between MAC Addresses,
IP Addresses, and user identity.</t>

<t>Given that large-scale databases of the MAC addresses of wireless
access points for geolocation purposes have been known to exist for
some time, the attacker could easily build a database linking MAC
Addresses and device or user identities, and use it to track the
movement of devices and of their owners.</t>

</section>
</section>
</section>
<section anchor="reported" title="Reported Instances of Large-Scale Attacks">

<t>The situation in reality is more bleak than that suggested by an
analysis of our idealized attacker. Through revelations of sensitive
documents in several media outlets, the Internet community has been
made aware of several intelligence activities conducted by US and UK
national intelligence agencies, particularly the US National Security
Agency (NSA) and the UK Government Communications Headquarters
(GCHQ). These documents have revealed methods that these agencies use
to attack Internet applications and obtain sensitive user information.</t>

<t>First, they have confirmed that these agencies have capabilities in
line with those of our idealized attacker, thorugh the large-scale
passive collection of Internet traffic
<xref target="pass1"/><xref target="pass2"/><xref target="pass3"/><xref target="pass4"/>. For example: - The NSA XKEYSCORE
system accesses data from multiple access points and searches for
“selectors” such as email addresses, at the scale of tens of terabytes
of data per day.  - The GCHQ Tempora system appears to have access to
around 1,500 major cables passing through the UK.  - The NSA MUSCULAR
program tapped cables between data centers belonging to major service
providers.  - Several programs appear to perform wide-scale collection
of cookies in web traffic and location data from location-aware
portable devices such as smartphones.</t>

<t>However, the capabilities described go beyond those available to our idealized attacker, including: </t>

<t><list style="symbols">
  <t>Decryption of TLS-protected Internet sessions
<xref target="dec1"/><xref target="dec2"/><xref target="dec3"/>.  For example, the NSA BULLRUN project
appears to have had a budget of around $250M per year to undermine
encryption through multiple approaches.</t>
  <t>Insertion of NSA devices as a man-in-the-middle of Internet
transactions <xref target="TOR1"/><xref target="TOR2"/>.  For example, the NSA QUANTUM system
appears to use several different techniques to hijack HTTP
connections, ranging from DNS response injection to HTTP 302
redirects.</t>
  <t>Direct acquisition of bulk data and metadata from service providers
<xref target="dir1"/><xref target="dir2"/><xref target="dir3"/>.  For example, the NSA PRISM program
provides the agency with access to many types of user data (e.g.,
email, chat, VoIP).</t>
  <t>Use of implants (covert modifications or malware) to undermine security and anonymity features <xref target="dec2"/><xref target="TOR1"/><xref target="TOR2"/>.  For example:  <list style="symbols">
      <t>NSA appears to use the QUANTUM man-in-the-middle system to direct users to a FOXACID server, which delivers an implant to compromise the browser of a user of the Tor anonymous communications network.</t>
      <t>Implants are apparently available for Cisco, Juniper, Huawei, Dell, and HP network elements, provided by the NSA Advanced Network Technology group <xref target="spiegel1"/> </t>
      <t>Compromised hosts at botnet scale, using tools by the NSA’s Remote Operations Center <xref target="spiegel3"/></t>
      <t>The BULLRUN program mentioned above includes the addition of covert modifications to software as one means to undermine encryption.  </t>
      <t>There is also some suspicion that NSA modifications to the DUAL_EC_DRBG random number generator were made to ensure that keys generated using that generator could be predicted by NSA.  These suspicions have been reinforced by reports that RSA Security was paid roughly $10M to make DUAL_EC_DRBG the default in their products.</t>
    </list></t>
</list></t>

<t>We use the term “pervasive attack” <xref target="RFC7258"/> to collectively
describe these operations.  The term “pervasive” is used because the
attacks are designed to indiscriminately gather as much data as
possible and to apply selective analysis on targets after the fact.
This means that all, or nearly all, Internet communications are
targets for these attacks.  To achieve this scale, the attacks are
physically pervasive; they affect a large number of Internet
communications. They are pervasive in content, consuming and
exploiting any information revealed by the protocol. And they are
pervasive in technology, exploiting many different vulnerabilities in
many different protocols.</t>

