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658 lines
29 KiB
Text
-------[ Phrack Magazine --- Vol. 9 | Issue 55 --- 09.09.99 --- 16 of 19 ]
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-------------------------[ Distributed Metastasis:
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A Computer Network Penetration Methodology
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-------[ Andrew J. Stewart <ajs@tentacle.org.uk>
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"You may advance and be absolutely irresistible, if you make for the enemy's
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weak points; you may retire and be safe from pursuit if your movements are more
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rapid than those of the enemy."
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- Sun Tzu, Art of War
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----[ (struct phrack *)ptr;
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You can find the original instance of this article in both Adobe .pdf and
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Microsoft Word 97 format at http://www.packetfactory.net.
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----[ Abstract
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Metastasis refers to the process by which an attacker propagates a computer
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penetration throughout a computer network. The traditional methodology for
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Internet computer penetration is sufficiently well understood to define
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behavior which may be indicative of an attack, e.g. for use within an Intrusion
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Detection System. A new model of computer penetration: distributed metastasis,
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increases the possible depth of penetration for an attacker, while minimizing
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the possibility of detection. Distributed Metastasis is a non-trivial
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methodology for computer penetration, based on an agent based approach, which
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points to a requirement for more sophisticated attack detection methods and
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software to detect highly skilled attackers.
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----[ Introduction
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In the study of medicine, the term "metastasis" refers to the spread of cancer
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from its original site to other areas in the body. Metastasis is the principal
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cause of death in cancer patients. Cancer cells have the ability to enter the
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vascular system and travel to virtually any part of the body where they detach
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and burrow into a target organ. Each cancer has an individualized way of
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spreading.
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The use of the term metastasis was first suggested in the context of computer
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security by William Cheswick and Steven Bellovin [1] and refers to the process
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by which an attacker, after compromising a computer host, attacks logically
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associated hosts by utilizing properties and resources of the compromised host:
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"Once an account is secured on a machine, the hacker has several hacking goals
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... [to] open new security holes or backdoors in the invaded machine ... [and
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to] find other hosts that trust the invaded host."
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Before the techniques and advantages of distributed metastasis can be
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explained,the traditional attack paradigm must be understood. Note that a
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verbose description of the traditional attack paradigm is outside the scope of
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this document; [2] describes that subject in detail.
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----[ Traditional Attack Paradigm
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The framework of processes and order of execution by which an attacker attempts
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to penetrate a remote computer network is sufficiently well understood to
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enable the creation of toolkits to attempt to exploit a weakness and/or to
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attempt to audit a system for potential weaknesses.
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The tasks an attacker performs to conventionally execute an attack can be
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categorized as 'information gathering', 'exploitation', and 'metastasis', and
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are described below.
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----[ Information Gathering
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The first phase of an attack, the information gathering phase, comprises the
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determination of the characteristics of the target network such as network
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topology, host OS type (within this paper the term 'host' will refer to a
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generic network entity such as a workstation, server, router, etc.), and
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"listening" applications e.g. WWW servers, FTP services, etc. This is
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ordinarily achieved by applying the following techniques:
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I. Host Detection
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Detection of the availability of a host. The traditional method is to elicit
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an ICMP ECHO_REPLY in response to an ICMP ECHO_REQUEST using the 'ping'
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program. Programs designed to perform host detection in parallel such as fping
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[3] enable large expanses of IP address space to be mapped quickly.
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II. Service Detection
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a.k.a. "port scanning". Detection of the availability of a TCP, UDP, or RPC
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service, e.g. HTTP, DNS, NIS, etc. Listening ports often imply associated
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services, e.g. a listening port 80/tcp often implies an active web server.
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III. Network Topology Detection
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Topology in this context relates to the relationship between hosts in terms of
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'hop count' ("distance" between hosts at the Internet/IP layer).
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Only two methods of network topology detection are known to the author: 'TTL
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modulation' and 'record route'. The UNIX 'traceroute' program performs network
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topology detection by modulating the TTL (time to live) field within IP
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packets; in the windows NT environment, tracert.exe provides broadly
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equivalent functionality. 'ping' can be used to "record [the] route" of ICMP
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packets, albeit to a finite depth. Both these techniques require a target host
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to act as the final destination of the probe.
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Firewalk [4] is a technique used to perform both network topology detection and
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service detection for hosts "protected" behind certain vulnerable
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configurations of gateway access control lists, e.g. as implemented in a
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firewall or screening router.
