|
Softpanorama
(slightly skeptical)
Open Source Software Educational Society |
May the
source be with you,
but remember the KISS principle ;-)
|
Architectural Issues of Intrusion Detection Infrastructure in Large Enterprises
(Webliography and Research Materials to the Article)
Please note that due to the size the introduction was converted to a separate
page, an article
Architectural Issues of Intrusion Detection Infrastructure in Large Enterprises
Notes:
- Those pages are written by people for whom English is not a
native language. Some amount of grammar and spelling errors
should be expected.
- This is a Spartan WHYFF (We Help You For Free) site. It
cannot replace the best teachers and
the
best books.
- The site contain some obsolete pages as it develops like a
living tree... Some links on older pages
are broken. Please
try to use Google, Open directory, etc. to find a replacement link
(see
HOWTO search the WEB for details).
We would appreciate if you can
mail us a correct link.
|
|
This George Akerlof ideas about asymmetrical information ("The
Market for 'Lemons'") are probably as applicable to used car as for
IDS.
More than a year ago, I wrote about the increasing
risks of data loss because more and more data fits
in smaller and smaller packages. Today I use a 4-GB
USB memory stick for backup while I am traveling. I
like the convenience, but if I lose the tiny thing I
risk all my data.
Encryption is the obvious solution for
this problem -- I use PGPdisk -- but
Secustick sounds even better: It automatically
erases itself after a set number of bad password
attempts. The company makes a bunch of other
impressive claims: The product was commissioned, and
eventually approved, by the French intelligence
service; it is used by many militaries and banks;
its technology is revolutionary.
Unfortunately, the only impressive aspect of
Secustick is its hubris, which was revealed when
Tweakers.net
completely
broke its security. There's no data
self-destruct feature. The password protection can
easily be bypassed. The data isn't even encrypted.
As a secure storage device, Secustick is pretty
useless.
On the surface, this is just another
snake-oil security story. But there's a deeper
question: Why are there so many bad security
products out there? It's not just that designing
good security is hard -- although it is -- and it's
not just that
anyone can design a security product that he
himself cannot break. Why do mediocre security
products beat the good ones in the marketplace?
In 1970, American economist George Akerlof wrote
a paper called "The
Market for 'Lemons'" (abstract and article for
pay
here), which established asymmetrical
information theory. He eventually won a Nobel Prize
for his work, which looks at markets where the
seller knows a lot more about the product than the
buyer.
Akerlof illustrated his ideas with a used car
market. A used car market includes both good cars
and lousy ones (lemons). The seller knows which is
which, but the buyer can't tell the difference -- at
least until he's made his purchase. I'll spare you
the math, but what ends up happening is that the
buyer bases his purchase price on the value of a
used car of average quality.
This means that the best cars don't get sold;
their prices are too high. Which means that the
owners of these best cars don't put their cars on
the market. And then this starts spiraling. The
removal of the good cars from the market reduces the
average price buyers are willing to pay, and then
the very good cars no longer sell, and disappear
from the market. And then the good cars, and so on
until only the lemons are left.
In a market where the seller has more information
about the product than the buyer, bad products can
drive the good ones out of the market.
The computer security market has a lot of the
same characteristics of Akerlof's lemons market.
Take the market for encrypted USB memory sticks.
Several companies make encrypted USB drives --
Kingston Technology sent me one in the mail a
few days ago -- but even I couldn't tell you if
Kingston's offering is better than Secustick. Or if
it's better than any other encrypted USB drives.
They use the same encryption algorithms. They make
the same security claims. And if I can't tell the
difference, most consumers won't be able to either.
Of course, it's more expensive to make an
actually secure USB drive. Good security design
takes time, and necessarily means limiting
functionality. Good security testing takes even more
time, especially if the product is any good. This
means the less-secure product will be cheaper,
sooner to market and have more features. In this
market, the more-secure USB drive is going to lose
out.
I see this kind of thing happening over and over
in computer security. In the late 1980s and early
1990s, there were more than a hundred competing
firewall products. The few that "won" weren't the
most secure firewalls; they were the ones that were
easy to set up, easy to use and didn't annoy users
too much. Because buyers couldn't base their buying
decision on the relative security merits, they based
them on these other criteria. The intrusion
detection system, or IDS, market evolved the same
way, and before that the antivirus market. The few
products that succeeded weren't the most secure,
because buyers couldn't tell the difference.
How do you solve this? You need what economists
call a "signal," a way for buyers to tell the
difference. Warrantees are a common signal.
Alternatively, an independent auto mechanic can tell
good cars from lemons, and a buyer can hire his
expertise. The Secustick story demonstrates this. If
there is a consumer advocate group that has the
expertise to evaluate different products, then the
lemons can be exposed.
Secustick, for one, seems to have been
withdrawn from
sale.
But security testing is both expensive and slow,
and it just isn't possible for an independent lab to
test everything. Unfortunately, the exposure of
Secustick is an exception. It was a simple product,
and easily exposed once someone bothered to look. A
complex software product -- a firewall, an IDS -- is
very hard to test well. And, of course, by the time
you have tested it, the vendor has a new version on
the market.
In reality, we have to rely on a variety of
mediocre signals to differentiate the good security
products from the bad. Standardization is one
signal. The widely used AES encryption standard has
reduced, although not eliminated, the number of
lousy encryption algorithms on the market.
Reputation is a more common signal; we choose
security products based on the reputation of the
company selling them, the reputation of some
security wizard associated with them, magazine
reviews, recommendations from colleagues or general
buzz in the media.
All these signals have their problems. Even
product reviews, which should be as comprehensive as
the Tweakers' Secustick review, rarely are. Many
firewall comparison reviews focus on things the
reviewers can easily measure, like packets per
second, rather than how secure the products are. In
IDS comparisons, you can find the same bogus "number
of signatures" comparison. Buyers lap that stuff up;
in the absence of deep understanding, they happily
accept shallow data.
With so many mediocre security products on the
market, and the difficulty of coming up with a
strong quality signal, vendors don't have strong
incentives to invest in developing good products.
And the vendors that do tend to die a quiet and
lonely death.
Comment on this article.
- - -
Bruce Schneier is the CTO of BT Counterpane
and the author of
Beyond Fear: Thinking Sensibly About Security in an
Uncertain World.
Mostly plain vanilla advertisement for the product. I am still unconvinced
about value of Squil vs Acid. Acid approach looks more modern to me and the idea
of "real time" alerts processing is pretty much bogus.
The UNIX philosophy is built around the idea of cooperating
tools. As quoted by Eric Raymond, Doug McIlroy makes this
claim: "This is the UNIX philosophy: Write programs that
do one thing and do it well. Write programs to work together.
Write programs to handle text streams, because that is a
universal interface."
[1]
Expanding on the idea of cooperating tools brings us
to Sguil, an open source suite for performing NSM.
Sguil is a cross-platform application designed "by analysts,
for analysts," to integrate alert, session, and full content
data streams in a single graphical interface. Access to
each sort of data is immediate and interconnected, allowing
fast retrieval of pertinent information.
Chapter 9 presented Bro and Prelude as two NIDSs that
generate alert data. Sguil currently uses Snort as its alert
engine. Because Snort is so well covered in other books,
here I concentrate on the mechanics of Sguil. It is important
to realize that Sguil is not another interface for Snort
alerts, like ACID or other products. Sguil brings Snort's
alert data, plus session and full content data, into a single
suite. This chapter shows how Sguil provides analysts with
incident indicators and a large amount of background data.
Sguil relies on alert data from Snort for the initial investigative
tip-off but expands the investigative options by providing
session and full content information.
Why Sguil?
