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Versions: (draft-gont-predictable-protocol-ids) 00 01 02 03 04 05 06 07

Internet Research Task Force (IRTF)                              F. Gont
Internet-Draft                                              SI6 Networks
Intended status: Informational                                   I. Arce
Expires: July 10, 2021                                         Quarkslab
                                                         January 6, 2021


           On the Generation of Transient Numeric Identifiers
               draft-irtf-pearg-numeric-ids-generation-05

Abstract

   This document performs an analysis of the security and privacy
   implications of different types of "transient numeric identifiers"
   used in IETF protocols, and tries to categorize them based on their
   interoperability requirements and the associated failure severity
   when such requirements are not met.  Subsequently, it provides advice
   on possible algorithms that could be employed to satisfy the
   interoperability requirements of each identifier category, while
   minimizing the negative security and privacy implications, thus
   providing guidance to protocol designers and protocol implementers.
   Finally, it describes a number of algorithms that have been employed
   in real implementations to generate transient numeric identifiers and
   analyzes their security and privacy properties.

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
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   Internet-Drafts are draft documents valid for a maximum of six months
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   material or to cite them other than as "work in progress."

   This Internet-Draft will expire on July 10, 2021.

Copyright Notice

   Copyright (c) 2021 IETF Trust and the persons identified as the
   document authors.  All rights reserved.





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   This document is subject to BCP 78 and the IETF Trust's Legal
   Provisions Relating to IETF Documents
   (https://trustee.ietf.org/license-info) 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.

Table of Contents

   1.  Introduction  . . . . . . . . . . . . . . . . . . . . . . . .   3
   2.  Terminology . . . . . . . . . . . . . . . . . . . . . . . . .   4
   3.  Threat Model  . . . . . . . . . . . . . . . . . . . . . . . .   5
   4.  Issues with the Specification of Transient Numeric
       Identifiers . . . . . . . . . . . . . . . . . . . . . . . . .   5
   5.  Protocol Failure Severity . . . . . . . . . . . . . . . . . .   6
   6.  Categorizing Transient Numeric Identifiers  . . . . . . . . .   6
   7.  Common Algorithms for Transient Numeric Identifier Generation   9
     7.1.  Category #1: Uniqueness (soft failure)  . . . . . . . . .   9
     7.2.  Category #2: Uniqueness (hard failure)  . . . . . . . . .  12
     7.3.  Category #3: Uniqueness, stable within context (soft
           failure)  . . . . . . . . . . . . . . . . . . . . . . . .  12
     7.4.  Category #4: Uniqueness, monotonically increasing within
           context (hard failure)  . . . . . . . . . . . . . . . . .  14
   8.  Common Vulnerabilities Associated with Transient Numeric
       Identifiers . . . . . . . . . . . . . . . . . . . . . . . . .  20
     8.1.  Network Activity Correlation  . . . . . . . . . . . . . .  20
     8.2.  Information Leakage . . . . . . . . . . . . . . . . . . .  21
     8.3.  Fingerprinting  . . . . . . . . . . . . . . . . . . . . .  22
     8.4.  Exploitation of the Semantics of Transient Numeric
           Identifiers . . . . . . . . . . . . . . . . . . . . . . .  23
     8.5.  Exploitation of Collisions of Transient Numeric
           Identifiers . . . . . . . . . . . . . . . . . . . . . . .  23
     8.6.  Cryptanalysis . . . . . . . . . . . . . . . . . . . . . .  23
   9.  Vulnerability Analysis of Specific Transient Numeric
       Identifiers Categories  . . . . . . . . . . . . . . . . . . .  24
     9.1.  Category #1: Uniqueness (soft failure)  . . . . . . . . .  24
     9.2.  Category #2: Uniqueness (hard failure)  . . . . . . . . .  24
     9.3.  Category #3: Uniqueness, stable within context (soft
           failure)  . . . . . . . . . . . . . . . . . . . . . . . .  24
     9.4.  Category #4: Uniqueness, monotonically increasing within
           context (hard failure)  . . . . . . . . . . . . . . . . .  25
   10. IANA Considerations . . . . . . . . . . . . . . . . . . . . .  27
   11. Security Considerations . . . . . . . . . . . . . . . . . . .  27
   12. Acknowledgements  . . . . . . . . . . . . . . . . . . . . . .  27
   13. References  . . . . . . . . . . . . . . . . . . . . . . . . .  28
     13.1.  Normative References . . . . . . . . . . . . . . . . . .  28
     13.2.  Informative References . . . . . . . . . . . . . . . . .  29
   Appendix A.  Algorithms and Techniques with Known Negative



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                Implications . . . . . . . . . . . . . . . . . . . .  33
     A.1.  Predictable Linear Identifiers Algorithm  . . . . . . . .  33
     A.2.  Random-Increments Algorithm . . . . . . . . . . . . . . .  35
     A.3.  Re-using identifiers across different contexts  . . . . .  36
   Authors' Addresses  . . . . . . . . . . . . . . . . . . . . . . .  36

1.  Introduction

   Network protocols employ a variety of transient numeric identifiers
   for different protocol entities, ranging from DNS Transaction IDs
   (TxIDs) to transport protocol ephemeral ports (e.g.  TCP ephemeral
   ports) or IPv6 Interface Identifiers (IIDs).  These identifiers
   usually have specific properties (e.g. uniqueness during a specified
   period of time) that must be satisfied such that they do not result
   in negative interoperability implications, and an associated failure
   severity when such properties are not met, ranging from soft to hard
   failures.

   For more than 30 years, a large number of implementations of the TCP/
   IP protocol suite have been subject to a variety of attacks, with
   effects ranging from Denial of Service (DoS) or data injection, to
   information leakages that could be exploited for pervasive monitoring
   [RFC7258].  The root cause of these issues has been, in many cases,
   the poor selection of transient numeric identifiers in such
   protocols, usually as a result of insufficient or misleading
   specifications.  While it is generally trivial to identify an
   algorithm that can satisfy the interoperability requirements of a
   given transient numeric identifier, empirical evidence exists that
   doing so without negatively affecting the security and/or privacy
   properties of the aforementioned protocols is prone to error
   [I-D.irtf-pearg-numeric-ids-history].

   For example, implementations have been subject to security and/or
   privacy issues resulting from:

   o  Predictable TCP Initial Sequence Numbers (ISNs) [RFC0793]

   o  Predictable initial timestamp in TCP timestamps Options (TSval in
      SYN or SYN/ACK) [RFC7323]

   o  Predictable TCP ephemeral port numbers [RFC0793]

   o  Predictable IPv4 or IPv6 Fragment Identifiers (Fragment IDs)
      [RFC0791] [RFC8200]

   o  Predictable IPv6 Interface Identifiers (IIDs) [RFC4291]

   o  Predictable DNS Transaction Identifiers (TxIDs) [RFC1035]



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   Recent history indicates that when new protocols are standardized or
   new protocol implementations are produced, the security and privacy
   properties of the associated transient numeric identifiers tend to be
   overlooked, and inappropriate algorithms to generate transient
   numeric identifiers are either suggested in the specifications or
   selected by implementers.  As a result, it should be evident that
   advice in this area is warranted.

   This document contains a non-exhaustive survey of transient numeric
   identifiers employed in various IETF protocols, and aims to
   categorize such identifiers based on their interoperability
   requirements, and the associated failure severity when such
   requirements are not met.  Subsequently, it provides advice on
   possible algorithms that could be employed to satisfy the
   interoperability requirements of each category, while minimizing
   negative security and privacy implications.  Finally, it analyzes
   several algorithms that have been employed in real implementations to
   meet such requirements, and analyzes their security and privacy
   properties.

2.  Terminology

   Transient Numeric Identifier:
      A data object in a protocol specification that can be used to
      definitely distinguish a protocol object (a datagram, network
      interface, transport protocol endpoint, session, etc.) from all
      other objects of the same type, in a given context.  Transient
      numeric identifiers are usually defined as a series of bits, and
      represented using integer values.  These identifiers are typically
      dynamically selected, as opposed to statically-assigned numeric
      identifiers (see e.g.  [IANA-PROT]).  We note that different
      transient numeric identifiers may have additional requirements or
      properties depending on their specific use in a protocol.  We use
      the term "transient numeric identifier" (or simply "numeric
      identifier" or "identifier" as short forms) as a generic term to
      refer to any data object in a protocol specification that
      satisfies the identification property stated above.

