The NIST Computer User’s Guide to the Protection of Information Resources

Computer User’s Guide to the Protection of Information

National Institute of Standards and Technology
The National Institute of Standards and Technology (NIST) is
responsible or developing standards, providing technical
assistance, and conducting research for computers and related
systems. These activities provide technical support to government
and industry in the effective, safe, and economical use of
computers. With the passage of the Computer Security
Act of 1987 (P.L. 100-235), NIST’s activities also include the
development of standards and guidelines needed to assure the
cost-effective security and privacy of sensitive information in
Federal computer systems. This guide is just one of three
brochures designed for a specific audience. The “Executive Guide
to the Protection of Information Resources,” and the “Managers
Guide to the Protection of Information Resources” complete the

This guide was written by Cheryl Helsing of Deloitte, Haskins &
Sells in conjunction with Marianne Swanson and Mary Anne Todd of
the National Institute of Standards and Technology.

Today’s computer technology, with microcomputers and on-line
access, has placed the power of the computer where it belongs, in
YOUR hands. YOU, the users, develop computer applications and
perform other data processing functions which previously were
only done by the computer operations personnel. These advances
have greatly improved our efficiency and effectiveness but, also
present a serious challenge in achieving adequate data security.

While excellent progress has been made in computer technology,
very little has been done to inform users of the vulnerability of
data and information to such threats as unauthorized
modification, disclosure, and destruction, either deliberate or
accidental. This guide will make you aware of some of the
undesirable things that can happen to data and will provide some
practical solutions for reducing your risks to these threats.

The statement that “security is everyone’s responsibility” is
absolutely true. Owners, developers, operators and users of
information systems each has a personal responsibility to protect
these resources. Functional managers have the responsibility to
provide appropriate security controls for any information
resources entrusted to them. These managers are personally
responsible for understanding the sensitivity and criticality of
their data and the extent of losses that could occur if the
resources are not protected. Managers must ensure that all users
of their data and systems are made aware of the practices and
procedures used to protect the information resources. When you
don’t know what your security responsibilities are, ASK YOUR
All data is sensitive to some degree; exactly how sensitive is
unique to each business environment. Within the Federal
Government, personal information is sensitive to unauthorized
disclosure under the Privacy Act of 1974. In some cases, data is
far more sensitive to accidental errors or omissions that
compromise accuracy, integrity, or availability. For example, in
a Management Information System, inaccurate, incomplete, or
obsolete information can result in erroneous management decisions
which could cause serious damage and require time and money to
rectify. Data and information which are critical to an agency’s
ability to perform its mission are sensitive to nonavailability.

Still other data are sensitive to fraudulent manipulation for
personal gain. Systems that process electronic funds transfers,
control inventories, issue checks, control accounts receivables
and payables, etc., can be fraudulently exploited resulting in
serious losses to an agency.
One way to determine the sensitivity of data is to ask the
questions “What will it cost if the data is wrong? Manipulated
for fraudulent purposes? Not available? Given to the wrong
person?” If the damage is more than you can tolerate, then the
data is sensitive and should have adequate security controls to
prevent or lessen the potential loss.

Over the past several decades, computers have taken over
virtually all of our major record-keeping functions. Recently,
personal computers have made it cost-effective to automate many
office functions. Computerization has many advantages and is here
to stay; however, automated systems introduce new risks, and we
should take steps to control those risks.
We should be concerned with the same risks that existed when
manual procedures were used, as well as some new risks created by
the unique nature of computers themselves. One risk introduced by
computers is the concentration of tremendous amounts of data in
one location. The greater the concentration, the greater the
consequences of loss or damage. Another example is that computer
users access information from remote terminals. We must be able
to positively identify the user, as well as ensure that the user
is only able to access information and functions that have been
authorized. Newspaper accounts of computer “hackers,” computer
virus attacks, and other types of intruders underscore the
reality of the threat to government and commercial computer

No matter how many controls or safeguards we use, we can never
achieve total security. We can, however, decrease the risk in
proportion to the strength of the protective measures. The degree
of protection is based on the value of the information; in other
words, how serious would be the consequences if a certain type of
information were to be wrongfully changed, disclosed, delayed, or

General Responsibilities
All Federal computer system users share certain general
responsibilities for information resource protection. The
following considerations should guide your actions.

Treat information as you would any valuable asset.
You would not walk away from your desk leaving cash or other
valuables unattended. You should take the same care to protect
information. If you are not sure of the value or sensitivity of
the various kinds of information you handle, ask your manager for

Use government computer systems only for lawful and authorized
The computer systems you use in your daily work should be used
only for authorized purposes and in a lawful manner. There are
computer crime laws that prescribe criminal penalties for those
who illegally access Federal computer systems or data.
Additionally, the unauthorized use of Federal computer systems or
use of authorized privileges for unauthorized purposes could
result in disciplinary action.

Observe policies and procedures established by agency
Specific requirements for the protection of information have been
established by your agency. These requirements may be found in
policy manuals, rules, or procedures. Ask your manager if you are
unsure about your own responsibilities for protection of

Recognize that you are accountable for your activities on
computer systems.
After you receive authorization to use any Federal computer
system, you become personally responsible and accountable for
your activity on the system. Accordingly, your use should be
restricted to those functions needed to carry out job

Report unusual occurrences to your manager.
Many losses would be avoided if computer users would report any
circumstances that seem unusual or irregular. Warning signals
could include such things as unexplainable system activity that
you did not perform, data that appears to be of questionable
accuracy, and unexpected or incorrect processing results. If you
should notice anything of a questionable nature, bring it to your
manager’s attention.

Security and Control Guidelines
Some common-sense protective measures can reduce the risk of
loss, damage, or disclosure of information. Following are the
most important areas of information systems controls that assure
that the system is properly used, resistant to disruptions, and

Make certain no one can impersonate you.
If a password is used to verify your identity, this is the key to
system security. Do not disclose your password to anyone, or
allow anyone to observe your password as you enter it during the
sign-on process. If you choose your own password, avoid selecting
a password with any personal associations, or one that is very
simple or short. The aim is to select a password that would be
difficult to guess or derive. “1REDDOG” would be a better
password than “DUKE.”
If your system allows you to change your own password, do so
regularly. Find out what your agency requires, and change
passwords at least that frequently. Periodic password changes
keep undetected intruders from continuously using the password of
a legitimate user.

After you are logged on, the computer will attribute all activity
to your user id. Therefore, never leave your terminal without
logging off — even for a few minutes. Always log off or
otherwise inactivate your terminal so no one could perform any
activity under your user id when you are away from the area.

Safeguard sensitive information from disclosure to others.
People often forget to lock up sensitive reports and computer
media containing sensitive data when they leave their work areas.
Information carelessly left on top of desks and in unlocked
storage can be casually observed, or deliberately stolen. Every
employee who works with sensitive information should have
lockable space available for storage when information is not in
use. If you aren’t sure what information should be locked up or
what locked storage is available, ask your manager.