Other projects correlate and integrate data from multiple
sources. The Automated Incident Reporting project (http://aircert.sourceforge.net/)
has ties to the popular Snort interface ACID. The Open Source
Security Information Management project (http://www.ossim.net/)
offers alert correlation, risk assessment, and identification
of anomalous activity. The Crusoe Correlated Intrusion Detection
System (http://crusoecids.dyndns.org/)
collects alerts from honeypots, network IDSs, and firewalls.
The Monitoring, Intrusion Detection, [and] Administration
System (http://midas-nms.sourceforge.net/)
is another option. With so many other tools available, why
implement Sguil?
These are projects worthy of attention, but they all
converge on a common implementation and worldview. NSM
practitioners believe these tools do not present the right
information in the best format. First, let's discuss the
programmatic means by which nearly all present IDS
data. Most modern IDS products display alerts in
Web-based interfaces. These include open source tools like
ACID as well as commercial tools like Cisco Secure IDS
and Sourcefire.
The browser is a powerful interface for many applications,
but it is not the best way to present and manipulate information
needed to perform dynamic security investigations. Web browsers
do not easily display rapidly changing information without
using screen refreshes or Java plug-ins. This limitation
forces Web-based tools to converge on backward-looking information.
[2] Rather than being an investigative tool, the
IDS interface becomes an alert management tool.
Consider ACID, the most mature and popular Web-based
interface for Snort data. It tends to present numeric information,
such as snapshots showing alert counts over the last 24
or 72 hours. Typically the most numerous alerts are given
top billing. The fact that an alert appears high in the
rankings may have no relationship whatsoever to the severity
of the event. An alert that appears a single time but might
be more significant could be buried at the bottom of ACID's
alert pile simply because it occurred only once. This backward-looking,
count-based method of displaying IDS alert data is
partially driven by the programmatic limitations of Web-based
interfaces.
Now that we've discussed some of the problems with using
Web browsers to investigate security events, let's discuss
the sort of information typically offered by those tools.
Upon selecting an alert of interest in ACID, usually only
the payload of the packet that triggered the IDS
rule is available. The unlucky analyst must judge the severity
and impact of the event based solely on the meager evidence
presented by the alert. The analyst may be able to query
for other events involving the source or destination
IP addresses, but she is restricted to alert-based
information. The intruder may have taken dozens or hundreds
of other actions that triggered zero IDS rules. Why
is this so?
Most IDS products and interfaces aim for "the
perfect detection." They put their effort toward collecting
and correlating information in the hopes of presenting their
best guess that an intrusion has occurred. This is a noble
goal, but NSM analysts recognize that perfect
detection can never be achieved. Instead, NSM
analysts look for indications and warnings, which they then
investigate by analyzing alert, full content, session, and
statistical data. The source of the initial tip-off, that
first hint that "something bad has happened," almost does
not matter. Once NSM analysts have that initial clue,
they swing the full weight of their analysis tools to bear.
For NSM, the alert is only the beginning of the quest,
not the end.
NIST IR 7007 "An Overview of Issues in Testing Intrusion Detection Systems",
June 2003
-
pdf file (77.5 KB)
The Open Road: Samhain by Joe "Zonker" Brockmeier a Host-Based Intrusion Detection
System Samhain.
Anyone who has worked with an intrusion detection
system knows that it can produce an enormous amount of data. For many network
security analysts this vast ocean of packets flagged for further inspection
quickly becomes an unruly beast to tame. How then to tame the beast?
The simplest and most efficient way to extract
needed data from the ever-growing database logging these packets is to use a
combination of Berkeley packet filters (bpf) and bitmask filters. Once you're
familiar with their syntax and usage, filtering out specific data is easy. Instead
of manually checking 200MB of packet data one packet at a time, you can tailor
that down to the interesting 500KB. This represents enormous savings in time
and trouble
The creator of Snort, the
open-source network-based Intrusion Detection System (IDS), says the software
is up for an overhaul.
IDS has failed to impress
the market, Martin Roesch told delegates at the AusCERT computer security conference
in Queensland. The inability of many to "tune" an
IDS -- minimising the number of false alarms triggered by the monitoring devices
-- has been a major draw-back for the widespread acceptance of the technology,
he said.
The next generation of Snort
will include "passive discovery" features, Roesch said, which will automatically
tweak the package's settings.
"IDS is not working as well
as had been hoped, or as well as had been hyped," he said. "People have been
saying... IDS can be used to secure your network. But that's not the role of
an IDS."
Now the chief technology officer
of US-based Sourcefire, which sells Snort-based intrusion detection systems,
Roesch says auto-discovery features could be used to apply specific detection
policies to particular devices on a network.
If the new software detects
an Apache server running on Linux, it will only look for attacks relevant to
that configuration, instead of monitoring the device for an attack that would
affect a Cisco router or Windows server.
"If you don't have a technology
that's capable of understanding what's out there on the network... then you
going to have big problems," he said.
Speaking to ZDNet Australia
after his presentation, Roesch said the new features had been discussed within
Sourcefire, but an actual release date to the open-source community is still
unclear. "We haven't really talked about this with the open source community
yet," he said. "Some big changes need to be made to the [Snort] engine to make
this work."
Unlike more passive intrusion
detection set-ups, re-vamped Snort will be able to enforce policies through
its new capabilities. "The idea is to take a policy like 'thou shalt not run
OS X on the network,' and then if someone with a Mac plugs into our network...
it can tell the firewall to [block them]," he said.
This section describes some different
IDSs, including logfile monitors, integrity monitors, signature scanners, and
anomaly detectors.
19.1.1 Host IDSs
Host-based network IDSs may be
loosely categorized into log monitors, integrity checkers, and kernel modules.
The following section will briefly describe each, with examples.
19.1.1.1 Logfile monitors
The simplest of IDSs,
logfile monitors , attempt to detect intrusions
by parsing system event logs. For example, a basic logfile monitor might grep
(search) an Apache access.log file for characteristic
/cgi-bin/ requests. This technology is limited
in that it only detects logged events, which attackers can easily alter. In
addition, such a system misses low-level system events, since event logging
is a relatively high-level operation. For example, such a host IDS will likely
miss an attacker reading a confidential file such as
/etc/passwd. This will happen unless you mark
the file as such and the intrusion detection system has the ability to monitor
read operations.
Logfile monitors are a prime
example of host-based IDSs, since they primarily lend themselves to monitoring
only one machine. However, it is entirely possible to have a host IDS monitor
multiple host logs, aggregated to a logging server. The host-based deployment
offers some advantages over monitoring with built-in system tools, since host
IDSs often have a secure audit transfer channel to a central server, unlike
the regular syslog. Also, they allow aggregation of logs that cannot normally
be combined on a single machine (such as Windows event logs).
In contrast, network-based IDSs
typically scan the network at the packet level, directly off the wire, like
sniffers. Network IDSs can coordinate data across multiple hosts. As we will
see in this chapter, each type is advantageous in different situations.
One well-known logfile monitor
is swatch (http://www.oit.ucsb.edu/~eta/swatch/),
short for "Simple Watcher."
... ... ....
swatch uses regular expressions
to find lines of interest. Once swatch finds a line that matches a pattern,
it takes an action, such as printing it to the screen, emailing an alert, or
taking a user-defined action.
The following is an excerpt from
a sample swatch configuration script.
watchfor /[dD]enied|/DEN.*ED/
echo bold
bell 3
mail
exec "/etc/call_pager 5551234 08"
In this example, swatch looks
for a line that contains the word "denied", "Denied", or anything that starts
with "den" and ends with "ed". When swatch finds a line that contains one of
the these strings, it echoes the line in bold to the terminal and makes a bell
sound (^G) three times. Then, swatch emails the user running swatch (who should
have permission to access the monitored logfiles—this often limits the choice
to root) with the alert and executes the /etc/call_pager
program with the given options.
