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Versions: (draft-gont-predictable-protocol-ids)
00 01 03
Internet Research Task Force (IRTF) F. Gont
Internet-Draft SI6 Networks
Intended status: Informational I. Arce
Expires: March 12, 2021 Quarkslab
September 8, 2020
On the Generation of Transient Numeric Identifiers
draft-irtf-pearg-numeric-ids-generation-03
Abstract
This document performs an analysis of the security and privacy
implications of different types of "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 security and privacy implications, thus providing
guidance to protocol designers and protocol implementers. Finally,
this 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
Task Force (IETF). Note that other groups may also distribute
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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."
This Internet-Draft will expire on March 12, 2021.
Copyright Notice
Copyright (c) 2020 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 Identifiers . . . . . . . . 5
5. Protocol Failure Severity . . . . . . . . . . . . . . . . . . 6
6. Categorizing 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) . . . . . . . . . . . . . . . . . 13
8. Common Vulnerabilities Associated with Transient Numeric
Identifiers . . . . . . . . . . . . . . . . . . . . . . . . . 19
8.1. Network Activity Correlation . . . . . . . . . . . . . . 19
8.2. Information Leakage . . . . . . . . . . . . . . . . . . . 20
8.3. Exploitation of Semantics of Transient Numeric
Identifiers . . . . . . . . . . . . . . . . . . . . . . . 21
8.4. Exploitation of Collisions of Transient Numeric
Identifiers . . . . . . . . . . . . . . . . . . . . . . . 21
8.5. Cryptanalysis . . . . . . . . . . . . . . . . . . . . . . 21
9. Vulnerability Analysis of Specific Transient Numeric
Identifiers Categories . . . . . . . . . . . . . . . . . . . 22
9.1. Category #1: Uniqueness (soft failure) . . . . . . . . . 22
9.2. Category #2: Uniqueness (hard failure) . . . . . . . . . 23
9.3. Category #3: Uniqueness, stable within context (soft
failure) . . . . . . . . . . . . . . . . . . . . . . . . 23
9.4. Category #4: Uniqueness, monotonically increasing within
context (hard failure) . . . . . . . . . . . . . . . . . 23
10. IANA Considerations . . . . . . . . . . . . . . . . . . . . . 25
11. Security Considerations . . . . . . . . . . . . . . . . . . . 26
12. Acknowledgements . . . . . . . . . . . . . . . . . . . . . . 26
13. References . . . . . . . . . . . . . . . . . . . . . . . . . 26
13.1. Normative References . . . . . . . . . . . . . . . . . . 26
13.2. Informative References . . . . . . . . . . . . . . . . . 28
Appendix A. Flawed Algorithms . . . . . . . . . . . . . . . . . 31
A.1. Predictable Linear Identifiers Algorithm . . . . . . . . 31
A.2. Random-Increments Algorithm . . . . . . . . . . . . . . . 32
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Authors' Addresses . . . . . . . . . . . . . . . . . . . . . . . 34
1. Introduction
Network protocols employ a variety of numeric identifiers for
different protocol entities, ranging from DNS Transaction IDs (TxIDs)
to transport protocol ports (e.g. TCP 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 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]
Recent history indicates that when new protocols are standardized or
new protocol implementations are produced, the security and privacy
properties of the associated identifiers tend to be overlooked, and
inappropriate algorithms to generate transient numeric identifiers
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are either suggested in the specification 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 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 the associated 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
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:
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
retransmission can be considered a soft failure.
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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.
The key words "MUST", "MUST NOT", "REQUIRED", "SHALL", "SHALL NOT",
"SHOULD", "SHOULD NOT", "RECOMMENDED", "MAY", and "OPTIONAL" in this
document are to be interpreted as described in RFC 2119 [RFC2119].
3. Threat Model
Throughout this document, we assume an attacker does not have
physical or logical access to the device(s) being attacked. We
assume the attacker can simply send any traffic to the target
device(s), to e.g. sample identifiers employed by such device(s).
