Taxonomies of Attacks and Vulnerabilities in Computer Systems

Taxonomies of Attacks and Vulnerabilities in Computer Systems
Igure, V.M.; Williams, R.D. IEEE Communications Surveys & Tutorials, Volume: 10 Issue: 1 (2008) R 林昕彥 R 陳政彥

Why do we need taxonomy? Their main goal was to organize information about known vulnerabilities or attacks, so that designers could use that information to build more secure systems or defense systems If the classification is based on the actual vulnerability exploited by the attack, the dimension of classification can be considered as the cause of flaw The taxonomy provides useful information to find unknown vulnerabilities as well as to avoid introducing similar vulnerabilities in future designs. They provide a classification of testing techniques based on the vulnerability the test is meant to discover. Each test class discovers all the vulnerabilities that have similar characteristics

Attack sophistication vs. intruder technical knowledge

INTRODUCTION

Introduction Security assessment of a system is the process of determining the system’s capability to resist attacks This process typically involves probing the system to detect the presence of known vulnerabilities most attacks typically exploit known vulnerabilities This process is limited because it only searches for known vulnerabilities Security assessment is an objective process only as long as it is limited to searching for known weaknesses Probing a system to detect previously unidentified flaws is still a very subjective process

Introduction Prior work has attempted to gain an understanding of the characteristics and nature of known vulnerabilities to support the prediction of vulnerabilities in new systems The first step in understanding vulnerabilities is to classify them into a taxonomy based on their characteristics A taxonomy classifies the large number of vulnerabilities into a few well defined and easily understood categories Such classification can serve as a guiding framework for performing a systematic security assessment of a system This article provides a state-of-the-art survey of existing security related taxonomies The survey covers papers published between 1974 and 2006

TAXONOMIES AND SECURITY ASSESSMENT

Taxonomies and Security Assessment
A taxonomy is formally defined as “the study of the general principles of scientific classification” This classification is done according to the relationships between the characteristics of the objects A good taxonomy also provides a common language for the study of the field

Taxonomies and Security Assessment
taxonomies of vulnerabilities and attacks might be useful in the security assessment process can also be useful for system designers can also provide a way to explore unknown attacks Many taxonomies of attacks and vulnerabilities have been published over the years, but there is still no standard or universally accepted taxonomy Our primary interest is in the development and use of attack and vulnerability taxonomies in the security assessment process

ATTACK TAXONOMIES

Attacks Goals Dimension of taxonomy Comments
Types of Computer Crimes (Perry & Wallich 1984) Listing main types of crimes Two-dimensional matrix: crime vs. users committing the crime Common characteristics: source of attack Replay Attacks in Crypto-Protocols (Syverson 1994) “consider which detection, representation, or prevention mechanisms are appropriate for a replay attack” Source of attack is the primary dimension of classification Common characteristic: source of attack Types of Misuse (Brinkley & Schell 1995) Listing of types of misuse; Not intended to be a taxonomy Two-level hierarchy; classes are not properly defined Provides overview of types of misuse IDS Attack Signatures (Kumar 1995) Classified attack signatures to develop comprehensive database for an IDS Based on manifestation of attacks in network traffic and logs Applied in IDS development Types of Misuse (Attacks) (Lindquist & Jonsson 1997) “Makes systematic study possible” “useful for reporting incidents to response teams” “included a grading of the severity” Extended Neumann and Parker’s taxonomy Discuss usefulness of selecting a good dimension of classification

Attacks Goals Dimension of taxonomy Comments Attacks Against
Information Systems (Cohen 1997) “Putting all of the methods of attack into a classification scheme and co-locating them with each other so that knowledgeable experts can … consider… possible attacks” No classification, just a long list of known attacks An exhaustive list of attacks is static and needs to be constantly updated to keep it relevant Attacks (Lough 2001) Develop a taxonomy of attacks in wireless networks Distilled the classes discussed in prior work on taxonomies into four common categories The categories are similar to the basic security properties Attacks against Mobile Agents (Man, Wei 2001) “Used in the analysis of existing protection schemes … useful for research developments” Hierarchical taxonomy: 1. Intention 2. Number of attackers 3. Read vs. non-read Classification is not based on characteristics of attack DoS Attacks in WSNs (Wood, Stankovic 2002) Highlight the various threats faced by WSNs Attacks classified under the various network layers of the communication protocol Dimension is similar to location of flaws Sybil Attacks in WSNs (Newsome et al. 2004) “To better understand the implications of the Sybil attack and how to defend against it” Multidimensional: 1. Mode of communication 2. Type of identity 3. Simultaneity Underscores the need for a taxonomy to study a new field

