Chapter 16
Attack Detection and Prevention
Attack Overview, Taxonomy, and Examples Attack Detection
Principles of Intrusion Detection Systems Distributed attack detection
Introduction
Definition: Intrusion
“An Intrusion is unauthorized access to and/or activity in an information system.”
Definition: Intrusion Detection
“The process of identifying that an intrusion has been attempted, is occurring or has occurred.”
Introduction
Intrusion Detection
Attack- / Invasion detection: Tries to detect unauthorized access by
outsiders
Misuse Detection: Tries to detect misuse by insiders, e.g. users that try to
access services on the internet by bypassing security directives
Anomaly Detection: Tries to detect abnormal states within a network, e.g.
sudden appearance of never used protocols, big amount of unsuccessful login attempts
Intrusion Prevention
An IPS adds further functionality to an IDS. After detecting a possible attack
the IPS tries to prevent the ongoing attack, e.g. by closing network connections or reconfiguring firewalls
Categorizing Attacks
Who / which device is attacking?
Normal user device located outside the infrastructure:
Examples: PC, PDA, mobile phone, ...
Commanded by a normal user not aware of what he is doing, or Hacked and commanded by a malicious attacker
Device located inside the infrastructure:
Examples: router, management workstation, ...
Either deliberately placed by an attacker inside the infrastructure, or Being part of the genuine infrastructure but hacked and commanded
by a malicious attacker
Which layer(s) is the attack aiming at?
Physical, MAC / Data Link, Network, Transport, Application
Which kind of attack is performed?
Availability: The Key Challenge for the Next Years
Security of transmitted information in the sense of confidentiality,
authenticity, etc. is well researched and many network security
protocols have been developed & standardized during the past decade
Examples: PPP/PPTP, L2TP, IPSec, SSL/TLS, SSH, GSM/GPRS/UMTS
security protocols, ....
In “infrastructure networks” (like the Internet), routing threats can be
effectively countered by deploying PKI-based approaches like S-BGP
However,
ensuring
availability
of our IT- and communication
infrastructure requires more than can be realized by standard network
security protocols, and thus
turns out to be the major challenge
for
the next years of security research!
Denial of Service
What is Denial of Service?
Denial of Service (DoS) attacks aim at denying or degrading legitimate
users’ access to a service or network resource, or at bringing down the servers offering such services
Motivations for launching DoS attacks:
Hacking (just for fun, by “script kiddies”, ...)
Gaining information leap (→ 1997 attack on bureau of labor statistics
server; was possibly launched as unemployment information has implications to the stock market)
Discrediting an organization operating a system (i.e. web server) Revenge (personal, against a company, ...)
Political reasons (“information warfare”) ...
Denial of Service Attacking Techniques
Resource destruction
(disabling services):
Hacking into systems
Making use of implementation weaknesses as buffer overrun Deviation from proper protocol execution
Resource depletion
by causing:
Storage of (useless) state information
High traffic load (requires high overall bandwidth from attacker) Expensive computations (“expensive cryptography”!)
Resource reservations that are never used (e.g. bandwidth)
Origin of malicious traffic:
Genuineness of source addresses: either genuine or forged Number of sources:
single source, or
Examples: Resource Destruction
Hacking:
Exploiting weaknesses that are caused by careless operation of a system Examples: default accounts and passwords not disabled, badly chosen
passwords, social engineering (incl. email worms), etc.
Deviation from proper protocol execution:
Example: exploit IP’s fragmentation & reassembly
Send IP fragments to broadcast address 192.168.133.0
Operating systems with origins in BSD often respond to this address
as a broadcast address
In order to respond, the packets have to be reassembled first
If an attacker sends a lot of fragments without ever sending a first /
last fragment, the buffer of the reassembling system gets overloaded
As some routers use BSD-based TCP/IP stacks, even the network
Countering Attacks: Three Principle Classes of Action
Prevention:
All measures taken in order to avert that an attacker succeeds in realizing
a threat
Examples:
Cryptographic measures: encryption, computation of modification
detection codes, running authentication protocols, etc.
Firewall techniques: packet filtering, service proxying, etc.
Preventive measures are by definition taken before an attack takes place
Attention: it is generally impossible to prevent every potential attack!