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Classical promiscuous-mode "network sniffing" is another, albeit non-invasive,
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method of network topology detection [5], but may not be applicable in
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those scenarios where traffic from the target network is not visible to an
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attacker at their initial network location.
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IV. OS Detection
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A common OS detection technique is "IP stack fingerprinting" - the
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determination of remote OS type by comparison of variations in OS IP stack
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implementation behavior. Ambiguities in the RFC definitions of core internet
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protocols coupled with the complexity involved in implementing a functional IP
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stack enable multiple OS types (and often revisions between OS releases) to be
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identified remotely by generating specifically constructed packets that will
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invoke differentiable but repeatable behavior between OS types, e.g. to
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distinguish between Sun Solaris and Microsoft Windows NT.
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The pattern of listening ports discovered using service detection techniques
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may also indicate a specific OS type; this method is particularly applicable
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to "out of the box" OS installations.
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V. Application-Layer Information Gathering
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Applications running on target hosts can often be manipulated to perform
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information gathering. SNMP (Simple Network Management Protocol) enabled
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devices are often not configured with security in mind, and can consequently be
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queried for network availability, usage, and topology data. Similarly, DNS
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servers can be queried to build lists of registered (and consequently likely
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active) hosts.
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Routers on (or logically associated with) the target network can often be
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queried via the RIP protocol for known routes [6]. This information can be used
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to further aid construction of a conceptual model of the topology of the target
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network.
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Many of these techniques are utilized by modern network management software to
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"map" a network.
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In summary, the information gathering phase of an attack comprises the
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determination of host availability: "what hosts are 'alive'?", service
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availability: "what network enabled programs run on those hosts?", network
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topology: "how are hosts organized?", and roles: "what 'jobs' do each host
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perform?".
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----[ Exploitation
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The exploitation phase of an attack is the initial chronological point at
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which an attacker commits to attempting to penetrate an individual host.
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The data generated in the information gathering phase of the attack is used to
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determine if any hosts on the target network are running a network service
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which has a known vulnerable condition that might be remotely exploitable.
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Services may either be intrinsically insecure "out of the box" or may become
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insecure through misconfiguration.
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The methods by which a service can be exploited vary widely, but the end-result
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often manifests as either the execution of a process in a privileged context
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e.g. opening a privileged command line, adding an account with no password,
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etc., or through the disclosure of security-critical information, e.g. a list
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of encrypted passwords which can (possibly) subsequently be "cracked". The
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observed proportion of weak passwords within a password file [7] imply that a
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password cracking attack is likely to be successful.
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To summarize, the exploitation phase of an attack involves the compromise of a
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vulnerable host on (or logically associated with) the target network.
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----[ Metastasis
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The metastasis phase of the attack, as defined by Cheswick and Bellovin, can
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be logically separated into two key components: 'consolidation', and
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'continuation', described here:
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I. Consolidation Component
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Once access has been gained to an individual host, the attack proceeds with the
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consolidation component of metastasis.
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It is imperative to the attacker that the exploitation phase not be detected.
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The attacker must remove evidence of the entry onto the host by removing
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relevant entries from OS and security application log files. If the
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opportunity exists, the attacker will remove any trace generated by the earlier
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information gathering phase also.
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Depending on the exploit employed, the exploitation phase may not have granted
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the attacker the highest level of privilege on the compromised system ('root'
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for UNIX derivatives, 'Administrator' for Windows NT), and if not, the attacker
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will attempt to escalate their privilege to the highest level. The methods
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used to escalate local privilege level often employ extremely similar
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techniques, even across multiple OS platforms. Such vulnerabilities reoccur
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frequently due to non security-cognizant OS and application programming. A
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notable category of local exploit is a "buffer overflow" [8].
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A program to enable remote unauthorized access is traditionally installed,
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sometimes called a "back door". A back door "listens" identically to a network
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daemon/service, and provides either full remote command line access or a set of
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specific actions e.g. upload/download file, execute/terminate process, etc.
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In summary, the goals of the consolidation component of the metastasis phase of
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an attack, are to remove any evidence of the exploitation phase, and to ensure
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that remote access is available to the attacker.
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II. Continuation Component
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The continuation component of metastasis is the most conceptually interesting
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and challenging, in terms of attempting to construct a model of the attackers
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actions.