Attacks Goals Dimension of taxonomy Comments DoS Attacks (Hussain et
“Provide the classification component of a realtime attack analysis to aid network administrators” Source of attack: single source vs. multiple sources Taxonomy can be used to develop tools for real-time defense Web Attacks (Alvarez, Petrovic 2003) “Help designers … build more secure application … a useful reference framework for security application” Multidimensional taxonomy based on a “Web attack life cycle” Common classification types: vulnerability; service; target Attacks: Defense centric (Killourhy et al. 2004) “Organizes attacks by virtue of the way they manifest as anomalies in sensor data” Anomaly seen in sensor data; four categories Mostly relevant only in IDS; lowlevel categories DDoS Attack and Defense Mechanisms (Mirkovic, Reiher 2004) “Structure the DDoS field and facilitate a global view of the problem and solution space” Eight characteristics of an attack; three characteristics of defenses Common characteristic: exploited weakness; impact on victim; type of victim Internet Attacks (Mostow, Bott 2000); (Delooze — 2004) Build an attack simulator; Taxonomy was used in the simulator model Effects of the attack Common characteristic: DoS, Deception, Reconnaissance, Unauthorized access

Attacks Goals Dimension of taxonomy Comments Attacks in VANETS (Golle
et al. — 2004) Taxonomy was not the main aim 1. Nature 2. Target 3. Scope 4. Impact Common characteristic nature of attack; impact on victim; scope; target; Shellcode Attacks (Arce 2004) “Understanding these programs’ technical capabilities and their connection to those who develop and use them” Functional perspective: 1. Attack vector 2. Exploitation technique 3. Payload Multiple ways to trigger a vulnerability Attacks (Hansman, Hunt — 2005) Develop a “pragmatic taxonomy that is useful to those dealing with attacks on a regular basis.” Four taxonomies based on: 2. Attack target 3. Vulnerability 4. Payload For application-specific taxonomies, it might be possible to combine all these into one taxonomy

Types of Computer Crimes [17]
The six classes of users are not distinct Two-dimensional matrix of computer attacks First dimension: Users Operators, programmers, data entry, internal users, outside users, and intruders Second dimension: Computer crimes Physical destruction, information destruction, data diddling, theft of services, browsing, and theft of information

Types of Computer Misuse [18]
Level One: Theft of computer resources Disruption of computer resources Unauthorized disclosure of information Unauthorized modification of information Level Two: Human error User abuse of authority Direct probing Probing with malicious software Direct penetration Subversion of security mechanism

Information System Attacks [19]
First attempts at developing a taxonomy to help the security assessment process put all possible attacks under a single taxonomy could be used to predict future attacks in existing systems The biggest drawback of [19] is that it is not a classification It is merely a long list of all known attacks The article lists 94 different attacks on information systems

Computer Attack [24] In [24] Neumann identified 26 different kinds of computer attacks and classified them into nine categories: External Hardware misuse Masquerading Pest programs Bypasses Active misuse Passive misuse Inactive misuse Indirect misuse This can be considered a hierarchical taxonomy because it has two levels of classification

Classify Computer Security Intrusions [7]
Lindquist and Jonsson’s taxonomy [7, 26] is a very good example of one that is suitable for a security assessment process the first to introduce the notion of dimension of classification they extended three of Neumann and Parker’s categories into multiple subdivisions: Bypass of intended controls Active misuse of resources Passive misuse of resources

IDS Related Taxonomies
Two main types of IDSs: Signature-based system Anomaly-based system The primary motivation for this classification was to provide a defense-centric taxonomy to help network defenders