Logfile monitors can justly
be considered intrusion detection systems, albeit a special kind. Logs
contain a lot of information not directly related to intrusions (just as network
traffic sniffed by the network IDS does). Logs may be considered a vast pool
of information—some normal (authorized user connected, daemon reconfigured,
etc.), some suspicious (connection from remote IP address, strange root access,
etc.), and some malicious (such as the RPC buffer overflow logged by the crashing
rpc.statd). Sifting through all the information is only a little easier than
sniffing traffic looking for web attacks or malformed packets.
If every application had a nice
security log where all "bad" events were recorded and categorized, log analyzers
would not be considered intrusion detection systems. In fact, if an event were
to show up in this magical log, it would be an intrusion. In real life, however,
pattern searches in logs are often just as valuable—if not more so—as looking
for patterns on the wire.
In fact, analyzing system logs
together with network IDS logs is a useful feature in a log analyzer. The log
analyzer sees more than just the wire and creates a meta-IDS functionality.
For example, management solutions such as netForensics enable cross-device log
analysis, normalization and correlation (rule-based log pattern matching), and
statistical (algorithmic) event analysis.
19.1.1.2 Integrity monitors
An
integrity monitor watches key system structures for change. For example,
a basic integrity monitor uses system files or registry keys as "bait" to track
changes by an intruder. Although they are limited, integrity monitors can add
an additional layer of protection to other forms of intrusion detection.
The most popular integrity monitor
is Tripwire (http://www.tripwire.com).
Tripwire is available for Windows and Unix, and it can monitor a number of attributes,
including the following:
-
File additions, deletions,
or modifications
-
File flags (i.e., hidden,
read-only, archive, etc.)
-
Last access time
-
Last write time
-
Change time
-
File size
-
Hash checking
Tripwire's capabilities vary
on Unix and Windows due to differing filesystem attributes. Tripwire can be
customized to your network's individual characteristics, and multiple Tripwire
agents can securely centralize the data. In fact, you can use Tripwire to monitor
any change to your system. Thus, it can be a powerful tool in your IDS arsenal.
Many other tools (most are free and open source) are written to accomplish the
same task. For example, AIDE (http://www.cs.tut.fi/~rammer/aide.html)
is a well-known Tripwire clone.
The key to using integrity checkers
for intrusion detection is recording a "known safe" baseline. Establishing such
a baseline can only be accomplished before the system is connected to the network.
Not having a "known safe" state severely limits the utility of such tools, since
the attacker might have already introduced her changes to the system before
the integrity-checking tool was run the first time.
While most such tools require
a baseline pre-attack state, some use their own knowledge of what constitutes
malicious. An example is the
chkrootkit tool (available at
http://www.chkrootkit.org).
It looks for multiple generic intrusion clues, which are often present on the
compromised system.
Integrity checkers provide maximum
value if some simple guidelines are met. First and foremost, they should be
deployed on a clean system, so they have no chance of recording a broken or
compromised state as normal. For example, Tripwire should be installed on a
system from the original vendor media with all the needed applications deployed,
before it is connected to a production network.
Also, storing "known good" databases
of recorded parameters on read-only media, such as CDROMs, is a very good idea.
Knowing that there is one true copy for comparison helps greatly during incident
resolution. Despite all of these precautions, however, hackers still might be
able to disable such systems.
Moskowit, Ira S., Myong H. Kang, LiWu Chang, & Garth E. Longdon, "Randomly
Roving Agents for Intrusion Detection", Proc. 15th IFIP WG 11.3 Working Conference
on Database and Application Security, Niagra on the Lake, Canada, July 2001,
Kluwer Press.
NRL CHACS Tech. Report 5540-TM/02/003
PostScript,
PDF
Agent based intrusion detection systems (IDS) have advantages such as scalability,
reconfigurability, and survivability. In this paper, we introduce a mobile-agent
based IDS, called ABIDE (Agent Based Intrusion Detection Environment). ABIDE
is comprised of various types of agents, all of which are mobile, lightweight,
and specialized. The most common form of agent is the DMA (Data Mining Agent),
which randomly moves around the network and collects information. The DMA then
relays the information it has gathered to a DFA (Data Fusion Agent) which assesses
the likelihood of intrusion. As we show in this paper, there is a quantifiable
relationship between the number of DMA and the probability of detecting an intrusion.
We study this relationship and its implications.
Meadows, Catherine, "A Cost-Based Framework for Analysis of Denial of Service
in Networks," Journal of Computer Security, to appear.
PostScript,
PDF
Denial of service is becoming a growing concern. As computer systems communicate
more and more with others that they know less and less, they become increasingly
vulnerable to hostile intruders who may take advantage of the very protocols
intended for the establishment and authentication of communication to tie up
resources and disable servers. This paper shows how some principles that have
already been used to make cryptographic protocols more resistant to denial of
service by trading off the cost to defender against the cost to the attacker
can be formalized based on a modification of the Gong-Syverson fail-stop model
of cryptographic protocols, and indicates the ways in which existing cryptographic
protocol analysis tools could be modified to operate within this formal framework.
We also indicate how this framework could be extended to protocols that do not
make use of strong authentication.
EXPERTS: IT MAKES SENSE TO OUTSOURCE IDS | News: SearchSecurity.com
Experts say that intrusion-detection systems (IDS) are candidates for outsourcing.
Most companies don't have the skill sets or experience to sift through the volumes
of logs or decipher inevitable
false-positives. Some companies, however, remain adamant against turning over
their security to an outsider.
GeodSoft
How-To Homegrown Intrusion Detection -- host based
But will he remain profitable? (Score:4,
Interesting)
by jschrod on Monday July 01, @03:18PM (#3802338)
(User
#172610 Info | about:blank)
|
| The point is not if he is profitable, but if he will
remain to be so after venture capital and the associated demands came
into his company. I hope that this guy did a very thorough cost-benefit
analysis before he took the money.
Venture capitalists are not in for the long run, they
want to capitalize their investments in the mid term. Quite some companies
went bankrupt or got in difficulties after external money and the demand
for quick market grab came in and drove solid growth strategy out. Look
at SuSE for an example from the Linux world.
Disclaimer: I'm owner and CEO of a (privately held,
incorporated) company. We still make profits, even in this harsh market,
because we didn't join the hype train, but brought solid add-on value
to our customers.
I wish Marty Roesch luck in choosing his business strategy...
|
Obligatory snide comment (Score:1)
by sparty (sparty_3@yahoo.dontspamme.com)
on Monday July 01, @03:26PM (#3802408)
(User
#63226 Info |
http://upside.net/~sparty/)
|
| This "take in more money than you spend" concept
is a little hard to grasp at first, but the more you think about it,
the more sense it makes, at least in a fuddy-duddy, "old economy" kind
of way.
As much as I sincerely want to believe that this is
attempting to be witty, it's far too close to the *cough*VALinux*cough*
truth *cough*Amazon*cough* coming from an OSDN employee.
|
Step two revealed (Score:5, Insightful)
by gmhowell
(gmhowell@comcast.nCHICAGOet minus city)
on Monday July 01, @03:27PM (#3802428)
(User
#26755 Info |
http://brewnix.sourceforge.net/
| Last Journal:
Sunday
June 30, @04:07PM) |
First go read the newsforge article.... Okay, the
joke is:
Step one: develop open source software
Step two: mumble, mumble
Step three: profit!
Now, it seems that step two is revealed. It's actually a few steps.
Now, for the first time ever:
Step two (a): Come up with (proprietary) tools that make the basic (GPL)
Snort code easy to understand and use for non-technical managers.
