Intrusion Detection Systems (IDS)
• What is an IDS?
– Definition
– Characteristics
– Examples of existing IDS
What is an IDS?
• Definition:
– A piece of software
– Monitors a computer system to detect:
• Intrusion: unauthorized attempts to use the system
• Misuse: abuse of existing privileges
– Responds:
• Log activity
• Notify a designated authority
• Take appropriate countermeasures
Why Use an IDS?
• Security is often expensive/cumbersome:
– Cost
– Restrictions on users/functionality
• Designers try to offer users “reasonable” levels of security
• Security breaches will still occur
• Detection allows:
– Finding and fixing the most serious security holes
– Perhaps holding intruders responsible for their actions
– Limiting the amount of damage an attacker can do
Goals of an IDS
•
•
•
•
•
•
•
Run continually
Be fault tolerant
Resist subversion
Minimize overhead
Be easily configurable
Cope with changing system behavior
Be difficult to fool
– Minimize false positives and false negatives
Intrusion Detection Systems
• Three main components of an IDS:
– Information source – provides a stream of event
records
– Analysis engine – finds signs of intrusions
– Response component – generates reactions
• What is the best information source for
intrusion detection?
Information Sources
• Host-based
– Operating System audit trails/system logs
– Application information
• Examples: database audit records, web server logs
• Network-based
– Network packets
– Network devices
• Security appliances
– Firewall
– Access control system
IDS Characteristics
• Detection Model
– Misuse detection vs. anomaly detection
• Scope
– Host based, multihost based, network based
• Operation
– Off-line vs. real-time
• Architecture
– Centralized vs. distributed
IDS Detection Model
• Misuse detection - recognize known attacks
– Define a set of attack signatures
– Detect actions that match a signature
– Add new signatures often
• Anomaly detection - recognize atypical behavior
– Define a set of metrics for the system
– Build a statistical model for those metrics during “normal”
operation
– Detect when metrics differ significantly from normal
• Hybrid
IDS Scope
• Host based
– Scrutinize data from a single host
• Multihost based
– Analyze data from multiple hosts
• Network based
– Examine network traffic (and possibly data from the
connected hosts)
Case Study: Tripwire
• A file integrity-checking tool
– Developed at Purdue university (released in 1993)
– Off-line, centralized, host-based, misuse detection
– Utilizes digital signatures to check for added, deleted,
modified files
– Popular
•
•
•
•
•
•
Portable
Configurable
Scalable
Manageable
Automated
Secure
Background – File Systems
• Provide long-term storage for:
– User data and programs
– System programs and databases
• A popular target for attackers:
– Unauthorized access to user or system files to uncover private
information
– Modify system databases to allow future entry (e.g. SAM
database)
– Modify system programs to allow future entry (e.g. back doors)
– Cleansing of system logs to thwart detection
Tripwire - Overview
• A checklist is created which contains one entry for each
file being monitored
• Checklist should:
– Be secure against unauthorized modifications
• Each entry in the checklist is a fingerprint for the
corresponding file
• Fingerprints should:
–
–
–
–
–
Be efficient to compute
Be hard to invert
Depend on the entire contents of the file
Be very likely to change if the file changes
Be very unlikely to match fingerprints from other files
Tripwire – Overview (cont)
generate
New
database
compare
Config file
Old
database
Files residing on file system
Apply
masks
Report
Tripwire Database
• Unencrypted and world-readable
• To prevent the database from being tampered with,
it is recommended it be:
– Installed and updated in a secure manner (e.g. singleuser mode)
– Stored either:
• On a read-only media
• On a write-protected disk
• On a “secure server” (e.g. read-only NFS)
Tripwire Configuration Files
• Contains:
– A list of directories (or files) to be monitored
– A mask for each that describes which attributes can change without being reported
• Mask bits (all fields stored in a file’s inode):
–
–
–
–
–
–
–
–
–
p: permissions
i: inode number
n: number of links
u: user id
g: group id
s: size of file
m: modification timestamp
a: access timestamp
[1-10]: signature #1, signature #2, etc.
• Signature algorithms supported (MD5, MD4, MD2, Snefru, SHA, CRC-32, CRC-16)
Tripwire Configuration Files
(cont)
• Using masks:
– Fields can be added (“+”) or subtracted (“-”) from the set of items
to be examined for a file
– Example: +pinugsm12-a = report changes to all fields except
access timestamp
• Mask templates:
– R = +pinugsm12-a = read-only files; only access timestamp is
ignored
– L = +pinug-sma12 = log files; changes to file size, access time,
modification time, and signatures are ignored
– N = +pinugsma12 = ignore nothing
– E = -pinugsma12 = ignore everything
Tripwire Configuration File Example
# file/dir
mask
/etc
all files under /etc are read-only
/etc/passwd
N
R
# ignore nothing
#
Tripwire - Overview
generate
New
database
compare
Config file
Old
database
Files residing on file system
Apply
masks
Report
Tripwire Reports
• New database is computed and compared with the old one
• Any differences are passed through the masks in the
configuration file
• If not masked out differences are written to a report:
Changed: -rw-r—r– root 20 Sep 17 13:46:43 2012 /.rhosts
### Attr
Observed
Expected
### ===
=======
=======
m
Fri Sep 17 13:46:43 2012 Tue Sep 13 20:05:10 2012
a
Fri Sep 17 13:46:43 2012 Tue Sep 13 20:05:10 2012
Limitations of Host Based
Intrusion Detection
• No global knowledge or context
information
• Must run IDS on host being monitored
– Does no scale
– Overhead
– Host compromise = IDS compromise
• Recovery options are limited
Snort
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
An open source, network-based IDS and IPS
Detection:
 Signature based
 Protocol based
 Anomaly based

