Network Working Group                                   J. Schoenwaelder
Request for Comments: 5345                      Jacobs University Bremen
Category: Informational                                     October 2008


              Simple Network Management Protocol (SNMP)
           Traffic Measurements and Trace Exchange Formats

Status of This Memo

  This memo provides information for the Internet community.  It does
  not specify an Internet standard of any kind.  Distribution of this
  memo is unlimited.

IESG Note

  The IESG thinks that this work is related to IETF work done in the
  Operations and Management Area related to SNMP, but this does not
  prevent publishing.  This RFC is not a candidate for any level of
  Internet Standard.  The IETF disclaims any knowledge of the fitness
  of this RFC for any purpose and notes that the decision to publish is
  not based on IETF review apart from the IETF Last Call on the
  allocation of a URI by IANA and the IESG review for conflict with
  IETF work.  The RFC Editor has chosen to publish this document at its
  discretion.  See RFC 3932 for more information.

Abstract

  The Simple Network Management Protocol (SNMP) is widely deployed to
  monitor, control, and (sometimes also) configure network elements.
  Even though the SNMP technology is well documented, it remains
  relatively unclear how SNMP is used in practice and what typical SNMP
  usage patterns are.

  This document describes an approach to carrying out large-scale SNMP
  traffic measurements in order to develop a better understanding of
  how SNMP is used in real-world production networks.  It describes the
  motivation, the measurement approach, and the tools and data formats
  needed to carry out such a study.

  This document was produced within the IRTF's Network Management
  Research Group (NMRG), and it represents the consensus of all of the
  active contributors to this group.








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Table of Contents

  1. Introduction ....................................................3
  2. Measurement Approach ............................................4
     2.1. Capturing Traffic Traces ...................................5
     2.2. Converting Traffic Traces ..................................6
     2.3. Filtering Traffic Traces ...................................7
     2.4. Storing Traffic Traces .....................................7
     2.5. Analyzing Traffic Traces ...................................8
  3. Analysis of Traffic Traces ......................................9
     3.1. Basic Statistics ...........................................9
     3.2. Periodic versus Aperiodic Traffic ..........................9
     3.3. Message Size and Latency Distributions .....................9
     3.4. Concurrency Levels ........................................10
     3.5. Table Retrieval Approaches ................................10
     3.6. Trap-Directed Polling - Myths or Reality? .................10
     3.7. Popular MIB Definitions ...................................11
     3.8. Usage of Obsolete Objects .................................11
     3.9. Encoding Length Distributions .............................11
     3.10. Counters and Discontinuities .............................11
     3.11. Spin Locks ...............................................12
     3.12. Row Creation .............................................12
  4. Trace Exchange Formats .........................................12
     4.1. XML Representation ........................................12
     4.2. CSV Representation ........................................17
  5. Security Considerations ........................................18
  6. IANA Considerations ............................................19
  7. Acknowledgements ...............................................19
  8. References .....................................................20
     8.1. Normative References ......................................20
     8.2. Informative References ....................................20




















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1.  Introduction

  The Simple Network Management Protocol (SNMP) was introduced in the
  late 1980s [RFC1052] and has since then evolved to what is known
  today as the SNMP version 3 Framework (SNMPv3) [RFC3410].  While SNMP
  is widely deployed, it is not clear what protocol versions are being
  used, which protocol features are being used, how SNMP usage differs
  in different types of networks or organizations, which information is
  frequently queried, and what typical SNMP interaction patterns occur
  in real-world production networks.

  There have been several publications in the recent past dealing with
  the performance of SNMP in general [SM99][Mal02][Pat01], the impact
  of SNMPv3 security [DSR01][CT04], or the relative performance of SNMP
  compared to Web Services [PDMQ04][PFGL04].  While these papers are
  generally useful to better understand the impact of various design
  decisions and technologies, some of these papers lack a strong
  foundation because authors typically assume certain SNMP interaction
  patterns without having experimental evidence that the assumptions
  are correct.  In fact, there are many speculations on how SNMP is
  being used in real-world production networks, and performance
  comparisons are based on limited test cases, but no systematic
  measurements have been performed and published so far.

  Many authors use the ifTable of the IF-MIB [RFC2863] or the
  tcpConnTable of the TCP-MIB [RFC4022] as a starting point for their
  analysis and comparison.  Despite the fact that there is no evidence
  that operations on these tables dominate SNMP traffic, it is even
  more unclear how these tables are read and which optimizations are
  done (or not done) by real-world applications.  It is also unclear
  what the actual traffic trade-off between periodic polling and more
  aperiodic bulk data retrieval is.  Furthermore, we do not generally
  understand how much traffic is devoted to standardized MIB objects
  and how much traffic deals with proprietary MIB objects and whether
  the operation mix between these object classes differs between
  different operational environments (e.g., backbone networks, access
  networks, enterprise networks).

  This document recommends an approach to collecting, codifying, and
  handling SNMP traffic traces in order to find answers to some of
  these questions.  It describes the tools that have been developed to
  allow network operators to collect traffic traces and to share them
  with research groups interested in analyzing and modeling network
  management interactions.

  While the SNMP trace collection and analysis effort was initiated by
  the research community, network operators can benefit from the SNMP
  measurements too.  Several new tools are being developed as part of



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  this effort that can be used to capture and analyze the traffic
  generated by management stations.  This resulting information can
  then be used to improve the efficiency and scalability of management
  systems.