Step two (b): Load Snort and the additional tools into a box, and sell
the box as a complete solution, instead of just selling software.
It's been said before that there is no incentive to make OSS easy to
use. Here (and elsewhere) is the proof. Make it hard to use. Release
it. BUT, make the config tools easy to use, IF you pay for them.
I'm not slagging the guy, he's gotta eat. But it is another notch in
the belt for those who are cynical about OSS and business. |
Beyond intrusion detection
Liz Simpson [29-05-2002]
Making sense of security software event logs,
whether it's from your firewall or an expensive intrusion detection system,
can be like trying to drink from a fire hose. Even when you find a real
problem, what do you do?
But intrusion detection is definitely not
a bad idea. No matter how smart you think you are, you've probably overlooked
something in your firewall configuration.
More importantly, your firewall has to let
certain kinds of traffic through, such as web requests or email, and firewalls
are just not designed to pick that traffic apart to tell if it's exploiting
the software on the inside.
Several years ago, Bruce Schneier, a well-known
cryptographer and a long-time advocate of paying attention to the human
factors of security, founded Counterpane Internet Security.
Managed security monitoring
The company provides what it describes as
managed security monitoring which is not that different from hiring a firm
to monitor your home burglar alarm. To this end, the company has two security
operations centres, staffed 24x7 with security analysts.
The two centres vacuum up all the events
generated by their clients' networking and security gear, and feed it to
a proprietary programme called Socrates.
Socrates sifts through the data and flags
the events that merit attention to a live human being. The events are then
investigated, and most are dismissed as harmless without ever needing to
bother the client.
When something serious does happen, however,
Counterpane alerts the client and shows them how to respond to the attack.
While not as sexy as designing new ciphers, it's vastly more marketable.
Just up the road from Counterpane in Mountain
View, California, Taher El-Gamal, another famous cryptographer, has founded
Securify, which has a radically different approach to the same problems.
Securify sells software, not a service. Like
traditional intrusion detection software, the company's SecurVantage vacuums
up packets and classifies them.
Patterns of activity
But rather than scanning for stock intrusion
patterns or signatures, it looks at each packet to determine whether it
fits into a pattern of activity permitted by a flexible policy. This is
a model that specifies the correct behaviour of the entire network from
the transport layer through to the application layer.
This sounds great, until you think about
how awful it could be to specify such a model for your legacy network. This
is where SecurVantage really stands out.
It combines the monitoring function with
the ability to automatically create a sophisticated model of your network,
which you can progressively refine according to reported anomalies.
The product is gaining a following in organisations
where security is such a high priority that outsourcing is not an option,
like the military and banking.
But whether through outsourcing or improved
software, it's clear that companies will need to move beyond traditional
intrusion detection approaches if they really want to get a grip on network
security.
Intrusion Detection
System
Increasing Performance in High Speed NIDS
Intrusion Detection:New
Directions
The Design
and Prototype Implementation of Stateful Network Intrusion Detection System
I 'm graduate student of NEU ( North
East University), doing IDS research now. I have just finished my dissertation
about some optimization algorithm about IDS based on Petri net, it seemed nobody
here has interesting about it, so I hope it can be spreaded so feedbacks are
available.
-
Polymorphic Shellcodes vs. Application IDSs
-
Experiences Benchmarking Inreusion Detection System
- INTRUSION
DETECTION SYSTEMS ANDMULTISENSOR DATA FUSION
- Defending
Yourself: The Role of Intrusion Detection System
-
Intrusion Detection & Vulnerability Assessment Group Test(Edition 1)
- Papers
from RAID2001
- Malicious-
and Accidental-Fault Tolerance for Internet Applications Towards a Taxonomy
of Intrusion Detection Systems and Attackst
- Modelling
Internt Attacks
-
Network Intrusion Detection: Evasion,Traffic Normalization,and End-to-End Protocol
Semantics
-
NEW DIRECTIONS IN Intrusion Detection
-
Why Firewalls are Not Enough
-
Maximizing the value of Network Intrusion Detection
-
NIDS on mass parallel processing architecture
-
To
Catch a Thief
- .Dragon
Claws its Way to the Top
-
Fast Content-Based Packet Handling for Intrusion Detection
-
Towards Faster String Matching for Intrusion Detection or Exceeding the Speed
of Snort
-
Gigabit Ethernet Intrusion Detection Solutions
Top Layer Networks & Internet Security Systems
-
Protocol Analysis and Command Parsing vs.
Pattern Matching in Intrusion Detection Systems
- Open-Source
Security Testing Methodology Manual
-
LAB TESTING SUMMARY REPORT(Intrusion.com
SecureNet Gig)
-
LAB TESTING SUMMARY REPORT(Network ICE
BlackICE Agent, v2.1)
-
LAB TESTING SUMMARY REPORT(Network ICE
BlackICE Sentry, v2.1
ISS RealSecure, v5.0
Axent NetProwler, v3.5)
- Intrusion
Detection Systems Terminology, Part Two:H - Z
- Intrusion
Detection Systems Terminology, Part One: A - H
-
Intrusion Detection &
Vulnerability Assessment Group Test (Edition 1)
-
NIDS placement in the real world
-
Intrusion Detection Product Evaluation Criteria
- An Intelligent
Decision Support System for Intrusion Detection and Response
- Data Mining
Approaches for Intrusion Detection
- Artificial
Neural Network for Misuse Detection
-
MASTER THESIS: Distributed Tracing of Intruders
- On a Difficulty
of Intrusion Detection
- A
Study in Using Neural Networks for Anomaly and Misuse
Detection
- Advanced
Evasion of IDS: buffer overflow detection
-
CLASSIFICATION AND DETECTION OF COMPUTER INTRUSIONS
-
How to Systematically Classify Computer Security Intrusions
-
Foundations of Intrusion Detection
-
Fun with Packets:Designing a Stick
-
Practical
Network Support for IP Traceback
- NIST Special
Publication on Intrusion Detection Systems
- DIDS - Distributed
IDS Systems] Creating the Ultimate Security Tools
- INTRUSION
DETECTION: Shadow Style
-
- 1998
DARPA Intrusion Detection Evaluation Plans: Part 1
- Packet
Capture Driver Performance
- Intrusion
Detection Deploying the Shomiti Century Tap
- How To
Guide - Implementing a Network Based Intrusion Detection System
- Unicode
and IDS evasion
-
Honey Pots and Intrusion Detection
- Rule-Based
Distributed Intrusion Detection
- Intrusion
Detection using Sequences of System Calls
-
Novelty Detection in Time Series Data using Ideas from Immunology
- A Data Mining
Framework for Constructing Features and Models for Intrusion Detection Systems
-
Adaptive Model Generation for Intrusion Detection Systems
- A software
platform for testing IDS
- Benchmarking
network IDS: Jolt2
- A Visual
Mathematical Model for Intrusion Detection
- Snort
Lightweight Intrusion Detection for Networks
- Large-scale
Distributed Intrusion Detection Framework Based on Attack Strategy Analysis
-
A Distributed Approach to Anomaly Detection
- SecureNet
Pro Software’s SNP-L Scripting System
-
Detecting
Intrusions Using System Calls: Alternative Data Models
- Multiple
Levels of De-synchronization and other concerns with testing an IDS system
- Benchmarking
Anomaly-Based Detection Systems
-
The Inevitability of Failure: The Flawed Assumption of Security in Modern Computing
Environments
- Integration
of Host-based Intrusion Detection Systems into the Tivoli Enterprise Console
- INTRUSION
DETECTION SYSTEM (IDS) PRODUCT SURVEY
-
The
Public IDS Zone Theory Diagram
- Writing
anti-IDS shellcode
- Measuring
Intrusion-Detection Systems
- nidsbench
- NFR Performance
Testing
- Intrusion
Detection in the Enterprise Network: Managing Hacking-Related Risk
-
libnids-1.14
-
NetSTAT:
A Network-based Intrusion Detection Approach
- Next Generation
Intrusion Detection in High-Speed Networks
-
Intrusion
Detection and Packet Filtering
- Insertion,
Evasion, and Denial of Service: Eluding Network Intrusion Detection
-
Linux
Kernel Enhancements for Immediate Intrusion Detection
- The Common
Intrusion Detection Framework
-
50 Reasons IDS Systems Work
- State of
the Practice of Intrusion Detection Technologies
-
IDS
Buyer`s Guide Part 1
-
IDS
Buyer`s Guide Part 2
- IDS FAQ
-
An Introduction to Intrusion Detection & ASSESSMENT
-
NFR_IDA_411_Documentation
- Automated
Intrusion Detection Methods Using NFR
- Network
Instrusion Detection
- A system
for distribted instrusion detection
-
The Design of GrIDS:A Graph-Based Intrusion Detection System
-
Network Based Intrusion Detection--A review of technologies
Kurt Seifried - Information security / IDS / Honeypotting with ...