<t>It’s important to note that although the attacks mentioned above were
executed by NSA and GCHQ, there are many other organizations that can
mount pervasive surveillance attacks. Because of the resources
required to achieve pervasive scale, these attacks are most commonly
undertaken by nation-state actors.  For example, the Chinese Internet
filtering system known as the “Great Firewall of China” uses several
techniques that are similar to the QUANTUM program, and which have a
high degree of pervasiveness with regard to the Internet in China.</t>

</section>
<section anchor="model" title="Threat Model">

<t>Given these disclosures, we must consider a broader threat model.</t>

<t>Pervasive surveillance aims to collect information across a large
number of Internet communications, analyzing the collected
communications to identify information of interest within individual
communications, or inferring information from correlated
communications.  his analysis sometimes benefits from decryption of
encrypted communications and deanonymization of anonymized
communications.  As a result, these attackers desire both access to
the bulk of Internet traffic and to the keying material required to
decrypt any traffic that has been encrypted.  Even if keys are not
available, note that the presence of a communication and the fact that
it is encrypted may both be inputs to an analysis, even if the
attacker cannot decrypt the communication.</t>

<t>The attacks listed above highlight new avenues both for access to
traffic and for access to relevant encryption keys.  They further
indicate that the scale of surveillance is sufficient to provide a
general capability to cross-correlate communications, a threat not
previously thought to be relevant at the scale of the Internet.</t>

<section anchor="attacker-capabilities" title="Attacker Capabilities">

<texttable>
      <ttcol align='left'>Attack Class</ttcol>
      <ttcol align='left'>Capability</ttcol>
      <c>Passive observation</c>
      <c>Directly capture data in transit</c>
      <c>Passive inference</c>
      <c>Infer from reduced/encrypted data</c>
      <c>Active</c>
      <c>Manipulate / inject data in transit</c>
      <c>Static key exfiltration</c>
      <c>Obtain key material once / rarely</c>
      <c>Dynamic key exfiltration</c>
      <c>Obtain per-session key material</c>
      <c>Content exfiltration</c>
      <c>Access data at rest</c>
</texttable>

<t>Security analyses of Internet protocols commonly consider two classes
of attacker: flow access attackers, who can simply listen in on
communications as they transit the network, and flow modification
attackers, who can modify or delete packets in addition to simply
collecting them.</t>

<t>In the context of pervasive passive surveillance, these attacks take
on an even greater significance.  In the past, these attackers were
often assumed to operate near the edge of the network, where attacks
can be simpler. For example, in some LANs, it is simple for any node
to engage in passive listening to other nodes’ traffic or inject
packets to accomplish flow modification attacks. However, as we now
know, both passive and flow modification attacks are undertaken by
pervasive attackers closer to the core of the network, greatly
expanding the scope and capability of the attacker.</t>

<t>Eavesdropping and observation at a larger scale make passive inference
attacks easier to carry out: a flow access attacker with access to a
large portion of the Internet can analyze collected traffic to create
a much more detailed view of individual behavior than an attacker that
collects at a single point. Even the usual claim that encryption
defeats flow access attackers is weakened, since a pervasive flow
access attacker can infer relationships from correlations over large
numbers of sessions, e.g., pairing encrypted sessions with unencrypted
sessions from the same host, or performing traffic fingerprinting
between known and unknown encrypted sessions.  Reports on the NSA
XKEYSCORE system would indicate it is an example of such an attacker.</t>

<t>A pervasive flow modification attacker likewise has capabilities
beyond those of a localized flow modification attacker.  flow
modification attacks are often limited by network topology, for
example by a requirement that the attacker be able to see a targeted
session as well as inject packets into it.  A pervasive flow
modification attacker with access at multiple points within the core
of the Internet is able to overcome these topological limitations and
perform attacks over a much broader scope.  Being positioned in the
core of the network rather than the edge can also enable a pervasive
flow modification attacker to reroute targeted traffic, amplifying the
ability to perform both eavesdropping and traffic injection.
Pervasive flow modification attackers can also benefit from pervasive
passive collection to identify vulnerable hosts.</t>