  The measurement approach described in this document is by design
  limited to the study of SNMP traffic.  Studies of other management
  protocols or the impact of management protocols such as SNMP on other
  traffic sharing the same network resources is left to future efforts.

  This is an Informational document, produced within the IRTF's Network
  Management Research Group (NMRG), and it represents the consensus of
  all of the active contributors to this group.

2.  Measurement Approach

  This section outlines the process of doing SNMP traffic measurements
  and analysis.  The process consists of the following five basic
  steps:

  1.  Capture raw SNMP traffic traces in pcap packet capture files [1].

  2.  Convert the raw traffic traces into a structured machine and
      human-readable format.  A suitable XML schema has been developed
      for this purpose that captures all SNMP message details.  Another
      more compact comma-separated values (CSV) format has been
      developed that only keeps key information about SNMP messages.

  3.  Filter the converted traffic traces to hide or anonymize
      sensitive information.  While the filtering is conceptually a
      separate step, filtering may actually be implemented as part of
      the previous data conversion step for efficiency reasons.

  4.  Submit the filtered traffic traces to a repository from which
      they can be retrieved and analyzed.  Such a repository may be
      public, under the control of a research group, or under the
      control of a network operator who commits to run analysis scripts
      on the repository on behalf of researchers.

  5.  Analyze the traces by creating and executing analysis scripts
      that extract and aggregate information.

  Several of the steps listed above require the involvement of network
  operators supporting the SNMP measurement projects.  In many cases,
  the filtered XML and CSV representation of the SNMP traces will be
  the interface between the researchers writing analysis scripts and
  the operators involved in the measurement activity.  It is therefore
  important to have a well-defined specification of these interfaces.



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  This section provides some advice and concrete hints on how the steps
  listed above can be carried out efficiently.  Some special tools have
  been developed to assist network operators and researchers so that
  the time spent on supporting SNMP traffic measurement projects is
  limited.  The following sections describe the five steps and some
  tools in more detail.

2.1.  Capturing Traffic Traces

  Capturing SNMP traffic traces can be done using packet sniffers such
  as tcpdump [2], wireshark [3], or similar applications.  Some care
  must be taken to specify pcap filter expressions that match the SNMP
  transport endpoints used to carry SNMP traffic (typically 'udp and
  (port 161 or port 162)').  Furthermore, it is necessary to ensure
  that full packets are captured, that is packets are not truncated
  (tcpdump option -s 0).  Finally, it is necessary to carefully select
  the placement of the capturing probe within the network.  Especially
  on bridged LANs, it is important to ensure that all management
  traffic is captured and that the probe has access to all virtual LANs
  carrying management traffic.  This usually requires placing the
  probe(s) close to the management system(s) and configuring dedicated
  monitoring ports on bridged networks.  Some bridges have restrictions
  concerning their monitoring capabilities, and this should be
  investigated and documented where necessary.

  It is recommended to capture at least a full week of data to capture
  diurnal patterns and one cycle of weekly behavior.  Operators are
  strongly encouraged to capture traces over even longer periods of
  time.  Tools such as tcpdump and tcpslice [2] or mergecap and
  editcap [3] can be used to split or merge pcap trace files as needed.

  Several operating systems can offload some of the TCP/IP processing
  such as the calculation of transport layer checksum to network
  interface cards.  Traces that include traffic to/from a capturing
  interface that supports TCP/IP offloading can include incorrect
  transport layer checksums.  The simplest solution is of course to
  turn checksum offloading off while capturing traces (if that is
  feasible without losing too many packets).  The other solution is to
  correct or ignore checksums during the subsequent conversion of the
  raw pcap files.

  It is important to note that the raw pcap files should ideally be
  kept in permanent storage (e.g., compressed and encrypted on a CD ROM
  or DVD).  To verify measurements, it might be necessary to go back to
  the original pcap files if, for example, bugs in the tools described
  below have been detected and fixed.





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  For each captured trace, some meta data should be recorded and made
  available.  The meta data should include information such as where
  the trace was collected (name of the network and name of the
  organization owning the network, description of the measurement point
  in the network topology where the trace was collected), when it was
  collected, contact information, the size of the trace, any known
  special events, equipment failures, or major infrastructure changes
  during the data collection period and so on.  It is also extremely
  useful to provide a unique identification.  There are special online
  services such as DatCat [4] where meta data can be stored and which
  provide unique identifiers.

2.2.  Converting Traffic Traces

  Raw traces in pcap format must be converted into a format that is
  human readable while also remaining machine readable for efficient
  post-processing.  Human readability makes it easy for an operator to
  verify that no sensitive data is left in a trace while machine
  readability is needed to efficiently extract relevant information.

  The natural choice here is to use an XML format since XML is human as
  well as machine readable and there are many tools and high-level
  scripting language application programming interfaces (APIs) that can
  be used to process XML documents and to extract meaningful
  information.  However, XML is also pretty verbose, which increases
  processing overhead.  In particular, the usage of XML streaming APIs
  is strongly suggested since APIs that require an in-memory
  representation of XML documents do not handle large traces well.

  Section 4.1 of this document defines a RELAX NG schema [OASISRNG] for
  representing SNMP traffic traces in XML.  The schema captures all
  relevant details of an SNMP message in the XML format.  Note that the
  XML format retains some information about the original ASN.1/BER
  encoding to support message size analysis.