While working, be aware of the visibility of data on your
personal computer or terminal display screen. You may need to
reposition equipment or furniture to eliminate over-the-shoulder
viewing. Be especially careful near windows and in public areas.
Label all sensitive diskettes and other computer media to alert
other employees of the need to be especially careful. When no
longer needed, sensitive information should be deleted or
discarded in such a way that unauthorized individuals cannot
recover the data. Printed reports should be finely shredded,
while data on magnetic media should be overwritten. Files that
are merely deleted are not really erased and can still be

Install physical security devices or software on personal
The value and popularity of personal computers make theft a big
problem, especially in low-security office areas. Relatively
inexpensive hardware devices greatly reduce the risk of equipment
loss. Such devices involve lock-down cables or enclosures that
attach equipment to furniture. Another approach is to place
equipment in lockable cabinets.
When data is stored on a hard disk, take some steps to keep
unauthorized individuals from accessing that data. A power lock
device only allows key-holders to turn on power to the personal
computer. Where there is a need to segregate information between
multiple authorized users of a personal computer, additional
security in the form of software is probably needed. Specific
files could be encrypted to make them unintelligible to
unauthorized staff, or access control software can divide storage
space among authorized users, restricting each user to their own

Avoid costly disruptions caused by data or hardware loss.
Disruptions and delays are expensive. No one enjoys working
frantically to re-enter work, do the same job twice, or fix
problems while new work piles up. Most disruptions can be
prevented, and the impact of disruptions can be minimized by
advance planning. Proper environmental conditions and power
supplies minimize equipment outages and information loss. Many
electrical circuits in office areas do not constitute an adequate
power source, so dedicated circuits for computer systems should
be considered. Make certain that your surroundings meet the
essential requirements for correct equipment operation. Cover
equipment when not in use to protect it from dust, water leaks,
and other hazards.

For protection from accidental or deliberate destruction of data,
regular data backups are essential. Complete system backups
should be taken at intervals determined by how quickly
information changes or by the volume of transactions. Backups
should be stored in another location, to guard against the
possibility of original and backup copies being destroyed by the
same fire or other disaster.

Maintain the authorized hardware/software configuration.
Some organizations have been affected by computer “viruses”
acquired through seemingly useful or innocent software obtained
from public access bulletin boards or other sources; others have
been liable for software illegally copied by employees. The
installation of unauthorized hardware can cause damage,
invalidate warranties, or have other negative consequences.
Install only hardware or software that has been acquired through
normal acquisition procedures and comply with all software
licensing agreement requirements.

Ultimately, computer security is the user’s responsibility. You,
the user, must be alert to possible breaches in security and
adhere to the security regulations that have been established
within your agency. The security practices listed are not
inclusive, but rather designed to remind you and raise your
awareness towards securing your information resources:

Keep it in a secure environment
Keep food, drink, and cigarettes AWAY from it
Know where the fire suppression equipment is located and know
how to use it

Keep unauthorized people AWAY from your equipment and data
Challenge strangers in your area

Never write it down or give it to anyone
Don’t use names, numbers or dates which are personally
identified with you
Change it often, but change it immediately if you think it has
been compromised

Don’t allow unauthorized access to your files and data
NEVER leave your equipment unattended with your password
activated – SIGN OFF!

Don’t use unauthorized software
Back up your files before implementing ANY new software

If the data or information is sensitive or critical to your
operation, lock it up!

Keep duplicates of your sensitive data in a safe place, out of
your immediate area
Back it up as often as necessary

Tell your manager if you see any unauthorized changes to your
Immediately report any loss of data or programs, whether
automated or hard copy

For Additional Information
National Institute of Standards and Technology
Computer Security Program Office
A-216 Technology
Gaithersburg, MD 20899
(301) 975-5200

For further information on the management of information
resources, NIST publishes Federal Information Processing
Standards Publications (FIBS PUBS). These publications deal with
many aspects of computer security, including password usage, data
encryption, ADP risk management and contingency planning, and
computer system security certification and accreditation. A list
of current publications is available from:

Standards Processing Coordinator (ADP)
National Computer Systems Laboratory
National Institute of Standards and Technology
Technology Building, B-64
Gaithersburg, MD 20899
Phone: (301) 975-2817

Telecom Computer Security Bulletin: Expansion of the Z80 Chip, by King Lucifer (Alias Byteman) on September 10, 1988


Expansion of the Z80 CPU Chip
Written by King Lucifer (Alias Byteman) on 9/10/88

A Telecom Computer Security Bulletin File
Volume One, Number 1, File 12 of 12

The circut described here expands the z80 uP’s 64k byte memory space to
512k bytes by switching among sixteen 32k byte banks. The approach allows
you to programs larger than 64k bytes for applications that can tolerate
an I/O operation each time the program crosses one of the 32k byte –

The Z80’s lower address lines (Schematic) provide access to the 32k-byte
common bank of memory. The sixteenth line (A15 through A18) by activating
four additional bits (A15 through A18) Consequently, the system can access
2;19 or 512k, unique memory locations.

_____________________________________________> (Ao – A14)
________ / \ __________
| z80 ao|_/ \|a ic 0|o________
| ic1 a1|_| |_|b 74ls1381|o–o |
| |_| |_|c 2|o–o |
| .|_| | | 3|o–o |
| .|_| _____|en 4|o–o |
| .|_| | ___|en 5|o–o |
| |_| | | _|en 6:o–o |
| |_| | | | | 7:o–o |___ ______ _______
| |_| | | – | | | | | |
| |_| | | |__________| ____|d Q|____| – |
| |_| | | |____|d Q|____| | |
| |___________|_|_____ |____|d Q|____| | A |
| |___ | | | | | 74ls | | – |
| |___| | | | | ~~~~|~~~ | -|a1
| |___| | | | | O | | |a2
| |___| | | | | | | | |a3
| |___| | | | | | | | |a4
| Z80 |___| | | | | | | -|
| |___| | | | | | | – |
| |___| | | | | | __| | |
| | | | | | | | |__| |B |
|________| | | | | | | |__| | |
O O | | | | | | |__| – |
| |______________| | | | | | |_______|
|_____________________| | | | | O |
|| | | | | |____| |
|| |_______________|_________________/_________|____________|_do-7
|| o(5v) |______________— _________|____________|
|| |_____— ___________________/—