4. Issues with the Specification of Identifiers
While assessing protocol specifications regarding the use of
identifiers, we found that most of the issues discussed in this
document arise as a result of one of the following conditions:
o Protocol specifications which under-specify the requirements for
their identifiers
o Protocol specifications that over-specify their 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 port numbers in [RFC0793], the
specification of TCP sequence numbers in [RFC0793], or the
specification of the DNS TxID in [RFC1035].
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
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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 application or protocol may not be the same as
that of the protocol in question. For example, a TCP connection that
is aborted may or may not result in a hard failure of the upper
application protocol: 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 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 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 the 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], since otherwise such connection-establishment attempts
would fail.
(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], since otherwise such connection-establishment attempts
could fail.
(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.
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., check_suitable_id() would always be
"true").
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
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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);
count = next_id;
do {
if (check_suitable_id(next_id))
return next_id;
if (next_id == max_id) {
next_id = min_id;
} else {
next_id++;
}
count--;
} while (count > 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
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 been employed). When an identifier is found to be
unsuitable, 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
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unavailable numeric IDs. For example, if this algorithm is
employed for transport protocol ephemeral port randomization
[RFC6056] and the local list 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.
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;
next_id = min_id + (random() % id_range);
count = id_range;
do {
if (check_suitable_id(next_id))
return next_id;
next_id = min_id + (random() % id_range);
count--;
} while (count > 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
where a large number of identifiers are 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.
This algorithm does not suffer from any of the issues discussed in
Section 8.
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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, all 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.
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.
/* Transient Numeric ID selection function */
id_range = max_id - min_id + 1;
counter = 0;
do {
offset = F(CONTEXT, counter, secret_key);
next_id = min_id + (offset % id_range);
if (check_suitable_id(next_id))
return next_id;
counter++;
} while (counter <= 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 card (NIC) and SLAAC
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autoconfiguration prefix, the CONTEXT should be the concatenation
of e.g. the 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.
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 'counter' variable and
recomputing F(), up to a maximum of MAX_RETRIES times.
For obvious reasons, the transient network 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 achieve low identifier reuse frequency while
still avoiding predictable sequences would be to employ a per-context
counter, as opposed to a global counter. Such an algorithm could be
described as follows:
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/* Transient Numeric ID selection function */
count = max_id - min_id + 1;
id_inc = increment() % count;
if(lookup_counter(CONTEXT) == ERROR){
create_counter(CONTEXT);
}
next_id = lookup_counter(CONTEXT);
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 + 1);
}
if (check_suitable_id(next_id)){
store_counter(CONTEXT, next_id);
return next_id;
}
count = count - id_inc;
} while (count > 0);
return ERROR;
NOTE:
increment() returns a small integer that is employed to increment
the current counter value to obtain a numeric ID. 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.
lookup_counter() returns the current counter for a given context,
or an error condition if such a counter does not exist.
create_counter() creates a counter for a given context, and
initializes such counter to a random value.
store_counter() saves (updates) the current counter 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, such counter is incremented to
obtain the new identifier, and the new identifier updates the
corresponding counter. If there is no counter for such context, a
new counter is created an 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.
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 An implementation may map more than one context to the same
counter, such the amount of memory required to store counters is
reduced, at the expense of a possible unnecessary increase in the
numeric identifier reuse frequency. In such cases, if the
identifiers are predictable by the destination system (in case the
destination host represents the "context"), a vulnerable host
might possibly leak to third parties the identifiers used by other
hosts to send traffic to it (i.e., a vulnerable Host B could leak
to Host C the identifier values that Host A is using to send
packets to Host B). Appendix A of [RFC7739] describes one
possible scenario for such leakage in detail. Employing small
random numbers for the increments (i.e., for increment() function)
may help mitigate this kind of information leakage.
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 unique for
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each {src IP, dst IP} set, then each possible combination of {src IP,
dst IP} should have a corresponding "next_id" value.