  A lightweight alternative to the full-blown XML representation based
  on comma-separated values (CSV) is defined in Section 4.2.  The CSV
  format only captures selected parts of SNMP messages and is thus more
  compact and faster to process.

  As explained in the previous sections, analysis programs that process
  raw pcap files should have an option to ignore incorrect checksums
  caused by TCP/IP offloading.  In addition, analysis programs that
  process raw pcap files should be able to perform IP reassembly for
  SNMP messages that were fragmented at the IP layer.






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  The snmpdump [5] package has been developed to convert raw pcap files
  into XML and CSV format.  The snmpdump program reads pcap, XML, or
  CSV files as input and produces XML files or CSV files as output.

  Specific elements can be filtered as required to protect sensitive
  data.

2.3.  Filtering Traffic Traces

  Filtering sensitive data (e.g., access control lists or community
  strings) can be achieved by manipulating the XML representation of an
  SNMP trace.  Standard XSLT processors (e.g., xsltproc [6]) can be
  used for this purpose.  People familiar with the scripting language
  Perl might be interested in choosing a suitable Perl module to
  manipulate XML documents [7].

  The snmpdump program, for example, can filter out sensitive
  information, e.g., by deleting or clearing all XML elements whose
  name matches a regular expression.  Data type specific anonymization
  transformations that maintain lexicographic ordering for values that
  appear in instance identifiers [HS06] can be applied.  Note that
  anonymization transformations are often bound to an initialization
  key and depend on the data being anonymized in an anonymization run.
  As a consequence, users must be careful when they merge data from
  independently anonymized traces.  More information about network
  traffic trace anonymization techniques can be found in [XFA02],
  [FXAM04], [PAPL06], and [RW07].

2.4.  Storing Traffic Traces

  The raw pcap traces as well as the XML / CSV formatted traces should
  be stored in a stable archive or repository.  Such an archive or
  repository might be maintained by research groups (e.g., the NMRG),
  network operators, or both.  It is of key importance that captured
  traces are not lost or modified as they may form the basis of future
  research projects and may also be needed to verify published research
  results.  Access to the archive might be restricted to those who have
  signed some sort of a non-disclosure agreement.

  While this document recommends that raw traces should be kept, it
  must be noted that there are situations where this may not be
  feasible.  The recommendation to keep raw traces may be ignored, for
  example, to comply with data-protection laws or to protect a network
  operator from being forced to provide the data to other
  organizations.






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  Lossless compression algorithms embodied in programs such as gzip or
  bzip2 can be used to compress even large trace files down to a size
  where they can be burned on DVDs for cheap long-term storage.

  It must be stressed again that it is important to keep the original
  pcap traces in addition to the XML/CSV formatted traces since the
  pcap traces are the most authentic source of information.
  Improvements in the tool chain may require going back to the original
  pcap traces and rebuilding all intermediate formats from them.

2.5.  Analyzing Traffic Traces

  Scripts that analyze traffic traces must be verified for correctness.
  Ideally, all scripts used to analyze traffic traces will be
  publically accessible so that third parties can verify them.
  Furthermore, sharing scripts will enable other parties to repeat an
  analysis on other traffic traces and to extend such analysis scripts.
  It might be useful to establish a common, versioning repository for
  analysis scripts.

  Due to the availability of XML parsers and the simplicity of the CSV
  format, trace files can be processed with tools written in almost any
  programming language.  However, in order to facilitate a common
  vocabulary and to allow operators to easily read scripts they execute
  on trace files, it is suggested that analysis scripts be written in
  scripting languages such as Perl using suitable Perl modules to
  manipulate XML documents <http://perl-xml.sourceforge.net/faq/>.
  Using a scripting language such as Perl instead of system programming
  languages such as C or C++ has the advantage of reducing development
  time and making scripts more accessible to operators who may want to
  verify scripts before running them on trace files that may contain
  sensitive data.

  The snmpdump tool provides an API to process SNMP messages in C/C++.
  While the coding of trace analysis programs in C/C++ should in
  general be avoided for code readability, verifiability, and
  portability reasons, using C/C++ might be the only option in dealing
  with very large traces efficiently.

  Any results produced by analyzing a trace must be interpreted in the
  context of the trace.  The nature of the network, the attachment
  point used to collect the trace, the nature of the applications
  generating SNMP traffic, or the events that happened while the trace
  was collected clearly influence the result.  It is therefore
  important to be careful when drawing general conclusions based on a
  potentially (too) limited data set.





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3.  Analysis of Traffic Traces

  This section discusses several questions that can be answered by
  analyzing SNMP traffic traces.  The questions raised in the following
  subsections are meant to be illustrative and no attempt has been made
  to provide a complete list.

3.1.  Basic Statistics

  Basic statistics cover things such as:

  o  protocol version used,

  o  protocol operations used,

  o  message size distribution,

  o  error message type frequency, or

  o  usage of authentication and encryption mechanisms.

  The Object Identifier (OID) names of the objects manipulated can be
  categorized into OID subtrees, for example, to identify
  'standardized', 'proprietary', and 'experimental' objects.

