Who are ethical hackers?

Successful ethical hackers possess a variety of skills. First and foremost, they must be
completely trustworthy. While testing the security of a client’s systems, the ethical
hacker may discover information about the client that should remain secret. In many
cases, this information, if publicized, could lead to real intruders breaking into the
systems, possibly leading to financial losses. During an evaluation, the ethical hacker
often holds the “keys to the company,” and therefore must be trusted to exercise tight
control over any information about a target that could be misused. The sensitivity of
the information gathered during an evaluation requires that strong measures be taken
to ensure the security of the systems being employed by the ethical hackers
themselves: limited-access labs with physical security protection and full ceiling-to
-floor walls, multiple secure Internet connections, a safe to hold paper documentation
from clients, strong cryptography to protect electronic results, and isolated networks
for testing.

Ethical hackers typically have very strong programming and computer networking
skills and have been in the computer and networking business for several years.
They are also adept at installing and maintaining systems that use the more popular
operating systems (e.g., UNIX** or Windows NT**) used on target systems. These
base skills are augmented with detailed knowledge of the hardware and software
provided by the more popular computer and networking hardware vendors. It should
be noted that an additional specialization in security is not always necessary, as strong
skills in the other areas imply a very good understanding of how the security on
various systems is maintained. These systems management skills are necessary for the
actual vulnerability testing, but are equally important when preparing the report for
the client after the test.

Finally, good candidates for ethical hacking have more drive and patience than most
people. Unlike the way someone breaks into a computer in the movies the work that
ethical hackers do demands a lot of time and persistence. This is a critical trait, since
criminal hackers are known to be extremely patient and willing to monitor systems for
days or weeks while waiting for an opportunity. A typical evaluation may require
several days of tedious work that is difficult to automate. Some portions of the
evaluations must be done outside of normal working hours to avoid interfering with
production at “live” targets or to simulate the timing of a real attack. When they
encounter a system with which they are unfamiliar, ethical hackers will spend the
time to learn about the system and try to find its weaknesses. Finally, keeping up
with the ever-changing world of computer and network security requires continuous
education and review.

One might observe that the skills we have described could just as easily belong to a
criminal hacker as to an ethical hacker. Just as in sports or warfare, knowledge of
the skills and techniques of your opponent is vital to your success. In the computer
security realm, the ethical hacker’s task is the harder one. With traditional crime
anyone can become a shoplifter, graffiti artist, or a mugger. Their potential targets
are usually easy to identify and tend to be localized. The local law enforcement
agents must know how the criminals ply their trade and how to stop them. On the
Internet anyone can download criminal hacker tools and use them to attempt to
break into computers anywhere in the world. Ethical hackers have to know the
techniques of the criminal hackers, how their activities might be detected, and how
to stop them.

Given these qualifications, how does one go about finding such individuals? The best
ethical hacker candidates will have successfully published research papers or released
popular open-source security software. The computer security community is strongly
self-policing, given the importance of its work. Most ethical hackers, and many of the
better computer and network security experts, did not set out to focus on these issues.
Most of them were computer users from various disciplines, such as astronomy and
physics, mathematics, computer science, philosophy, or liberal arts, who took it
personally when someone disrupted their work with a hack.

Assessing the impact of a design decision

Design agents evaluate the consequences of their decisions by inferring ahead
as to whether the decision value will satisfy constraints or support goals. In doing
so, it is likely that some of the information required in the inference process is not
yet available, and therefore the agent will attempt to substitute for it with an
expectation.

Figure 1. Design expectation example

Imagine the frame design agent, in our chair design problem, making a decision
about the frame material. Before committing to the design decision the agent
may verify whether the decision will satisfy cost constraints. Therefore it will
need to know the conditions that influence the cost, and the specific correlations
between the values for the determined conditions and the cost ranges. An expectation
such as the one described in Figure 1 could be critical in validating the
agent’s decision before all the cost components are known. Alternatively, the
frame design agent may take a decision which is perfectly valid at that point, that
will be used by other agents, only to be later invalidated in a cost analysis process.

Data Hoarding

Data hoarding releases currency, therefore changes object semantics. A receiver
hoards replicas from a sender and each replica is denoted as (objectID, semantics),
where semantics is either primary or copy.

General hoarding (G-hoarding): sender owns the primary of an object, i.e.
(objectID, primary), and receiver hoards a copy from the sender. After G-hoarding,
sender still owns the primary, i.e. sender (objectID, primary), and receiver
(objectID, copy).

Primary hoarding (P-hoarding): sender owns the primary of the object, i.e. (objectID,
primary), and receiver hoards the primary from the sender. After P-hoarding, the
primary is transferred from the sender to the receiver and the one in the sender
becomes a copy, i.e. sender (objectID, copy), and receiver (objectID, primary).