Signature-based system
Every attack manifests itself as some kind of event or sequence of events in a network These unique events are called the signatures of the attack Every known attack is given a signature based on its characteristics Attack taxonomy can ensure that all known attacks are represented in the database

Signature-based system
In [27] Kumar presents a taxonomy signatures to help build an effective IDS Attack signatures are classified into five categories: Existence Sequence Partial order Duration Interval

Anomaly-based system Looking for any network activity that deviates from the norm Killourhy et al. [28] developed a taxonomy of attacks based on their manifestation as anomalies in IDS sensor data Every attack manifests itself either as a: Foreign symbol Minimal foreign sequence Dormant sequence Non-anomalous sequence

DoS Attack Related Taxonomies
Attacker can carry out a successful attack without penetrating the target network In [29] Neumann lists three types of DoS attacks based on the source of the attack no network penetration and can be carried out remotely over the Internet attacker exploits some known vulnerability to penetrate the network and then carries out resource exhaustion attacks distributed DoS (DDoS) attacks, attackers penetrate or compromise many third party computers and use them to launch a DoS attack against the target network

Mirkovic and Reiher [8] intended to build a taxonomy that would provide a complete overview of the field of DDoS attacks and defenses Each attack has multiple characteristics, and Mirkovic and Reiher classify attacks along multiple dimensions This classification is not mutually exclusive Eight dimensions: Degree of automation Exploited weakness Source address validity Attack rate dynamics Possibility of characterization (based on packet content) Persistence of agent set Victim type Impact on the victim

In [35] Campbell uses a novel dance metaphor to characterize DoS attacks He characterizes a DoS attacker as a third person interrupting two dancing partners He groups all DoS attacks under four classes that represent the attacker’s strategy for success: Partner -> spoofing Flood -> flooding Trip -> shutting down Intervene -> interception

Web Attack Taxonomies Alvarez and Petrovic [34] analyzed and classified Web attacks, their goal was to extract useful information for application developers to build more secure systems

Specialized Attack Taxonomies
There are many attack taxonomies that cover only certain specific applications Man and Wei [42] developed a taxonomy of attacks against mobile agents The goal of the work was to understand all possible attacks against mobile agents and then use this understanding to develop appropriate protection mechanisms The first level of classification in [42] divides attacks into two categories based on the intentions of the attack hierarchical, and this characteristic is useful for security assessment

Taxonomies for Security Assessment
Lough presents an exhaustive survey of computer attack and vulnerability taxonomies in [15] Classifies all attacks under four categories: Incorrect validation Incorrect exposure Incorrect randomness Incorrect deallocation This classification is made on the cause of attack dimension Lough’s taxonomy is not application-specific

Taxonomies for Security Assessment
In [25] Hansman and Hunt aim to develop a “pragmatic taxonomy that is useful to those dealing with attacks on a regular basis.” They conclude that it is difficult to develop an effective tree-structure taxonomy of attacks Four dimension: Attack vector Attack target Vulnerabilities and exploits Attacks with payloads If the taxonomy were application-specific instead of trying to incorporate all possible kinds of attacks, it might not be very difficult to develop a single tree-structure taxonomy of attacks

VULNERABILITY TAXONOMIES

Vulnerability Taxonomy
One of the earliest works on this topic was done by McPhee. McPhee’s paper was published in 1974, and since then there has been much research done on computer security. McPhee lists seven class of integrity flaws in operating systems: System data in user area Non-unique identification of system resource System violation of storage protection User data passed as system data User-supplied address of protected control blocks Concurrent use of serial resources Uncontrolled sensitive system resource

Attanasio described the methodology and results of penetration testing experiments. The penetration analysts had three goals: The paper does not provide a taxonomy, as that was not their goal, but it makes the important contribution of listing operations system characteristics that are likely to have flaws. To obtain information to which they were not entitled To launch a DoS attack by exhausting resources To obtain resources bypassing the accountability mechanisms

After the penetration testing experiment, Attanasio et al. Listed 16 OS features that are likely to have flaws: Implicit or explicit resource sharing mechanisms Man-machine interfaces administered by the OS Configuration management problem Add-on features Design modifications and design extensions Parameter checking Control of security descriptors

Error handling Side effects Parallelism Access to microprogramming Complex interfaces Duplication of function Limits and prohibitions Access to residual information Violation of design principles

TAXONOMY OF SOFTWARE PROGRAM FLAWS

Taxonomy of Software Program Flaws
The Research in Secured Operating Systems (RISOS) project and the Protection Analysis (PA) project were two of the earliest efforts at producing taxonomies of vulnerabilities in computer software. Both of the projects examined the vulnerabilities in different operating systems.