   Failure Severity:
      The consequences of a failure to comply with the interoperability
      requirements of a given identifier.  Severity considers the worst
      potential consequence of a failure, determined by the system
      damage and/or time lost to repair the failure.  In this document
      we define two types of failure severity: "soft failure" and "hard
      failure".

   Soft Failure:




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      A soft failure is a recoverable condition in which a protocol does
      not operate in the prescribed manner but normal operation can be
      resumed automatically in a short period of time.  For example, a
      simple packet-loss event that is subsequently recovered with a
      packet-retransmission can be considered a soft failure.

   Hard Failure:
      A hard failure is a non-recoverable condition in which a protocol
      does not operate in the prescribed manner or it operates with
      excessive degradation of service.  For example, an established TCP
      connection that is aborted due to an error condition constitutes,
      from the point of view of the transport protocol, a hard failure,
      since it enters a state from which normal operation cannot be
      resumed.

3.  Threat Model

   Throughout this document, we assume an attacker does not have
   physical or logical access to the device(s) being attacked, and does
   not have access to the packets being transferred between the sender
   and the receiver(s) of the target protocol (if any).  However, we
   assume the attacker can send any traffic to the target device(s), to
   e.g. sample transient numeric identifiers employed by such device(s).

4.  Issues with the Specification of Transient Numeric Identifiers

   While assessing protocol specifications regarding the use of
   transient numeric identifiers, we have found that most of the issues
   discussed in this document arise as a result of one of the following
   conditions:

   o  Protocol specifications that under-specify the requirements for
      their transient numeric identifiers

   o  Protocol specifications that over-specify their transient numeric
      identifiers

   o  Protocol implementations that simply fail to comply with the
      specified requirements

   A number of protocol specifications (too many of them) have simply
   overlooked the security and privacy implications of transient numeric
   identifiers [I-D.irtf-pearg-numeric-ids-history].  Examples of them
   are the specification of TCP ephemeral ports in [RFC0793], the
   specification of TCP sequence numbers in [RFC0793], or the
   specification of the DNS TxID in [RFC1035].





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   On the other hand, there are a number of protocol specifications that
   over-specify some of their associated transient numeric identifiers.
   For example, [RFC4291] essentially overloads the semantics of IPv6
   Interface Identifiers (IIDs) by embedding link-layer addresses in the
   IPv6 IIDs, when the interoperability requirement of uniqueness could
   be achieved in other ways that do not result in negative security and
   privacy implications [RFC7721].  Similarly, [RFC2460] suggested the
   use of a global counter for the generation of Fragment Identification
   values, when the interoperability properties of uniqueness per {Src
   IP, Dst IP} could be achieved with other algorithms that do not
   result in negative security and privacy implications [RFC7739].

   Finally, there are protocol implementations that simply fail to
   comply with existing protocol specifications.  For example, some
   popular operating systems (notably Microsoft Windows) still fail to
   implement transport protocol ephemeral port randomization, as
   recommended in [RFC6056].

5.  Protocol Failure Severity

   Section 2 defines the concept of "Failure Severity", along with two
   types of failure severities that we employ throughout this document:
   soft and hard.

   Our analysis of the severity of a failure is performed from the point
   of view of the protocol in question.  However, the corresponding
   severity on the upper protocol (or application) might not be the same
   as that of the protocol in question.  For example, a TCP connection
   that is aborted might or might not result in a hard failure of the
   upper application: if the upper application can establish a new TCP
   connection without any impact on the application, a hard failure at
   the TCP protocol may have no severity at the application level.  On
   the other hand, if a hard failure of a TCP connection results in
   excessive degradation of service at the application layer, it will
   also result in a hard failure at the application.

6.  Categorizing Transient Numeric Identifiers

   This section includes a non-exhaustive survey of transient numeric
   identifiers, and proposes a number of categories that can accommodate
   these identifiers based on their interoperability requirements and
   their failure modes (soft or hard)









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   +------------------+---------------------------------+--------------+
   |    Identifier    |  Interoperability Requirements  |   Failure    |
   |                  |                                 |   Severity   |
   +------------------+---------------------------------+--------------+
   |   IPv6 Frag ID   |    Uniqueness (for IP address   |  Soft/Hard   |
   |                  |              pair)              |     (1)      |
   +------------------+---------------------------------+--------------+
   |     IPv6 IID     |  Uniqueness (and stable within  |   Soft (3)   |
   |                  |         IPv6 prefix) (2)        |              |
   +------------------+---------------------------------+--------------+
   |     TCP ISN      |   Monotonically-increasing (4)  |   Hard (4)   |
   +------------------+---------------------------------+--------------+
   |   TCP initial    |   Monotonically-increasing (5)  |   Hard (5)   |
   |    timestamps    |                                 |              |
   +------------------+---------------------------------+--------------+
   |  TCP eph. port   |  Uniqueness (for connection ID) |     Hard     |
   +------------------+---------------------------------+--------------+
   | IPv6 Flow Label  |            Uniqueness           |   None (6)   |
   +------------------+---------------------------------+--------------+
   |     DNS TxID     |            Uniqueness           |   None (7)   |
   +------------------+---------------------------------+--------------+

             Table 1: Survey of Transient Numeric Identifiers

   Notes:

   (1)
      While a single collision of Fragment ID values would simply lead
      to a single packet drop (and hence a "soft" failure), repeated
      collisions at high data rates might trash the Fragment ID space,
      leading to a hard failure [RFC4963].

   (2)
      While the interoperability requirements are simply that the
      Interface ID results in a unique IPv6 address, for operational
      reasons it is typically desirable that the resulting IPv6 address
      (and hence the corresponding Interface ID) be stable within each
      network [RFC7217] [RFC8064].

   (3)
      While IPv6 Interface IDs must result in unique IPv6 addresses,
      IPv6 Duplicate Address Detection (DAD) [RFC4862] allows for the
      detection of duplicate addresses, and hence such Interface ID
      collisions can be recovered.

   (4)
      In theory, there are no interoperability requirements for TCP
      Initial Sequence Numbers (ISNs), since the TIME-WAIT state and



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      TCP's "quiet time" concept take care of old segments from previous
      incarnations of a connection.  However, a widespread optimization
      allows for a new incarnation of a previous connection to be
      created if the ISN of the incoming SYN is larger than the last
      sequence number seen in that direction for the previous
      incarnation of the connection.  Thus, monotonically-increasing TCP
      sequence numbers allow for such optimization to work as expected
      [RFC6528], and can help avoid connection-establishment failures.

   (5)
      Strictly speaking, there are no interoperability requirements for
      the *initial* TCP timestamp employed by a TCP (i.e., the TS Value
      (TSval) in a segment with the SYN bit set).  However, a some TCP
      implementations allow a new incarnation of a previous connection
      to be created if the TSval of the incoming SYN is larger than the
      last TSval seen in that direction for the previous incarnation of
      the connection (please see [RFC6191]).  Thus, monotonically-
      increasing TCP initial timestamps (across connections to the same
      endpoint) allow for such optimization to work as expected
      [RFC6191], and can help avoid connection-establishment failures.

   (6)
      The IPv6 Flow Label is typically employed for load sharing
      [RFC7098], along with the Source and Destination IPv6 addresses.
      Reuse of a Flow Label value for the same set {Source Address,
      Destination Address} would typically cause both flows to be
      multiplexed onto the same link.  However, as long as this does not
      occur deterministically, it will not result in any negative
      implications.

   (7)
      DNS TxIDs are employed, together with the Source Address,
      Destination Address, Source Port, and Destination Port, to match
      DNS requests and responses.  However, since an implementation
      knows which DNS requests were sent for that set of {Source
      Address, Destination Address, Source Port, and Destination Port,
      DNS TxID}, a collision of TxID would result, if anything, in a
      small performance penalty (the response would nevertheless be
      discarded when it is found that it does not answer the query sent
      in the corresponding DNS query).

