15-August-2000 AT&T

Network Securityand

Intrusion Detection

Survey of the Art and Practice

Dr. Michah Lerner

AT&T Labs15-August-2000

15-August-2000 AT&T

Outline

Model Principles Assumptions Methods Products

No silver bullets

Published sources only

Note: this talk describes some attack models.

If you’d like “try them out”, don’t!

15-August-2000 AT&T

Intrusion Detection Systems, IDS Identified by Dorothy Denning in 1987 IEEE Software

Engineering• Protect systems and networks from threats, vulnerabilities, and

intrusions Art includes:

• “Bro: A System for Detecting Network Intruders in Real Time” (Vern Paxon)

• JiNao – Protect link state routing – Felix Wu Rule-based expert system, statistical analysis, protocol analysis, OSPF

MIB, distributed programming interface (DPI)

Vendors include: • Amazon.com lists 171 security products• Axent (NetProwler, and Tivoli modules), ISS, Network

Associates, Cisco

15-August-2000 AT&T

A Story … Jane the Dandelion wine merchant

• Running SSL to protect her eCommerce site

Coalition against Dandelion Wine• Quietly launches a chosen ciphertext attack

against her SSL server (Daniel Bleichenbacher, LNCS 1462, 1998)

• Exploit weakness in SSL V.3.0 Generate many authentication requests SSL reports which ones were incorrectly formatted The Coalition obtained her master secret!

• They tested about one million chosen ciphertexts – on her server!• She just thought that SSL was slow!• IDS would have found incomplete SSL handshakes, and probably foiled the intruder

15-August-2000 AT&T

Assumptions Assumptions …

• RFC 1636 – encryption essential to security Open networks violate this assumption Encryption should protect control information, as well as

contents See section 7.3 of the RFC

• In attack from Vi net Vj assume only one of Vi, Vj is the attacker

DDOS violates this assumption

Assumptions are “sometimes” wrong• Replay attack can masquerade with encrypted data• Distributed attacks can leverage multiple attackers• Encryption can be broken

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Not much used for first break-in discovery, but invaluable for security incident analysis and follow-up: it answers typical questions like: When did the first break-in happen? Which other systems may have been attacked? Which other services on the attacked system may have been compromised?

Concept – Collection & AnalysisCERNCERN European Laboratory for Particle Physics European Laboratory for Particle Physics

Birth Place of “The Web Browser” – http://www.cern.ch

Network

Filter

Analyzer

Suspicious behavior

Database

Reports

Security officer

Every time something suspicious is detected, the session’s security weight is increased When the security weight gets higher than a given threshold, detailed monitoring starts Encryption was, until recently, not allowed by the French law

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Intrusion – Examples

Denial of Service Hijacking of session or router Theft

• Resources – bandwidth theft or blockage

• Identity

• Information

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Intrusion at any layer or sliceDifficult and Complex Problem

RTP

MediaMPEG etc.

Content

IPv4, IPv6

Ap

plic

atio

nT

ran

spo

rtN

etw

ork

SIP RTSP RSVP RTCPHTTP H.323

TCP UDP

PPP PPPAAL3/4 AAL5

Static &dynamic page

Quality ofService

MediaTransport

Lin

kP

hys

ical

SONET ATM Ethernet V.34

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Resources• Exhaust, overload or consume

Control Functions• Undermine direct control protocols

Assert authentication or authorization contrary to policy

Block authentication or authorization • Undermine indirect control

Subvert timing or other policing methods Transport Functions

Transmit forged content Modify, Read or Block content

“Many attackers use tools like COPS or SATAN, which automate the process of checking for known bugs in remote network systems. These freely available tools, as well as commercial tools such as ISS’s Internet Scanner, are designed to help systems administrators audit their own networks, but are equally useful to an attacker.” [Wallach99]

See http://www.cert.org/advisories

Mobsters101 – How to Intrude1

1For discussion purposes only

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Intrusion – Definition Intrusion

• Violation of the network policy, even where the policy is not completely stated