The seven classes of vulnerabilities in the RISOS project were: Incomplete parameter validation Inconsistent parameter validation Implicit sharing of privileged/confidential data Inadequate identification Authentication or authorization Asynchronous validation or inadequate serialization Violable prohibition or limiting and exploitable logic error

The ten classes from the PA project were: Consistency of data over time Validation of operands Validation of residuals Validation of naming Validation of domain Serialization Interrupted atomic operations Exposed misrepresentations Queue management dependencies Critical operator selection error

The categories of both the RISOS and PA classifications indicate that the dimension of classification was by operations. This means that the categories represent operations of the OS which can be misused to cause attacks. The RISOS and PA categories would be greatly beneficial in a larger taxonomy.

Bishop analyzed the RISOS and PA taxonomies, and showed that these classes could be mapped onto each other. Bishop classified each vulnerability along six axes: Nature of the flaw Time of introduction Exploitation domain of the vulnerability The effect domain The minimum number of components needed to exploit the vulnerability The source of the identification of the vulnerability

After the PA project, the most influential work on taxonomies of flaws was done by Landwehr et al. They did not limit their taxonomy to operating systems but provided a more general taxonomy of flaws in computer programs. They classified their flaws in three different dimensions: Genesis Time of introduction location

Jiwnani et al. used Landwehr’s taxonomy to aid security testing. They adapted Landwehr’s three dimensions to build a matrix that related the cause of the vulnerability. To be effective, the taxonomy must be used in conjunction with all the dimensions of the classification. The assessment process can be more systematic if these dimensions are arranged hierarchically.

All the work we have seen so far classified attacks or vulnerabilities based on some inherent characteristic of the attack or vulnerability itself. Krsul departed from this norm. He developed a taxonomy based on the observation that most of the vulnerabilities were introduced into programs because of mistaken assumptions by the programmer. He classified flaws according to the assumption that led to their introduction into the software.

Aslam focused only on the UNIX operating system. Aslam’s taxonomy is hierarchical, and the first level had three main categories: Configuration flaws Environment flaws Coding flaws The dimension of classification for these three classes is the cause of the flaw.

Du and Mathur described each flaw with multiple attributes. They classify flaws along three axes: Cause Impact Fix Landwehr’s original genesis class had two main subclasses: intentional and inadvertent flaws. Du and Mathur ignore the intentional flaws. Instead, they focused on the inadvertent flaws in the software. Since the taxonomy provides details about the flaws, it could be effective in a security assessment process.

Kamara et al. successfully use Du and Mathur’s taxonomy for analyzing vulnerabilities in Internet firewalls. They break down a firewall into its constituent components, and its operations and data flow. They analyze some of the well-known firewall vulnerabilities, and map them to both Du and Mathur’s taxonomy and the specific operations and parts of the firewalls. The result is a matrix that identifies which operations and parts of a firewall are likely to produce flaws. This is very useful in future security assessments of other firewalls as well as in preventing the same kinds of flaws in new products.

Gray’s aim was to develop a taxonomy of vulnerabilities that would be useful to people in various positions in a software development organization. Gray combined the work of Landwehr, Bishop, and Wang into an extended and multi-perspective taxonomy.

The taxonomy had ten classes of program flaws: Genesis Time of introduction Location Execution environment Quality impact Method of discovery Thread and exploitation scenarios Monitoring and exploitation scenarios Limitation and remediation scenarios Elimination methods

Gray’s approach of combining all the perspectives within one taxonomy is not very efficient. Gray does not offer any subclasses for any of these classes. Such a single-level taxonomy does not provide adequate information about the flaws. This ineffectiveness shows that taxonomies are most useful when they are developed for a particular application from a specific perspective.