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Because a host on the target network has been compromised, the attacker can now
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utilize 'passive' as well as the previous described 'active' attack methods to
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deepen the penetration. Traditionally, a "password sniffer" is installed - a
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promiscuous mode network protocol monitor, designed to log the usernames and
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passwords associated with those application layer protocols that utilize plain
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text transmission, e.g. Telnet, FTP, rlogin, etc.
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Implicit to modern enterprise network environments is the concept of trust.
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[9] defines trust as:
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"[the] situation when a ... host ... can permit a local resource to be used by
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a client without password authentication when password authentication is
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normally required."
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Metastasis involves the use/abuse of trust relationships between a compromised
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host and other prospective target hosts.
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Regardless of OS type, a host is likely to engage in multiple trust
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relationships, often in the areas of authentication, authorization, remote
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access, and shared resources. The process of trust relationship exploitation
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involves identifying and "following" trust relationships that exist on a
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compromised host, in order to deepen a penetration. There is often no need to
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perform the exploitation stage of an attack against other hosts on the target
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network if they already implicitly trust the compromised host in some way.
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The classical example of trust relationship exploitation involves the
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subversion of the Berkley "R" commands and their configuration files in the
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UNIX environment: '.rhosts' and '/etc/hosts.equiv'.
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----[ Properties of the Traditional Attack Paradigm
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It is valuable to identify those properties that define the traditional
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attack paradigm, as outlined above.
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I. One to One, One to Many Model
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Information gathering techniques are traditionally performed using a "one to
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one" or "one to many" model; an attacker performs network operations against
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either one target host or a logical grouping of target hosts (e.g. a subnet).
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This process is ordinarily executed in a linear way, and is often optimized for
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speed by utilizing parallel or multi-threaded program execution.
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This linear process can be visualized using a conceptually simplified network
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topology diagram. Fig 1 shows attacker host A1 "attacking" (i.e. performing
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the host and/or service detection phases of an attack) against a single target
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host T1.
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A1 -------> T1
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Fig 1. One to One Model
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Fig 2 shows attacker host A1 attacking multiple target hosts T1 ... Tn.
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A1 -------> T1
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A1 -------> T2
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A1 -------> Tn
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Fig 2. One to Many Model
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Note that although the concepts of "one to one", "one to many", etc., are
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simplistic - they are particularly relevant and important to modeling the
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network activity generated by an attacker as they metastasize across a network.
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II. Server Centricity
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Traditional, remote exploitation techniques target a server program by
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approximating a client because, by definition [10]:
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"the client/server message paradigm specifies that a server provides a service
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that a client may request ... the attacker (client) makes a request (attack) to
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any server offering the service and may do so at any point."
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Server programs typically run with elevated privileges and are therefore
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advantageous targets for attack; this conveniently maps to the "one to one"
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and "one to many" models described in I.
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III. Attack Chaining
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The traditional attack process is often chained from compromised host to host
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in an attempt to obscure the "real" location of an attacker. Fig 3 shows an
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attack on target host T1 from attacking host A1 in which the attacker is
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logically located at host H1, and is connected to A1 through host H2; only the
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connection from A1 can be "seen" from T1.
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H1 -------> H2 -------> A1 -------> T1
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Fig 3. Attack Chaining
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IV. Latency
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Because password sniffer log files are traditionally written to disk, an
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attacker must return to a compromised host to collect information that could
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enable the depth of the penetration to be increased.
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Similarly, an attacker must return to a compromised host in order to proxy
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(chain) the attack process.
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----[ Distributed Metastasis
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These properties that define the traditional attack paradigm can be evolved.
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The core of the distributed metastasis methodology is a desire to utilize the
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distributed, client/server nature of the modern IP network environment, and to
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perform a logical automation of the metastasis phase of the traditional attack
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process.
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The impetus for the distributed metastasis approach comes from the observation
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of commercial "network enabled" security technology.
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Manufacturers of security software tools have, in the majority, evolved their
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products from a stand-alone model (single host e.g. COPS [11]) to a distributed
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one - in which multiple embedded agents reside on topologically disparate
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hosts, and communicate security-relevant information to a logically centralized
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"manager". This strategy is advantageous in terms of:
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I. Scalability
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The agent population is almost certainly fluid in nature - agents can be added
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and removed over time, but the manager remains constant. This model maps to
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the most common operating environment - the infrastructure is malleable but the
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security monitoring function (hopefully) remains stable.