3.2.  Periodic versus Aperiodic Traffic

  SNMP is used to periodically poll devices as well as to retrieve
  information at the request of an operator or application.  The
  periodic polling leads to periodic traffic patterns while on-demand
  information retrieval causes more aperiodic traffic patterns.  It is
  worthwhile to understand what the relationship is between the amount
  of periodic and aperiodic traffic.  It will be interesting to
  understand whether there are multiple levels of periodicity at
  different time scales.

  Periodic polling behavior may be dependent on the application and
  polling engine it uses.  For example, some management platforms allow
  applications to specify how long polled values may be kept in a cache
  before they are polled again.  Such optimizations need to be
  considered when analyzing traces for periodic and aperiodic traffic.

3.3.  Message Size and Latency Distributions

  SNMP messages are size constrained by the transport mappings used and
  the buffers provided by the SNMP engines.  For the further evolution
  of the SNMP framework, it would be useful to know what the actual
  message size distributions are.  It would be useful to understand the



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  latency distributions, especially the distribution of the processing
  times by SNMP command responders.  Some SNMP implementations
  approximate networking delays by measuring request-response times,
  and it would be useful to understand to what extent this is a viable
  approach.

  Some SNMP implementations update their counters from the underlying
  instrumentation following adaptive algorithms, not necessarily
  periodically, and not necessarily on-demand.  The granularity of
  internal counter updates may impact latency measurements and should
  be taken into account.

3.4.  Concurrency Levels

  SNMP allows management stations to retrieve information from multiple
  agents concurrently.  It will be interesting to identify what the
  typical concurrency level is that can be observed on production
  networks or whether management applications prefer more sequential
  ways of retrieving data.

  Furthermore, it will be interesting to analyze how many redundant
  requests coming from applications are processed almost simultaneously
  by a device.  The concurrency level and the amount of redundant
  requests has implications on caching strategies employed by SNMP
  agents.

3.5.  Table Retrieval Approaches

  Tables can be read in several different ways.  The simplest and most
  inefficient approach is to retrieve tables object-by-object in
  column-by-column order.  More advanced approaches try to read tables
  row-by-row or even multiple-rows-by-multiple-rows.  The retrieval of
  index elements can be suppressed in most cases or only a subset of
  columns of a table are retrieved.  It will be useful to know which of
  these approaches are used on production networks since this has a
  direct implication on agent implementation techniques and caching
  strategies.

3.6.  Trap-Directed Polling - Myths or Reality?

  SNMP is built around a concept called trap-directed polling.
  Management applications are responsible to periodically poll SNMP
  agents to determine their status.  In addition, SNMP agents can send
  traps to notify SNMP managers about events so that SNMP managers can
  adapt their polling strategy and basically react faster than normal
  polling would allow.





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  Analysis of SNMP traffic traces can identify whether trap-directed
  polling is actually deployed.  In particular, the question that
  should be addressed is whether SNMP notifications lead to changes in
  the short-term polling behavior of management stations.  In
  particular, it should be investigated to what extent SNMP managers
  use automated procedures to track down the meaning of the event
  conveyed by an SNMP notification.

3.7.  Popular MIB Definitions

  An analysis of object identifier prefixes can identify the most
  popular MIB modules and the most important object types or
  notification types defined by these modules.  Such information would
  be very valuable for the further maintenance and development of these
  and related MIB modules.

3.8.  Usage of Obsolete Objects

  Several objects from the early days have been obsoleted because they
  cannot properly represent today's networks.  A typical example is the
  ipRouteTable that was obsoleted because it was not able to represent
  classless routing, introduced and deployed on the Internet in 1993.
  Some of these obsolete objects are still mentioned in popular
  publications as well as research papers.  It will be interesting to
  find out whether they are also still used by management applications
  or whether management applications have been updated to use the
  replacement objects.

  Depending on the data recorded in a trace, it might be possible to
  determine the age of devices by looking at the values of objects such
  as sysObjectID and sysDecr [RFC3418].  The age of a device can then
  be taken into consideration when analyzing the use of obsolete and
  deprecated objects.

3.9.  Encoding Length Distributions

  It will be useful to understand the encoding length distributions for
  various data types.  Assumptions about encoding length distributions
  are sometimes used to estimate SNMP message sizes in order to meet
  transport and buffer size constraints.

3.10.  Counters and Discontinuities

  Counters can experience discontinuities [RFC2578].  A widely used
  discontinuity indicator is the sysUpTime scalar of the SNMPv2-MIB
  [RFC3418], which can be reset through a warm start to indicate
  counter discontinuities.  Some MIB modules introduce more specific
  discontinuity indicators, e.g., the ifCounterDiscontinuityTime of the



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  IF-MIB [RFC2863].  It will be interesting to study to what extent
  these objects are actually used by management applications to handle
  discontinuity events.

3.11.  Spin Locks

  Cooperating command generators can use advisory locks to coordinate
  their usage of SNMP write operations.  The snmpSetSerialNo scalar of
  the SNMPv2-MIB [RFC3418] is the default coarse-grain coordination
  object.  It will be interesting to find out whether there are command
  generators that coordinate themselves using these spin locks.

3.12.  Row Creation

  Row creation is an operation not natively supported by the protocol
  operations.  Instead, conceptual tables supporting row creation
  typically provide a control column that uses the RowStatus textual
  convention defined in the SNMPv2-TC [RFC2579] module.  The RowStatus
  itself supports different row creation modes, namely createAndWait
  (dribble-mode) and createAndGo (one-shot mode).  Different approaches
  can be used to derive the instance identifier if it does not have
  special semantics associated with it.  It will be useful to study
  which of the various row creation approaches are actually used by
  management applications on production networks.