Widely deployed “de facto” industry standard

URL: www.snort.org
Snort - Overview
Goals are performance, simplicity, and flexibility
Performance depends on:
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Number of rules (detection signatures)
Performance of the machine on which Snort is running
Load on the network
Use libpcap promiscuous packet sniffing library
for:
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Packet capture
Filtering
Snort Components
Packet Decoder
Takes packets from different types of network interfaces
(e.g. Ethernet, SLIP, PPP)
Has subroutines that correspond to various network
layers/protocols:
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Data link layer
Network layer (IP)
Transport layer (TCP, UDP, etc)
Application layer (HTTP, FTP, DNS, SMTP, etc.)
Annotates raw packet data by overlaying data structures

Pointers into the packet data for later analysis by the detection
engine
Preprocessors
Arrange or modify data packets prior to processing by the
detection engine
Example, detection engine contains a rule to flag the string
“scripts/iisadmin” in HTTP packets
Attackers try to evade IDS by disguising malicious strings using:
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“scripts/./iisadmin”
“scripts/examples/../iisadmin”
“scripts\iisadmin”
“scripts/.\iisadmin”
Uniform Resource Identifier (URI) hexadecimal characters or Unicode
characters
A Snort preprocessor module converts all these representations
into a canonical form

Preprocessor Modules (cont)
Attackers try to evade IDS by fragmenting packets
Example:


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
Packet 1: “scrip
Packet 2: ts/ii
Packet 3: sadmin”
No signatures match because half the payload is in
one packet while half is in a subsequent one
A Snort preprocessor module is responsible for
defragmenting packets

Preprocessor Modules (cont)
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Attackers try to evade IDS by manipulating the TCP data stream

Example:

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“scdef<bs><bs><bs>ripts/ijk<bs><bs>isade<bs>min
”
No signatures match if the TCP stream isn’t reassembled
A Snort preprocessor module is responsible for TCP stream
reassembly

Preprocessor Modules (cont)
Attackers try to evade IDS by showing the IDS different data
than what is seen by the end host


Example:
 Packet 1 (TTL set to reach end host): “scrip
 Packet 2 (TTL set to be dropped one hop beyond the IDS):
ABCDEFGHIJKLMNOP
 Packet 3 (TTL set to reach end host): ts/iisadmin”
Detection Engine
Detection is guided by a set of rules
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Standard rule database available from Snort
Can add custom rules
Rules can apply to:
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IP header fields
TCP, UDP, ICMP header fields
Application header fields
Data
Rules are stored in a (chained) data structure to
optimize matching
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Two dimensional linked list
Rule Chain Structure
Chain Header
Chain Header
Dest IP = 192.168.78.100
Dest Port = 80
Dest IP = 192.168.78.101
Dest Port = 25
Chain Option
Chain Option
Content = “scripts/iisadmin”
Chain Option
TCP Flags = URG
Chain Header
Logging and Alerting

Logging options
 Store packets flagged by the detection engine in decoded,
human readable format to an IP-based directory structure
(slow)
 Store packets in tcpdump binary format to a single log file
(faster)
 Do not store packets (fastest)
Logging and Alerting (cont)

Alerting options
 Send to syslog
 Send to an alert text file (different formats)
 Send as WinPopup messages using Samba
 Discarded (during security testing)
Output Modules
Process log entries and alerts
Generate final output:
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Logging to a database
Generating eXtensible Markup Language (XML) output
Etc.
Execute response actions:
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Modifying configuration on routers and firewalls
Sending Server Message Block (SMB) messages to
Microsoft Windows-based machines
Snort Rules
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Rules tell the detection engine:
 What patterns to match
 What to do with packets that match a given rule
Three basic directives:
 Pass – silently drop the packet
 Log – write the packet to the logging routine
 Alert – log the packet and generate an event notification
Snort Rules - Examples
• Record all traffic inbound for port 79 going to the 10.1.1.0
subnet:
– log tcp any any -> 10.1.1.0/24 79
Detect attempts to access the PHF service on any of
subnet 10.1.1.0’s web servers
Generate an event notification alert
Log the packet

– alert tcp any any -> 10.1.1.0/24 80 (content: "/cgi-bin/phf";
msg: "PHF probe!";)
Snort Rules - Structure

Every Snort rule has two parts:
Rule Header Rule Options
Rule header (required)
 What action a rule takes
 Some matching criteria
• Rule options (optional) - Enclosed in parentheses
 Additional actions and matching criteria
Rule Header
Seven fields:

Action (e.g. pass, log, alert, etc.)
Protocol (e.g. IP, ICMP, UDP, TCP, etc.)
Address – IP address specifying a single host,
multiple hosts, or network address
Port – UDP/TCP source and destination ports
Direction – specifies which address and port
number is the source and which is the destination
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Rule Header – Action Field
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Basics – pass, log, alert
Advanced:
 Activate
 Create an alert
 Activate another rule for checking more conditions
 Dynamic
 Invoked by other rules using the “activate” action
 User defined actions
Rule Header – Direction Field
A -> symbol shows that address and port numbers on the left
hand side of the direction field are the source

A <- symbol shows that address and port numbers on the right
hand side of the direction field are the source

A <> symbol means that the rule will be applied to packets
traveling in either direction

Intrusion Detection Systems (IDS)
• An Intrusion Detection System (IDS) is a piece of software that
monitors a computer system to detect:
– Intrusion (unauthorized attempts to use the system) and Misuse (abuse of
existing privileges)
• And responds by:
– Logging activity, notifying a designated authority, or taking appropriate
countermeasures
• Many different IDSs are available and they can be categorized
according to their:
– Detection model (misuse detection, anomaly detection, hybrid)
– Scope (host based, multihost based, network based)
• Tripwire (file integrity checking IDS)
• Snort (network-based IDS)