Network Working Group                                          R. Barnes
Intended status: Informational                               B. Schneier
Expires: August 10, 2015
                                                             C. Jennings

                                                               T. Hardie

                                                             B. Trammell

                                                              C. Huitema

                                                             D. Borkmann

                                                       February 06, 2015

 Confidentiality in the Face of Pervasive Surveillance: A Threat Model
                         and Problem Statement


   Documents published in 2013 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 a completely passive attacker with an interest in
   undetected, indiscriminate eavesdropping, then expand the threat
   model with a set of verified attacks that have been published.  Based
   on this threat model, we discuss the techniques that can be employed
   in Internet protocol design to increase the protocols robustness to
   pervasive surveillance.

Status of This Memo

   This Internet-Draft is submitted in full conformance with the
   provisions of BCP 78 and BCP 79.

   Internet-Drafts are working documents of the Internet Engineering
   Task Force (IETF).  Note that other groups may also distribute
   working documents as Internet-Drafts.  The list of current Internet-
   Drafts is at

   Internet-Drafts are draft documents valid for a maximum of six months
   and may be updated, replaced, or obsoleted by other documents at any
   time.  It is inappropriate to use Internet-Drafts as reference
   material or to cite them other than as "work in progress."

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   This Internet-Draft will expire on August 10, 2015.

Copyright Notice

   Copyright (c) 2015 IETF Trust and the persons identified as the
   document authors.  All rights reserved.

   This document is subject to BCP 78 and the IETF Trust's Legal
   Provisions Relating to IETF Documents
   ( in effect on the date of
   publication of this document.  Please review these documents
   carefully, as they describe your rights and restrictions with respect
   to this document.  Code Components extracted from this document must
   include Simplified BSD License text as described in Section 4.e of
   the Trust Legal Provisions and are provided without warranty as
   described in the Simplified BSD License.

1.  Introduction

   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.

   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 [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

   The remainder of this document is structured as follows.  In
   Section 3, we describe an idealized passive attacker, one which could
   completely undetectably compromise communications at Internet scale.
   In Section 4, we provide a brief summary of some attacks that have
   been disclosed, and use these to expand the assumed capabilities of
   our idealized attacker.  Section 5 describes a threat model based on
   these attacks, focusing on classes of attack that have not been a
   focus of Internet engineering to date.

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2.  Terminology

   This document makes extensive use of standard security and privacy
   terminology; see [RFC4949] and [RFC6973].  Terms used from [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:

   Passive Attack:  In this document, the term passive attack is used
      with respect to the traffic stream: a passive attack 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.  Passive
      attacks are undetectable from the endpoints.

   Active Attack:  In constrast to a passive attack, and active attack
      may modify a traffic stream, at the cost of possible detection at
      the endpoints.

   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 [RFC7258]

   Observation:  Information collected directly from communications by
      an eavesdropper or observer.  For example, the knowledge that
      <> sent a message to <> via SMTP
      taken from the headers of an observed SMTP message would be an

   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

   Collaborator:  An entity that is a legitimate participant in a
      communication, but who deliberately provides information about
      that interaction to an attacker.

   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.

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   Key Exfiltration:  The transmission of keying material for an
      encrypted communication from a collaborator, deliberately or
      unwittingly, to an attacker

   Content Exfiltration:  The transmission of the content of a
      communication from a collaborator, deliberately or unwittingly, to
      an attacker

3.  An Idealized Pervasive Passive Attacker

   In considering the threat posed by pervasive surveillance, we begin
   by defining an idealized pervasive passive attacker.  While this
   attacker is less capable than those which we now know to have
   compromised the Internet from press reports, as elaborated in
   Section 4, 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.

   Our idealized attacker is an indiscriminate eavesdropper on an
   Internet-attached computer network that:

   o  can observe every packet of all communications at any hop in any
      network path between an initiator and a recipient;

   o  can observe data at rest in any intermediate system between the
      endpoints controlled by the initiator and recipient; and

   o  can share information with other such attackers; but

   o  takes no other action with respect to these communications (i.e.,
      blocking, modification, injection, etc.).