4.  Trace Exchange Formats

4.1.  XML Representation

  The XML format has been designed to keep all information associated
  with SNMP messages.  The format is specified in RELAX NG compact
  notation [OASISRNC].  Freely available tools such as trang [8] can be
  used to convert RELAX NG compact syntax to other XML schema
  notations.

  The XML format can represent SNMPv1, SNMPv2c, and SNMPv3 messages.
  In case a new version of SNMP is introduced in the future or existing
  SNMP versions are extended in ways that require changes to the XML
  format, a new XML format with a different namespace needs to be
  defined (e.g., by incrementing the version number included in the
  namespace URI).

# Relax NG grammar for the XML SNMP trace format.
#
# Published as part of RFC 5345.






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default namespace = "urn:ietf:params:xml:ns:snmp-trace-1.0"

start =
 element snmptrace {
   packet.elem*
 }

packet.elem =
 element packet {
   element time-sec  { xsd:unsignedInt },
   element time-usec { xsd:unsignedInt },
   element src-ip    { ipaddress.type },
   element src-port  { xsd:unsignedInt },
   element dst-ip    { ipaddress.type },
   element dst-port  { xsd:unsignedInt },
   snmp.elem
 }

snmp.elem =
 element snmp {
   length.attrs?,
   message.elem
 }

message.elem =
 element version   { length.attrs, xsd:int },
 element community { length.attrs, xsd:hexBinary },
 pdu.elem

message.elem |=
 element version { length.attrs, xsd:int },
 element message {
   length.attrs,
   element msg-id         { length.attrs, xsd:unsignedInt },
   element max-size       { length.attrs, xsd:unsignedInt },
   element flags          { length.attrs, xsd:hexBinary },
   element security-model { length.attrs, xsd:unsignedInt }
 },
 usm.elem?,
 element scoped-pdu {
   length.attrs,
   element context-engine-id { length.attrs, xsd:hexBinary },
   element context-name      { length.attrs, xsd:string },
   pdu.elem
 }

usm.elem =
 element usm {



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   length.attrs,
   element auth-engine-id    { length.attrs, xsd:hexBinary },
   element auth-engine-boots { length.attrs, xsd:unsignedInt },
   element auth-engine-time  { length.attrs, xsd:unsignedInt },
   element user              { length.attrs, xsd:hexBinary },
   element auth-params       { length.attrs, xsd:hexBinary },
   element priv-params       { length.attrs, xsd:hexBinary }
 }

pdu.elem =
 element trap {
   length.attrs,
   element enterprise        { length.attrs, oid.type },
   element agent-addr        { length.attrs, ipv4address.type },
   element generic-trap      { length.attrs, xsd:int },
   element specific-trap     { length.attrs, xsd:int },
   element time-stamp        { length.attrs, xsd:int },
   element variable-bindings { length.attrs, varbind.elem* }
 }

pdu.elem |=
 element (get-request | get-next-request | get-bulk-request |
          set-request | inform-request | snmpV2-trap |
          response | report) {
   length.attrs,
   element request-id        { length.attrs, xsd:int },
   element error-status      { length.attrs, xsd:int },
   element error-index       { length.attrs, xsd:int },
   element variable-bindings { length.attrs, varbind.elem* }
 }

varbind.elem =
 element varbind { length.attrs, name.elem, value.elem }

name.elem =
 element name { length.attrs, oid.type }

value.elem =
 element null              { length.attrs, empty } |
 element integer32         { length.attrs, xsd:int } |
 element unsigned32        { length.attrs, xsd:unsignedInt } |
 element counter32         { length.attrs, xsd:unsignedInt } |
 element counter64         { length.attrs, xsd:unsignedLong } |
 element timeticks         { length.attrs, xsd:unsignedInt } |
 element ipaddress         { length.attrs, ipv4address.type } |
 element octet-string      { length.attrs, xsd:hexBinary } |
 element object-identifier { length.attrs, oid.type } |
 element opaque            { length.attrs, xsd:hexBinary } |



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 element no-such-object    { length.attrs, empty } |
 element no-such-instance  { length.attrs, empty } |
 element end-of-mib-view   { length.attrs, empty }

# The blen attribute indicates the number of octets used by the BER
# encoded tag / length / value triple.  The vlen attribute indicates
# the number of octets used by the BER encoded value alone.

length.attrs =
 ( attribute blen { xsd:unsignedShort },
   attribute vlen { xsd:unsignedShort } )?

oid.type =
 xsd:string {
   pattern =
     "(([0-1](\.[1-3]?[0-9]))|(2.(0|([1-9]\d*))))" ~
     "(\.(0|([1-9]\d*))){0,126}"
 }

# The types below are for IP addresses.  Note that SNMP's buildin
# IpAddress type only supports IPv4 addresses; IPv6 addresses are only
# introduced to cover SNMP over IPv6 endpoints.

ipv4address.type =
 xsd:string {
   pattern =
     "((0|(1[0-9]{0,2})" ~
     "|(2(([0-4][0-9]?)|(5[0-5]?)|([6-9]?)))|([3-9][0-9]?))\.){3}" ~
     "(0|(1[0-9]{0,2})" ~
     "|(2(([0-4][0-9]?)|(5[0-5]?)|([6-9]?)))|([3-9][0-9]?))"
 }

ipv6address.type =
 xsd:string {
   pattern =
     "(([0-9a-fA-F]+:){7}[0-9a-fA-F]+)|" ~
     "(([0-9a-fA-F]+:)*[0-9a-fA-F]+)?::(([0-9a-fA-F]+:)*[0-9a-fA-F]+)?"
 }

ipaddress.type = ipv4address.type | ipv6address.type

  The following example shows an SNMP trace file in XML format
  containing an SNMPv1 get-next-request message for the OID
  1.3.6.1.2.1.1.3 (sysUpTime) and the response message returned by the
  agent.