... the host operating system without trace, among
several possible problems. Access
to the host operating system must be strictly controlled and ...
www.seifried.org/security/ids/ 20020107-honeypot-vmware-basics.html
- 15k -
Cached -
Similar pages
Application-Integrated Data Collection for Security Monitoring
File Format: PDF/Adobe Acrobat -
View as HTML
... 1.192 median Impact W/ IDS No IDS Round-trip (s) ...
bin/phf 3. GET / HTTP 1.1 Host: victim
Content-Length: 3 123GET /cgi ... 16 Problems 1) Invasive Because
the module ...
www.raid-symposium.org/Raid2001/slides/ almgren_lindqvist_raid2001.pdf
-
Similar pages
[PDF]
Polymorphic Shellcodes vs. Application IDSs
File Format: PDF/Adobe Acrobat -
View as HTML
... a better approach, but has some problems too: o Since decrypter
engine mutates ... port
scanning, cgi exploitation, etc). * Host IDS : This type of IDS
looks ...
www.ngsec.com/docs/ polymorphic_shellcodes_vs_app_IDSs.PDF
-
Similar pages
Intrusion detection is a technology which
enables network and security administrators to detect patterns of misuse within
the content of their network traffic. There are two ways that intrusion detection
is implemented in the industry today - host-based systems and network-based
systems.
Host-Based Intrusion Detection
Host-based intrusion detection systems use information from the operating system
audit records to watch all operations occurring on the host that the intrusion
detection software has been installed upon. These operations are then compared
with a pre-defined security policy. This analysis of the audit trail imposes
potentially significant overhead requirements on the system because of the increased
amount of processing power which must be utilized by the intrusion detection
system. Depending on the size of the audit trail and the processing ability
of the system, the review of audit data could result in the loss of a real-time
analysis capability.
Network-Based Intrusion Detection
Network-based intrusion detection passively monitors network activity for indications
of attacks. Network monitoring offers several advantages over traditional host-based
intrusion detection systems. Because many intrusions occur over networks at
some point, and because networks are increasingly becoming the targets of attack,
these techniques are an excellent method of detecting many attacks which may
be missed by host-based intrusion detection mechanisms.
Lucidian Technologies,
Inc. was formed in 1997 by a group of engineers that wanted to create a network
intrusion detection system (IDS) that would combine some of the best features
of existing IDS products, and solve the speed and modularity problems endemic
to current Intrusion Detection systems.
The Speed Problem
One of the principle problems
with existing IDS products is their failure to perform at "real" network speeds.
Most ID products work fine at 10 Mbps, but when they are installed at the 100
Mbps backbones and departments of leading IS infrastructures, they cannot handle
the packet load.
Another speed problem is
that existing IDS products will not run all of their attack recognition signatures
at high speeds; these products need to have their active signatures reduced
significantly in order to detect a few common attacks. In fact, some of the
products will not perform any faster by reducing the number of active signatures
used! Both of these shortcomings, the ability to handle fast network loads and
the failure to process signatures at these speeds, make the products less effective
in the real world.
The Modularity Problem
Another problem with existing
network intrusion detection systems is their lack of modularity. Most of these
IDS systems are designed and sold to work with only one type of processor or
management system. They are not adaptable to many of the hardware and software
platforms already in place within current networks.
NetDetect
Lucidian's product, named "NetDetect",
is a software IDS technology that is designed to identify network attacks and
intrusions on 100 Mbps networks. NetDetect combines a real-time attack signature
recognition capability with the modularity to be adapted to any real-time processing
environment. This capability allows it to be configured within a variety of
networked devices including dedicated hosts, switches, routers, firewalls, and
security equipment.
NetDetect is not a commercially
available product, but rather a software technology that can be adapted to a
vendor's set of products. This feature allows NetDetect to act as part of the
network, rather than a separately installed and managed entity.
Imagine network security the way it should be.
You show up for work in the morning and get a report via e-mail from your Intrusion
Detection System (IDS): Everything is OK. You might feel a little dubious about
this, but why should you? After all, isn't the goal of network security to prevent
problems in the first place?
Today's IDSs don't come close to reaching that
goal. Instead, their main allure is reporting what might be wrong in your network,
and most products focus on producing lots of alerts about incidents so that
you don't feel that you wasted your time and money deploying the system. And
while knowing what's happening on your network is a worthwhile goal, it doesn't
in itself do anything to solve the problems manifesting through the medium of
the IDS console.
Perhaps I am being a bit unfair. But if you do
nothing but listen to vendors rave about their products, you are bound to be
misled and disappointed when the reality of what your shiny new IDS can't do
sets in. IDS products are getting better, but they still have a long way to
go.
A Distant Dream?
This article is not about products. Producing
a useful review of IDS products is a very difficult task-one that's illustrated
well by a review by Greg Shipley, director of consulting services with Neohapsis
(see Resources). According to Shipley, the review should be published at roughly
the same time as this issue of Network Magazine.
In this column, I'll focus on the technology
behind IDSs, as well as an idealized view on some features that would dramatically
increase these products' functionality.
First, some terminology. There are at least two
general types of IDS: host-based and network-based. Host-based systems are installed
on the server or desktop they're designed to protect, and generally monitor
logfiles for certain events and key files for changes. Some host-based systems
are hybrids, as they also monitor network traffic sent to the host where they're
installed. Host-based IDSs send alerts to a central console, as do network-based
systems.
Network-based IDSs (NIDSs) sniff network traffic
using a system called a sensor. The sensor collects all packets and evaluates
both the network headers and the data, looking for signs of misuse. Many sensors
focus on attack signatures-that is, a pattern in the header or data that matches
a known attack. Some sensors go beyond mere signature matching, attempting to
match traffic with correct layer-4 and layer-7 protocols.
While researching this column, I spoke with Shipley,
who disclosed some results of the Neohapsis product review. Some of the details
were striking. For example, many NIDS sensors crashed during the testing
under real, not test, network loads. The fastest sensor caught almost
every attack, but it had a user interface that only a Unix sysadmin would adore.
A different product with an even faster sensor had a great user interface, but
only a tiny signature database-so it missed many attacks.
Another issue for existing NIDS is that some
of the best-known vendors are only now catching up to some of the tricks used
to evade IDSs. In early 1998, Thomas Ptacek and Timothy Newsham published a
paper about bypassing NIDSs using fragmentation and out-of-order packets. And
what was true in 1998 remains true to some degree today. While many NIDS do
attempt to defragment packets sniffed off a network, it's just not as simple
as that. (See Network Defense, July 1999, for more information on fragmentation
issues and NIDS.) And while vendors might claim it's not so easy to fragment
attacks, Dug Song, while an employee of IDS vendor Anzen, wrote fragrouter,
a tool that makes fragmenting any network traffic easy.