<t>While not directly related to pervasiveness, attackers that are in a
position to mount a pervasive flow modification attack are also often
in a position to subvert authentication, a traditional protection
against such attacks.  Authentication in the Internet is often
achieved via trusted third party authorities such as the Certificate
Authorities (CAs) that provide web sites with authentication
credentials. An attacker with sufficient resources may also be able to
induce an authority to grant credentials for an identity of the
attacker’s choosing.  If the parties to a communication will trust
multiple authorities to certify a specific identity, this attack may
be mounted by suborning any one of the authorities (the proverbial
“weakest link”).  Subversion of authorities in this way can allow an
flow modification attack to succeed in spite of an authentication
check.</t>

<t>Beyond these three classes (observation, inference, and active),
reports on the BULLRUN effort to defeat encryption and the PRISM
effort to obtain data from service providers suggest three more
classes of attack:</t>

<t><list style="symbols">
  <t>Static key exfiltration</t>
  <t>Dynamic key exfiltration</t>
  <t>Content exfiltration</t>
</list></t>

<t>These attacks all rely on a collaborator providing the attacker with
some information, either keys or data.  These attacks have not
traditionally been considered in scope for the Security Considerations
sections of IETF protocols, as they occur outside the protocol.</t>

<t>The term “key exfiltration” refers to the transfer of keying material
for an encrypted communication from the collaborator to the attacker.
By “static”, we mean that the transfer of keys happens once, or
rarely, typically of a long-lived key.  For example, this case would
cover a web site operator that provides the private key corresponding
to its HTTPS certificate to an intelligence agency.</t>

<t>“Dynamic” key exfiltration, by contrast, refers to attacks in which
the collaborator delivers keying material to the attacker frequently,
e.g., on a per-session basis.  This does not necessarily imply
frequent communications with the attacker; the transfer of keying
material may be virtual.  For example, if an endpoint were modified in
such a way that the attacker could predict the state of its
psuedorandom number generator, then the attacker would be able to
derive per-session keys even without per-session communications.</t>

<t>Finally, content exfiltration is the attack in which the collaborator
simply provides the attacker with the desired data or metadata. Unlike
the key exfiltration cases, this attack does not require the attacker
to capture the desired data as it flows through the network.  The risk
is to data at rest as opposed to data in transit.  This increases the
scope of data that the attacker can obtain, since the attacker can
access historical data – the attacker does not have to be listening
at the time the communication happens.</t>

<t>Exfiltration attacks can be accomplished via attacks against one of
the parties to a communication, i.e., by the attacker stealing the
keys or content rather than the party providing them willingly. In
these cases, the party may not be aware that they are collaborating,
at least at a human level.  Rather, the subverted technical assets are
“collaborating” with the attacker (by providing keys/content) without
their owner’s knowledge or consent.</t>

<t>Any party that has access to encryption keys or unencrypted data can
be a collaborator.  While collaborators are typically the endpoints of
a communication (with encryption securing the links), intermediaries
in an unencrypted communication can also facilitate content
exfiltration attacks as collaborators by providing the attacker access
to those communications.  For example, documents describing the NSA
PRISM program claim that NSA is able to access user data directly from
servers, where it is stored unencrypted.  In these cases, the operator
of the server would be a collaborator, if an unwitting one.  By
contrast, in the NSA MUSCULAR program, a set of collaborators enabled
attackers to access the cables connecting data centers used by service
providers such as Google and Yahoo.  Because communications among
these data centers were not encrypted, the collaboration by an
intermediate entity allowed NSA to collect unencrypted user data.</t>

</section>
<section anchor="attacker-costs" title="Attacker Costs">

<texttable>
      <ttcol align='left'>Attack Class</ttcol>
      <ttcol align='left'>Cost / Risk to Attacker</ttcol>
      <c>Passive observation</c>
      <c>Passive data access</c>
      <c>Passive inference</c>
      <c>Passive data access + processing</c>
      <c>Active</c>
      <c>Active data access + processing</c>
      <c>Static key exfiltration</c>
      <c>One-time interaction</c>
      <c>Dynamic key exfiltration</c>
      <c>Ongoing interaction / code change</c>
      <c>Content exfiltration</c>
      <c>Ongoing, bulk interaction</c>
</texttable>