   Based on the survey above, we can categorize identifiers as follows:









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   +-----+---------------------------------------+---------------------+
   | Cat |                Category               |   Sample Proto IDs  |
   |  #  |                                       |                     |
   +-----+---------------------------------------+---------------------+
   |  1  |       Uniqueness (soft failure)       |  IPv6 Flow L., DNS  |
   |     |                                       |        TxIDs        |
   +-----+---------------------------------------+---------------------+
   |  2  |       Uniqueness (hard failure)       |  IPv6 Frag ID, TCP  |
   |     |                                       |    ephemeral port   |
   +-----+---------------------------------------+---------------------+
   |  3  |   Uniqueness, stable within context   |      IPv6 IIDs      |
   |     |             (soft failure)            |                     |
   +-----+---------------------------------------+---------------------+
   |  4  |  Uniqueness, monotonically increasing |     TCP ISN, TCP    |
   |     |     within context (hard failure)     |  initial timestamps |
   +-----+---------------------------------------+---------------------+

                      Table 2: Identifier Categories

   We note that Category #4 could be considered a generalized case of
   category #3, in which a monotonically increasing element is added to
   a stable (within context) element, such that the resulting
   identifiers are monotonically increasing within a specified context.
   That is, the same algorithm could be employed for both #3 and #4,
   given appropriate parameters.

7.  Common Algorithms for Transient Numeric Identifier Generation

   The following subsections describe some sample algorithms that can be
   employed for generating transient numeric identifiers for each of the
   categories above.

   All of the variables employed in the algorithms of the following
   subsections are of "unsigned integer" type, except for the "retry"
   variable, that is of (signed) "integer" type.

7.1.  Category #1: Uniqueness (soft failure)

   The requirement of uniqueness with a soft failure mode can be
   complied with a Pseudo-Random Number Generator (PRNG).

   We note that since the premise is that collisions of numeric
   identifiers of this category only leads to soft failures, in many (if
   not most) cases, the algorithm will not need to check the suitability
   of a selected identifier (i.e., in such cases check_suitable_id()
   could always return "true").





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   In scenarios where e.g. simultaneous use of a given numeric ID is
   undesirable and the implementation detects such condition, an
   implementation may opt to select the next available identifier in the
   same sequence, or select another random number.  Section 7.1.1 is an
   implementation of the former strategy, while Section 7.1.2 is an
   implementation of the later.

7.1.1.  Simple Randomization Algorithm

       /* Transient Numeric ID selection function */

       id_range = max_id - min_id + 1;
       next_id = min_id + (random() % id_range);
       retry = id_range;

       do {
           if (check_suitable_id(next_id)) {
               return next_id;
           }

           if (next_id == max_id) {
               next_id = min_id;
           } else {
               next_id++;
           }

           retry--;

       } while (retry > 0);

       return ERROR;

   NOTES:
      random() is a function that returns a pseudo-random unsigned
      integer number of appropriate size.  Note that the output needs to
      be unpredictable, and typical implementations of the POSIX
      random() function do not necessarily meet this requirement.  See
      [RFC4086] for randomness requirements for security.  Beware that
      "adapting" the length of the output of random() with a modulo
      operator (e.g., C language's "%") may change the distribution of
      the PRNG.

      The function check_suitable_id() can check, when possible and
      desirable, whether this identifier is suitable (e.g. it is not
      already in use).  Depending on how/where the numeric identifier is
      used, it may or may not be possible (or even desirable) to check
      whether the numeric identifier is in use (or whether it has been
      recently employed).  When an identifier is found to be unsuitable,



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      this algorithm selects the next available numeric identifier in
      sequence.

      Even when this algorithm selects numeric IDs randomly, it is
      biased towards the first available numeric ID after a sequence of
      unavailable numeric IDs.  For example, if this algorithm is
      employed for transport protocol ephemeral port randomization
      [RFC6056] and the local list of unsuitable port numbers (e.g.,
      registered port numbers that should not be used for ephemeral
      ports) is significant, an attacker may actually have a
      significantly better chance of guessing a port number.

      All the variables (in this and all the algorithms discussed in
      this document) are unsigned integers.

   Assuming the randomness requirements for the PRNG are met (see
   [RFC4086]), this algorithm does not suffer from any of the issues
   discussed in Section 8.

7.1.2.  Another Simple Randomization Algorithm

   The following pseudo-code illustrates another algorithm for selecting
   a random numeric identifier which, in the event a selected identifier
   is found to be unsuitable (e.g., already in use), another identifier
   is randomly selected:

       /* Transient Numeric ID selection function */

       id_range = max_id - min_id + 1;
       retry = id_range;

       do {
           next_id = min_id + (random() % id_range);

           if (check_suitable_id(next_id)) {
               return next_id;
           }

           retry--;

       } while (retry > 0);

       return ERROR;


   This algorithm might be unable to select an identifier (i.e., return
   "ERROR") even if there are suitable identifiers available, in cases




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   where a large number of identifiers are found to be unsuitable (e.g.
   "in use").

   The same considerations from Section 7.1.1 with respect to the
   properties of random() and the adaptation of its output length apply
   to this algorithm.

   Assuming the randomness requirements for the PRNG are met (see
   [RFC4086]), this algorithm does not suffer from any of the issues
   discussed in Section 8.

7.2.  Category #2: Uniqueness (hard failure)

   One of the most trivial approaches for achieving uniqueness for an
   identifier (with a hard failure mode) is to reduce the identifier
   reuse frequency by generating the numeric identifiers with a
   monotonically-increasing function (e.g. linear).  As a result, any of
   the algorithms described in Section 7.4 ("Category #4: Uniqueness,
   monotonically increasing within context (hard failure)") can be
   readily employed for complying with the requirements of this numeric
   identifier category.

   In cases where suitability (e.g. uniqueness) of the selected
   identifiers can be definitely assessed by the local system, any of
   the algorithms described in Section 7.1 ("Category #1: Uniqueness
   (soft failure)") can be readily employed for complying with the
   requirements of this numeric identifier category.

   NOTE:
      In the case of e.g.  TCP ephemeral ports or TCP ISNs, a transient
      numeric identifier that might seem suitable from the perspective
      of the local system, might actually be unsuitable from the
      perspective of the remote system (e.g., because there is state
      associated with the selected identifier at the remote system).
      Therefore, in these cases it is not possible employ the algorithms
      from Section 7.1 ("Category #1: Uniqueness (soft failure)").

7.3.  Category #3: Uniqueness, stable within context (soft failure)

   The goal of the following algorithm is to produce identifiers that
   are stable for a given context (identified by "CONTEXT"), but that
   change when the aforementioned context changes.

   In order to avoid storing in memory the numeric identifier computed
   for each CONTEXT value, the following algorithm employs a calculated
   technique (as opposed to keeping state in memory) to generate a
   stable identifier for each given context.




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       /* Transient Numeric ID selection function  */

       id_range = max_id - min_id + 1;

       retry = 0;

       do {
           offset = F(CONTEXT, retry, secret_key);
           next_id = min_id + (offset % id_range);

           if (check_suitable_id(next_id)) {
               return next_id;
           }

           retry++;

       } while (retry <= MAX_RETRIES);

       return ERROR;


   In the following algorithm, the function F() provides a stateless and
   stable per-CONTEXT numeric identifier, where CONTEXT is the
   concatenation of all the elements that define the given context.

      For example, if this algorithm is expected to produce IPv6 IIDs
      that are unique per network interface and SLAAC autoconfiguration
      prefix, the CONTEXT should be the concatenation of e.g. the
      network interface index and the SLAAC autoconfiguration prefix
      (please see [RFC7217] for an implementation of this algorithm for
      generation of stable IPv6 IIDs).

   F() must be a cryptographically-secure hash function (e.g.  SHA-256
   [FIPS-SHS]), that is computed over the concatenation of its
   arguments.  The result of F() is no more secure than the secret key,
   and therefore 'secret_key' must be unknown to the attacker, and must
   be of a reasonable length. 'secret_key' must remain stable for a
   given CONTEXT, since otherwise the numeric identifiers generated by
   this algorithm would not have the desired stability properties (i.e.,
   stable for a given CONTEXT).  In most cases, 'secret_key' can be
   selected with a PRNG (see [RFC4086] for recommendations on choosing
   secrets) at an appropriate time, and stored in stable or volatile
   storage for future use.

   The result of F() is stored in the variable 'offset', which may take
   any value within the storage type range, since we are restricting the
   resulting identifier to be in the range [min_id, max_id] in a similar
   way as in the algorithm described in Section 7.1.1.