A related issue has to do with out-of-order packets.
Another way of playing hob with NIDS is sending small packets that contain an
attack split among them, so that the attack signature doesn't appear in any
one of them, and sending the first packet last. The NIDS sensor's task is to
reassemble the data stream, then analyze it for attacks in what IDS vendors
now call ⌠maintaining state.■ But adding this detail to an NIDS sensor already
operating at its performance limits often pushes it right over the edge.
A sensor claiming to monitor 100Mbits/sec can
often only do this part of the time. In another article (see Resources), Shipley
claims that this is due in part to packet size. A 100Mbit/sec Ethernet link
filled with maximum-size packets can carry, at most, 8,120 packets per second.
But send the smallest possible packets (for example, pure TCP ACK packets),
and the packets-per-second rate goes up to 144,880. Now, to make things really
interesting, let's make many of those packet acknowledgments to ongoing TCP
connections that the sensor is supposed to be monitoring in its state table-and
you can really begin to understand why many sensors experience meltdown.
It's one thing to sniff 144,880 packets per second
(no mean feat), and another to check them for known attack signatures. Matching
them to existing data streams before checking them, however, is quite another
matter. An attacker can, through a port scanner, quickly set up thousands of
connections in the state table, leading to memory overload. According to Shipley,
many products he reviewed had memory leaks-places in the code where memory was
used but never freed-that led to crashes over time.
People Power
IDSs' failings may be legion, but I'm not claiming
these products are useless. In fact, a properly working IDS brings up the next
big issue for proper deployment: Who will handle the potential security incident
that the IDS reports?
I recently spoke with an employee of a large
Web hosting and Internet services company about NIDS' practical uses. This employee
uses the free NIDS tool snort to monitor the internal backbone at a large colocation
facility. At this facility, snort collects between five thousand and six thousand
alerts each weekday (fewer over weekends), and this is with a trimmed list of
attack signatures. With so many potential incidents, all they do at this site
is filter through the alert logs on an hourly basis to determine exactly what
is significant and what, if anything, can be done about it.
Most sites won't have to deal with thousands
of alerts each day. But even dealing with several alerts each day is a full-time
job for someone skilled in network and operating system security. The person
monitoring the IDS console must first perform triage-deciding which alert deserves
immediate attention, and which can wait. Then this person must locate the potentially
compromised system, determine if the attack has succeeded, and, if so, decide
the next step. Should the system be further analyzed? Saved for evidence? Or
just reformatted, with a new, patched operating system and applications installed?
And does this attack hint at more undiscovered vulnerabilities on other systems
that should also be patched immediately?
Just installing a single sensor and an NIDS console
can easily consume weeks. Proper installation involves not only the physical
process of installing the sensor and the console software, but also configuring
the NIDS itself. Almost all IDS products support some level of customization.
Sometimes the IDS will do this ⌠automatically■-you launch a tool, and the tool
scans the network, attempts to identify operating systems, then only watches
for attacks specific to those IP addresses and the operating system associated
with a particular address. Of course, you must remember to launch this configuration
process anytime a system is added to your network.
More than likely, you'll need to manually
select sets of attack signatures that you're most interested in. For
example, if your organization has nothing but Microsoft systems, you don't want
the IDS console annoying you with alerts about Unix/Linux exploits directed
at internal systems. You might want the IDS to alert you to attacks against
external Unix systems coming from your own network, though. And as you use a
tool, you'll begin to learn which alerts will most likely be false positives-something
the IDS picks up as an attack, but which actually represent normal network activity
at your site.
The console will also be of critical importance
to users. It must be capable of providing a high-level view but still permit
you to drill down to collect more detailed information about a particular alert.
There must be a mechanism for clearing alerts when you're done with them, or
annotating the alerts, so you can remember later what you've done about a specific
alert.
Hopefully, the console won't just present you
with a terse log-style message, but will provide information about what the
alert means, how serious it might be, how to actually verify if the alert represents
a real event and, finally, how to patch the system involved.
Keeping the Dream Alive?
While some IDSs do hint at what an alert means,
and a few even make suggestions about how to check a system and see if the attack
has been successful, that's far from the ⌠dream■ IDS envisioned earlier in this
column. But let's stay with that dream for a minute and imagine what a Manhattan
Project approach ($2 billion in 1945 dollars) could do to implement the ideal
IDS.
The ideal IDS would be a hybrid, with both
host-based and network-based sensors. The host-based module would also
permit operating system software and upgrading on monitored machines, and the
ability to adjust file permissions/ownerships, registry keys/configuration,
and operating system tuning parameters-all without rebooting. And this host-based
IDS would consume few CPU cycles, so installing it even on heavily loaded servers
wouldn't be a problem.
The NIDS sensors would be installed in switches
(two vendors have already achieved this) so that all traffic could easily be
monitored. The sensors wouldn't just be passive network traffic monitors, but
would keep track of in-use IP addresses and use passive fingerprinting to identify
operating systems, and active fingerprinting if necessary. If a new system appeared,
the sensor would go into active mode and perform a vulnerability scan of the
new system, installing any operating system or application updates that were
previously approved for that platform. The sensor would also inform the central
console of a new system on the network.
The NIDS sensor would keep a history of all network
traffic. If a new service suddenly appeared on a system, this could be an indication
of either a successful attack or the installation of a Trojan. The NIDS would
not only alert the console but also might take countermeasures against the possible
Trojan-especially if the NIDS sensor detected other suspicious activity, such
as a sudden flood or port scan originating from the suspect system.
While this type of system remains a dream, it's
not mine alone. Department of Defense (DoD) research projects such as Emerald
and Sapphire focus on assimilating reports from an array of sensors to provide
the big picture, correlation between reports, and the ability to drill down
to get details from individual sensors or hosts. Someday, the dream may come
true.
Rik Farrow is an independent security consultant.
His Web site, www.spirit.com, contains security links and information about
network and computer security courses. He can be reached at rik@spirit.com.
Resources
Thomas Ptacek and Timothy Newsham's Intrusion
Detection (ID) paper is located at this link.
Greg Shipley's article about Intrusion Detection
Systems (IDSs) from Network Computing is located here.
Greg Shipley and Neohapsis' review of ID products
will appear at Neohapsis sometime in August 2001.
Dug Song wrote fragrouter, a tool for testing
network IDSs, while he worked for Anzen. Go to http://packetstorm.securify.com/UNIX/IDS/fragrouter-1.6.tar.gz
or www.monkey.org to download fragrouter.
The CERIAS page defines IDS terms and provides
IDS references. Go to this link.
A nice summary of different types of IDSs (including
vulnerability scanners) can be found here.
For most of its short history, the network and
information security industry has aimed to create a static defensive perimeter--the
electronic equivalent of a fortified wall. But that wall is far from impenetrable;
the size and complexity of modern networks can make it difficult for an administrator
to even know where the perimeter is, much less secure it. Moreover, most successful
security breaches are perpetrated by the company's own employees, partners,
or clients--attackers who start out inside the defensive perimeter.
The development of intrusion detection systems
(IDSs) in the late 1990's brought real-time detection and response within the
grasp of most mid-to-large sized businesses. Operating on the assumption
that at some level an attack looks different from legitimate activity, IDSs
automatically collect and analyze different types of data from various sources
throughout the network. By monitoring activity as it happens, the IDS
can identify suspicious behavioral patterns and either notify network administrators,
initiate an automated response to the perceived attack, or both. Administrators
can then act to counter a specific attack and/or tailor defenses to defeat similar
attacks in the future.