The Milnet File by Brigadier General Swipe/Dispater

][ ][
][ Finally it’s here………. ][
][ /\/\ /\/\ ][
][ / \ / / ][
][ \/\/\/il\/\/et ][
][ by: ___ __ ______ ][
][ __) / _` / ____/ ][
][ __)rigadier \__eneral / /wipe ][
][ ______________________/ / ][
][ /_______________________/ ][
][ (aka: Dispater) ][
][ ][
][ Thanx to: no one! G.D.I. (God Damn Independant) ][
][ ][
First of all Milnet is a system used by the Air Force and the Pentagon for
communication use. You know you are on milnet when you see that infamous
TAC login xxx. Milnet is run out of the University of Southern California,
(this might give some of you some ideas who live around there).
Logon Info
The Milnet number is 1-800-368-2217.
The ISI MASTER DIAL UP IS 213-306-1366.
This is a more tricky logon procedure but if you got balls, you’re using a
trunk box, or you are just S-T-U-P-I-D here goes:
1> call 213-306-1366
2> when the phone stops ringing you are connected
3> enter location number (9 digits) + 1 or 0
4> hang up and it will call you
5> pick up the phone and hit the ‘*’ on your phone
6> hit a carriage return on the computer
7> at the ‘what class?’ prompt hit RETURN!!!
8> then a ‘go’ prompt will appear and log on as you would the 800 number.
If you have trouble connecting try 300 bauds instead of 1200. It’s a bite in
the ass but, sometime the connection will fuck up if you don’t.
When you first connect you will see:
CALL NIC 1-800-235-3155 FOR HELP
WRPAT TAC 113 #:36
(you type)
@o 1/103
YOU ALWAYS TYPE @o then other connections are:
ISIA 3/103
ISIB 10:3/52
ISID 10:0/27
ISIF 2/103
VAX A 10:2/27
Next you will see a ‘USER-ID’ promt. The first 4 characters vary but it is
is always followed by a ‘-‘ and what ever connection you choose.
User-Id: (example) CER5-ISIE or MRW1-ISIE
The first three letters are the initials of the user followed by a random
number (1-9).
Access Code: (example) 2285UNG6A or 22L8KK5CH
An access code will never contain a ( 1, 0, G, Z).
The first 3 letters will be SAC. This stands for Strategic Air
Followint that is a ‘.’ Then the squadron number and the prime mission.
In this case ‘305AREFW’, (305TH AIR REFULING WING). Then a ‘-‘ and the
a fancey name for the motor pool. I’ll try and get a list of these there are
tons of names.
The password will not be echoed back and should be entered after a
the username.
The new user password as a default is: NEW-UZER-ACNT
+————-+ and what they are for
copied direcly from the help manual
ADUTY aids in management of additional duty assignments.
(International help – use the ? and keys, HELP.)
ARCHIVE requests files to be stored on tape for later retreval.
CHAT Provides near real time communication between terminal users on the
same host computer.
(Use ? with CHAT.)
DAILY Executive appointment scheduleing program
DCOPY Handles output on DIABLO and XEROX printers
EMACS Powerful full-screen text editor
FOLLOW Suspense follow up program
FTP provides file transfer capabilites between host computers
FKEYS allows user to define function key (real spiffaruni)
HELP the command used by stupid generals or hackers that have never used
milnet before
NCPCALC spreadsheet program
PHOTO saves transcripts of sessions
REMIND sends user-created reminders
RIPSORT a sophisticated data sorting program
(Described in SAC’s User manual (sorry))
SCRIBE a powerful text formatter for preparing documents.
(ISI’s manual, SCRIBE manual – soon on MILNET V.2)
SPELL text file spelling checker.
(HELP at TOPS-20 and directory international help -?)
SUSCON allows the creating, sending, and clearing of suspenses.
(international help – ? and , HELP command)
TACOPY used for printing hard copies of files
(international help – ?)
TALK pretty much the same as chat.
TIPCOPY predecessor of TACOPY
TN Tel-Net provides multi-host access on MILNET.
(HELP at TOPS-20 and directory,
international help – use ? and )
XED line oriented text editor.
(HELP at TOPS-20 and directory)
The Milnet ID card If you should be trashing somewhere and find a card that
+——————+ looks like this, then save it. (it will be blue & white)
/ \ It’s also wallet sized so you may
HOST USC-ISIE wish to mug someone who you know
HOST ADMINISTRATOR GORDON,VICKI L. is in the air force..haha!
————————————— (just kidding!)
CARD 118445

Application to Join Network Hackers Alliance (June 1, 1991)

Network Hackers Alliance INC

Inphiniti’s Edge BBS 06/01/91

Due to the fact of recent bustings as of 06/01/91. ISCC has radically
changed. It is strictly a private elite group. ‘Inphiniti’ was
questioned on 06/02/91 by two blue vested fbi agents. ‘Inphiniti’ knows
not what the saught, but they didn’t find shit.

Notice of Warning to the Applicant:
ISCC is a non-profit orginzation setup to educate the general
elite public. Any uses of any of our tech journals is strongly
discouraged and the authors and editors hold no responsibility for
the actions that are taken by the reader. All uses of all information
for a beneficial use are also strongly discouraged.

Please do not lie on this application. All information will we check
to the best of our efforts. If you are found to lie on this application
you will not be allowed into ISCC-PUNK. If accepted and found to lie
on your application your ass is out of the group as fast as you came
into the group.

Real Name:
Voice Number:
Date Number:
Address #1:
Address #2:

‘X’ the boxes inwhich you know most about the subject.

[ ] Hacking [ ] Viral Development
[ ] Unix/Vax Etc [ ] Anarchism
[ ] Networks [ ] Art of Crashing/Trashing
[ ] Phreaking [ ] Credit Fraud

What groups are you a current member if any

In the following lines please explain to me all you know about
‘Extenders’ and their uses in general.

In the following lines please explain to me all you know about
‘Unix/Vaxs/Networks’ and their uses in general.

In the following lines please explain to me all you know about
‘Diverters/Loops’ and their uses in general.

In the following lines please explain to me all you know about
‘PBXs’ and their uses in geneal.

In the following lines please explain to me all you know about
‘Hacking’ into InterNet/Tyment etc and all the uses..

Have you ever social engineered anything?

Please define the following acronyms.

In the next 50 lines please write a H/P text file on whatever
subject you like. Make this worth while as if we are going
to use it for future release. (Nothing smaller than 35 lines
will be accepted) If you have already written a H/P file attach
it to this application and tell us about it.


Are you a sysop?
Are you applying to be a Dist Site?
Are you applying to be a writer?
Are you applying to be a Sublingual Writer?

Dist Site Application
ISCC System must be 24 hour systems running at the minium of 1200
bps with the smallest a 5 meg drive. Must have users fro other area
codes currently calling (20% of users must be LD) and the board must
be within respectful looks/ideas and users. Exceptions may be made.

BBS Name:
BBS Number:
BBS Software:
BBS Total Storage:
BBS SysOp:
Does this BBS Support any other groups?
If yes which ones?

NFS Tracing by Passive Network Monitoring, by Matt Blaze of the Dept. of Computer Science at Princeton

NFS Tracing By Passive Network Monitoring

Matt Blaze

Department of Computer Science Princeton University


Traces of filesystem activity have proven to be useful for a wide variety of
purposes, ranging from quantitative analysis of system behavior to
trace-driven simulation of filesystem algorithms. Such traces can be
difficult to obtain, however, usually entailing modification of the
filesystems to be monitored and runtime overhead for the period of the
trace. Largely because of these difficulties, a surprisingly small number of
filesystem traces have been conducted, and few sample workloads are
available to filesystem researchers.