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   check_suitable_id() checks that the candidate identifier has suitable
   uniqueness properties.  Collisions (i.e., an identifier that is not
   unique) are recovered by incrementing the 'retry' variable and
   recomputing F(), up to a maximum of MAX_RETRIES times.  However,
   recovering from collisions will usually result in identifiers that
   fail to remain constant for the specified context.  This is normally
   acceptable when the probability of collisions is small, as in the
   case of e.g.  IPv6 IIDs resulting from SLAAC [RFC7217] [RFC4941].

   For obvious reasons, the transient numeric identifiers generated with
   this algorithm allow for network activity correlation within
   "CONTEXT".  However, this is essentially a design goal of this
   category of transient numeric identifiers.

7.4.  Category #4: Uniqueness, monotonically increasing within context
      (hard failure)

7.4.1.  Per-context Counter Algorithm

   One possible way to select unique monotonically-increasing
   identifiers is to employ a per-context counter.  Such an algorithm
   could be described as follows:





























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       /* Transient Numeric ID selection function */

       id_range = max_id - min_id + 1;
       retry = id_range;
       id_inc = increment() % id_range;

       if( (next_id = lookup_counter(CONTEXT)) == ERROR){
            next_id = min_id + random() % id_range;
       }

       do {
           if ( (max_id - next_id) >= id_inc){
               next_id = next_id + id_inc;
           }
           else {
               next_id = min_id + id_inc - (max_id - next_id);
           }

           if (check_suitable_id(next_id)){
               store_counter(CONTEXT, next_id);
               return next_id;
           }

           retry = retry - id_inc;

       } while (retry > 0);

       return ERROR;

   NOTES:
      increment() returns a small integer that is employed to increment
      the current counter value to obtain a numeric ID.  This value must
      be much smaller than the number of possible values for the numeric
      IDs (i.e., "id_range").  Most implementations of this algorithm
      employ a constant increment of 1.  Using a value other than 1 may
      help mitigate some information leakages (please see below), at the
      expense of a possible increase in the numeric ID reuse frequency.

      The code above makes sure that the increment employed in the
      algorithm (id_inc) is always smaller than the number of possible
      values for the numeric IDs (i.e., "max_id - min_d + 1").  However,
      as noted above, this value must also be much smaller than the
      number of possible values for the numeric IDs.

      lookup_counter() returns the current counter for a given context,
      or an error condition if that counter does not exist.

      store_counter() saves a counter value for a given context.



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      check_suitable_id() is a function that checks whether the
      resulting identifier is acceptable (e.g., whether it is not
      already in use, etc.).

   Essentially, whenever a new identifier is to be selected, the
   algorithm checks whether there there is a counter for the
   corresponding context.  If there is, the value of such counter is
   incremented to obtain the new identifier, and the counter is updated.
   If no counter exists for such context, a new counter is created and
   initialized to a random value, and used as the new identifier.  This
   algorithm produces a per-context counter, which results in one
   monotonically-increasing function for each context.  Since each
   counter is initialized to a random value, the resulting values are
   unpredictable by an off-path attacker.

   The choice of id_inc has implications on both the security and
   privacy properties of the resulting identifiers, but also on the
   corresponding interoperability properties.  On one hand, minimizing
   the increments generally minimizes the identifier reuse frequency,
   albeit at increased predictability.  On the other hand, if the
   increments are randomized, predictability of the resulting
   identifiers is reduced, and the information leakage produced by
   global constant increments is mitigated.  However, using larger
   increments than necessary can result in higher identifier reuse
   frequency.

   This algorithm has the following drawbacks:

   o  This algorithm requires an implementation to store each per-
      CONTEXT counter in memory.  If, as a result of resource
      management, the counter for a given context must be removed, the
      last identifier value used for that context will be lost.  Thus,
      if subsequently an identifier needs to be generated for the same
      context, that counter will need to be recreated and reinitialized
      to random value, thus possibly leading to reuse/collision of
      numeric identifiers.

   o  Keeping one counter for each possible "context" may in some cases
      be considered too onerous in terms of memory requirements.

   Otherwise, the identifiers produced by this algorithm do not suffer
   from the other issues discussed in Section 8.

7.4.2.  Simple Hash-Based Algorithm

   The goal of this algorithm is to produce monotonically-increasing
   sequences, with a randomized initial value, for each given context.
   For example, if the identifiers being generated must be



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   monotonically-increasing for each {src IP, dst IP} set, then each
   possible combination of {src IP, dst IP} should have a separate
   monotonically-increasing sequence, that starts at a different random
   value.

   Instead of maintaining a per-context counter (as in the algorithm
   from Section 7.4.1), the following algorithm employs a calculated
   technique to maintain a random offset for each possible context.

   In the following algorithm, the function F() provides a (stateless)
   unpredictable offset for each given context (as identified by
   'CONTEXT').

       /* Initialization code */
       counter = 0;

       /* Transient Numeric ID selection function  */

       id_range = max_id - min_id + 1;
       id_inc = increment() % id_range;
       offset = F(CONTEXT, secret_key);
       retry = id_range;

       do {
           next_id = min_id + (offset + counter) % id_range;
           counter = counter + id_inc;

           if (check_suitable_id(next_id)) {
               return next_id;
           }

           retry = retry - id_inc;

       } while (retry > 0);

       return ERROR;


   The function F() provides a "per-CONTEXT" fixed offset within the
   numeric identifier "space".  Both the 'offset' and 'counter'
   variables may take any value within the storage type range since we
   are restricting the resulting identifier to be in the range [min_id,
   max_id] in a similar way as in the algorithm described in
   Section 7.1.1.  This allows us to simply increment the 'counter'
   variable and rely on the unsigned integer to wrap around.

   The function F() should be a cryptographically-secure hash function
   (e.g.  SHA-256 [FIPS-SHS]).  CONTEXT is the concatenation of all the



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   elements that define a given context.  For example, if this algorithm
   is expected to produce identifiers that are monotonically-increasing
   for each set (Source IP Address, Destination IP Address), CONTEXT
   should be the concatenation of these two IP addresses.

   The result of F() is no more secure than the secret key, and
   therefore 'secret_key' must be unknown to the attacker, and must be
   of a reasonable length. 'secret_key' must remain stable for a given
   CONTEXT, since otherwise the numeric identifiers generated by this
   algorithm would not have the desired stability properties (i.e.,
   monotonically-increasing for a given CONTEXT).  In most cases,
   'secret_key' can be selected with a PRNG (see [RFC4086] for
   recommendations on choosing secrets) at an appropriate time, and
   stored in stable or volatile storage for future use.

   It should be noted that, since this algorithm uses a global counter
   ("counter") for selecting identifiers (i.e., all counters share the
   same increments space), this algorithm produces an information
   leakage (as described in Section 8.2).  For example, if this
   algorithm were used for selecting TCP ephemeral ports, and an
   attacker could force a client to periodically establish a new TCP
   connection to an attacker-controlled machine (or through an attacker-
   observable routing path), the attacker could subtract consecutive
   source port values to obtain the number of outgoing TCP connections
   established globally by the target host within that time period (up
   to wrap-around issues and five-tuple collisions, of course).  This
   information leakage could be partially mitigated by employing small
   random values for the increments (i.e., increment() function),
   instead of the constant "1".

   We nevertheless note that an improved mitigation of this information
   leakage would result from employing the algorithm from Section 7.4.3,
   instead.

7.4.3.  Double-Hash Algorithm

   A trade-off between maintaining a single global 'counter' variable
   and maintaining 2**N 'counter' variables (where N is the width of the
   result of F()), could be achieved as follows.  The system would keep
   an array of TABLE_LENGTH integers, which would provide a separation
   of the increment space into multiple buckets.  This improvement could
   be incorporated into the algorithm from Section 7.4.2 as follows:









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       /* Initialization code */

       for(i = 0; i < TABLE_LENGTH; i++) {
           table[i] = random();
       }

       /* Transient Numeric ID selection function */

       id_range = max_id - min_id + 1;
       id_inc = increment() % id_range;
       offset = F(CONTEXT, secret_key1);
       index = G(CONTEXT, secret_key2) % TABLE_LENGTH;
       retry = id_range;

       do {
           next_id = min_id + (offset + table[index]) % id_range;
           table[index] = table[index] + id_inc;

           if (check_suitable_id(next_id)) {
               return next_id;
           }

          retry = retry - id_inc;

       } while (retry > 0);

       return ERROR;


   'table[]' could be initialized with random values, as indicated by
   the initialization code in the pseudo-code above.