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  <snmptrace xmlns="urn:ietf:params:xml:ns:snmp-trace-1.0">
    <packet>
      <time-sec>1147212206</time-sec>
      <time-usec>739609</time-usec>
      <src-ip>192.0.2.1</src-ip>
      <src-port>60371</src-port>
      <dst-ip>192.0.2.2</dst-ip>
      <dst-port>12345</dst-port>
      <snmp blen="42" vlen="40">
        <version blen="3" vlen="1">1</version>
        <community blen="8" vlen="6">7075626c6963</community>
        <get-next-request blen="29" vlen="27">
          <request-id blen="6" vlen="4">1804289383</request-id>
          <error-status blen="3" vlen="1">0</error-status>
          <error-index blen="3" vlen="1">0</error-index>
          <variable-bindings blen="15" vlen="13">
            <varbind blen="13" vlen="11">
              <name blen="9" vlen="7">1.3.6.1.2.1.1.3</name>
              <null blen="2" vlen="0"/>
            </varbind>
          </variable-bindings>
        </get-next-request>
      </snmp>
    </packet>
    <packet>
      <time-sec>1147212206</time-sec>
      <time-usec>762891</time-usec>
      <src-ip>192.0.2.2</src-ip>
      <src-port>12345</src-port>
      <dst-ip>192.0.2.1</dst-ip>
      <dst-port>60371</dst-port>
      <snmp blen="47" vlen="45">
        <version blen="3" vlen="1">1</version>
        <community blen="8" vlen="6">7075626c6963</community>
        <response blen="34" vlen="32">
          <request-id blen="6" vlen="4">1804289383</request-id>
          <error-status blen="3" vlen="1">0</error-status>
          <error-index blen="3" vlen="1">0</error-index>
          <variable-bindings blen="20" vlen="18">
            <varbind blen="18" vlen="16">
              <name blen="10" vlen="8">1.3.6.1.2.1.1.3.0</name>
              <unsigned32 blen="6" vlen="4">26842224</unsigned32>
            </varbind>
          </variable-bindings>
        </response>
      </snmp>
    </packet>
  </snmptrace>



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4.2.  CSV Representation

  The comma-separated values (CSV) format has been designed to capture
  only the most relevant information about an SNMP message.  In
  situations where all information about an SNMP message must be
  captured, the XML format defined above must be used.  The CSV format
  uses the following fields:

  1.   Timestamp in the format seconds.microseconds since 1970, for
       example, "1137764769.425484".

  2.   Source IP address in dotted quad notation (IPv4), for example,
       "192.0.2.1", or compact hexadecimal notation (IPv6), for
       example, "2001:DB8::1".

  3.   Source port number represented as a decimal number, for example,
       "4242".

  4.   Destination IP address in dotted quad notation (IPv4), for
       example, "192.0.2.1", or compact hexadecimal notation (IPv6),
       for example, "2001:DB8::1".

  5.   Destination port number represented as a decimal number, for
       example, "161".

  6.   Size of the SNMP message (a decimal number) counted in octets,
       for example, "123".  The size excludes all transport, network,
       and link-layer headers.

  7.   SNMP message version represented as a decimal number.  The
       version 0 stands for SNMPv1, 1 for SNMPv2c, and 3 for SNMPv3,
       for example, "3".

  8.   SNMP protocol operation indicated by one of the keywords get-
       request, get-next-request, get-bulk-request, set-request, trap,
       snmpV2-trap, inform-request, response, report.

  9.   SNMP request-id in decimal notation, for example, "1511411010".

  10.  SNMP error-status in decimal notation, for example, "0".

  11.  SNMP error-index in decimal notation, for example, "0".

  12.  Number of variable-bindings contained in the varbind-list in
       decimal notation, for example, "5".

  13.  For each varbind in the varbind list, three output elements are
       generated:



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       1.  Object name given as object identifier in dotted decimal
           notation, for example, "1.3.6.1.2.1.1.3.0".

       2.  Object base type name or exception name, that is one of the
           following: null, integer32, unsigned32, counter32,
           counter64, timeticks, ipaddress, octet-string, object-
           identifier, opaque, no-such-object, no-such-instance, and
           end-of-mib-view.

       3.  Object value is printed as a number if the underlying base
           type is numeric.  An IPv4 addresses is rendered in the
           dotted quad notation and an IPv6 address is rendered in the
           usual hexadecimal notation.  An octet string value is
           printed in hexadecimal format while an object identifier
           value is printed in dotted decimal notation.  In case of an
           exception, the object value is empty.

  Note that the format does not preserve the information needed to
  understand SNMPv1 traps.  It is therefore recommended that
  implementations be able to convert the SNMPv1 trap format into the
  trap format used by SNMPv2c and SNMPv3, according to the rules
  defined in [RFC3584].  The activation of trap format conversion
  should be the user's choice.