This paper describes a portable toolkit for deriving approximate traces of
NFS [1] activity by non-intrusively monitoring the Ethernet traffic to and
from the file server. The toolkit uses a promiscuous Ethernet listener
interface (such as the Packetfilter[2]) to read and reconstruct NFS-related
RPC packets intended for the server. It produces traces of the NFS activity
as well as a plausible set of corresponding client system calls. The tool is
currently in use at Princeton and other sites, and is available via
anonymous ftp.

1. Motivation

Traces of real workloads form an important part of virtually all analysis of
computer system behavior, whether it is program hot spots, memory access
patterns, or filesystem activity that is being studied. In the case of
filesystem activity, obtaining useful traces is particularly challenging.
Filesystem behavior can span long time periods, often making it necessary to
collect huge traces over weeks or even months. Modification of the
filesystem to collect trace data is often difficult, and may result in
unacceptable runtime overhead. Distributed filesystems exa cerbate these
difficulties, especially when the network is composed of a large number of
heterogeneous machines. As a result of these difficulties, only a relatively
small number of traces of Unix filesystem workloads have been conducted,
primarily in computing research environments. [3], [4] and [5] are examples
of such traces.

Since distributed filesystems work by transmitting their activity over a
network, it would seem reasonable to obtain traces of such systems by
placing a “tap” on the network and collecting trace data based on the
network traffic. Ethernet[6] based networks lend themselves to this approach
particularly well, since traffic is broadcast to all machines connected to a
given subnetwork. A number of general-purpose network monitoring tools are
avail able that “promiscuously” listen to the Ethernet to which they are
connected; Sun’s etherfind[7] is an example of such a tool. While these
tools are useful for observing (and collecting statistics on) specific types
of packets, the information they provide is at too low a level to be useful
for building filesystem traces. Filesystem operations may span several
packets, and may be meaningful only in the context of other, previous

Some work has been done on characterizing the impact of NFS traffic on
network load. In [8], for example, the results of a study are reported in
which Ethernet traffic was monitored and statistics gathered on NFS
activity. While useful for understanding traffic patterns and developing a
queueing model of NFS loads, these previous stu dies do not use the network
traffic to analyze the file access traffic patterns of the system, focusing
instead on developing a statistical model of the individual packet sources,
destinations, and types.

This paper describes a toolkit for collecting traces of NFS file access
activity by monitoring Ethernet traffic. A “spy” machine with a promiscuous
Ethernet interface is connected to the same network as the file server. Each
NFS-related packet is analyzed and a trace is produced at an appropriate
level of detail. The tool can record the low level NFS calls themselves or
an approximation of the user-level system calls (open, close, etc.) that
triggered the activity.

We partition the problem of deriving NFS activity from raw network traffic
into two fairly distinct subprob lems: that of decoding the low-level NFS
operations from the packets on the network, and that of translating these
low-level commands back into user-level system calls. Hence, the toolkit
consists of two basic parts, an “RPC decoder” (rpcspy) and the “NFS
analyzer” (nfstrace). rpcspy communicates with a low-level network
monitoring facility (such as Sun’s NIT [9] or the Packetfilter [2]) to read
and reconstruct the RPC transactions (call and reply) that make up each NFS
command. nfstrace takes the output of rpcspy and reconstructs the sys tem
calls that occurred as well as other interesting data it can derive about
the structure of the filesystem, such as the mappings between NFS file
handles and Unix file names. Since there is not a clean one-to-one mapping
between system calls and lower-level NFS commands, nfstrace uses some simple
heuristics to guess a reasonable approximation of what really occurred.

1.1. A Spy’s View of the NFS Protocols

It is well beyond the scope of this paper to describe the protocols used by
NFS; for a detailed description of how NFS works, the reader is referred to
[10], [11], and [12]. What follows is a very brief overview of how NFS
activity translates into Ethernet packets.

An NFS network consists of servers, to which filesystems are physically
connected, and clients, which per form operations on remote server
filesystems as if the disks were locally connected. A particular machine can
be a client or a server or both. Clients mount remote server filesystems in
their local hierarchy just as they do local filesystems; from the user’s
perspective, files on NFS and local filesystems are (for the most part)
indistinguishable, and can be manipulated with the usual filesystem calls.

The interface between client and server is defined in terms of 17 remote
procedure call (RPC) operations. Remote files (and directories) are referred
to by a file handle that uniquely identifies the file to the server. There
are operations to read and write bytes of a file (read, write), obtain a
file’s attributes (getattr), obtain the contents of directories (lookup,
readdir), create files (create), and so forth. While most of these
operations are direct analogs of Unix system calls, notably absent are open
and close operations; no client state information is maintained at the
server, so there is no need to inform the server explicitly when a file is
in use. Clients can maintain buffer cache entries for NFS files, but must
verify that the blocks are still valid (by checking the last write time with
the getattr operation) before using the cached data.

An RPC transaction consists of a call message (with arguments) from the
client to the server and a reply mes sage (with return data) from the server
to the client. NFS RPC calls are transmitted using the UDP/IP connection
less unreliable datagram protocol[13]. The call message contains a unique
transaction identifier which is included in the reply message to enable the
client to match the reply with its call. The data in both messages is
encoded in an “external data representation” (XDR), which provides a
machine-independent standard for byte order, etc.

Note that the NFS server maintains no state information about its clients,
and knows nothing about the context of each operation outside of the
arguments to the operation itself.

2. The rpcspy Program

rpcspy is the interface to the system-dependent Ethernet monitoring
facility; it produces a trace of the RPC calls issued between a given set of
clients and servers. At present, there are versions of rpcspy for a number
of BSD-derived systems, including ULTRIX (with the Packetfilter[2]), SunOS
(with NIT[9]), and the IBM RT running AOS (with the Stanford enet filter).

For each RPC transaction monitored, rpcspy produces an ASCII record
containing a timestamp, the name of the server, the client, the length of
time the command took to execute, the name of the RPC command executed, and
the command- specific arguments and return data. Currently, rpcspy
understands and can decode the 17 NFS RPC commands, and there are hooks to
allow other RPC services (for example, NIS) to be added reasonably easily.