Policy • Allocation, usage and return of resources

Possibly multiple policies active on a network Varied requirements of business, administration or trust

Resources• Finite• Independent• Layered• Protocol-driven

Protocols• Efficient, not perfect

• IP spoofing – packets are not uniquely att-ributable to the origin

• Costly to stop

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Prevention – Policies & Assurances Violations of policy may define intrusion Except:

• Seldom have such a precise policy in IP• The policy could be buggy• New applications could violate the policy• Cost is prohibitive for many applications• Can plug anything into the Internet – not just “safe”

applications. IEEE 802.3 (Ethernet) is ubiquitous An alternative to formal policy is assurances

• General policy, but less rigorous Availability – connections, bandwidth, low delay Integrity – privacy, reliability, and low error-rate

15-August-2000 AT&T

Detection Assurances are threatened by:

• Misuse – specific attack behavior Based on expert knowledge of patterns associated with attack Patterns of misuse defined by experts, or by machine learning –

should not occur Examples:

– Mismatched SYN/ACK– Same authenticated user from multiple locations?– Multiple failed authentications? From different address??

Problem: only recognizes anticipated threats (but can combine several threats that might otherwise be missed)

• Anomalous use – possible attack Recognize increased risk to network Compare actual with expected behavior Load rising atypically?

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How to Protect the Assurances? Redundancy

• Makes it harder to corrupt• Make it easier to identify corruption• May make it easier to locate the corruption

Explicit redundancy: add to network or data• Tags and attributes• Input/output validation

Implicit redundancy: already in the network• Anonymous – timing• Private – network attributes• Content – privacy and easily evaded• Per-protocol or general properties

State-machine compliance? Frame-format?

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Two Keys to ProtectionPrevention

Define multiple layers• Define behavior of each

layer, including resources• Enforce each behavior• Prohibit actions that may

compromise the behavior Examples

• IP DDOS does not affect ATM integrity

• Replay of short-lifetime HTTP cookies is traceable

• Link-layer marking • Ingress/egress filtering• End-to-end coordination

Detection Identify correct behavior Reinforce or augment

• Redundancy Format (protocol) Augmentation (tags) Validations

Characterize activities Recognize anomalies

• Unusual transit duration, route, or augmentation

• Item – invalid packet header• Aggregate – bad path or

invalid protocol sequence• Honeypot traces

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Explicit Redundancy – Protection Content transformation

• SSL• Cookies

Protocol hardening against adversarial “errors”• IPSec• Invalid session properties (i.e. stale keys, invalid

context or content) may indicate attack Packet augmentation

• Security labels• Properties inherited from ingress• Requirements incumbent upon egress• Min/max trust and validation of information flow1

Management at Ingress/Egress• Interaction with authentication and multiple domains

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Implicit Redundancy – Detection Packet

• Well-formed packets (protocol-compliant)• Well-defined packets (service behavior)• Source, destination, format

May validate endpoints and actions

Traffic profile• Acquire by observation of usage

Statistical model – “distinctive characteristics (packet size, timing) … not on connection contents”

Resists encryption, and preserves privacy Database of representative samples

Does the traffic profile fit the source/destination profiles?

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General Technique Collect traffic and audit information

• Protocol analysis• Various sensors

Content-independent sensors may work even on encrypted data

State-based sensors evaluate the trustworthiness of connection path

State-free sensors operate without change to firewall or network-element

Compute patterns of misuse or abuse Recognize patterns of a possible attack

Previously observed or predicted attack patterns Uncharacteristic changes in predicted performance

15-August-2000 AT&T

Information to Collect Audit information

• Management information bases (MIBS) and logs• After-the-fact analysis of traffic artifacts

Historical information• Recognition of previously used contents, such as serial

numbers, someone else’s password, etc.• Strength of evidence follows the strength of the content

source Distributed

• Exchange data on suspected intrusions (IETF IDWG) • Information from IP authentication systems