Detection:
All measures taken to recognize an attack while or after it occurred Examples:
Recording and analysis of audit trails
On-the-fly traffic monitoring and intrusion detection
Reaction:
Attack Strategy
Scan for vulnerabilities
Detection of vulnerable hosts and applications
Compromising hosts
Manual hacking
Viruses, Trojans, Worms
Distributed denial-of-service attack
Bandwidth depletion Resource depletion
Port Scan
Background
Identification of vulnerable systems / applications Automated distribution of worms
Scan types
Vertical scan: sequential or random scan of multiple (5 or more) ports of
a single IP address from the same source during a one hour period
Horizontal scan: scan of several machines (5 or more) in a subnet at the
same target port from the same source during a one hour period
Coordinated scan: scans from multiple sources (5 or more) aimed at a
particular port of destinations in the same /24 subnet within a one hour window; also called distributed scan
Stealth scan: horizontal or vertical scans initiated with a very low
Port Scan (2)
Scan characteristics
Port distribution Source distribution
Scan rates for top 10
destination port categories between May-July, 2002.
Distribution of coordinated, horizontal and vertical
scans for the month of June, 2002
Distributed Denial-of-Service Attacks
Bandwidth depletion
Flood
UDP flood ICMP flood
Amplification (i.e. using a
reflector network)
Smurf (ICMP echo request) Fraggle (UDP echo, e.g.
chargen)
Resource depletion
Protocol exploit
TCP SYN
PUSH+ACK (to unload TCP
buffer + ACK to overflow a receiver)
Malformed packet attacks
Usage of incorrect formatted IP
packets to crash the victim system
Sleep deprivation
Rendering a pervasive
computing device inoperable by draining the battery
TCP-SYN flood
>90% of DDoS attacks use TCP [Moore2001] Several defense mechanisms
SYN cache, SYN cookies, SynDefender, SYN proxying, …
… stateful, have to be installed at victims FW, rely on traceback
Flooding detection system (FDS) [Wang2002] Stateless, low computation overhead Relies on SYN-FIN/RST pairs
Uses CUSUM (cumulative sum) algorithm
Automated model approach [Tupakula2004] Controller-agent model
#SYN - #ACK > limit? Agent sends an alarm to the controller
SYN Flood Protection: TCP SYN cookies
SYN cookies as a reaction to an attack SYN cookies are a particular choice of the
initial seq number.
The server generates the initial sequence
number α such as:
α = h(SSYN, DSYN , K)
SSYN: src addr of the SYN packet DSYN: addr of the server
K: a secret key
h is a cryptographic hash function. At arrival of the ACK message, the server
calculates α again.
Then, it verifies if the ack number is correct. If yes, it assumes that the client has sent a
SYN message recently (considered as normal behavior), and allocates TCB memory.
client server
SYN seq=x
SYN seq= α , ACK x+1
ACK α +1
connection established
Intrusion Detection
Data collection issues
Reliable and complete data
Collection is expensive, collecting the right information is important
Detection techniques
Misuse detection (or signature-based or knowledge-based) Anomaly detection
Response
Counteracting an attack
Evaluation
System effectiveness, performance, network-wide analysis False-positive rate
Classification of Attack Detection
Four dimensions
Host
based
Network
based
Knowledge
based
Anomaly
detection
Classification of Attack Detection (2)
Host Intrusion Detection Systems (HIDS)
Works on information available on a system, e.g. OS-Logs, application-logs,
timestamps
Can easily detect attacks by insiders, as modification of files, illegal access
to files, installation of Trojans or rootkits
Problems: has to be installed on every System, produces lots of information,
often no realtime-analysis but predefined time intervals, hard to manage a huge number of systems
Network Intrusion Detection System (NIDS)
Works on information provided by the network, mainly packets sniffed from
the network layer. Uses signature detection (stateful), protocol decoding, statistical anomaly analysis, heuristical analysis
Detects: DoS with buffer overflow attacks, invalid packets, attacks on
Placement of a Network Intrusion Detection System
Internet
LAN
DMZ
Monitors all incoming traffic •High load
•High rate of false alarms
Monitors all traffic to and from systems in the DMZ •Reduced amount of Data •Can only detect Intrusions on these Computers
Monitors all traffic within the corporate LAN
•Possible detection of misuse by insiders •Possible detection of intrusion via mobile machines (notebooks...)
Knowledge-based Detection
Based on signatures or patterns of well-known attacks Working principles
Scan for attacks using well known vulnerabilities, e.g. patterns to attack IIS web
server or MSSQL databases
Scan for pre-defined numbers of ICMP, TCP SYN, etc. packets Patterns can be specified at each protocol level
Network protocol (e.g. IP, ICMP) Transport protocol (e.g. TCP, UDP) Application protocol (e.g. HTTP, SMTP)
Pros
Fast, requires few state information, low false-positive rate
Cons
Recognizes only known attacks
Examples
Snort
OpenSource
Support for Windows, UNIX, Linux,...