Copy hoarding (C-hoarding): sender owns only the copy of the object, i.e. (objectID,
copy), and receiver hoards a copy from the sender. After C-hoarding, both the sender
and the receiver hold copies, i.e. sender (objectID, copy), and receiver (objectID, copy).

Bandwidth Estimation on Protocol Mechanisms

A simple mechanism to measure the available bandwidth on a link is the packet-pair
method. It entails sending two packets back-to-back on a link, and measuring the
inter-arrival time of those packets at the receiver. If the packets are sent on a
point-to-point link with no other traffic, the inter-arrival time measures the raw
bandwidth of the link for that size of packets. It is the absolute minimum period at
which packets of that size can be sent. Sending packets at a smaller spacing will
only queue packets at the outbound interface, with no increase in throughput. If the
packets are sent on a multiple hop path mixed with other traffic, routers on the way
may insert other packets between the two packets that were sent back-to-back,
making them arrive farther apart. The number of packets inserted is directly
proportional to the load on the outbound port each router uses to send the packets,
and does not depend on packet size if no fragmentation occurs, as time in the
routers is normally bound by protocol processing and not packet size. If packet size
is equal to the path MTU, the inter-arrival time measured at the receiver is a snapshot
of the bandwidth of the path. The interarrival time is the minimum period at which
packets can be sent that will not create a queue in any of the routers on the path.
If the load of all routers in the path is a constant, then the inverse of the inter-arrival
time defines the optimal rate to send packets through this link. The load not being a
constant, the measurement will have to be repeated from time to time to adjust the 
rate to the current conditions.

System Objects, Attributes and Constraints of Software Vulnreability

The de nition of software vulnerability includes mismatches between the assumptions
about the environment made during the development and operation of the program,
and the environment in which the program executes. The definitions in this section
refer to these assumptions.

In a computer system, a system object is an entity that contains or receives infor-
mation, that has a unique name, and that has a set of operations that can be carried
out on it. An attribute of an object is a data component of an object. A derived
attribute of another attribute is a data component of the later attribute. A property
of an attribute is a characteristic of the attribute that can be derived from the attribute
by the application of a function to the attribute.

An attribute re nement is a nite re nement of attributes within attributes, and results in
the identification of the attributes about which assumptions are made. The attribute
refinement cannot contain a property of an attribute.

Physical Attacks on Secure Embedded Systems

For an embedded system on a circuit board, physical attacks can be launched by
using probes to eavesdrop on inter-component communications. However, for a
system-on-chip, sophisticated microprobing techniques become necessary. The
first step in such attacks is de-packaging. De-packaging involves removal of the
chip package by dissolving the resin covering the silicon using fuming acid. The
next step involves layout reconstruction using a systematic combination of
microscopy and invasive removal of covering layers. During layout
reconstruction, the internals of the chip can be inferred at various granularities.
While higher-level architectural structures within the chip such as data and
address buses, memory and processor boundaries, etc., can be extracted with
little effort, detailed views of lower-level structures such as the instruction
decoder and ALU in a processor, ROM cells, etc., can also be obtained. Finally,
techniques such as manual microprobing or e-beam microscopy are typically
used to observe the values on the buses and interfaces of the components in
a de-packaged chip.

Physical attacks at the chip level are relatively har to use because of
their expensive infrastructure requirements (relative to other attacks).
However, they can be performed once and then used as precursors
to the design of successful non-invasive attacks. For example, layout
reconstruction is needed before performing electromagnetic radiation
monitoring around selected chip areas. Likewise, the knowledge of
ROM contents, such as cryptographic routines and control data, can
provide an attacker with information that can assist in the design of a
suitable non-invasive attack.

Sidestepping a Dictionary Attack with Username Selection

Of course, a password is only half of the required login credential. A username is
also required. While it is less likely that a dictionary word would be used as a
username, there are still some common usernames that hackers are certain to try
with a brute force attack. First among these are “admin” and “administrator”. These
names are especially dangerous since they are not only easily guessed, but the
accounts they represent are usually highly privileged administrative accounts. If the
hacker’s dictionary attack could gain access to an administrative account, he could
probably do much more damage to the system than he could if he gained access to
a regular user’s account.

Administrative accounts are not the only problem: many Web applications and
Web application frameworks create default users during installation. If the site
administrator does not remove these default users or at least change their
passwords, these accounts will be easy targets for a dictionary attack. Finally,
when users are allowed to choose their own usernames, they often choose their
email address, since it is easy to remember. Once again, the user’s laziness is a
benefit to a hacker using a brute force attack. Armed with a list of email
addresses (perhaps obtained from a spammer) and a dictionary of passwords
(easily obtained anywhere), an attacker has an excellent chance of breaking into
at least one user’s account.