The output may be read directly or piped into another program (such as
nfstrace) for further analysis; the for mat is designed to be reasonably
friendly to both the human reader and other programs (such as nfstrace or

Since each RPC transaction consists of two messages, a call and a reply,
rpcspy waits until it receives both these components and emits a single
record for the entire transaction. The basic output format is 8 vertical-bar
separated fields:

timestamp | execution-time | server | client | command-name | arguments |

where timestamp is the time the reply message was received, execution-time
is the time (in microseconds) that elapsed between the call and reply,
server is the name (or IP address) of the server, client is the name (or IP
address) of the client followed by the userid that issued the command,
command-name is the name of the particular program invoked (read, write,
getattr, etc.), and arguments and reply-data are the command dependent
arguments and return values passed to and from the RPC program,

The exact format of the argument and reply data is dependent on the specific
command issued and the level of detail the user wants logged. For example, a
typical NFS command is recorded as follows:

690529992.167140 | 11717 | paramount | merckx.321 | read |
{“7b1f00000000083c”, 0, 8192} | ok, 1871

In this example, uid 321 at client “merckx” issued an NFS read command to
server “paramount”. The reply was issued at (Unix time) 690529992.167140
seconds; the call command occurred 11717 microseconds earlier. Three
arguments are logged for the read call: the file handle from which to read
(represented as a hexadecimal string), the offset from the beginning of the
file, and the number of bytes to read. In this example, 8192 bytes are
requested starting at the beginning (byte 0) of the file whose handle is
“7b1f00000000083c”. The command completed successfully (status “ok”), and
1871 bytes were returned. Of course, the reply message also included the
1871 bytes of data from the file, but that field of the reply is not logged
by rpcspy.

rpcspy has a number of configuration options to control which hosts and RPC
commands are traced, which call and reply fields are printed, which Ethernet
interfaces are tapped, how long to wait for reply messages, how long to run,
etc. While its primary function is to provide input for the nfstrace program
(see Section 3), judi cious use of these options (as well as such programs
as grep, awk, etc.) permit its use as a simple NFS diag nostic and
performance monitoring tool. A few screens of output give a surprisingly
informative snapshot of current NFS activity; we have identified quickly
using the program several problems that were otherwise difficult to
pinpoint. Similarly, a short awk script can provide a breakdown of the most
active clients, servers, and hosts over a sampled time period.

2.1. Implementation Issues

The basic function of rpcspy is to monitor the network, extract those
packets containing NFS data, and print the data in a useful format. Since
each RPC transaction consists of a call and a reply, rpcspy maintains a
table of pending call packets that are removed and emitted when the matching
reply arrives. In normal operation on a reasonably fast workstation, this
rarely requires more than about two megabytes of memory, even on a busy net
work with unusually slow file servers. Should a server go down, however, the
queue of pending call messages (which are never matched with a reply) can
quickly become a memory hog; the user can specify a maximum size the table
is allowed to reach before these “orphaned” calls are searched out and

File handles pose special problems. While all NFS file handles are a fixed
size, the number of significant bits varies from implementation to
implementation; even within a vendor, two different releases of the same
operating system might use a completely different internal handle format. In
most Unix implementations, the handle contains a filesystem identifier and
the inode number of the file; this is sometimes augmented by additional
information, such as a version number. Since programs using rpcspy output
generally will use the handle as a unique file identifier, it is important
that there not appear to be more than one handle for the same file.
Unfortunately, it is not sufficient to simply consider the handle as a
bitstring of the maximum handle size, since many operating systems do not
zero out the unused extra bits before assigning the handle. Fortunately,
most servers are at least consistent in the sizes of the handles they
assign. rpcspy allows the user to specify (on the command line or in a
startup file) the handle size for each host to be monitored. The handles
from that server are emitted as hexadecimal strings truncated at that
length. If no size is specified, a guess is made based on a few common
formats of a reasonable size.

It is usually desirable to emit IP addresses of clients and servers as their
symbolic host names. An early ver sion of the software simply did a
nameserver lookup each time this was necessary; this quickly flooded the
network with a nameserver request for each NFS transaction. The current
version maintains a cache of host names; this requires a only a modest
amount of memory for typical networks of less than a few hundred hosts. For
very large networks or those where NFS service is provided to a large number
of remote hosts, this could still be a potential problem, but as a last
resort remote name resolution could be disabled or rpcspy configured to not
translate IP addresses.

UDP/IP datagrams may be fragmented among several packets if the datagram is
larger than the maximum size of a single Ethernet frame. rpcspy looks only
at the first fragment; in practice, fragmentation occurs only for the data
fields of NFS read and write transactions, which are ignored anyway.

3. nfstrace: The Filesystem Tracing Package

Although rpcspy provides a trace of the low-level NFS commands, it is not,
in and of itself, sufficient for obtaining useful filesystem traces. The
low-level commands do not by themselves reveal user-level activity. Furth
ermore, the volume of data that would need to be recorded is potentially
enormous, on the order of megabytes per hour. More useful would be an
abstraction of the user-level system calls underlying the NFS activity.

nfstrace is a filter for rpcspy that produces a log of a plausible set of
user level filesystem commands that could have triggered the monitored
activity. A record is produced each time a file is opened, giving a summary
of what occurred. This summary is detailed enough for analysis or for use as
input to a filesystem simulator.

The output format of nfstrace consists of 7 fields:

timestamp | command-time | direction | file-id | client | transferred | size

where timestamp is the time the open occurred, command-time is the length of
time between open and close, direc tion is either read or write (mkdir and
readdir count as write and read, respectively). file-id identifies the
server and the file handle, client is the client and user that performed the
open, transferred is the number of bytes of the file actually read or
written (cache hits have a 0 in this field), and size is the size of the
file (in bytes).

An example record might be as follows:

690691919.593442 | 17734 | read | basso:7b1f00000000400f | frejus.321 | 0 |

Here, userid 321 at client frejus read file 7b1f00000000400f on server
basso. The file is 24576 bytes long and was able to be read from the client
cache. The command started at Unix time 690691919.593442 and took 17734
microseconds at the server to execute.

Since it is sometimes useful to know the name corresponding to the handle
and the mode information for each file, nfstrace optionally produces a map
of file handles to file names and modes. When enough information (from
lookup and readdir commands) is received, new names are added. Names can
change over time (as files are deleted and renamed), so the times each
mapping can be considered valid is recorded as well. The mapping infor
mation may not always be complete, however, depending on how much activity
has already been observed. Also, hard links can confuse the name mapping,
and it is not always possible to determine which of several possible names a
file was opened under.

What nfstrace produces is only an approximation of the underlying user
activity. Since there are no NFS open or close commands, the program must
guess when these system calls occur. It does this by taking advantage of the
observation that NFS is fairly consistent in what it does when a file is
opened. If the file is in the local buffer cache, a getattr call is made on
the file to verify that it has not changed since the file was cached.
Otherwise, the actual bytes of the file are fetched as they are read by the
user. (It is possible that part of the file is in the cache and part is not,
in which case the getattr is performed and only the missing pieces are
fetched. This occurs most often when a demand-paged executable is loaded).
nfstrace assumes that any sequence of NFS read calls on the same file issued
by the same user at the same client is part of a single open for read. The
close is assumed to have taken place when the last read in the sequence
completes. The end of a read sequence is detected when the same client reads
the beginning of the file again or when a timeout with no reading has
elapsed. Writes are handled in a similar manner.

Reads that are entirely from the client cache are a bit harder; not every
getattr command is caused by a cache read, and a few cache reads take place
without a getattr. A user level stat system call can sometimes trigger a
getattr, as can an ls -l command. Fortunately, the attribute caching used by
most implementations of NFS seems to eliminate many of these extraneous
getattrs, and ls commands appear to trigger a lookup command most of the
time. nfstrace assumes that a getattr on any file that the client has read
within the past few hours represents a cache read, otherwise it is ignored.
This simple heuristic seems to be fairly accurate in practice. Note also
that a getattr might not be performed if a read occurs very soon after the
last read, but the time threshold is generally short enough that this is
rarely a problem. Still, the cached reads that nfstrace reports are, at
best, an estimate (generally erring on the side of over-reporting). There is
no way to determine the number of bytes actually read for cache hits.