AT&T15-August-2000

Information to Compute Attack signatures

• Hard problem – needs attack models to organize data• Attacks are often distributed – requires coordination• ISS publishes about 350 Real Secure Signatures at

http://www.iss.net Backdoors Denial of Service Distributed Denial of Service OS Sensor Suspicious Activity Unauthorized Access Attempts

• Only three detect RIP attacks on routing • None of the published signatures mention streaming,

VoIP, MPEG, Quality of Service, or attacks on OSPF

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Detailed Taxonomy

Source:IBM RZ 3176 (# 93222) 10/25/99 Computer Science/Mathematics (23 pages). A ReviseTaxonomy for Intrusion-Detection Systems by Hervé Debar, Marc Dacier, Andreas Wespi

Knowledge-based• Expert systems; Signature analysis• Petri nets; State-transition analysisBehavior-based• Statistics; Expert systems• Neural networks; “User Intention” model

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Information Collection Tools

Tcpdump Bro NetMon Snort All can

use rules

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Protocol Monitoring Validate Appropriate Traffic Flows:

• Multiple granularities of description• Recognize change from the behavior

Activation/deactivation of connections Correlation/evaluation of connection attributes

How• Protocol scrubbing [InfoComm 2000]

State machines for correct protocol flow Error states for erroneous traffic

• Pattern recognition• Simulation/validation of expected behaviors

Does the expected response follow, or something else?

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ASAX and Russel

State full event detection Correlation of events across multiple hosts

• consolidate intrusion evidence from several scattered sources and correlate them intelligently at a central location.

Declarative Language

Russel Rules

automata

Internet FUNDPUniv.

FW-1

ISP

Router

Sniffer

ASAX

• SYN-Flood• IP spoof• Port Scan• Host Scan• etc.

Source: Aziz MounjiAbdelaziz.Mounji@swift.com

(RUle-baSed Sequence Evaluation Language)

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Russell -- ASX

Rule1(uid)

Rulek(x,y)

Rule1(uid)

Rulek(uid)

Rule1(uid)

Rulek(uid)

time

Evt1 Evt2Evtn

State full Detection

Event Stream

Automatic Actions

• Disable account• Log to file • SNMP traps• Email Sec-Ad• Exec any command• Send event to manager

Interface with C

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What if Alert?

Block offending traffic sources Terminate suspicious processes Coordinate with multiple domains

• Intruder Detection and Isolation Protocol (IDIP)

TraceReportDirective (discovery coordinator)

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Products(Names changing all the time)

Boundary controllers• NAI Gauntlet, ARGuE, MPOG, etc.• Secure Computing Sidewinder

Detectors• Axent, Cisco• SRI Emerald expert-system• NAI CyberCop• ISS RealSecure• NFR www.nfr.net• Event-based traffic analysis, pattern matching,

aggregation and adaptation SUNY, BRO, CIDF, IDIAN, DPF packet filter compiler …

15-August-2000 AT&T

Source: RZ 3253 (# 93299) 06/26/00; Computer Science 45 pages Integration of Host-based Intrusion Detection Systems into the Tivoli Enterprise Console, Christian Gigandet (IBM Research; Zurich Research Laboratory)

Vendors and Products – Tivoli Compatibility

15-August-2000 AT&T

Cisco Intrusion Detection System• NetSonar (Scanner)• NetRanger (Monitor)

The Cisco Secure IDS includes two components: Sensor (renamed NetSonar) and Director (renamed NetRanger).

Cisco Secure IDS Sensors, which are high-speed network "appliances," analyze the content and context of individual packets to determine if traffic is authorized.

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ISS RealSecure

• Network engine resides on PC, monitors network transmissions for “signs of abuse and attack”

• About 350 attack signatures currently published

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ID module embedded in router/switch/firewall:• Evaluates all incoming and outgoing traffic for intrusions across all ports

• Switching. Monitors heavily routed or switched networks at the most heavily-trafficked network junctions.

• Speed. May also address speed issues by embedding ID in higher-performance hardware.