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II. Cost of Ownership
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The impact of performing a single installation of an agent on a host is less
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costly over time in both physical and administrative terms than with repeated
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visitation.
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Agents that can be remotely "programmed" (i.e. instructed how to perform) from
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a remote location enable the function of the security software to be changed
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more rapidly throughout the enterprise (such as with a security policy change),
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than with multiple per-host installations.
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III. Coverage
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By utilizing multiple automated, semi or fully autonomous agents, that can
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either be scheduled to perform security analysis regularly or run continuously,
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the depth of agent coverage is increased, and consequently the probability of
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detecting anomalous (i.e. security relevant) behavior is increased.
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Although security vendors understand the functional requirements associated
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with large infrastructures in terms of scalability and cost of ownership, these
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properties have not yet been fully leveraged by the attacker community in
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extending the traditional attack methodology.
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----[ Properties of Distributed Metastasis
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A distributed, agent based approach, can be utilized in the metastasis phase
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of the traditional attack methodology to reap appreciable benefits for an
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attacker.
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The properties that define distributed metastasis are as follows:
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I. Agent Based
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The "back door" traditionally installed as part of the consolidation stage is,
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with distributed metastasis, a remotely controllable agent in a similar vein to
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those employed by network enabled security tools.
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The attacker will never "log in" in the traditionally sense to a compromised
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host once an agent is installed. This approach brings time saving advantages
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to an attacker because the log-file "clean up" operation involved with a
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conventional login does not have to be repeated ad infinitum.
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II. Many to One, Many to Many Model
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Whereas the traditional attack paradigm conventionally employs a "one to one"
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or "one to many" model of information gathering, the use of multiple
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distributed agents facilitates "many to one" and "many to many" models also.
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A custom client can deliver a "task definition" to an agent which defines a
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host and/or service detection task. An agent can return the results to a
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client either in (pseudo) real time or on task completion.
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For execution of host and service detection techniques that require low-level
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packet forgery (e.g. to enable a SYN port scan), the availability of a portable
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network packet generation library [12] eases the development time required to
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implement this functionality.
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As described in [13], the ability to utilize multiple source hosts for
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gathering host, service, and network topology information has advantages in the
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areas of stealth, correlation, and speed.
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Fig 4 and Fig 5 illustrate multiple source hosts (agents) used to perform
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information gathering in "one to many" and "many to many" scenarios
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respectively:
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A1 -------> T1
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A2 -------> T1
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An -------> T1
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Fig 3. Many to One Model
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A1 -------> T1 ... Tn
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A2 -------> T1 ... Tn
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An -------> T1 ... Tn
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Fig 5. Many to Many Model
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Agents can be remotely programmed either to execute or to forward scan
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definitions to functionally duplicate the "chaining" present in the
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traditional attack approach.
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Although an agent based approach is not implicitly required for "many to one"
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and "many to many" models of information gathering, it is made substantially
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easier through a programmatic approach. The ability of an agent to multiplex
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scan definitions allows an attacker to have topological control over which
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links in the network attack-related network traffic flows.
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III. Real Time Monitoring
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As described previously, delay exists when an attacker wishes to utilize a
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compromised host for further attacks and to collect log files from data
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collection programs such as password sniffers and keystroke recorders.
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With a distributed model, collected data such as username/password pairs can be
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transferred in (pseudo) real time to a remote location, and as shown, this
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process can be chained through multiple compromised hosts.
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Embedded password sniffing functionality could be extended to support
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regular-expression style pattern matching which again, because of the benefits
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of the agent based approach, would be remotely programmable.
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Conceptually, there is no limit to the amount or type of data that could be
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collected and forwarded by agents. Possible areas of interest to an attacker
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might include patterns of user activity and host and network utilization
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metrics.
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IV. Minimal Footprint
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In the traditional attack paradigm (albeit dependent on the "back door"
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employed), the attacker is exposed to a window of possible detection when the
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attacker re-enters a previously compromised host, between a login and the
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removal of the evidence of the login. With an agent based approach, the
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consolidation phase need never be repeated after the agent installation.
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V. Communication
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Covert channels between agents and managers and between agents can be created
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by utilizing steganography techniques. [14] describes the ubiquitous nature of
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ICMP network traffic to TCP/IP networks, and that it can subsequently be used
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to tunnel information which (superficially) appears benign.