Keeping one counter for each possible "context" may in many cases be
considered too onerous in terms of memory requirements. As a
workaround, the following algorithm employs a calculated technique
(as opposed to keeping state in memory) to maintain the 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;
offset = F(CONTEXT, secret_key);
count = id_range;
do {
next_id = min_id + (offset + counter) % id_range;
id_inc = increment();
counter = counter + id_inc;
if (check_suitable_id(next_id))
return next_id;
count = count - id_inc;
} while (count > 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
elements that define a given context. For example, if this algorithm
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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.,
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.
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 mitigated by employing small random
values for the increments (i.e., increment() function), instead of
the constant "1".
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;
offset = F(CONTEXT, secret_key1);
index = G(CONTEXT, secret_key2) % TABLE_LENGTH;
count = id_range;
do {
next_id = min_id + (offset + table[index]) % id_range;
id_inc = increment();
table[index] = table[index] + id_inc;
if (check_suitable_id(next_id))
return next_id;
count = count - id_inc;
} while (count > 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 a 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 secreted 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., stable for a given CONTEXT). In most cases, both secret keys
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.
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The array 'table[]' assures that successive identifiers for a given
context will be monotonically-increasing. However, the increments
space is separated into TABLE_LENGTH different spaces, and thus
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 of '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 or stable 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 address 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
the same across networks) allows not only network activity
correlation within the same network, but also across networks ("host
tracking").
Similarly, a node that generates TCP ISNs with a global counter could
allow network activity correlation across networks, since the
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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_1) + mono(CONTEXT_2);
This generic expression generates identifiers by adding a
monotonically-increasing function (e.g. linear) to an offset.
offset() is constant within a given context, whereas mono() is a
monotonically-increasing function for a given context (possibly
different to that of offset()). Identifiers generated with this
expression will generally be predictable within CONTEXT_1. Thus,
CONTEXT_1 essentially specifies the context within which information
will be "leaked". When both CONTEXT_1 and CONTEXT_2 are a constant
value, then all the corresponding transient numeric identifiers
become predictable in all contexts.
NOTE: If offset() has a global context and the specific value is
known, the resulting identifiers may leak even more information.
For example, the if Fragment Identification values are generated
with the generic function above, and CONTEXT_1 is "global", then
the corresponding identifiers will leak the number of fragmented
datagrams sent for CONTEXT_2. If both CONTEXT_1 and CONTEXT_2 are
"global", then Fragment Identification values would be generated
with a global counter (initialized to offset()), and thus each
generated Fragment Identification value would leak the number of
fragmented datagrams transmitted by the node since it has been
bootstrapped.
On the other hand, mono() will be predictable within CONTEXT_2. The
predictability of mono(), irrespective of the context and/or
predictability of offset(), can leak out information that is of use
to attackers. For example, a node that selects ephemeral port
numbers on 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
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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(Srd_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., a global CONTEXT_2) --
particularly when it is a linear function (constant increments of 1).
8.3. Exploitation of 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 underlying network
interface card. This fact may be leveraged by an attacker meaning to
"guess" MAC addresses and 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 a number by traditional IID-
generation algorithms that embed MAC addresses (now replaced by
[RFC8064] with [RFC7217]).
8.4. 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]. Similarly, predictable TCP ISNs open the door to trivial
connection-reset and data injection attacks (see e.g.
[Joncheray1995]).
8.5. 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
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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:
[IPID-DEV] describes two vulnerable numeric ID generators that
employ cryptographically-weak hash functions. Additionally, one
of such implementations employs a 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 identifiers of this category
are:
o Use of trivial algorithms (e.g. global counters) that generate
predictable identifiers
o Use of flawed PRNGs (please see e.g. [Zalewski2001],
[Zalewski2002] and [Klein2007])
Since the only interoperability requirement for these identifiers is
uniqueness (with an associated soft failure), the obvious approach to
generate them is to employ a PRNG. 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.
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9.2. Category #2: Uniqueness (hard failure)
As noted in Section 7.2 this category typically employs 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.