<t>Each of the attack types discussed in the previous section entails
certain costs and risks. These costs differ by attack, and can be
helpful in guiding response to pervasive attack.</t>

<t>Depending on the attack, the attacker may be exposed to several types
of risk, ranging from simply losing access to arrest or prosecution.
In order for any of these negative consequences to occur, however, the
attacker must first be discovered and identified.  So the primary risk
we focus on here is the risk of discovery and attribution.</t>

<t>A flow access attack is the simplest to mount in some ways.  The base
requirement is that the attacker obtain physical access to a
communications medium and extract communications from it.  For
example, the attacker might tap a fiber-optic cable, acquire a mirror
port on a switch, or listen to a wireless signal.  The need for these
taps to have physical access or proximity to a link exposes the
attacker to the risk that the taps will be discovered.  For example, a
fiber tap or mirror port might be discovered by network operators
noticing increased attenuation in the fiber or a change in switch
configuration.  Of course, flow access attacks may be accomplished
with the cooperation of the network operator, in which case there is a
risk that the attacker’s interactions with the network operator will
be exposed.</t>

<t>In many ways, the costs and risks for an flow modification attack are
similar to those for a flow access attack, with a few additions.  An
flow modification attacker requires more robust network access than a
flow access attacker, since for example they will often need to
transmit data as well as receiving it.  In the wireless example above,
the attacker would need to act as an transmitter as well as receiver,
greatly increasing the probability the attacker will be discovered
(e.g., using direction-finding technology).  flow modification attacks
are also much more observable at higher layers of the network.  For
example, an flow modification attacker that attempts to use a
mis-issued certificate could be detected via Certificate Transparency
<xref target="RFC6962"/>.</t>

<t>In terms of raw implementation complexity, flow access attacks require
only enough processing to extract information from the network and
store it.  flow modification attacks, by contrast, often depend on
winning race conditions to inject pakets into active connections.  So
flow modification attacks in the core of the network require
processing hardware to that can operate at line speed (roughly 100Gbps
to 1Tbps in the core) to identify opportunities for attack and insert
attack traffic in a high-volume traffic.  Key exfiltration attacks
rely on flow access attack for access to encrypted data, with the
collaborator providing keys to decrypt the data.  So the attacker
undertakes the cost and risk of a flow access attack, as well as
additional risk of discovery via the interactions that the attacker
has with the collaborator.</t>

<t>In this sense, static exfiltration has a lower risk profile than
dynamic.  In the static case, the attacker need only interact with the
collaborator a small number of times, possibly only once, say to
exchange a private key.  In the dynamic case, the attacker must have
continuing interactions with the collaborator.  As noted above these
interactions may real, such as in-person meetings, or virtual, such as
software modifications that render keys available to the attacker.
Both of these types of interactions introduce a risk that they will be
discovered, e.g., by employees of the collaborator organization
noticing suspicious meetings or suspicious code changes.</t>

<t>Content exfiltration has a similar risk profile to dynamic key
exfiltration.  In a content exfiltration attack, the attacker saves
the cost and risk of conducting a flow access attack.  The risk of
discovery through interactions with the collaborator, however, is
still present, and may be higher.  The content of a communication is
obviously larger than the key used to encrypt it, often by several
orders of magnitude.  So in the content exfiltration case, the
interactions between the collaborator and the attacker need to be much
higher-bandwidth than in the key exfiltration cases, with a
corresponding increase in the risk that this high-bandwidth channel
will be discovered.</t>

<t>It should also be noted that in these latter three exfiltration cases,
the collaborator also undertakes a risk that his collaboration with
the attacker will be discovered.  Thus the attacker may have to incur
additional cost in order to convince the collaborator to participate
in the attack.  Likewise, the scope of these attacks is limited to
case where the attacker can convince a collaborator to participate.
If the attacker is a national government, for example, it may be able
to compel participation within its borders, but have a much more
difficult time recruiting foreign collaborators.</t>