   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

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   inference, especially inference based only on unprotected portions of
   communications (e.g.  IP and TCP headers for TLS [RFC5246]).

3.1.  Information subject to direct observation

   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 [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 [RFC1035], as DNSSEC [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.

   Protocols which imply the storage of some data at rest in
   intermediaries (e.g.  SMTP [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

3.2.  Information useful for inference

   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).

   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[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.

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   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

   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.

   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

3.3.  An illustration of an ideal passive attack

   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.

3.3.1.  Analysis of IP headers

   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.

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   Tools like IPFIX [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.

   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.

3.3.2.  Correlation of IP addresses to user identities

   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

   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 "".  This particular type
   of reverse DNS lookup generally reveals only coarse-grained location
   or provider information, equivalent to that available from
   geolocation databases.

   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.

3.3.3.  Monitoring messaging clients for IP address correlation

   Even if the ISP does not cooperate, user identity can often be
   obtained via inference.  POP3 [RFC1939] and IMAP [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

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   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 [RFC3261] and many
   instant messaging services operating over the Internet using
   proprietary protocols.

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

3.3.4.  Retrieving IP addresses from mail headers

   SMTP [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:

   "Received: from (HELO
   ? ( by
   with ESMTPSA (DHE-RSA-AES256-SHA encrypted, authenticated); 27 Oct
   2013 21:47:14 +0100 Message-ID: <> Date:
   Sun, 27 Oct 2013 20:47:14 +0000 From: Some One <>

   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 (
   [RFC1918] that used the IP address  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.

   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".

3.3.5.  Tracking address usage with web cookies

   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

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   if the advertisement services want to keep tracking the user across
   multiple sessions that may use different IP addresses.

   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.

3.3.6.  Graph-based approaches to address correlation

   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.

3.3.7.  Tracking of MAC Addresses

   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.

   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.

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4.  Reported Instances of Large-Scale Attacks

   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

   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 [pass1][pass2][pass3][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.

   However, the capabilities described go beyond those available to our
   idealized attacker, including:

   o  Decryption of TLS-protected Internet sessions [dec1][dec2][dec3].
      For example, the NSA BULLRUN project appears to have had a budget
      of around $250M per year to undermine encryption through multiple

   o  Insertion of NSA devices as a man-in-the-middle of Internet
      transactions [TOR1][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

   o  Direct acquisition of bulk data and metadata from service
      providers [dir1][dir2][dir3].  For example, the NSA PRISM program
      provides the agency with access to many types of user data (e.g.,
      email, chat, VoIP).

   o  Use of implants (covert modifications or malware) to undermine
      security and anonymity features [dec2][TOR1][TOR2].  For example:

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      *  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.

      *  The BULLRUN program mentioned above includes the addition of
         covert modifications to software as one means to undermine

      *  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.

   We use the term "pervasive attack" [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.

   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.

5.  Threat Model

   Given these disclosures, we must consider a broader threat model.

   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

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   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.

   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.

5.1.  Attacker Capabilities

    | Attack Class             | Capability                          |
    | Passive observation      | Directly capture data in transit    |
    |                          |                                     |
    | Passive inference        | Infer from reduced/encrypted data   |
    |                          |                                     |
    | Active                   | Manipulate / inject data in transit |
    |                          |                                     |
    | Static key exfiltration  | Obtain key material once / rarely   |
    |                          |                                     |
    | Dynamic key exfiltration | Obtain per-session key material     |
    |                          |                                     |
    | Content exfiltration     | Access data at rest                 |

   Security analyses of Internet protocols commonly consider two classes
   of attacker: Passive attackers, who can simply listen in on
   communications as they transit the network, and active attackers, who
   can modify or delete packets in addition to simply collecting them.

   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 active attacks.  However, as we now know, both
   passive and active attacks are undertaken by pervasive attackers
   closer to the core of the network, greatly expanding the scope and
   capability of the attacker.

   Eavesdropping and observation at a larger scale make passive
   inference attacks easier to carry out: a passive attacker with access
   to a large portion of the Internet can analyze collected traffic to

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   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 passive attackers is weakened, since a pervasive
   passive 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.