Rule Based Intrusion Detection
Ruleset can be edited individually
Huge number of predefined rules
Daily community rules update
Reporting into: Logfiles, LogServer, Database
Different formats for captured data supported: libpcap, ...
Supports packet de-fragmentation, protocol decoding, state inspection
Possible reactions: TCP reset, ICMP unreachable, configuration of
firewalls, alerting via email, pager, SMS (plugins)
Snort (2)
Mainly signature based, each intrusion needs a predefined rule
alert tcp $HOME_NET any -> any 9996 \
(msg:"Sasser ftp script to transfer up.exe"; \
content:"|5F75702E657865|"; depth:250; flags:A+; classtype: misc-activity; \ sid:1000000; rev:3)
Three step processing of captured information (capturing is done by
libpcap):
Preprocessing (normalized and reassembled packets)
Detection Engine works on the data and decides what action should be
taken
Action is taken (log, alert, pass)
Anomaly Detection
Based on the analysis of long-term and short-term traffic behavior
Working principles
Scan for anomalies in
Traffic behavior Protocol behavior Application behavior
Pros
Recognizes unknown attacks as well
Cons
False-positive rate might be high
Examples
Anomaly Detection (2)
Generic anomaly detection system
Anomaly Detection (3)
Anomaly Detection (4)
Classification criteria
ALAD
Application Layer Anomaly Detection (ALAD) [Mahoney2002]
Extension to PHAD
Five models:
1. P(src IP | dest IP)
Learns normal set of clients for each host, i.e. the set of clients allowed on a restricted service
2. P(src IP | dest IP, dest port)
Like (1), but one model for each server on each host
3. P(dest IP, dest port)
Learns the set of local servers which normally receive requests
4. P(TCP flags | dest port)
Learns the set of TCP flags for all packets of a particular connection
5. P(keyword | dest port)
Defense Challenges
Need for a distributed response at many points on the Internet
Coordinated response is necessary for successful countermeasures
Economic and social factors
Deployment of response systems at parties that do not suffer direct damage from the DDoS attack
Lack of detailed information
Thorough understanding of attacks is required
Lack of defense system benchmarks
Difficulty of large-scale testing
Attack Prevention / Counteracting
Anti-Spoof Mechanisms
Filtering of forged packets Cryptographic authentication Traceback
Counteracting DDoS attacks
Counteracting TCP SYN flood Distributed Firewalling
Address Spoofing
The Spoofing Problem:
Packet routing in IP networks is based on destination address information
only, correctness of source address is not verified
Most (D)DoS attacks consist of packets with spoofed or faked source
addresses in order to disguise the identity of the attacking systems
Identification of the attacking systems is needed for installing efficient
defense mechanisms
Some detection mechanisms also require valid information about the
attack sources
Further issues: legal prosecution of attackers and prevention of new
Anti-Spoof Mechanisms
Filtering of forged packets
Ingress filtering: implementation of “anti-spoof” ACLs based on
(static/dynamic) knowledge about “own” IP address range
RPF: reverse path forwarding, known from multicast routing, fails for
dynamic load-balancing
SAVE: source address validity enforcement protocol [Li2002]
Associates interfaces with valid source address ranges Also useful for RPF check, e.g. for multicast routing
Cryptographic authentication
IPSec authentication, problem: key management
Traceback
Real-time / Forensic methods Most promising solution!
Traceback (1)
Goal:
Identify the source address (or at least the ingress point) and the attack
path of a packet without relying on the source address information
Challenges:
Short path reconstruction time
Processing and storage requirements Scalability
Traceback (2)
Taxonomy of traceback mechanisms
active passive
Traceback
packet
insertion markingpacket reconfig.network loggingpacket loggingflow
link
Packet Insertion
ICMP traceback (ITrace) [Bellovin2000]:
For 1 out of 20.000 packets, routers send an ITrace message with router ID and
information about original packet to the same destination
If a flow contains enough packets, the destination is likely to receive ITrace
messages from every router on the path.
Limitations:
Router infrastructure has to be modified
Requires large number of packets/flow Î long t.b. time for distributed low-rate
attacks
Destination has to store original packets for later comparison with ITrace message ITrace messages need to be authenticated, e.g. using PKI
packet P
ITrace(R1, P)
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