  The following example shows an SNMP trace file in CSV format
  containing an SNMPv1 get-next-request message for the OID
  1.3.6.1.2.1.1.3 (sysUpTime) and the response message returned by the
  agent.  (Note that the example uses backslash line continuation marks
  in order to fit the example into the RFC format.  Backslash line
  continuations are not part of the CSV format.)

  1147212206.739609,192.0.2.1,60371,192.0.2.2,12345,42,1,\
    get-next-request,1804289383,0,0,1,1.3.6.1.2.1.1.3,null,
  1147212206.762891,192.0.2.2,12345,192.0.2.1,60371,47,1,\
    response,1804289383,0,0,1,1.3.6.1.2.1.1.3.0,timeticks,26842224

5.  Security Considerations

  SNMP traffic traces usually contain sensitive information.  It is
  therefore necessary to (a) remove unwanted information and (b) to
  anonymize the remaining necessary information before traces are made
  available for analysis.  It is recommended to encrypt traces when
  they are archived.

  Implementations that generate CSV or XML traces from raw pcap files
  should have an option to suppress or anonymize values.  Note that
  instance identifiers of tables also include values, and it might
  therefore be necessary to suppress or anonymize (parts of) the



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  instance identifiers.  Similarly, the packet and message headers
  typically contain sensitive information about the source and
  destination of SNMP messages as well as authentication information
  (community strings or user names).

  Anonymization techniques can be applied to keep information in traces
  that could otherwise reveal sensitive information.  When using
  anonymization, values should only be kept when the underlying data
  type is known and an appropriate anonymization transformation is
  available (filter-in principle).  For values appearing in instance
  identifiers, it is usually desirable to maintain the lexicographic
  order.  Special anonymization transformations that preserve this
  property have been developed, although their anonymization strength
  is usually reduced compared to transformations that do not preserve
  lexicographic ordering [HS06].

  The meta data associated with traces and in particular information
  about the organization owning a network and the description of the
  measurement point in the network topology where a trace was collected
  may be misused to decide/pinpoint where and how to attack a network.
  Meta data therefore needs to be properly protected.

6.  IANA Considerations

  Per this document, IANA has registered a URI for the SNMP XML trace
  format namespace in the IETF XML registry [RFC3688].  Following the
  format in RFC 3688, the following registration has been made:

  URI: "urn:ietf:params:xml:ns:snmp-trace-1.0"

  Registrant Contact: The NMRG of the IRTF.

  XML: N/A, the URI is an XML namespace.

7.  Acknowledgements

  This document was influenced by discussions within the Network
  Management Research Group (NMRG).  Special thanks to Remco van de
  Meent for writing the initial Perl script that lead to the
  development of the snmpdump software package and Matus Harvan for his
  work on lexicographic order preserving anonymization transformations.
  Aiko Pras contributed ideas to Section 3 while David Harrington
  helped to improve the readability of this document.

  Last call reviews have been received from Bert Wijnen, Aiko Pras,
  Frank Strauss, Remco van de Meent, Giorgio Nunzi, Wes Hardacker, Liam
  Fallon, Sharon Chisholm, David Perkins, Deep Medhi, Randy Bush, David
  Harrington, Dan Romascanu, Luca Deri, and Marc Burgess.  Karen R.



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  Sollins reviewed the document for the Internet Research Steering
  Group (IRSG).  Jari Arkko, Pasi Eronen, Chris Newman, and Tim Polk
  provided helpful comments during the Internet Engineering Steering
  Group (IESG) review.

  Part of this work was funded by the European Commission under grant
  FP6-2004-IST-4-EMANICS-026854-NOE.

8.  References

8.1.  Normative References

  [RFC2578]   McCloghrie, K., Perkins, D., and J. Schoenwaelder,
              "Structure of Management Information Version 2 (SMIv2)",
              STD 58, RFC 2578, April 1999.

  [OASISRNG]  Clark, J. and M. Makoto, "RELAX NG Specification",
              OASIS Committee Specification, December 2001.

  [OASISRNC]  Clark, J., "RELAX NG Compact Syntax", OASIS Committee
              Specification, November 2002.

  [RFC3584]   Frye, R., Levi, D., Routhier, S., and B. Wijnen,
              "Coexistence between Version 1, Version 2, and Version 3
              of the Internet-standard Network Management Framework",
              BCP 74, RFC 3584, August 2003.

  [RFC3688]   Mealling, M., "The IETF XML Registry", BCP 81, RFC 3688,
              January 2004.

8.2.  Informative References

  [RFC1052]   Cerf, V., "IAB Recommendations for the development of
              Internet network management standards", RFC 1052,
              April 1998.

  [RFC2579]   McCloghrie, K., Perkins, D., and J. Schoenwaelder,
              "Textual Conventions for SMIv2", STD 58, RFC 2579,
              April 1999.

  [RFC3418]   Presuhn, R., Ed., "Management Information Base (MIB) for
              the Simple Network Management Protocol (SNMP)", STD 62,
              RFC 3418, December 2002.

  [RFC2863]   McCloghrie, K. and F. Kastenholz, "The Interfaces Group
              MIB", RFC 2863, June 2000.