   A pervasive active attacker likewise has capabilities beyond those of
   a localized active attacker.  Active 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 active 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 active attacker to reroute targeted traffic,
   amplifying the ability to perform both eavesdropping and traffic
   injection.  Pervasive active attackers can also benefit from
   pervasive passive collection to identify vulnerable hosts.

   While not directly related to pervasiveness, attackers that are in a
   position to mount a pervasive active 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
   active attack to succeed in spite of an authentication check.

   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:

   o  Static key exfiltration

   o  Dynamic key exfiltration

   o  Content exfiltration

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   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

   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.

   "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.

   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.

   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.

   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

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   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.

5.2.  Attacker Costs

     | Attack Class             | Cost / Risk to Attacker           |
     | Passive observation      | Passive data access               |
     |                          |                                   |
     | Passive inference        | Passive data access + processing  |
     |                          |                                   |
     | Active                   | Active data access + processing   |
     |                          |                                   |
     | Static key exfiltration  | One-time interaction              |
     |                          |                                   |
     | Dynamic key exfiltration | Ongoing interaction / code change |
     |                          |                                   |
     | Content exfiltration     | Ongoing, bulk interaction         |

   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.

   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.

   A passive 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, passive 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.

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   In many ways, the costs and risks for an active attack are similar to
   those for a passive attack, with a few additions.  An active attacker
   requires more robust network access than a passive 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).  Active attacks are also much more observable at
   higher layers of the network.  For example, an active attacker that
   attempts to use a mis-issued certificate could be detected via
   Certificate Transparency [RFC6962].

   In terms of raw implementation complexity, passive attacks require
   only enough processing to extract information from the network and
   store it.  Active attacks, by contrast, often depend on winning race
   conditions to inject pakets into active connections.  So active
   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 passive 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 passive
   attack, as well as additional risk of discovery via the interactions
   that the attacker has with the collaborator.

   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.

   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 passive 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.

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   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.

   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.

6.  Security Considerations

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

7.  IANA Considerations

   This document has no actions for IANA.

8.  Acknowledgements

   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.

9.  References

9.1.  Normative References

   [RFC6973]  Cooper, A., Tschofenig, H., Aboba, B., Peterson, J.,
              Morris, J., Hansen, M., and R. Smith, "Privacy
              Considerations for Internet Protocols", RFC 6973, July

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9.2.  Informative References

   [pass1]    The Guardian, "How the NSA is still harvesting your online
              data", 2013,

   [pass2]    The Guardian, "NSA's Prism surveillance program: how it
              works and what it can do", 2013,

   [pass3]    The Guardian, "XKeyscore: NSA tool collects 'nearly
              everything a user does on the internet'", 2013,

   [pass4]    The Guardian, "How does GCHQ's internet surveillance
              work?", n.d., <

   [dec1]     The New York Times, "N.S.A. Able to Foil Basic Safeguards
              of Privacy on Web", 2013,

   [dec2]     The Guardian, "Project Bullrun - classification guide to
              the NSA's decryption program", 2013,

   [dec3]     The Guardian, "Revealed: how US and UK spy agencies defeat
              internet privacy and security", 2013,

   [TOR]      The Tor Project, "Tor", 2013,

   [TOR1]     Schneier, B., "How the NSA Attacks Tor/Firefox Users With
              QUANTUM and FOXACID", 2013,

   [TOR2]     The Guardian, "'Tor Stinks' presentation - read the full
              document", 2013,

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   [dir1]     The Guardian, "NSA collecting phone records of millions of
              Verizon customers daily", 2013,

   [dir2]     The Guardian, "NSA Prism program taps in to user data of
              Apple, Google and others", 2013,

   [dir3]     The Guardian, "Sigint - how the NSA collaborates with
              technology companies", 2013,

   [secure]   Schneier, B., "NSA surveillance: A guide to staying
              secure", 2013,

   [snowden]  Technology Review, "NSA Leak Leaves Crypto-Math Intact but
              Highlights Known Workarounds", 2013,

              Golle, P., "The Design and Implementation of Protocol-
              Based Hidden Key Recovery", 2003,

   [RFC1035]  Mockapetris, P., "Domain names - implementation and
              specification", STD 13, RFC 1035, November 1987.