The output of nfstrace is necessarily produced out of chronological order,
but may be sorted easily by a post-processor.

nfstrace has a host of options to control the level of detail of the trace,
the lengths of the timeouts, and so on. To facilitate the production of very
long traces, the output can be flushed and checkpointed at a specified inter
val, and can be automatically compressed.

4. Using rpcspy and nfstrace for Filesystem Tracing

Clearly, nfstrace is not suitable for producing highly accurate traces;
cache hits are only estimated, the timing information is imprecise, and data
from lost (and duplicated) network packets are not accounted for. When such
a highly accurate trace is required, other approaches, such as modification
of the client and server kernels, must be employed.

The main virtue of the passive-monitoring approach lies in its simplicity.
In [5], Baker, et al, describe a trace of a distributed filesystem which
involved low-level modification of several different operating system
kernels. In contrast, our entire filesystem trace package consists of less
than 5000 lines of code written by a single programmer in a few weeks,
involves no kernel modifications, and can be installed to monitor multiple
heterogeneous servers and clients with no knowledge of even what operating
systems they are running.

The most important parameter affecting the accuracy of the traces is the
ability of the machine on which rpcspy is running to keep up with the
network traffic. Although most modern RISC workstations with reasonable
Ethernet interfaces are able to keep up with typical network loads, it is
important to determine how much informa tion was lost due to packet buffer
overruns before relying upon the trace data. It is also important that the
trace be, indeed, non-intrusive. It quickly became obvious, for example,
that logging the traffic to an NFS filesystem can be problematic.

Another parameter affecting the usefulness of the traces is the validity of
the heuristics used to translate from RPC calls into user-level system
calls. To test this, a shell script was written that performed ls -l, touch,
cp and wc commands randomly in a small directory hierarchy, keeping a record
of which files were touched and read and at what time. After several hours,
nfstrace was able to detect 100% of the writes, 100% of the uncached reads,
and 99.4% of the cached reads. Cached reads were over-reported by 11%, even
though ls com mands (which cause the “phantom” reads) made up 50% of the
test activity. While this test provides encouraging evidence of the accuracy
of the traces, it is not by itself conclusive, since the particular workload
being monitored may fool nfstrace in unanticipated ways.

As in any research where data are collected about the behavior of human
subjects, the privacy of the individu als observed is a concern. Although
the contents of files are not logged by the toolkit, it is still possible to
learn something about individual users from examining what files they read
and write. At a minimum, the users of a mon itored system should be informed
of the nature of the trace and the uses to which it will be put. In some
cases, it may be necessary to disable the name translation from nfstrace
when the data are being provided to others. Commercial sites where filenames
might reveal something about proprietary projects can be particularly
sensitive to such concerns.

5. A Trace of Filesystem Activity in the Princeton C.S. Department

A previous paper[14] analyzed a five-day long trace of filesystem activity
conducted on 112 research worksta tions at DEC-SRC. The paper identified a
number of file access properties that affect filesystem caching perfor
mance; it is difficult, however, to know whether these properties were
unique artifacts of that particular environment or are more generally
applicable. To help answer that question, it is necessary to look at similar
traces from other computing environments.

It was relatively easy to use rpcspy and nfstrace to conduct a week long
trace of filesystem activity in the Princeton University Computer Science
Department. The departmental computing facility serves a community of
approximately 250 users, of which about 65% are researchers (faculty,
graduate students, undergraduate researchers, postdoctoral staff, etc), 5%
office staff, 2% systems staff, and the rest guests and other “external”
users. About 115 of the users work full-time in the building and use the
system heavily for electronic mail, netnews, and other such communication
services as well as other computer science research oriented tasks (editing,
compiling, and executing programs, formatting documents, etc).

The computing facility consists of a central Auspex file server (fs) (to
which users do not ordinarily log in directly), four DEC 5000/200s (elan,
hart, atomic and dynamic) used as shared cycle servers, and an assortment of
dedicated workstations (NeXT machines, Sun workstations, IBM-RTs, Iris
workstations, etc.) in indi vidual offices and laboratories. Most users log
in to one of the four cycle servers via X window terminals located in
offices; the terminals are divided evenly among the four servers. There are
a number of Ethernets throughout the building. The central file server is
connected to a “machine room network” to which no user terminals are
directly connected; traffic to the file server from outside the machine room
is gatewayed via a Cisco router. Each of the four cycle servers has a local
/, /bin and /tmp filesystem; other filesystems, including /usr, /usr/local,
and users’ home directories are NFS mounted from fs. Mail sent from local
machines is delivered locally to the (shared) fs:/usr/spool/mail; mail from
outside is delivered directly on fs.

The trace was conducted by connecting a dedicated DEC 5000/200 with a local
disk to the machine room net work. This network carries NFS traffic for all
home directory access and access to all non-local cycle-server files
(including the most of the actively-used programs). On a typical weekday,
about 8 million packets are transmitted over this network. nfstrace was
configured to record opens for read and write (but not directory accesses or
individual reads or writes). After one week (wednesday to wednesday),
342,530 opens for read and 125,542 opens for write were recorded, occupying
8 MB of (compressed) disk space. Most of this traffic was from the four
cycle servers.

No attempt was made to “normalize” the workload during the trace period.
Although users were notified that file accesses were being recorded, and
provided an opportunity to ask to be excluded from the data collection, most
users seemed to simply continue with their normal work. Similarly, no
correction is made for any anomalous user activity that may have occurred
during the trace.

5.1. The Workload Over Time

Intuitively, the volume of traffic can be expected to vary with the time of
day. Figure 1 shows the number of reads and writes per hour over the seven
days of the trace; in particular, the volume of write traffic seems to
mirror the general level of departmental activity fairly closely.

An important metric of NFS performance is the client buffer cache hit rate.
Each of the four cycle servers allocates approximately 6MB of memory for the
buffer cache. The (estimated) aggregate hit rate (percentage of reads served
by client caches) as seen at the file server was surprisingly low: 22.2%
over the entire week. In any given hour, the hit rate never exceeded 40%.
Figure 2 plots (actual) server reads and (estimated) cache hits per hour
over the trace week; observe that the hit rate is at its worst during
periods of the heaviest read activity.

Past studies have predicted much higher hit rates than the aggregate
observed here. It is probable that since most of the traffic is generated by
the shared cycle servers, the low hit rate can be attributed to the large
number of users competing for cache space. In fact, the hit rate was
observed to be much higher on the single-user worksta tions monitored in the
study, averaging above 52% overall. This suggests, somewhat
counter-intuitively, that if more computers were added to the network (such
that each user had a private workstation), the server load would decrease
considerably. Figure 3 shows the actual cache misses and estimated cache
hits for a typical private works tation in the study.