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By utilizing such a ubiquitous transport, the ability to communicate between
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widely disparate agents is less likely to be affected by network devices that
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implement network traffic policy enforcement, e.g. screening routers,
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firewalls, etc.
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Confidentiality and integrity can be added using Cryptography.
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VI. Client Centricity
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The structure of the traditional attack methodology lends itself to server
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centric attacks - attacks which attempt to subvert a server by approximating a
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client. With a distributed approach in which an embedded agent resides on a
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server, client requests to that server can consequently be intercepted and
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subverted.
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----[ Monoculture
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As described, fundamentally, distributed metastasis advocates an agent based
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approach. The logical implication is that an attacker must construct a
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functional agent for each OS variant that is likely to be encountered in the
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target environment (and which it is considered desirable to compromise).
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Admittedly, this requires initial time and intellectual investment by an
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attacker; however, the predominance of "monoculture" IT environments simplifies
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this task. Also, cross-platform programming languages such as Java make
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cross-platform operability realizable.
|
|
|
|
In the fields of ecology and biology, "monoculture" refers to the dominance of
|
|
a single species in an environment - a state considered to be pathologically
|
|
unstable. Economies of scale make monoculture installations attractive -
|
|
greater short term efficiency is likely to be achieved, and therefore the
|
|
majority of large organizations tend towards monoculture installations that
|
|
employ one or two key OS types.
|
|
|
|
|
|
----[ Internet Worm Analogy
|
|
|
|
The distributed metastasis approach shares similarities to the propagation
|
|
method used by the Internet "worm" [15] - the proliferation of remote agents.
|
|
Once an instance of the Internet worm infected a host, it attempted to
|
|
communicate with an external entity, although this was later thought to be a
|
|
deliberate attempt at throwing those people attempting to reverse engineer the
|
|
worm "off the scent".
|
|
|
|
A combined attack form in which a worm was used as a vector to seed agents
|
|
which can then be remotely controlled would increase the speed of penetration,
|
|
but would likely be less controllable, unless the worm was specifically
|
|
targeted and rate limited in terms of expansion - perhaps using a "proximity
|
|
control" mechanism similar to that employed by the SATAN network vulnerability
|
|
scanner [16].
|
|
|
|
|
|
----[ A Challenge for State and Event Monitoring
|
|
|
|
Would todays state and event monitoring tools detect a distributed metastasis
|
|
attack? Clearly, the answer is dependent on the proliferation, sophistication,
|
|
and configuration of those tools within the target environment.
|
|
|
|
If an attacker can compromise a host and remove evidence of the attack, state
|
|
monitoring tools will not detect the hostile activity if it falls between those
|
|
scheduled times when the tool performs its sweep. Host based IDS, dependent on
|
|
the exploitation and privilege escalation method used by an attacker, may
|
|
detect the attack. Clearly therefore, a combination of state monitoring and
|
|
real time state monitoring (a.k.a. intrusion detection) tools should both be
|
|
employed within a technical security architecture.
|
|
|
|
"Many to Many" and "Many to One" attacks are less likely to be detected by
|
|
network based intrusion detection systems (N-IDS) than with a linear model.
|
|
The techniques described in [17] can be implemented to assist evasion of N-IDS.
|
|
|
|
As discussed, with an agent based approach, once an agent is installed and
|
|
hidden, the intrusion is less likely to be detected than with continual
|
|
re-visitation of a host (e.g. with Telnet) as in the traditional attack
|
|
methodology. If an agent can be installed and hidden, if it is not detected at
|
|
an early stage it is unlikely to be discovered from that point forward.
|
|
|
|
For "open source" OS' (e.g. OpenBSD, Linux, etc.) an agent could even be
|
|
incorporated into the kernel itself. Similarly, any OS that enables loading
|
|
of run-time kernel modules could be compromised in this way.
|
|
|
|
Polymorphic techniques could perhaps be implemented to increase the complexity
|
|
of detection (cf. polymorphic strains of virus).
|
|
|
|
|
|
----[ A New Architecture for Vulnerability Scanning
|
|
|
|
There exists several advantages in using a distributed agent model for
|
|
commercial vendors of network vulnerability scanning technology. A distributed
|
|
model would enable localized 'zones of authority' (i.e. delegation of
|
|
authority), would facilitate information gathering behind NAT (and firewalls,
|
|
where configured), and overcome network topology specific bandwidth
|
|
restrictions.