   [RFC1918]  Rekhter, Y., Moskowitz, R., Karrenberg, D., Groot, G., and
              E. Lear, "Address Allocation for Private Internets", BCP
              5, RFC 1918, February 1996.

   [RFC1939]  Myers, J. and M. Rose, "Post Office Protocol - Version 3",
              STD 53, RFC 1939, May 1996.

   [RFC2015]  Elkins, M., "MIME Security with Pretty Good Privacy
              (PGP)", RFC 2015, October 1996.

   [RFC2821]  Klensin, J., "Simple Mail Transfer Protocol", RFC 2821,
              April 2001.

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   [RFC3261]  Rosenberg, J., Schulzrinne, H., Camarillo, G., Johnston,
              A., Peterson, J., Sparks, R., Handley, M., and E.
              Schooler, "SIP: Session Initiation Protocol", RFC 3261,
              June 2002.

   [RFC3365]  Schiller, J., "Strong Security Requirements for Internet
              Engineering Task Force Standard Protocols", BCP 61, RFC
              3365, August 2002.

              4rev1", RFC 3501, March 2003.

   [RFC3851]  Ramsdell, B., "Secure/Multipurpose Internet Mail
              Extensions (S/MIME) Version 3.1 Message Specification",
              RFC 3851, July 2004.

   [RFC4033]  Arends, R., Austein, R., Larson, M., Massey, D., and S.
              Rose, "DNS Security Introduction and Requirements", RFC
              4033, March 2005.

   [RFC4301]  Kent, S. and K. Seo, "Security Architecture for the
              Internet Protocol", RFC 4301, December 2005.

   [RFC4303]  Kent, S., "IP Encapsulating Security Payload (ESP)", RFC
              4303, December 2005.

   [RFC4306]  Kaufman, C., "Internet Key Exchange (IKEv2) Protocol", RFC
              4306, December 2005.

   [RFC4949]  Shirey, R., "Internet Security Glossary, Version 2", RFC
              4949, August 2007.

   [RFC5246]  Dierks, T. and E. Rescorla, "The Transport Layer Security
              (TLS) Protocol Version 1.2", RFC 5246, August 2008.

   [RFC5321]  Klensin, J., "Simple Mail Transfer Protocol", RFC 5321,
              October 2008.

   [RFC5655]  Trammell, B., Boschi, E., Mark, L., Zseby, T., and A.
              Wagner, "Specification of the IP Flow Information Export
              (IPFIX) File Format", RFC 5655, October 2009.

   [RFC5750]  Ramsdell, B. and S. Turner, "Secure/Multipurpose Internet
              Mail Extensions (S/MIME) Version 3.2 Certificate
              Handling", RFC 5750, January 2010.

   [RFC6120]  Saint-Andre, P., "Extensible Messaging and Presence
              Protocol (XMPP): Core", RFC 6120, March 2011.

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   [RFC6962]  Laurie, B., Langley, A., and E. Kasper, "Certificate
              Transparency", RFC 6962, June 2013.

   [RFC6698]  Hoffman, P. and J. Schlyter, "The DNS-Based Authentication
              of Named Entities (DANE) Transport Layer Security (TLS)
              Protocol: TLSA", RFC 6698, August 2012.

   [RFC7011]  Claise, B., Trammell, B., and P. Aitken, "Specification of
              the IP Flow Information Export (IPFIX) Protocol for the
              Exchange of Flow Information", STD 77, RFC 7011, September

   [RFC7258]  Farrell, S. and H. Tschofenig, "Pervasive Monitoring Is an
              Attack", BCP 188, RFC 7258, May 2014.

Authors' Addresses

   Richard Barnes


   Bruce Schneier


   Cullen Jennings


   Ted Hardie


   Brian Trammell


   Christian Huitema


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   Daniel Borkmann


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