Network-based IDSs (NIDS)--such as
NFR's NID,
Internet Security System's RealSecure Network Sensor,
Intrusion.com's SecureNet Pro,
and the open-source application
Snort--are
the most commonly deployed type of IDS. These systems examine individual data
packets as they move throughout the network, and compare them against a database
of known attack patterns (or "signatures"), much like anti-viral software. Commercial
NIDS packages usually rely on dedicated hardware sensor appliances installed
on specific network segments to examine traffic as it passes, but most can also
collect traffic data from different firewalls, routers, and hosts.
NIDS are extremely fast, and can automatically
block suspicious traffic or adjust network configuration in response to a perceived
attack in progress. Because they operate in real time, however, NIDS can act
as a traffic bottleneck and adversely affect network performance. The size of
a performance impact--if any--is difficult to predict, and will vary widely
from moment to moment based on available hardware and software, type and amount
of network traffic, and network topology.
Host-based IDSs (HIDS) also look
for attack signatures, but monitor operating system activity on specific machines,
rather than network traffic. Repeated attempts
to guess a log-on password might set off a HIDS alert, for example, as might
attempts to access restricted local files. Some host-based tools can also monitor
specific applications for strange behavior.
eEye's SecureIIS Application Firewall,
for example, monitors
Microsoft's Internet Information Services (IIS)
application. HIDS can operate in real time, use automated responses, and typically
share most of NIDS' strengths and weaknesses, but HIDS are best suited to detecting
different kinds of attacks.
Most commercial vendors bundle NIDS, HIDS, and
other tools such as file integrity checkers and log analyzers into a single
package. "These are complementary rather than competing technologies," says
Marcus Ranum, CTO at NFR Security. "Each is optimized to find different kinds
of problems, and together provide overlapping 'fields of fire.' They can also
share data, letting them catch issues that anyone alone would miss."
IDS downsides
When they were first introduced, IDSs were
heralded as the ultimate weapon against online intruders. Finally, network administrators
would have the ability to see the attackers in action, and would therefore be
able to stop them in their tracks. Years later, however, IDS packages are only
beginning to gain mainstream acceptance, and many view
them as too expensive and resource-intensive for most companies. (Purchase
price is only a part of the equation. Needs assessment, planning, installation,
and configuration will usually add up to far more than list price. Total install
cost is going to depend on the specific arrangements negotiated with the party
doing the install, and will vary widely according to the size of the project
and the relationship between the client and installer.)
Moreover, many specialists have begun to question whether
IDSs represent the best use of limited security resources.
According to Andrew van der Stock, senior architect
at security consultancy e-Secure, "IDS is worse
than useless in most environments--in most cases, it only gives a false sense
of security. IDS is really only suitable once you have a top-notch security
environment and are looking for an additional layer of defense."
Perhaps the most serious difficulty with IDS
is what is commonly known as the "tuning problem." Most successful online attacks
are specifically designed to closely resemble legitimate activity, and a variety
of issues can cause harmless or accidental activity to resemble an attack. Every
network, moreover, has different norms for acceptable activity. As a result,
IDS packages must be carefully "tuned" to minimize the number of false alarms,
while still catching actual attacks. In practice, most IDS packages will produce
a substantial number of "false positives" no matter how well tuned; over time,
overworked administrators tend to tune out or turn off their IDS.
Moreover, the security community has only begun
to develop effective responses to attacks in progress. Though most IDS packages
are capable of automated responses, most experts warn against their use on a
regular basis. Given the frequency of "false positives," automated responses
can easily end up interfering with legitimate activity. For example,
a savvy attacker can intentionally trigger automated responses simply to cause
interference. On the other hand, manual responses tend to be both slow and non-specific.
While administrators can take steps to counter or minimize the damage from a
specific attack, they are often left with the choice of isolating their network
from the Internet (losing much or most of its functionality) or simply allowing
an attack to continue.
Though IDS packages are far from a cure-all,
they can be a valuable addition to the security professional's toolbox.
They are complex and difficult tools to use, however. Perhaps the
most important step is recognizing that an IDS is not a replacement for more
traditional security tools; it should be seen as "icing on the cake."
Well-developed security policies and procedures, solid network architecture,
properly configured firewalls, and strong authentication are all prerequisites
for an effective IDS deployment.
Don't underestimate the amount of time and resources
necessary to properly plan and prepare for initial IDS installation. Properly
placing IDS sensors requires a thorough understanding as to which data and assets
you're trying to defend, as well as the types of threats of primary concern.
Tuning alerts to minimize false positives requires an intricate understanding
of your standard network activity, security policies, and enforcement standards.
Substantial as they are, initial deployment costs
are only a small fraction of the total investment needed to make an IDS effective.
The most common mistake in deploying an IDS is thinking of it as a "set
and forget" tool. Be prepared for an ongoing commitment of staffing, training,
and financial resources. If you can't afford a dedicated security staff,
consider outsourcing your IDS management to a specialist "managed security"
firm such as Counterpane Internet Security, Guardent, or Riptech.
An IDS can be a powerful defensive weapon. If
you're looking to improve your security, take a look. But be aware of what you
may be getting yourself into.
San Francisco-based security consultant and
columnist David Raikow holds a law degree from U.C. Berkeley's Boalt Hall School
of Law. You can reach him at
techupdates@cnet.com.
A recent National Infrastructure Protection Center
(NIPC) Report dated March 15, 2001 and the Internet crime division of the FBI
announced a new attack/tool (called "Stick") that attempts to flood a
network or computer with too many "false positives" for an intrusion detection
software (IDS) to handle, thereby causing it to become inoperative.
If successful, a hacker might try to take advantage of the failed IDS to locate
and exploit an unrelated vulnerability on the victim's system, perhaps to seek
root access. IDS systems play an important role in a layered information security
architecture - by scanning the network against a database of known vulnerabilities,
IDS systems can potentially detect if someone has accessed the system.
Tracking
the physical location of IP addresses can be tricky business, but Clements used
a company named Nami Media Inc. to trace back addresses to originating countries,
and in some cases, cities. In this case, Nami Media acts as a reseller of tracking
information provided by Digital Envoy.
Nami Media’s CEO, Gary Mittman, said technological
advancements and plain old hard work has refined such IP tracking to the point
where it’s reliable.
[DOC]
Evading Intrusion Detection
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... IDS to spend all its time doing useless work. ... Security
Systems, Inc.’s automated
network intrusion detection system. We tested version 1.0.97.224
...
Conferences
New Directions in Network Intrusion Detection
Author: Jeremy Elson
MIT Lincoln Laboratory - DARPA Intrusion Detection Evaluation Publications Listed
are Lincoln Laboratory publications and publications by various members of the Intrusion
Detection research community that relate to the DARPA Intrusion Detection Evaluations.