   Both F() and G() should be cryptographically-secure hash functions
   (e.g.  SHA-256 [FIPS-SHS]) computed over the concatenation of each of
   their respective arguments.  Both F() and G() would employ the same
   CONTEXT (the concatenation of all the elements that define a given
   context), and would use separate secret keys (secret_key1, and
   secret_key2, respectively).

   The results of F() and G() are no more secure than their respective
   secret keys ('secret_key1' and 'secret_key2', respectively), and
   therefore both secret keys must be unknown to the attacker, and must
   be of a reasonable length.  Both secret keys must remain stable for
   the given CONTEXT, since otherwise the numeric identifiers generated
   by this algorithm would not have the desired stability properties
   (i.e., monotonically-increasing for a given CONTEXT).  In most cases,
   both secret keys can be selected with a PRNG (see [RFC4086] for




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   recommendations on choosing secrets) at an appropriate time, and
   stored in stable or volatile storage for future use.

   The array 'table[]' assures that successive identifiers for a given
   context will be monotonically-increasing.  Since the increments space
   is separated into TABLE_LENGTH different spaces, the identifier reuse
   frequency will be (probabilistically) lower than that of the
   algorithm in Section 7.4.2.  That is, the generation of an identifier
   for one given context will not necessarily result in increments in
   the identifier sequence for other contexts.  It is interesting to
   note that the size of 'table[]' does not limit the number of
   different identifier sequences, but rather separates the *increments*
   into TABLE_LENGTH different spaces.  The identifier sequence will
   result from adding the corresponding entry from 'table[]' to the
   variable 'offset', which selects the actual identifier sequence (as
   in the algorithm from Section 7.4.2).

   An attacker can perform traffic analysis for any "increment space"
   (i.e., context) into which the attacker has "visibility" -- namely,
   the attacker can force a node to generate identifiers where
   G(CONTEXT, secret_key2) identifies the target "increment space".
   However, the attacker's ability to perform traffic analysis is very
   reduced when compared to the predictable linear identifiers
   (described in Appendix A.1) and the hash-based identifiers (described
   in Section 7.4.2).  Additionally, an implementation can further limit
   the attacker's ability to perform traffic analysis by further
   separating the increment space (that is, using a larger value for
   TABLE_LENGTH) and/or by randomizing the increments (i.e., increment()
   returning a small random number as opposed to the constant 1).

   Otherwise, this algorithm does not suffer from the issues discussed
   in Section 8.

8.  Common Vulnerabilities Associated with Transient Numeric Identifiers

8.1.  Network Activity Correlation

   An identifier that is predictable within a given context allows for
   network activity correlation within that context.

   For example, a stable IPv6 Interface Identifier allows for network
   activity to be correlated for the context in which that Interface
   Identifier is stable [RFC7721].  A stable-per-network IPv6 Interface
   Identifier (as in [RFC7217]) allows for network activity correlation
   within a network, whereas a constant IPv6 Interface Identifier (that
   remains constant across networks) allows not only network activity
   correlation within the same network, but also across networks ("host
   tracking").



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   Similarly, a node that generates TCP ISNs with a global counter could
   allow network activity correlation across networks, since the
   communicating nodes could infer the identity of the node based on the
   TCP ISNs employed for subsequent communication instances.  Similarly,
   a node that generates predictable IPv6 Fragment Identification values
   could be subject to network activity correlation (see e.g.
   [Bellovin2002]).

8.2.  Information Leakage

   Transient numeric identifiers that are not randomized can leak out
   information to other communicating nodes.  For example, it is common
   to generate identifiers like:

                   ID = offset(CONTEXT) + mono(CONTEXT);

   This generic expression generates identifiers by adding a
   monotonically-increasing function (e.g. linear) to a randomized
   offset. offset() is constant within a given context, whereas mono()
   is monotonically-increasing function for a given context.
   Identifiers generated with this expression will generally be
   predictable within CONTEXT.

   On the other hand, mono() will result in a monotonically-increasing
   sequence within CONTEXT.  The predictability of mono(), irrespective
   of the predictability of offset(), can leak out information can be of
   use to attackers.  For example, a node that selects ephemeral port
   numbers as in:

                 ephemeral_port = offset(Dest_IP) + mono()

   that is, with a per-destination offset, but global mono() function
   (e.g., a global counter), will leak information about the number of
   outgoing connections that have been issued between any two issued
   outgoing connections.

   Similarly, a node that generates Fragment Identification values as
   in:

                 Frag_ID = offset(Src_IP, Dst_IP) + mono()

   will leak out information about the number of fragmented packets that
   have been transmitted between any two other transmitted fragmented
   packets.  The vulnerabilities described in [Sanfilippo1998a],
   [Sanfilippo1998b], and [Sanfilippo1999] are all associated with the
   use of a global mono() function (i.e., irrespective of CONTEXT) --
   particularly when it is a linear function (constant increments of 1
   for each selected transient numeric identifier).



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   Predicting transient numeric identifiers can be of help for other
   types of attacks.  For example, predictable TCP ISNs open the door to
   trivial connection-reset and data injection attacks (see e.g.
   [Joncheray1995].

8.3.  Fingerprinting

   Fingerprinting is the capability of an attacker to identify or re-
   identify a visiting user, user agent or device via configuration
   settings or other observable characteristics.  Observable protocol
   objects and characteristics can be employed to identify/re-identify a
   variety of entities, ranging from the underlying hardware or
   Operating System (vendor, type and version), to the user itself (i.e.
   his/her identity).  [EFF] illustrates web browser-based
   fingerprinting, but similar techniques can be applied at other layers
   and protocols, whether alternatively or in conjunction with it.

   Transient numeric identifiers are one of the observable protocol
   components that could be leveraged for fingerprinting purposes.  That
   is, an attacker could sample transient numeric identifiers to infer
   the algorithm (and its associated parameters, if any) for generating
   such identifiers, possibly revealing the underlying Operating System
   (OS) vendor, type, and version.  This information could possibly be
   further leveraged in conjunction with other fingerprinting techniques
   and sources.

   Evasion of protocol-stack fingerprinting can prove to be a very
   difficult task: most systems make use of a variety of protocols, each
   of which have a large number of parameters that can be set to
   arbitrary values or generated with a variety of algorithms with
   multiple parameters.

   NOTE:
      General protocol-based fingerprinting is discussed in [RFC6973],
      along with guidelines to mitigate the associated vulnerability.
      [Fyodor1998] and [Fyodor2006] are classic references on Operating
      System detection via protocol-based fingerprinting.  Nmap [nmap]
      is probably the most popular tool for remote OS detection via
      active TCP/IP stack fingerprinting. p0f [Zalewski2012], on the
      other hand, is a tool for performing remote OS detection via
      passive TCP/IP stack fingerprinting.  Finally, [TBIT] is a TCP
      fingerprinting tool that aims at characterizing the behavior of a
      remote TCP peer based on active probes, and which has been widely
      used in the research community.

   Algorithms that, from the perspective of an observer (e.g., the
   legitimate communicating peer), result in specific values or
   patterns, will allow for at least some level of fingerprinting.  For



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   example, the algorithm from Section 7.3 will typically allow
   fingerprinting within the context where the resulting identifiers are
   stable.  Similarly, the algorithms from Section 7.4 will result in a
   monotonically-increasing sequences within a given context, thus
   allowing for at least some level of fingerprinting (when the other
   communicating entity can correlate different sampled identifiers as
   belonging to the same monotonically-increasing sequence).

   Thus, where possible, algorithms from Section 7.1 should be preferred
   over algorithms that result in specific values or patterns.

8.4.  Exploitation of the Semantics of Transient Numeric Identifiers

   Identifiers that are not semantically opaque tend to be more
   predictable than semantically-opaque identifiers.  For example, a MAC
   address contains an OUI (Organizationally-Unique Identifier) which
   identifies the vendor that manufactured the network interface card.
   This fact may be leveraged by an attacker trying to "guess" MAC
   addresses, who has some knowledge about the possible NIC vendor.

   [RFC7707] discusses a number of techniques to reduce the search space
   when performing IPv6 address-scanning attacks by leveraging the
   semantics of the IIDs produced by traditional IID-generation
   algorithms that embed MAC addresses (now replaced by [RFC7217]).