• ID module running on adapter card:– Processor provides most of the analysis.– Speed. Hardware assist with packet classification provides wire-speed intrusion detection.– Security is painful. Shrink-wrap ID engine -- easy to install, easy to manage with relatively low cost.

• ID module as an ASIC:– ID as a true design component. Installed on networking backplane, e.g. multi-gigabit switch, Probably only

way to handle– Switching. Embedded in high-performance network device allows access to all packets at single location.– Speed. Wire-speed intrusion detection.

• ID module embedded in host protocol stack:– Attached to protocol stack above encryption layer.– Encryption. Allows intrusion detection to exist in the presence of encrypted traffic while still providing

adequate value.

APIs solve top 4 problems

Pla

tform

Sup

port

Act

ive

Res

pons

e

Management Programming

Data Acquisition

Sig

natu

re D

efin

ition

Attack Recognition

Response

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CyberSafe Centrax

15-August-2000 AT&T

Summary Maintain integrity:

• Per layer • Per slice (protocol)

Validate packets• Ingress/egress counters

Squelch attack sources that do not comply with reasonable usage• Test carefully to ensure not a new application• Streaming media is not a UDP attack!

Measure and understand “flow” properties• Recognize statistically significant variation from these

path properties

15-August-2000 AT&T

Backup Slides

A bit more formalityA glimpse at some academic research

15-August-2000 AT&T

Assumptions Assumptions

• RFC 1636 – encryption essential to security Open networks violate this assumption Encryption should protect control information, as well as

contents

• In attack from Vi net Vj assume only one of Vi, Vj is the attacker

DDOS violates this assumption

Assumptions are sometimes wrong• Replay attack can masquerade with encrypted data• Distributed attacks can leverage multiple attackers• Encryption can be broken

15-August-2000 AT&T

General Network Model(circumscribes problem domain)

G = (V, E) Path = {Vin, {Ej}, {Vj}, … {Ek}, {Vk}, {El}, {Vout}} Path consists of vertices and edges Edges E:

• Propagate signal

Vertices V:• Receive signal

• Compute output

• Emit signal

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Network Model Edges (links)

• Signal propagation• Impairments due to random noise

Redundancy manages noise, fade or analog error Detect and correct by protocols through algebraic redundancy

Vertices (routers/switches)• Aggregate bits into packet• Classify and enqueue packet

Packet-type and priority (UDP? TCP? ICMP? RSVP?) Loss due to load variation and queue size Detect and correct by redundant payload or retransmission

• Dequeue packet Data packet: compute output as f(packet, control) Control packet: modify control as f(packet, control)

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Vertex Control function f(packet,control)

Data packet:• Pure IP: f(packet, control) is nearly the identity

function modify TTL, next-hop, etc

• Proxy or active protocol: f(packet, control) not identity Augment packets in more complex “custom” ways

Control packets:• Routing: static or dynamic

• Resource: modify resources, i.e. queues, priorities

• Behavior: modify function, i.e. classifier, marking, etc.

15-August-2000 AT&T

Monitoring Entity Signatures Entity output descriptions

• Compute usage signatures (local and complete) Entity to neighbors Entity to endpoints

Entity input descriptions:• Receivers compute signature of received data

Comparisons• Entities exchange signatures (or log centrally)

Anomaly detected from signature mismatches

15-August-2000 AT&T

JiNao – Protect Link-State Routing

Router/OS Kernel

FIB Where shouldI forward this packet?

Routing ProtocolEIGRP

RIB

Routing ProtocolBGP

RIB

Routing ProtocolOSPF

RIB

Originator

JiNao

Prevention Module

Interception Module Network

Protocol Engine

Statistical Analysis

ProtocolAnalysis

Detection Module

Decision Module

Info. Abst. Module

IDS MIB

SNMPv3 Eng.

Sec

urit

y O

ffic

er

Finite state machine withtiming analysis, verifiesValidity of OSPF actions,and guards against anyintrusion – even one with“valid” security credentials