- Lincoln Laboratory Publications 2001
- Joshua Haines, Lee Rossey, Rich Lippmann and Robert Cunnigham, "Extending
the 1999 Evaluation", In the Proceedings of DISCEX 2001, June 11-12,
Anaheim, CA. [PDF]
- Joshua W. Haines, Richard P. Lippmann, David J. Fried, Eushiuan Tran,
Steve Boswell, Marc A. Zissman, "1999 DARPA Intrusion Detection System Evaluation:
Design and Procedures", MIT Lincoln Laboratory Technical Report,
[PDF]
- Lincoln Laboratory Publications 2000
- Richard Lippmann, Joshua W. Haines, David J. Fried, Jonathan Korba,
Kumar Das "The 1999 DARPA Off-Line Intrusion Detection Evaluation", Draft
of paper submitted to Computer Networks, In Press, 2000. [PDF]
- Jonathan Korba, "Windows NT Attacks for the Evaluation of Intrusion
Detection Systems", S.M. Thesis, Massachusetts Institute of Technology,
June, 2000. [PDF]
- Richard P. Lippmann, David J. Fried, Isaac Graf, Joshua W. Haines,Kristopher
R. Kendall, David McClung, Dan Weber, Seth E. Webster, Dan Wyschogrod, Robert
K. Cunningham, and Marc A. Zissman, "Evaluating Intrusion Detection Systems:
the 1998 DARPA Off-Line Intrusion Detection Evaluation", Proceedings
of the 2000 DARPA Information Survivability Conference and Exposition,
2000, Vol. 2, pp. [PDF]
A Hacker's Approach to ID by Mudge weak
A Glimpse Into the Future of ID by Tim Bass and Dave Gruber
On Reliability by John Sellens
IEEE Software:
Defending
Yourself: The Role of Intrusion Detection Systems
by John McHugh, Alan Christie, and Julia Allen
What is the role of intrusion detection systems in an organization's overall defensive
posture? This article provides guidelines for IDS deployment, operation, and maintenance.
[Jul 27, 2000] Sysadmin, September 2000
Snort - A Look Inside an Intrusion Detection
System by Kristy Westphal. This article will explore setting up Snort, how to
use the various plugins, how to interpret the output of packet captures from
Snort, and how it can complement other IDS's.
Chances are, your company's intrusion detection software stopped suspicious-looking
traffic today. Chances are, it was a false alarm, too.
Network attacks, including distributed denial-of-service and buffer overflow
incursions, have put intrusion detection software on the front line in the battle
against hackers. But the wider the deployment of intrusion detection, the more
administrators are realizing the technology's limits and frustrations.
The reason: Too often, the software puts out false-positive alerts, which
warn administrators about traffic that turns out to be innocuous but still send
IT managers scurrying to plug security holes.
"It got to an absurd point, where every other day we were literally just
blowing away our log file," said Robert Boyle, CEO of Tellurian Networks Inc.,
a managed-service provider in Newton, N.J.
Technically, false-positive intrusions are a
hard problem for software companies to solve. The technology is a slave
to a statistical phenomenon called the base rate fallacy. Attacks are rare relative
to the amount of traffic coming into a network. The rarer the event, the more
accurate the test must be to be useful. Right now, intrusion detection is not
accurate enough and returns more false positives than true positives.
Your network is being scanned for vulnerabilities. This may
happen only once a month or twice a day, regardless, there are people out there
probing your network and systems for weaknesses. I can say this with confidence
because I have yet to work on a network that has not been probed. My personal
network of six systems at home is on a dedicated ISDN line. This network has
no valuable data, nor represents any organization, yet I get probed two to four
times a week. If you have a system or network connected to the Internet, you
become a target. This article will discuss how you can protect yourself by detecting
these intrusion attempts. I will then cover what you can do when you discover
these attempts.
Setting up Intrusion Detection
The methods we will be discussing are simple in use and implementation.
For larger or more security conscientious organizations, you may want to consider
third party Intrusion Detection Systems, such as Network Flight Recorder (http://www.nfr.net/nfr).
These more advanced IDS systems use traffic analysis and advance algorithms
to determine if a probe has been conducted. Our approach will be somewhat simpler.
There are a variety of different probes hackers will attempt.
The first type we will prepare for is one of the most common, port scans. Port
scans are where an inidvidual attempts to connect to a variety of different
ports. The scans can be used on a specific target, or used to scan entire IP
ranges, often chosen at random This is one of the most popular information gathering
methods used by hackers today as it identifies what ports and services are open.
To detect these scans, we will build a system that emails
us alerts whenever someone connects to a predetermined port. First, we identify
three to five of the most commonly scanned ports. Then we select two to three
systems to listen on these ports. When an intruder scans our network, he will
most likely hit our systems listening on these ports. When these ports are scanned,
the systems log the attempt, execute various predetermined actions, then email
an alert to a point of contact.
(Jun 19, 2000, 05:12 UTC) (991 reads) (0 talkbacks) (Posted by
mhall)
"This document takes you through the basics
of intrusion detection, the steps necessary to configure a host to run the snort
network intrusion detection system, testing its operation, and alerting you to possible
intrusion events."
Firewalls FAQ
computer-security/most-common-qs, ( Mar 26 2002)
computer-security/secmaillist (outdated)
Intrusion Detection FAQ
FAQ- Network Intrusion Detection Systems
SANS
Reading Room- Intrusion Detection
Basic Intrusion Detection FAQ [3] - Sniffing FAQ
UNIX Review - Kernel Audit Security Data
Analysis
and Response for Intrusion Detection in Large Networks
COAST Audit Trails Format Group
List of accepted papers
BW: Network ICE Offers First Intrusion Detection System for Linux(May 08, 2000)
LinuxSecurity.com: Build a Secure System with LIDS(Apr 25, 2000)
Lids.org: LIDS Hacking HOWTO(Apr 09, 2000)
Network Computing: Best Practices in Network Security(Mar 18, 2000)
LinuxSecurity.com: Intrusion Detection Primer(Mar 13, 2000)
TechWeb: Linux Suppliers Focus On Improved Security [via Tripwire](Mar 03, 2000)
Security Portal: Some thoughts on (network) intrusion detection systems(Jan
16, 2000)
Security Portal: Network Intrusion Detection Systems and Virus Scanners - are they
the answer?(Jan 09, 2000)
Security Portal: Do you have an Intrusion Detection Response Plan?(Aug 24, 1999)
Security Portal: Detecting Intruders in Linux(Aug 16, 1999)
Slashdot: Intrusion Detection [Book Review](Jan 27, 2000)
Slashdot: Review: Network Intrusion Detection: An Analysis Handbook(Sep 28,
1999)
http://www.anticode.com
- huge selection, nicely layed out, the supermarket of exploit sites
http://www.rootshell.com
- out of date but nicely searchable index
http://www.technotronic.com
- exploit code and other tools such as sniffers and intrusion detection
http://www.nmap.org - Nmap scanner
http://www.nessus.org - Nessus
intrusion scanner
http://www.marko.net/cheops/
- Cheops
http://www.isag.com - Internet
Security Advisors Group (Ira Winkler is President of said company)
http://securityportal.com/research/research.underground.html - Underground Resources
USENIX ;login - intrusion-detection systems
CyberCop, originally produced by Network General, is an IDS
recently released by Network Associates <www.nai.com>,
an organization that is constantly at work acquiring technologies in the field
of security. After their acquisition of Network General's product, Nai made
some changes to CyberCop. (It must be remembered that the auditing/scanning
software now called CyberCop Scanner -- also known as Ballista -- is different
from the totally software-based product we are discussing here.)
Installing CyberCop does not require the network to be reconfigured
or plug-ins to be added. Like other IDSs, CyberCop builds a layer of additional
software which works by monitoring the ports and services enabled by the firewall.
The first version of CyberCop, announced in 1997, consists
of two elements, the management server and the sensors. The latter are positioned
at strategic points on the network and communicate any suspicious events to
the management server. These events are classed according to a set of 170 different
attacks.
If an attempt is made to access the network, the product,
currently called CyberCop Server, informs the security administrator in real
time, providing a detailed report of the event. The designers feel that within
a few minutes CyberCop can give the input the security manager needs to take
the necessary steps to resolve the problem. Management of the configuration
of CyberCop, as well as the receiving and transmitting of the intrusion detection
reports, can take place from a remote location using an encrypted link, which
is activated only after recognition of the parties.
Of course, all the traffic monitored is stored in log files
which can be consulted at any time by the security manager, both in order to
trace the attacks a