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  [RFC3410]   Case, J., Mundy, R., Partain, D., and B. Stewart,
              "Introduction and Applicability Statements for Internet-
              Standard Management Framework", RFC 3410, December 2002.

  [RFC4022]   Raghunarayan, R., "Management Information Base for the
              Transmission Control Protocol (TCP)", RFC 4022,
              March 2005.

  [PDMQ04]    Pras, A., Drevers, T., van de Meent, R., and D. Quartel,
              "Comparing the Performance of SNMP and Web Services based
              Management", IEEE Transactions on Network and Service
              Management 1(2), November 2004.

  [Pat01]     Pattinson, C., "A Study of the Behaviour of the Simple
              Network Management Protocol", Proc. 12th IFIP/IEEE
              Workshop on Distributed Systems: Operations and
              Management , October 2001.

  [DSR01]     Du, X., Shayman, M., and M. Rozenblit, "Implementation
              and Performance Analysis of SNMP on a TLS/TCP Base",
              Proc. 7th IFIP/IEEE International Symposium on Integrated
              Network Management , May 2001.

  [CT04]      Corrente, A. and L. Tura, "Security Performance Analysis
              of SNMPv3 with Respect to SNMPv2c", Proc. 2004 IEEE/IFIP
              Network Operations and Management Symposium , April 2004.

  [PFGL04]    Pavlou, G., Flegkas, P., Gouveris, S., and A. Liotta, "On
              Management Technologies and the Potential of Web
              Services", IEEE Communications Magazine 42(7), July 2004.

  [SM99]      Sprenkels, R. and J. Martin-Flatin, "Bulk Transfers of
              MIB Data", Simple Times 7(1), March 1999.

  [Mal02]     Malowidzki, M., "GetBulk Worth Fixing", Simple
              Times 10(1), December 2002.

  [HS06]      Harvan, M. and J. Schoenwaelder, "Prefix- and
              Lexicographical-order-preserving IP Address
              Anonymization", IEEE/IFIP Network Operations and
              Management Symposium NOMS 2006, April 2006.

  [XFA02]     Xu, J., Fan, J., and M. Ammar, "Prefix-Preserving IP
              Address Anonymization: Measurement-based Security
              Evaluation and a New Cryptography-based Scheme", 10th
              IEEE International Conference on Network
              Protocols ICNP'02, November 2002.




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  [FXAM04]    Fan, J., Xu, J., Ammar, M., and S. Moon, "Prefix-
              Preserving IP Address Anonymization", Computer
              Networks 46(2), October 2004.

  [PAPL06]    Pang, R., Allman, M., Paxson, V., and J. Lee, "The Devil
              and Packet Trace Anonymization", Computer Communication
              Review 36(1), January 2006.

  [RW07]      Ramaswamy, R. and T. Wolf, "High-Speed Prefix-Preserving
              IP Address Anonymization for Passive Measurement
              Systems", IEEE Transactions on Networking 15(1),
              February 2007.

URIs

  [1]  <http://en.wikipedia.org/wiki/Pcap>

  [2]  <http://www.tcpdump.org/>

  [3]  <http://www.wireshark.org/>

  [4]  <http://www.datcat.org/>

  [5]  <https://svn.eecs.jacobs-university.de/svn/schoenw/src/snmpdump>

  [6]  <http://xmlsoft.org/XSLT/>

  [7]  <http://perl-xml.sourceforge.net/faq/>

  [8]  <http://www.relaxng.org/>

Author's Address

  Juergen Schoenwaelder
  Jacobs University Bremen
  Campus Ring 1
  28725 Bremen
  Germany

  Phone: +49 421 200-3587
  EMail: [email protected]










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Full Copyright Statement

  Copyright (C) The IETF Trust (2008).

  This document is subject to the rights, licenses and restrictions
  contained in BCP 78 and at http://www.rfc-editor.org/copyright.html,
  and except as set forth therein, the authors retain all their rights.

  This document and the information contained herein are provided on an
  "AS IS" basis and THE CONTRIBUTOR, THE ORGANIZATION HE/SHE REPRESENTS
  OR IS SPONSORED BY (IF ANY), THE INTERNET SOCIETY, THE IETF TRUST AND
  THE INTERNET ENGINEERING TASK FORCE DISCLAIM ALL WARRANTIES, EXPRESS
  OR IMPLIED, INCLUDING BUT NOT LIMITED TO ANY WARRANTY THAT THE USE OF
  THE INFORMATION HEREIN WILL NOT INFRINGE ANY RIGHTS OR ANY IMPLIED
  WARRANTIES OF MERCHANTABILITY OR FITNESS FOR A PARTICULAR PURPOSE.

Intellectual Property

  The IETF takes no position regarding the validity or scope of any
  Intellectual Property Rights or other rights that might be claimed to
  pertain to the implementation or use of the technology described in
  this document or the extent to which any license under such rights
  might or might not be available; nor does it represent that it has
  made any independent effort to identify any such rights.  Information
  on the procedures with respect to rights in RFC documents can be
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  Copies of IPR disclosures made to the IETF Secretariat and any
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  attempt made to obtain a general license or permission for the use of
  such proprietary rights by implementers or users of this
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  http://www.ietf.org/ipr.

  The IETF invites any interested party to bring to its attention any
  copyrights, patents or patent applications, or other proprietary
  rights that may cover technology that may be required to implement
  this standard.  Please address the information to the IETF at
  [email protected].












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