8.5.  Exploitation of Collisions of Transient Numeric Identifiers

   In many cases, the collision of transient network identifiers can
   have a hard failure severity (or result in a hard failure severity if
   an attacker can cause multiple collisions deterministically, one
   after another).  For example, predictable Fragment Identification
   values open the door to Denial of Service (DoS) attacks (see e.g.
   [RFC5722].).

8.6.  Cryptanalysis

   A number of algorithms discussed in this document (such as
   Section 7.4.2 and Section 7.4.3) rely on cryptographically-secure
   hash functions.  Implementations that employ weak hash functions and
   keys of inappropriate size may be subject to cryptanalysis, where an
   attacker may be able to obtain the secret key employed for the hash
   algorithms, predict numeric identifiers, etc.

   Furthermore, an implementation that overloads the semantics of the
   secret key may result in more trivial cryptanalysis, possibly
   resulting in the leakage of the value employed for the secret key.

   NOTE:



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      [IPID-DEV] describes two vulnerable numeric ID generators that
      employ cryptographically-weak hash functions.  Additionally, one
      of such implementations employs 32-bits of a kernel address as the
      secret key for a hash function, and therefore successful
      cryptanalysis leaks the aforementioned kernel address, allowing
      for Kernel Address Space Layout Randomization (KASLR) [KASLR]
      bypass.

9.  Vulnerability Analysis of Specific Transient Numeric Identifiers
    Categories

   The following subsections analyze common vulnerabilities associated
   with the generation of identifiers for each of the categories
   identified in Section 6.

9.1.  Category #1: Uniqueness (soft failure)

   Possible vulnerabilities associated with the algorithms from
   Section 7.1 include:

   o  Use of flawed PRNGs (please see e.g.  [Zalewski2001],
      [Zalewski2002] and [Klein2007])

   An implementer should consult [RFC4086] regarding randomness
   requirements for security, and consult relevant documentation when
   employing a PRNG provided by the underlying system.

   Use of algorithms other than PRNGs for generating identifiers of this
   category is discouraged.

9.2.  Category #2: Uniqueness (hard failure)

   As noted in Section 7.2, this category can employ the same algorithms
   as Category #4, since a monotonically-increasing sequence tends to
   minimize the identifier reuse frequency.  Therefore, the
   vulnerability analysis of Section 9.4 applies to this category.

   Additionally, as noted in Section 7.2, some identifiers of this
   category might be able to use the algorithms from Section 7.1, in
   which case the same considerations from Section 9.1 apply.

9.3.  Category #3: Uniqueness, stable within context (soft failure)

   Possible vulnerabilities associated with the algorithms from
   Section 7.3 are:

   1.  Use cryptographically-weak hash functions, or inappropriate
       secret keys (whether inappropriate selection or inappropriate



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       size) that might allow for cryptanalysis, which could eventually
       be exploited by an attacker to predict future numeric
       identifiers.

   2.  Fingerprinting within the specified context.

9.4.  Category #4: Uniqueness, monotonically increasing within context
      (hard failure)

   A simple way to generalize algorithms employed for generating
   identifiers of Category #4 would be as follows:

       /* Transient Numeric ID selection function */

       id_range = max_id - min_id + 1;
       retry = id_range;
       id_inc = increment() % id_range;

       do {
           update_mono(CONTEXT, id_inc);
           next_id = min_id + (offset(CONTEXT) + \
                               mono(CONTEXT)) % id_range;

           if (check_suitable_id(next_id)) {
               return next_id;
           }

           retry = retry - id_inc;

       } while (retry > 0);

       return ERROR;


   NOTES:
      increment() returns a small integer that is employed to generate a
      monotonically-increasing function.  Some implementations employ a
      constant value for "increment()" (usually 1).  The value returned
      by increment() must be much smaller than the value computed for
      "id_range".

      update_mono(CONTEXT, id_inc) increments the counter corresponding
      to CONTEXT by "id_inc".

      mono(CONTEXT) reads the counter corresponding to CONTEXT.






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   Essentially, an identifier (next_id) is generated by adding a
   monotonically-increasing function (mono()) to an offset value,
   unknown to the attacker and stable for given context (CONTEXT).

   The following aspects of the algorithm should be considered:

   o  For the most part, it is the offset() function that results in
      identifiers that are unpredictable by an off-patch attacker.
      While the resulting sequence is known to be monotonically-
      increasing, the use of an randomized offset value makes the
      resulting values unknown to the attacker.

   o  The most straightforward "stateless" implementation of offset() is
      with a cryptographically-secure hash function that takes the
      values that identify the context and a "secret_key" (not shown in
      the figure above) as arguments.

   o  One possible implementation approach for mono() is to maintain
      per-context counters, initialized to random values.  When a new
      identifier is to be selected, the corresponding counter is looked-
      up (based on the context) and incremented, to obtain a new
      transient numeric identifier.  For example, the algorithm in
      Section 7.4.1 could be such an implementation of mono().  Another
      possible implementation of mono() would be to have mono()
      internally employ a single counter (as in the algorithm from
      Section 7.4.2), or map the increments for different contexts into
      a number of counters/buckets, such that the number of counters
      that need to be maintained in memory is reduced (as in the
      algorithm from Section 7.4.3).

   o  In all cases, a monotonically-increasing function is implemented
      by incrementing the previous value of the counter by increment().
      In the most trivial case, increment() could return the constant
      "1".  But increment() could also be implemented to return small
      random integers such that the increments are unpredictable (see
      Appendix A of [RFC7739]).  This represents a trade-off between the
      unpredictability of the resulting transient numeric IDs and the
      transient numeric ID reuse frequency.

   Considering the generic algorithm illustrated above, we can identify
   the following possible vulnerabilities:

   o  Since the algorithms for this category are similar to those of
      Section 9.3, with the addition of a monotonically-increasing
      function, all the issues discussed in Section 9.3 ("Category #3:
      Uniqueness, stable within context (soft failure)") also apply to
      this case.




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   o  mono() can be correlated to the number of identifiers generated
      for a given context (CONTEXT).  Thus, if mono() spans more than
      the necessary context, the "increments" could be leaked to other
      parties, thus disclosing information about the number of
      identifiers generated for CONTEXT.  This is particularly the case
      when the algorithm employs a constant increment of 1.  For
      example, an implementation where mono() is actually a single
      global counter, will unnecessarily leak information about the
      number of transient numeric identifiers that have been generated.
      [Fyodor2004] is one example of how such information leakages can
      be exploited.  However, limiting the span of the increments space
      will require a larger number of counters to be stored in memory
      (i.e., a larger size for the TABLE_LENGTH parameter of the
      algorithm in Section 7.4.3.

   o  Transient numeric identifiers generated with this type of
      algorithm will normally allow for fingerprinting within CONTEXT
      since, for such context, the resulting identifiers will have an
      identifiable pattern (i.e. a monotonically-increasing sequence).

10.  IANA Considerations

   There are no IANA registries within this document.  The RFC-Editor
   can remove this section before publication of this document as an
   RFC.

11.  Security Considerations

   The entire document is about the security and privacy implications of
   transient numeric identifiers.
   [I-D.gont-numeric-ids-sec-considerations] recommends that protocol
   specifications specify the interoperability requirements of their
   transient numeric identifiers, and include an assessment of the
   security and privacy implications of their transient numeric
   identifiers.  This document analyzes possible algorithms (and their
   implications) that could be employed to comply with the
   interoperability properties of transient numeric identifiers, while
   minimizing the associated negative security and privacy implications.

12.  Acknowledgements

   The authors would like to thank (in alphabetical order) Bernard
   Aboba, Steven Bellovin, Luis Leon Cardenas Graide, Guillermo Gont,
   Joseph Lorenzo Hall, Gre Norcie, Shivan Sahib, and Martin Thomson,
   and Michael Tuexen, for providing valuable comments on earlier
   versions of this document.





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   The authors would like to thank Diego Armando Maradona for his magic
   and inspiration.

13.  References

13.1.  Normative References

   [RFC0791]  Postel, J., "Internet Protocol", STD 5, RFC 791,
              DOI 10.17487/RFC0791, September 1981,
              <https://www.rfc-editor.org/info/rfc791>.

   [RFC0793]  Postel, J., "Transmission Control Protocol", STD 7,
              RFC 793, DOI 10.17487/RFC0793, September 1981,
              <https://www.rfc-editor.org/info/rfc793>.