9.3. Category #3: Uniqueness, stable within context (soft failure)
There are three main vulnerabilities that may be associated with
identifiers of this category:
1. Use algorithms or sources that result in predictable identifiers
2. Use cryptographically-weak hash functions, or inappropriate
secret key sizes that allow for cryptanalysis
3. Employing the same identifier across contexts in which stability
is not required (overloading the numeric identifier)
At times, an implementation or specification may be tempted to employ
a source for the numeric identifiers which is known to provide unique
values, that may have other properties such as being predictable or
leaking information about the node in question. For example, as
noted in [RFC7721], embedding link-layer addresses for generating
IPv6 IIDs not only results in predictable values, but also leaks
information about the manufacturer of the network interface card.
Employing cryptographically-weak hash functions or inappropriate
secret key sizes may allow for cryptanalysis, which may eventually be
exploited by an attacker to predict future numeric identifiers and
perform a variety of attacks.
On the other hand, using an identifier across contexts where
stability is not required can be leveraged for correlation of
activities. On of the most trivial examples of this is the use of
IPv6 IIDs that are stable across networks (such as IIDs that embed
the underlying link-layer address).
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:
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/* Transient Numeric ID selection function */
count = max_id - min_id + 1;
do {
id_inc = increment();
update_mono(CONTEXT_2, id_inc);
next_id = offset(CONTEXT_1) + mono(CONTEXT_2);
if (check_suitable_id(next_id))
return next_id;
count = count - id_inc;
} while (count > 0);
return ERROR;
NOTES:
update_mono(CONTEXT_2, id_inc) increments the counter
corresponding to CONTEXT_2 by "id_inc" (usually 1).
mono(CONTEXT_2) reads the counter corresponding to CONTEXT_2.
Essentially, an identifier (next_id) is generated by adding a
monotonically-increasing function (mono()) to an offset value, which
is unknown to the attacker, and stable for given context (CONTEXT_1).
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-path attacker. While
the resulting sequence will be monotonically-increasing, the use
of an offset value that is unknown to the attacker makes the
resulting values unknown to the attacker.
o The most straightforward "stateless" implementation of offset
would be that in which offset() is the result of 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 Another possible (but stateful) approach would be to simply
generate a random "per-context" "counter" and store it in memory,
and then look-up the corresponding context when a new identifier
is to be selected, and increment the counter to obtain the
transient numeric identifier. The algorithm in Section 7.4.1 is
essentially an implementation of this type.
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o The monotonically increasing function is implemented by
incrementing the previous value of the function by increment().
In the most trivial case increment() could return the constant
"1". But it could also possibly return small random integers such
the increments are unpredictable. This represents a tradeoff
between the unpredictability of the resulting numeric IDs, and the
numeric ID reuse frequency.
Considering the generic algorithm illustrated above we can identify
the following possible vulnerabilities:
o All the vulnerabilities discussed in Section 9.3 ("Category #3:
Uniqueness, stable within context (soft failure)") since the
algorithms for this category are similar to those of Section 9.3,
with the addition of a monotonically-increasing function.
o The function mono() could be seen as representing the number of
identifiers that have so far been generated for a given context
(CONTEXT_2). If mono() spans more than the necessary context, the
"increments" could be leaked to other parties, thus disclosing
information about the number of identifiers that have so far been
generated. This is particularly the case when the algorithm
employs a constant increment of 1. For example, an implementation
in which mono() is implemented as a single global counter will
unnecessarily leak information the number of identifiers that have
been produced. [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 increment() determines the increments of mono() for each
identifier that is selected. In the most simple case, increment()
returns the constant "1". However, increment() may be implemented
so as to return a small random integer value such that even if the
current mono() value employed by the generator is guessed (see
Appendix A of [RFC7739]), the exact next identifier to be selected
will be harder to guess.
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.
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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 to include an appropriate analysis of the
interoperability, security, and privacy implications of the transient
numeric identifiers they specify and employ, while this document
analyzes possible algorithms (and their implications) that could be
employed to comply with the interoperability properties of a
transient numeric identifier, while mitigating the possible security
and privacy implications.