|
|
|
|
Information chaining would enable the construction of a hierarchical reporting
|
|
and messaging hierarchy, as opposed to the "flat" hierarchy implemented in the
|
|
majority of tools today.
|
|
|
|
At this time I am aware of no commercial (or free) vulnerability scanners that
|
|
employ a distributed architecture as described.
|
|
|
|
|
|
----[ Conclusion
|
|
|
|
Although some notable remotely programmable embedded agents exist [14] [18]
|
|
[19], they have not been fully utilized in continuation of the remote attack
|
|
paradigm.
|
|
|
|
Considerable benefits exist for an attacker in utilizing a distributed
|
|
penetration methodology, centered on an agent based approach; these benefits
|
|
are not dissimilar to the benefits available through the use of distributed, as
|
|
opposed to static, security state and event monitoring tools.
|
|
|
|
Distributed metastasis is, in comparison to the traditional attack paradigm, a
|
|
non-trivial methodology for computer penetration, the advantages of which are
|
|
likely only to be considered worth the expenditure in effort by a small
|
|
minority of skilled attackers; however, strategically - those advantages could
|
|
be significant.
|
|
|
|
|
|
----[ References
|
|
|
|
|
|
[1] William R. Cheswick & Steven M. Bellovin, "Firewalls and Internet
|
|
Security", Addison-Wesley, 1994.
|
|
|
|
[2] Andrew J. Stewart, "Evolution in Network Contour Detection", 1999.
|
|
|
|
[3] Roland J. Schemers III, "fping", Stanford University, 1992.
|
|
|
|
[4] Michael Schiffman & David Goldsmith, "Firewalking - A Traceroute-Like
|
|
Analysis of IP Packet Responses to Determine Gateway Access Control
|
|
Lists", Cambridge Technology Partners, 1998. www.packetfactory.net.
|
|
|
|
[5] David C. M. Wood, Sean S. Coleman, & Michael F. Schwartz, "Fremont: A
|
|
System for Discovering Network Characteristics and Problems", University
|
|
of Colorado, 1993.
|
|
|
|
[6] Merit GateD Consortium, "ripquery - query RIP gateways", 1990-1995,
|
|
www.gated.org.
|
|
|
|
[7] Daniel V. Klein, "Foiling the Cracker; A Survey of, and Improvements to
|
|
Unix Password Security", Proceedings of the 14th DoE Computer Security
|
|
Group, 1991.
|
|
|
|
[8] Aleph One, "Smashing The Stack For Fun And Profit", Phrack Magazine,
|
|
Volume 7, Issue 49, File 14 of 16, 1996, www.phrack.com.
|
|
|
|
[9] Dan Farmer & Wietse Venema, "Improving the Security of Your Site by
|
|
Breaking Into it", 1993, www.fish.com.
|
|
|
|
[10] Michael D. Schiffman, Index, Phrack 53, Volume 8, Issue 53, Article 01
|
|
of 15, 1998, www.phrack.com.
|
|
|
|
[11] Dan Farmer, "COPS", 1989, www.fish.com.
|
|
|
|
[12] Michael D. Schiffman, "Libnet", 1999, www.packetfactory.net.
|
|
|
|
[13] Stephen Northcutt, "SHADOW Indications Technical Analysis - Coordinated
|
|
Attacks and Probes", Navel Surface Warfare Center, 1998.
|
|
|
|
[14] Michael D. Schiffman, "Project Loki", Phrack 49, File 06 of 16, 1996,
|
|
www.phrack.com.
|
|
|
|
[15] Eugene H. Spafford, "The Internet Worm Program: An Analysis", Purdue
|
|
University, 1988.
|
|
|
|
[16] Dan Farmer & Weitse Venema, "SATAN", 1995, www.fish.com.
|
|
|
|
[17] Thomas H. Ptacek & Timothy N. Newsham, "Insertion, Evasion, and Denial
|
|
of Service: Eluding Network Intrusion Detection", Secure Networks Inc,
|
|
1998.
|
|
|
|
[18] Cult of the Dead Cow, "Back Orifice 2000 (a.k.a. BO2K)", 1999,
|
|
www.bo2k.com.
|
|
|
|
[19] Greg Hogland et al, 1999, www.rootkit.com.
|
|
|
|
|
|
----[ EOF
|