<t>As noted above, the collaborator in an exfiltration attack can be
unwitting; the attacker can steal keys or data to enable the attack.
In some ways, the risks of this approach are similar to the case of an
active collaborator.  In the static case, the attacker needs to steal
information from the collaborator once; in the dynamic case, the
attacker needs to continued presence inside the collaborators systems.
The main difference is that the risk in this case is of automated
discovery (e.g., by intrusion detection systems) rather than discovery
by humans.</t>

</section>
</section>
<section anchor="security-considerations" title="Security Considerations">

<t>This document describes a threat model for pervasive surveillance
attacks. Mitigations are to be given in a future document.</t>

</section>
<section anchor="iana-considerations" title="IANA Considerations">

<t>This document has no actions for IANA.</t>

</section>
<section anchor="acknowledgements" title="Acknowledgements">

<t>Thanks to Dave Thaler for the list of attacks and taxonomy; to
Security Area Directors Stephen Farrell, Sean Turner, and Kathleen
Moriarty for starting and managing the IETF’s discussion on pervasive
attack; and to Stephan Neuhaus, Mark Townsley, Chris Inacio, Evangelos
Halepilidis, Bjoern Hoehrmann, Aziz Mohaisen, as well as the IAB
Privacy and Security Program, for their input.</t>

</section>


  </middle>

  <back>

    <references title='Normative References'>

&RFC6973;