   [RFC1035]  Mockapetris, P., "Domain names - implementation and
              specification", STD 13, RFC 1035, DOI 10.17487/RFC1035,
              November 1987, <https://www.rfc-editor.org/info/rfc1035>.

   [RFC2460]  Deering, S. and R. Hinden, "Internet Protocol, Version 6
              (IPv6) Specification", RFC 2460, DOI 10.17487/RFC2460,
              December 1998, <https://www.rfc-editor.org/info/rfc2460>.

   [RFC4086]  Eastlake 3rd, D., Schiller, J., and S. Crocker,
              "Randomness Requirements for Security", BCP 106, RFC 4086,
              DOI 10.17487/RFC4086, June 2005,
              <https://www.rfc-editor.org/info/rfc4086>.

   [RFC4291]  Hinden, R. and S. Deering, "IP Version 6 Addressing
              Architecture", RFC 4291, DOI 10.17487/RFC4291, February
              2006, <https://www.rfc-editor.org/info/rfc4291>.

   [RFC4862]  Thomson, S., Narten, T., and T. Jinmei, "IPv6 Stateless
              Address Autoconfiguration", RFC 4862,
              DOI 10.17487/RFC4862, September 2007,
              <https://www.rfc-editor.org/info/rfc4862>.

   [RFC4941]  Narten, T., Draves, R., and S. Krishnan, "Privacy
              Extensions for Stateless Address Autoconfiguration in
              IPv6", RFC 4941, DOI 10.17487/RFC4941, September 2007,
              <https://www.rfc-editor.org/info/rfc4941>.

   [RFC5722]  Krishnan, S., "Handling of Overlapping IPv6 Fragments",
              RFC 5722, DOI 10.17487/RFC5722, December 2009,
              <https://www.rfc-editor.org/info/rfc5722>.






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   [RFC6056]  Larsen, M. and F. Gont, "Recommendations for Transport-
              Protocol Port Randomization", BCP 156, RFC 6056,
              DOI 10.17487/RFC6056, January 2011,
              <https://www.rfc-editor.org/info/rfc6056>.

   [RFC6191]  Gont, F., "Reducing the TIME-WAIT State Using TCP
              Timestamps", BCP 159, RFC 6191, DOI 10.17487/RFC6191,
              April 2011, <https://www.rfc-editor.org/info/rfc6191>.

   [RFC6528]  Gont, F. and S. Bellovin, "Defending against Sequence
              Number Attacks", RFC 6528, DOI 10.17487/RFC6528, February
              2012, <https://www.rfc-editor.org/info/rfc6528>.

   [RFC7217]  Gont, F., "A Method for Generating Semantically Opaque
              Interface Identifiers with IPv6 Stateless Address
              Autoconfiguration (SLAAC)", RFC 7217,
              DOI 10.17487/RFC7217, April 2014,
              <https://www.rfc-editor.org/info/rfc7217>.

   [RFC7323]  Borman, D., Braden, B., Jacobson, V., and R.
              Scheffenegger, Ed., "TCP Extensions for High Performance",
              RFC 7323, DOI 10.17487/RFC7323, September 2014,
              <https://www.rfc-editor.org/info/rfc7323>.

   [RFC8064]  Gont, F., Cooper, A., Thaler, D., and W. Liu,
              "Recommendation on Stable IPv6 Interface Identifiers",
              RFC 8064, DOI 10.17487/RFC8064, February 2017,
              <https://www.rfc-editor.org/info/rfc8064>.

   [RFC8200]  Deering, S. and R. Hinden, "Internet Protocol, Version 6
              (IPv6) Specification", STD 86, RFC 8200,
              DOI 10.17487/RFC8200, July 2017,
              <https://www.rfc-editor.org/info/rfc8200>.

13.2.  Informative References

   [Bellovin2002]
              Bellovin, S., "A Technique for Counting NATted Hosts",
              IMW'02 Nov. 6-8, 2002, Marseille, France, 2002.

   [CPNI-TCP]
              Gont, F., "Security Assessment of the Transmission Control
              Protocol (TCP)",  United Kingdom's Centre for the
              Protection of National Infrastructure (CPNI) Technical
              Report, 2009, <https://www.gont.com.ar/papers/tn-03-09-
              security-assessment-TCP.pdf>.





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   [EFF]      EFF, "Cover your tracks: See how trackers view your
              browser", 2020, <https://coveryourtracks.eff.org/>.

   [FIPS-SHS]
              FIPS, "Secure Hash Standard (SHS)",  Federal Information
              Processing Standards Publication 180-4, August 2015,
              <https://nvlpubs.nist.gov/nistpubs/FIPS/
              NIST.FIPS.180-4.pdf>.

   [Fyodor1998]
              Fyodor, "Remote OS Detection via TCP/IP Stack
              Fingerprinting",  Phrack Magazine, Volume 9, Issue 54,
              1998, <http://www.phrack.org/archives/issues/54/9.txt>.

   [Fyodor2004]
              Fyodor, "Idle scanning and related IP ID games", 2004,
              <http://www.insecure.org/nmap/idlescan.html>.

   [Fyodor2006]
              Fyodor, "Remote OS Detection via TCP/IP Fingerprinting
              (2nd Generation)", 1998,
              <http://insecure.org/nmap/osdetect/>.

   [I-D.gont-numeric-ids-sec-considerations]
              Gont, F. and I. Arce, "Security Considerations for
              Transient Numeric Identifiers Employed in Network
              Protocols", draft-gont-numeric-ids-sec-considerations-06
              (work in progress), December 2020.

   [I-D.irtf-pearg-numeric-ids-history]
              Gont, F. and I. Arce, "Unfortunate History of Transient
              Numeric Identifiers", draft-irtf-pearg-numeric-ids-
              history-04 (work in progress), December 2020.

   [IANA-PROT]
              IANA, "Protocol Registries",
              <https://www.iana.org/protocols>.

   [IPID-DEV]
              Klein, A. and B. Pinkas, "From IP ID to Device ID and
              KASLR Bypass (Extended Version)", June 2019,
              <https://arxiv.org/pdf/1906.10478.pdf>.

   [Joncheray1995]
              Joncheray, L., "A Simple Active Attack Against TCP", Proc.
              Fifth Usenix UNIX Security Symposium, 1995.





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   [KASLR]    PaX Team, "Address Space Layout Randomization",
              <https://pax.grsecurity.net/docs/aslr.txt>.

   [Klein2007]
              Klein, A., "OpenBSD DNS Cache Poisoning and Multiple O/S
              Predictable IP ID Vulnerability", 2007,
              <http://www.trusteer.com/files/OpenBSD_DNS_Cache_Poisoning
              _and_Multiple_OS_Predictable_IP_ID_Vulnerability.pdf>.

   [Morris1985]
              Morris, R., "A Weakness in the 4.2BSD UNIX TCP/IP
              Software", CSTR 117, AT&T Bell Laboratories, Murray Hill,
              NJ, 1985,
              <https://pdos.csail.mit.edu/~rtm/papers/117.pdf>.

   [nmap]     Fyodor, "Nmap: Free Security Scanner For Network
              Exploration and Audit", 2020,
              <https://www.insecure.org/nmap>.

   [RFC4963]  Heffner, J., Mathis, M., and B. Chandler, "IPv4 Reassembly
              Errors at High Data Rates", RFC 4963,
              DOI 10.17487/RFC4963, July 2007,
              <https://www.rfc-editor.org/info/rfc4963>.

   [RFC6973]  Cooper, A., Tschofenig, H., Aboba, B., Peterson, J.,
              Morris, J., Hansen, M., and R. Smith, "Privacy
              Considerations for Internet Protocols", RFC 6973,
              DOI 10.17487/RFC6973, July 2013,
              <https://www.rfc-editor.org/info/rfc6973>.

   [RFC7098]  Carpenter, B., Jiang, S., and W. Tarreau, "Using the IPv6
              Flow Label for Load Balancing in Server Farms", RFC 7098,
              DOI 10.17487/RFC7098, January 2014,
              <https://www.rfc-editor.org/info/rfc7098>.

   [RFC7258]  Farrell, S. and H. Tschofenig, "Pervasive Monitoring Is an
              Attack", BCP 188, RFC 7258, DOI 10.17487/RFC7258, May
              2014, <https://www.rfc-editor.org/info/rfc7258>.