Thu 00:00 Thu 06:00 Thu 12:00 Thu 18:00 Fri 00:00 Fri 06:00 Fri 12:00
Fri 18:00 Sat 00:00 Sat 06:00 Sat 12:00 Sat 18:00 Sun 00:00 Sun 06:00 Sun
12:00 Sun 18:00 Mon 00:00 Mon 06:00 Mon 12:00 Mon 18:00 Tue 00:00 Tue 06:00
Tue 12:00 Tue 18:00 Wed 00:00 Wed 06:00 Wed 12:00 Wed 18:00







Reads/Writes per hour


Reads (all)

Figure 1 – Read and Write Traffic Over Time

5.2. File Sharing

One property observed in the DEC-SRC trace is the tendency of files that are
used by multiple workstations to make up a significant proportion of read
traffic but a very small proportion of write traffic. This has important
implications for a caching strategy, since, when it is true, files that are
cached at many places very rarely need to be invalidated. Although the
Princeton computing facility does not have a single workstation per user, a
similar metric is the degree to which files read by more than one user are
read and written. In this respect, the Princeton trace is very similar to
the DEC-SRC trace. Files read by more than one user make up more than 60% of
read traffic, but less than 2% of write traffic. Files shared by more than
ten users make up less than .2% of write traffic but still more than 30% of
read traffic. Figure 3 plots the number of users who have previously read
each file against the number of reads and writes.

5.3. File “Entropy”

Files in the DEC-SRC trace demonstrated a strong tendency to “become”
read-only as they were read more and more often. That is, the probability
that the next operation on a given file will overwrite the file drops off
shar ply in proportion to the number of times it has been read in the past.
Like the sharing property, this has implications for a caching strategy,
since the probability that cached data is valid influences the choice of a
validation scheme. Again, we find this property to be very strong in the
Princeton trace. For any file access in the trace, the probability that it
is a write is about 27%. If the file has already been read at least once
since it was last written to, the write probability drops to 10%. Once the
file has been read at least five times, the write probability drops below
1%. Fig ure 4 plots the observed write probability against the number of
reads since the last write.

Thu 00:00 Thu 06:00 Thu 12:00 Thu 18:00 Fri 00:00 Fri 06:00 Fri 12:00
Fri 18:00 Sat 00:00 Sat 06:00 Sat 12:00 Sat 18:00 Sun 00:00 Sun 06:00 Sun
12:00 Sun 18:00 Mon 00:00 Mon 06:00 Mon 12:00 Mon 18:00 Tue 00:00 Tue 06:00
Tue 12:00 Tue 18:00 Wed 00:00 Wed 06:00 Wed 12:00 Wed 18:00






Total reads per hour

Cache Hits (estimated)

Cache Misses (actual)

Figure 2 – Cache Hits and Misses Over Time

6. Conclusions

Although filesystem traces are a useful tool for the analysis of current and
proposed systems, the difficulty of collecting meaningful trace data makes
such traces difficult to obtain. The performance degradation introduced by
the trace software and the volume of raw data generated makes traces over
long time periods and outside of comput ing research facilities particularly
hard to conduct.

Although not as accurate as direct, kernel-based tracing, a passive network
monitor such as the one described in this paper can permit tracing of
distributed systems relatively easily. The ability to limit the data
collected to a high-level log of only the data required can make it
practical to conduct traces over several months. Such a long term trace is
presently being conducted at Princeton as part of the author’s research on
filesystem caching. The non-intrusive nature of the data collection makes
traces possible at facilities where kernel modification is impracti cal or

It is the author’s hope that other sites (particularly those not doing
computing research) will make use of this toolkit and will make the traces
available to filesystem researchers.

7. Availability

The toolkit, consisting of rpcspy, nfstrace, and several support scripts,
currently runs under several BSD-derived platforms, including ULTRIX 4.x,
SunOS 4.x, and IBM-RT/AOS. It is available for anonymous ftp over the
Internet from, in the compressed tar file

Thu 00:00 Thu 06:00 Thu 12:00 Thu 18:00 Fri 00:00 Fri 06:00 Fri 12:00
Fri 18:00 Sat 00:00 Sat 06:00 Sat 12:00 Sat 18:00 Sun 00:00 Sun 06:00 Sun
12:00 Sun 18:00 Mon 00:00 Mon 06:00 Mon 12:00 Mon 18:00 Tue 00:00 Tue 06:00
Tue 12:00 Tue 18:00 Wed 00:00 Wed 06:00 Wed 12:00 Wed 18:00 0




Reads per hour

Cache Hits (estimated)

Cache Misses (actual)

Figure 3 – Cache Hits and Misses Over Time – Private Workstation

0 5 10 15 20

n (readers)







% of Reads and Writes used by > n users



Figure 4 – Degree of Sharing for Reads and Writes

0 5 10 15 20

Reads Since Last Write




P(next operation is write)

Figure 5 – Probability of Write Given >= n Previous Reads

8. Acknowledgments

The author would like to gratefully acknowledge Jim Roberts and Steve Beck
for their help in getting the trace machine up and running, Rafael Alonso
for his helpful comments and direction, and the members of the pro gram
committee for their valuable suggestions. Jim Plank deserves special thanks
for writing jgraph, the software which produced the figures in this paper.

9. References

[1] Sandberg, R., Goldberg, D., Kleiman, S., Walsh, D., & Lyon, B. “Design
and Implementation of the Sun Net work File System.” Proc. USENIX, Summer,

[2] Mogul, J., Rashid, R., & Accetta, M. “The Packet Filter: An Efficient
Mechanism for User-Level Network Code.” Proc. 11th ACM Symp. on Operating
Systems Principles, 1987.

[3] Ousterhout J., et al. “A Trace-Driven Analysis of the Unix 4.2 BSD File
System.” Proc. 10th ACM Symp. on Operating Systems Principles, 1985.

[4] Floyd, R. “Short-Term File Reference Patterns in a UNIX Environment,”
TR-177 Dept. Comp. Sci, U. of Rochester, 1986.

[5] Baker, M. et al. “Measurements of a Distributed File System,” Proc. 13th
ACM Symp. on Operating Systems Principles, 1991.

[6] Metcalfe, R. & Boggs, D. “Ethernet: Distributed Packet Switching for
Local Computer Networks,” CACM July, 1976.

[7] “Etherfind(8) Manual Page,” SunOS Reference Manual, Sun Microsystems,

[8] Gusella, R. “Analysis of Diskless Workstation Traffic on an Ethernet,”
TR-UCB/CSD-87/379, University Of California, Berkeley, 1987.

[9] “NIT(4) Manual Page,” SunOS Reference Manual, Sun Microsystems, 1988.

[10] “XDR Protocol Specification,” Networking on the Sun Workstation, Sun
Microsystems, 1986.

[11] “RPC Protocol Specification,” Networking on the Sun Workstation, Sun
Microsystems, 1986.

[12] “NFS Protocol Specification,” Networking on the Sun Workstation, Sun
Microsystems, 1986.

[13] Postel, J. “User Datagram Protocol,” RFC 768, Network Information
Center, 1980.