    </references>

    <references title='Informative References'>

<reference anchor="pass1" target="http://www.theguardian.com/world/2013/jun/27/nsa-online-metadata-collection">
  <front>
    <title>How the NSA is still harvesting your online data</title>
    <author >
      <organization>The Guardian</organization>
    </author>
    <date year="2013"/>
  </front>
</reference>
<reference anchor="pass2" target="http://www.theguardian.com/world/2013/jun/08/nsa-prism-server-collection-facebook-google">
  <front>
    <title>NSA's Prism surveillance program: how it works and what it can do</title>
    <author >
      <organization>The Guardian</organization>
    </author>
    <date year="2013"/>
  </front>
</reference>
<reference anchor="pass3" target="http://www.theguardian.com/world/2013/jul/31/nsa-top-secret-program-online-data">
  <front>
    <title>XKeyscore: NSA tool collects 'nearly everything a user does on the internet'</title>
    <author >
      <organization>The Guardian</organization>
    </author>
    <date year="2013"/>
  </front>
</reference>
<reference anchor="pass4" target="http://www.theguardian.com/uk/2013/jun/21/how-does-gchq-internet-surveillance-work">
  <front>
    <title>How does GCHQ's internet surveillance work?</title>
    <author >
      <organization>The Guardian</organization>
    </author>
    <date year="n.d."/>
  </front>
</reference>
<reference anchor="dec1" target="http://www.nytimes.com/2013/09/06/us/nsa-foils-much-internet-encryption.html">
  <front>
    <title>N.S.A. Able to Foil Basic Safeguards of Privacy on Web</title>
    <author >
      <organization>The New York Times</organization>
    </author>
    <date year="2013"/>
  </front>
</reference>
<reference anchor="dec2" target="http://www.theguardian.com/world/interactive/2013/sep/05/nsa-project-bullrun-classification-guide">
  <front>
    <title>Project Bullrun – classification guide to the NSA's decryption program</title>
    <author >
      <organization>The Guardian</organization>
    </author>
    <date year="2013"/>
  </front>
</reference>
<reference anchor="dec3" target="http://www.theguardian.com/world/2013/sep/05/nsa-gchq-encryption-codes-security">
  <front>
    <title>Revealed: how US and UK spy agencies defeat internet privacy and security</title>
    <author >
      <organization>The Guardian</organization>
    </author>
    <date year="2013"/>
  </front>
</reference>
<reference anchor="TOR" target="https://www.torproject.org/">
  <front>
    <title>Tor</title>
    <author >
      <organization>The Tor Project</organization>
    </author>
    <date year="2013"/>
  </front>
</reference>
<reference anchor="TOR1" target="https://www.schneier.com/blog/archives/2013/10/how_the_nsa_att.html">
  <front>
    <title>How the NSA Attacks Tor/Firefox Users With QUANTUM and FOXACID</title>
    <author initials="B." surname="Schneier" fullname="Bruce Schneier">
      <organization></organization>
    </author>
    <date year="2013"/>
  </front>
</reference>
<reference anchor="TOR2" target="http://www.theguardian.com/world/interactive/2013/oct/04/tor-stinks-nsa-presentation-document">
  <front>
    <title>'Tor Stinks' presentation – read the full document</title>
    <author >
      <organization>The Guardian</organization>
    </author>
    <date year="2013"/>
  </front>
</reference>
<reference anchor="dir1" target="http://www.theguardian.com/world/2013/jun/06/nsa-phone-records-verizon-court-order">
  <front>
    <title>NSA collecting phone records of millions of Verizon customers daily</title>
    <author >
      <organization>The Guardian</organization>
    </author>
    <date year="2013"/>
  </front>
</reference>
<reference anchor="dir2" target="http://www.theguardian.com/world/2013/jun/06/us-tech-giants-nsa-data">
  <front>
    <title>NSA Prism program taps in to user data of Apple, Google and others</title>
    <author >
      <organization>The Guardian</organization>
    </author>
    <date year="2013"/>
  </front>
</reference>
<reference anchor="dir3" target="http://www.theguardian.com/world/interactive/2013/sep/05/sigint-nsa-collaborates-technology-companies">
  <front>
    <title>Sigint – how the NSA collaborates with technology companies</title>
    <author >
      <organization>The Guardian</organization>
    </author>
    <date year="2013"/>
  </front>
</reference>
<reference anchor="secure" target="http://www.theguardian.com/world/2013/sep/05/nsa-how-to-remain-secure-surveillance">
  <front>
    <title>NSA surveillance: A guide to staying secure</title>
    <author initials="B." surname="Schneier" fullname="Bruce Schneier">
      <organization>The Guardian</organization>
    </author>
    <date year="2013"/>
  </front>
</reference>
<reference anchor="snowden" target="http://www.technologyreview.com/news/519171/nsa-leak-leaves-crypto-math-intact-but-highlights-known-workarounds/">
  <front>
    <title>NSA Leak Leaves Crypto-Math Intact but Highlights Known Workarounds</title>
    <author >
      <organization>Technology Review</organization>
    </author>
    <date year="2013"/>
  </front>
</reference>
<reference anchor="spiegel1" target="http://www.spiegel.de/international/world/nsa-secret-toolbox-ant-unit-offers-spy-gadgets-for-every-need-a-941006.html">
  <front>
    <title>NSA's Secret Toolbox: Unit Offers Spy Gadgets for Every Need</title>
    <author initials="." surname="C Stocker" fullname="Christian Stocker">
      <organization></organization>
    </author>
    <date year="2013" month="December" day="30"/>
  </front>
</reference>
<reference anchor="spiegel3" target="http://www.spiegel.de/international/world/new-snowden-docs-indicate-scope-of-nsa-preparations-for-cyber-battle-a-1013409.html">
  <front>
    <title>The Digital Arms Race: NSA Preps America for Future Battle</title>
    <author initials="." surname="H Schmundt" fullname="Hilmar Schmundt">
      <organization></organization>
    </author>
    <date year="2014" month="January" day="17"/>
  </front>
</reference>
<reference anchor="key-recovery" target="http://crypto.stanford.edu/~pgolle/papers/escrow.pdf">
  <front>
    <title>The Design and Implementation of Protocol-Based Hidden Key Recovery</title>
    <author initials="P." surname="Golle" fullname="Phillippe Golle">
      <organization></organization>
    </author>
    <date year="2003"/>
  </front>
</reference>
&RFC1035;
&RFC1918;
&RFC1939;
&RFC2015;
&RFC2821;
&RFC3261;
&RFC3365;
&RFC3501;
&RFC3851;
&RFC4033;
&RFC4301;
&RFC4303;
&RFC4306;
&RFC4949;
&RFC5246;
&RFC5321;
&RFC5655;
&RFC5750;
&RFC6120;
&RFC6962;
&RFC6698;
&RFC7011;
&RFC7258;


    </references>



  </back>
</rfc>