   [RFC7707]  Gont, F. and T. Chown, "Network Reconnaissance in IPv6
              Networks", RFC 7707, DOI 10.17487/RFC7707, March 2016,
              <https://www.rfc-editor.org/info/rfc7707>.

   [RFC7721]  Cooper, A., Gont, F., and D. Thaler, "Security and Privacy
              Considerations for IPv6 Address Generation Mechanisms",
              RFC 7721, DOI 10.17487/RFC7721, March 2016,
              <https://www.rfc-editor.org/info/rfc7721>.




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   [RFC7739]  Gont, F., "Security Implications of Predictable Fragment
              Identification Values", RFC 7739, DOI 10.17487/RFC7739,
              February 2016, <https://www.rfc-editor.org/info/rfc7739>.

   [Sanfilippo1998a]
              Sanfilippo, S., "about the ip header id", Post to Bugtraq
              mailing-list, Mon Dec 14 1998,
              <http://seclists.org/bugtraq/1998/Dec/48>.

   [Sanfilippo1998b]
              Sanfilippo, S., "Idle scan", Post to Bugtraq mailing-list,
              1998, <https://github.com/antirez/hping/blob/master/docs/
              SPOOFED_SCAN.txt>.

   [Sanfilippo1999]
              Sanfilippo, S., "more ip id", Post to Bugtraq mailing-
              list, 1999,
              <https://github.com/antirez/hping/raw/master/docs/MORE-
              FUN-WITH-IPID>.

   [Shimomura1995]
              Shimomura, T., "Technical details of the attack described
              by Markoff in NYT", Message posted in USENET's
              comp.security.misc newsgroup  Message-ID:
              <3g5gkl$5j1@ariel.sdsc.edu>, 1995,
              <https://www.gont.com.ar/docs/post-shimomura-usenet.txt>.

   [Silbersack2005]
              Silbersack, M., "Improving TCP/IP security through
              randomization without sacrificing interoperability",
              EuroBSDCon 2005 Conference, 2005,
              <http://citeseerx.ist.psu.edu/viewdoc/
              download?doi=10.1.1.91.4542&rep=rep1&type=pdf>.

   [TBIT]     TBIT, "TBIT, the TCP Behavior Inference Tool", 2001,
              <http://www.icir.org/tbit/>.

   [TCPT-uptime]
              McDanel, B., "TCP Timestamping - Obtaining System Uptime
              Remotely", March 2001,
              <https://securiteam.com/securitynews/5np0c153pi/>.

   [Zalewski2001]
              Zalewski, M., "Strange Attractors and TCP/IP Sequence
              Number Analysis", 2001,
              <http://lcamtuf.coredump.cx/oldtcp/tcpseq.html>.





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   [Zalewski2002]
              Zalewski, M., "Strange Attractors and TCP/IP Sequence
              Number Analysis - One Year Later", 2001,
              <http://lcamtuf.coredump.cx/newtcp/>.

   [Zalewski2012]
              Zalewski, M., "p0f v3 (version 3.09b)", 2012,
              <http://lcamtuf.coredump.cx/p0f.shtml>.

Appendix A.  Algorithms and Techniques with Known Negative Implications

   The following subsections document algorithms and techniques that
   generally have negative security and privacy implications.

A.1.  Predictable Linear Identifiers Algorithm

   One of the most trivial ways to achieve uniqueness with a low
   identifier reuse frequency is to produce a linear sequence.  This
   type of algorithm has been employed in the past to generate
   identifiers of Categories #1, #2, and #4.

   For example, the following algorithm has been employed (see e.g.
   [Morris1985], [Shimomura1995], [Silbersack2005] and [CPNI-TCP]) in a
   number of operating systems for selecting IP fragment IDs, TCP
   ephemeral ports, etc.:


























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       /* Initialization code */

       next_id = min_id;
       id_inc= 1;


       /* Transient Numeric ID selection function */

       id_range = max_id - min_id + 1;
       retry = id_range;

       do {
           if (next_id == max_id) {
               next_id = min_id;
           }
           else {
               next_id = next_id + id_inc;
           }

           if (check_suitable_id(next_id)) {
               return next_id;
           }

           retry--;

       } while (retry > 0);

       return ERROR;

   Note:
      check_suitable_id() is a function that checks whether the
      resulting identifier is acceptable (e.g., whether it's in use,
      etc.).

   For obvious reasons, this algorithm results in predicable sequences.
   If a global counter is used (such as "next_id" in the example above),
   a node that learns one numeric identifier can guess past numeric
   identifiers and also predict future values to be generated by the
   same algorithm in the future.  Since the value employed for the
   increments is known (such as "1" in this case), an attacker can
   sample two values, and learn the number of identifiers that have been
   were generated in-between.  Furthermore, if the counter is
   initialized e.g. when the system its bootstrapped to some known
   value, the algorithm will leak additional information, such as the
   number of transmitted in the case of an IP ID generator
   [Sanfilippo1998a], or the system uptime in the case of TCP timestamps
   [TCPT-uptime].




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A.2.  Random-Increments Algorithm

   This algorithm offers a middle ground between the algorithms that
   select random numeric identifiers (such as those described in
   Section 7.1.1 and Section 7.1.2), and those that select numeric
   identifiers as a monotonically-increasing function with a random
   origin (such as those described in Section 7.4.2 and Section 7.4.3).

       /* Initialization code */

       next_id = random();        /* Initialization value */
       id_rinc = 500;             /* Determines the trade-off */


       /* Transient Numeric ID selection function */

       id_range = max_id - min_id + 1;
       retry = id_range;


       do {
           /* Random increment */
           id_inc = (random() % id_rinc) + 1;

           if ( (max_id - next_id) >= id_inc){
               next_id = next_id + id_inc;
           }
           else {
               next_id = min_id + id_inc - (max_id - next_id);
           }

           if (check_suitable_id(next_id)) {
              return next_id;
           }

           retry = retry - id_inc;

       } while (retry > 0);

       return ERROR;


   This algorithm aims at producing a global monotonically-increasing
   sequence of numeric identifiers, while avoiding the use of fixed
   increments, which would lead to trivially predictable sequences.  The
   value "id_inc" allows for direct control of the trade-off between
   unpredictability and identifier reuse frequency.  The smaller the
   value of "id_inc", the more similar this algorithm is to a



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   predicable, global linear ID generation algorithm.  The larger the
   value of "id_inc", the more similar this algorithm is to the
   algorithm described in Section 7.1.1 of this document.

   When the identifiers wrap, there is the risk of collisions of
   identifiers (i.e., identifier reuse).  Therefore, "id_inc" should be
   selected according to the following criteria:

   o  It should maximize the wrapping time of the identifier space.

   o  It should minimize identifier reuse frequency.

   o  It should maximize unpredictability.

   Clearly, these are competing goals, and the decision of which value
   of "id_inc" to use is a trade-off.  Therefore, the value of "id_inc"
   should be configurable so that system administrators can make the
   trade-off for themselves.  We note that the alternative algorithms
   discussed throughout this document offer better interoperability,
   security and privacy implications than this algorithm, and hence
   implementation of this algorithm is discouraged.

A.3.  Re-using identifiers across different contexts

   Employing the same identifier across contexts in which stability is
   not required (overloading the numeric identifier) usually has has
   negative security and privacy implications.

   For example, in order to generate transient numeric identifiers of
   Category #2 or Category #3, an implementation or specification might
   be tempted to employ a source for the numeric identifiers which is
   known to provide unique values, but that may also have other
   properties such as being predictable or leaking information about the
   entity generating the identifier.  This technique has been employed
   in the past for e.g. generating IPv6 IIDs.  However, as noted in
   [RFC7721] and [RFC7707], embedding link-layer addresses in IPv6 IIDs
   not only results in predictable values, but also leaks information
   about the manufacturer of the underlying network interface card,
   allows for network activity correlation, and makes address-based
   scanning attacks feasible.

Authors' Addresses









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   Fernando Gont
   SI6 Networks
   Evaristo Carriego 2644
   Haedo, Provincia de Buenos Aires  1706
   Argentina

   Email: fgont@si6networks.com
   URI:   https://www.si6networks.com


   Ivan Arce
   Quarkslab

   Email: iarce@quarkslab.com
   URI:   https://www.quarkslab.com




































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