[14] Blaze, M., and Alonso, R., “Long-Term Caching Strategies for Very Large
Distributed File Systems,” Proc. Summer 1991 USENIX, 1991.

Matt Blaze is a Ph.D. candidate in Computer Science at Princeton University,
where he expects to receive his degree in the Spring of 1992. His research
interests include distributed systems, operating systems, databases, and
programming environments. His current research focuses on caching in very
large distributed filesystems. In 1988 he received an M.S. in Computer
Science from Columbia University and in 1986 a B.S. from Hunter College. He
can be reached via email at or via US mail at Dept. of
Computer Science, Princeton University, 35 Olden Street, Princeton NJ

The Book of MOD: Part 5: Who are They And Where Did They Come From? (Summer 1991)

=============================================================================== Who are they and where did they come from?

Well, it’s time again for another journal. It’s now the
middle of summer 1991. Lately we’ve heard a few good stories
out of the mouths of people we don’t even know. There have
even been a few funny occurances in the past few weeks.

1) There are rumours that Phiber Optik was wasting his life
away and not using his talents wisely. Well, the truth of
the matter is, he has been a speaker in many public debates
and conferences on hacking in general and computer security.
He is also working as a programmer/developer for a computer
firm in NYC. Also, he is working closely with the EFF (which
recently have set up their own system for their organization).

2) COMSEC is formed. The *new* LOD (whose only member
consists of Erik Bloodaxe) goes into the computer security
business. Nothing to date is documented on their services and
we have yet to see what the hell they can provide. EBA for
one is an original member and he knows close to nothing
(except for the things that he asked Phiber Optik to tell
him). Not to mention these guys are hardly corporate and have
NO experience in the business end of computer security; which
explains why they got caught misrepresenting themselves as
Landmark Graphics to other well-established computer security
firms. Also, they have bragged about narking on a few members
of MOD in their jealous rage. This we can prove through

MOD was never a textfile “how-to” group. It was always based
on a brotherhood type deal and everything done is secretive
and has a purpose behind it. LOD on the other hand, never
made sense to any of us anymore. It was good at first, when
all the original (knowledgable) members were active, but
lately it’s become to be known as a group of guys with
very sparce telecom knowledge riding on a name that once
actually stood for something.

Even Phiber Optik questioned whether LOD meant Legion of Doom
or Lump of Doo-doo (on Gyrotechnic’s private bbs). He stood
firm against all the other members on the system until finally
they were dumbfounded and speechless. Well, the board died.
Now, PO and the rest of the MOD bunch take to them like a
swatter to flies. Give it up fellas.. it’ll never work.

3) Renegade Hacker (a NYC local) thinks he’s cool. He gets
raided, starts talking, and when confronted by MOD, hides
behind mommy. Then he says he hates MOD (which is funny since
he was sweating MOD’s nuts since the day he first got a modem;
those who were at the 2600 know what I mean..) The fact
remains he is a real loser out to make a name for himself by
trying to inspire those who have less contact with the better
hackers in the community.

NASTY (his group) = BIG Joke.
(they write files..the National Enquirer of the h/p world)

*Rent-A-Gay Hacker changed his phone #.. please note the new
one in the database.*

4) Lord Micro gets Xenix and creates what will be modnet 2.
(The Wing is the administrator of #1 in PA) Crazy Eddie
plans to put up a bbs (open forum) in the 2600 Magazine
format (like OSUNY, Central Office, The Toll Center).
NO illegal shit…just theoretical discussion..what real
hackers are made of.

5) Vinny (The Technician) is “outed”. He is an admitted
homosexual. I’m telling you.. watch out for these SSWC
guys..they’re a little funny, ya know?

6) Mind Rape, or something like that, of NSA is a new pest.
Gimme a break. When will they ever learn? Infiniti was
another one, but I guess he’s kept quiet..which is good.
Let’s just hope he doesn’t ask Mind Dweeb for help. Add
Purple “no-show” Mustard (codez kid..see MOD/database for more
info) to this catagory. Also, there’s another guy using
Acid’s handle in 216. Wasn’t home when we called twice.

Special thanks to Jack Hitt and Paul Tough of Harper’s Magazine.
Great guys, good writers/editors.. damn that stuff was fun.

Hello to State Police Officer Donald Delaney. Not such a bad guy,
just that he IS a cop and he DID bust some of us. But he also got
those guys pirating cellular service in Queens, which really was a
major bust. Nice tie.

= Another MOD.duh =
= file.. = “More eLiTenezz in one pinky
= = than 2 cans of LOD!”
= All replies can =
= be sent to: =
= =
= MOD@modnet.UUCP =
-> kill r0dentz!!!

The Book of MOD: Part Four: End of ’90-‘1991

=============================================================================== [End of ’90-1991]

Two weeks before his bust, Lord Micro was introduced into the group.
Unfortunately he was busted for hacking FON cards off the 800/877-8000. Sure,
he knew he was gonna get busted but he didn’t listen, or care for that matter.
After hours (and hours, and hours) of community service, LM lived to joke
about his ordeal being that he IS a funny guy. Don’t ever get this guy drunk.

For quite a long time now, MOD has come to realize what a bunch of
idiot posers the LOD was (with the exception of a few). It just goes to show,
ANYONE can be a great hacker as long as enough people think so too. Why
bother resparking interest in LOD? Why bother keeping the damn thing going
when the new members aren’t half as good as the originals? I don’t know, but
you can ask Erik Bloodaxe who is the self-proclaimed “leader” at this point
in time. Jeez, and I thought bringing back TAP was stupid.

Another poser that came out of the woodwork is Skandle (STAN), who
somehow decided he had power in DPAK (Supernigger’s group). After hours of
trying to figure this one out, we just had to conclude was just another
dumb Jersey hick. Oh well.. so much for that.

A new group, FORCE 1(ONE) Hackers led by Expose(which sounds fuckin gay
if ya ask me), decided to declare war on MOD. Assisted by Hellrat, he says:
“You guys (MOD) should stay out of the hackin’ buziness ‘cuz none of my fellas
are ‘fraid of you. I’ll take all of you out myself.” …along with a lot of
other nonsense about 10-way billing and other ca-ca he’s read in one too many

One thing that’s cool is the addition of a lamer database online (on
wingnet now MODNET). It’s great when you’re planning roll-ups and shit and
it’s a great organizer that takes care of all that rummaging through papers
and shit. Hundreds of losers for hours of fun!

During the first week in February, LOD finally declared,”That’s it!
It’s official now. LOD declares war on MOD!” Oh brother..

eenie-meenie-minie-moe..I declare war on…..YOU! Nyah-nyah. Well, it is now
the second week of February and the only thing that has happened so far in the
“MOD-LOD War” is that there were about 5 invalid login attempts on modnet. It
seems that “MOB” has decided to join in the war. What a fucking joke, they are
tied with MCWS for lameness (which isn’t hard to do).

The legacy of the underground “clandestine” network continues and so does the
war (and ridiculing) against all the self-proclaimed, so-called “elite”.

–EOF (