12. Acknowledgements
The authors would like to thank (in alphabetical order) Steven
Bellovin, Joseph Lorenzo Hall, Gre Norcie, Shivan Sahib, and Martin
Thomson, and Michael Tuexen, for providing valuable comments on
earlier versions of this document.
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>.
[RFC2119] Bradner, S., "Key words for use in RFCs to Indicate
Requirement Levels", BCP 14, RFC 2119,
DOI 10.17487/RFC2119, March 1997,
<https://www.rfc-editor.org/info/rfc2119>.
[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>.
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[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>.
[RFC5722] Krishnan, S., "Handling of Overlapping IPv6 Fragments",
RFC 5722, DOI 10.17487/RFC5722, December 2009,
<https://www.rfc-editor.org/info/rfc5722>.
[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>.
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[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>.
[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>.
[Fyodor2004]
Fyodor, "Idle scanning and related IP ID games", 2004,
<http://www.insecure.org/nmap/idlescan.html>.
[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-05
(work in progress), July 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-02 (work in progress), April 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>.
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[Joncheray1995]
Joncheray, L., "A Simple Active Attack Against TCP", Proc.
Fifth Usenix UNIX Security Symposium, 1995.
[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>.
[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>.
[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>.
[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>.
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[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>.
[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>.
[Zalewski2002]
Zalewski, M., "Strange Attractors and TCP/IP Sequence
Number Analysis - One Year Later", 2001,
<http://lcamtuf.coredump.cx/newtcp/>.
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Appendix A. Flawed Algorithms
The following subsections document algorithms with known 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.
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.:
/* Initialization code */
next_id = min_id;
id_inc= 1;
/* Transient Numeric ID selection function */
count = max_id - min_id + 1;
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;
count--;
} while (count > 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.).
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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 also learn or guess
values employed by past and future protocol instances. On the other
hand, when the value of increments is known (such as "1" in this
case), an attacker can sample two values, and learn the number of
identifiers that were generated in-between. Furthermore, if the
counter is initialized e.g. when the system its bootstrapped to some
known value, it will likely leak information (for example, 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]).
Where identifier reuse would lead to a hard failure, one typical
approach to generate unique identifiers (while minimizing the
security and privacy implications of predictable identifiers) is to
obfuscate the resulting numeric identifiers by either:
o Replacing the global counter with multiple counters (initialized
to a random value)
o Randomizing the "increments"
Avoiding global counters essentially means that learning one
identifier for a given context (e.g., one TCP ephemeral port for a
given {src IP, Dst IP, Dst Port}) is of no use for learning or
guessing identifiers for a different context (e.g., TCP ephemeral
ports that involve other peers). However, this may imply keeping one
additional variables/counter per contexts, which may be prohibitive
in some environments.
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 (as in "id_inc = 1" in our case) 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.
A.2. Random-Increments Algorithm
This algorithm offers a middle ground between the algorithms that
select numeric identifiers randomly (such as those described in
Section 7.1.1 and Section 7.1.2), and those that offer obfuscation
but no randomization (such as those described in Section 7.4.2 and
Section 7.4.3).
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/* Initialization code */
next_id = random(); /* Initialization value */
id_inc = 500; /* Determines the trade-off */
/* Transient Numeric ID selection function */
id_range = max_id - min_id + 1;
count = id_range;
do {
/* Random increment */
next_id = next_id + (random() % id_inc) + 1;
/* Keep the identifier within acceptable range */
next_id = min_id + (next_id % id_range);
if (check_suitable_id(next_id))
return next_id;
count--;
} while (count > 0);
return ERROR;
This algorithm aims at producing a 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 the level
of obfuscation and the identifier reuse frequency. The smaller the
value of "id_inc", the more similar this algorithm is to a
predicable, global monotonically-increasing 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 obfuscation.
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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.
Authors' Addresses
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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