Tsipenyuk et al. seek to simplify the existing software vulnerabilities taxonomies. They claim that most of the existing taxonomies are too complex.

In order to help software developers and security practitioners, they group all software security flaws under eight classes: Input validation and representation API abuse security features time and state Errors Code quality Encapsulation Environment

Yu et al. provide a framework for analyzing the security of Web software service. The unique contribution is that they relate all the attacks with the software vulnerabilities each attack exploits.

Yongzheng and Xiochen develop a taxonomy of vulnerabilities to aid the security risk assessment process. They base on the concept of “privilege sets” and “privilege escalation.” A vulnerability can be viewed as a feature that gives additional privileges to the attacker. The paper ranks the privilege sets of nine user classes, ranging from common user to root. The paper provides a ranking of the impacts of each privilege level, with the root level causing the greatest damage and the user level causing the least.

Wang’s work also explored the link between a flaw and the risk posed by that flaw. A flaw that could be exploited in multiple ways can be considered more risky. Than one that can be exploited only in one way.

Alhazmi et al. test the efficacy of vulnerability discovery models to predict the number of vulnerabilities in a software product. Having a target number of vulnerabilities could help the security analyst, but traditional taxonomy–based classifications would have to be used to find the actual vulnerabilities.

Network Vulnerability Taxonomies

Ristenbatt describes a methodology name Network Communications Vulnerability Assessment (NCVA) which was developed to perform network vulnerability assessment. The first taxonomy classified the various types of networks according to their design.

The objective of this taxonomy was to provide the analyst with a high-level overview of the network. The top-level categories were: The transfer strategy The network transfer control method The transfer link structure Link access method or protocol System topology architecture

The second taxonomy outlined the typical network susceptibilities. He defines susceptibilities as system features that might be targeted by attackers. Susceptibilities are potential vulnerabilities. The network susceptibilities taxonomy has five classes: Topology Physical layer Data link layer Network layer Management and control

Jayaram and Morse provide a taxonomy of security threats to networks. Their taxonomy has five categories: Physical threats System weak spots Malign problems Access rights Communication-based threats

A more elaborate taxonomy of threats to networks is provided by Welch and Lathrop. The taxonomy was developed to build a security architecture for a wireless network. The taxonomy is hierarchical and provides a systematic approach for analyzing al the security threats faced by a network. They begin by considering threats to each of the basic security properties: confidentiality and integrity.

The taxonomy lists seven attacks that pose a threat to security properties: Traffic analysis Passive eavesdropping Active eavesdropping Unauthorized access Man-in-the-middle Session highjacking Replay attacks

Pothamsetty and Akyol made an effort at producing a taxonomy of network protocol vulnerabilities. Their main goal was to organize information about known vulnerabilities. They classify the vulnerabilities into seven categories: Clear text communication Non-robust protocol message parsing Insecure protocol state handling Inability to handle abnormal packet rates Replay and reuse Protocol field authentication Entropy problems

Properties of a Taxonomy for Security Assessment

The goal is to identify a set of characteristics for a very specific taxonomy: one that can be used effectively in a security assessment process. The taxonomy must be tailored to the viewpoint of an assessment professional. It should also help make the process as objective as possible. The basic properties of such a taxonomy would be: Application- or system-specific taxonomy Taxonomy must be layered or hierarchical First level of classification – attack impact Second level of classification – system-specific attack types Third level of classification – system components (attack targets) Fourth level of classification – system features (source of vulnerability) Classes need not be mutually exclusive

The efficacy of a security assessment process should be measured by its objectivity and vulnerability coverage. A process with good vulnerability coverage explores all relevant system features that are likely to have vulnerabilities. Although there are no metrics for measuring objectivity and vulnerability coverage, we believe that a taxonomy with the above properties greatly aids a security assessment process.

Conclusion This article presents a survey of all taxonomies related to computer and network security. The survey analyzes existing work on security taxonomies and assess their usefulness in terms of security assessment. The analysis helps identify specific properties of taxonomies that aid security assessment.

Taxonomies of Attacks and Vulnerabilities in Computer Systems

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