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Handling and Reporting Security Advisories:
A Scorecard Approach
Dimitrios Lekkasa
and Diomidis Spinellisb
aDepartment of
Product and Systems Design Engineering
University of the Aegean, Syros Island 84100, Greece
tel:+30 2281097100, fax:+30 2281097109, e-mail: dlek@aegean.gr
bDepartment of
Management Science and Technology
Athens University of Economics & Business
76 Patission St., Athens GR-10434, Greece, e-mail: dds@aueb.gr
Abstract
Security advisories
aim to inform the community on new security vulnerabilities, their possible
impact and candidate solutions. Various product vendors and independent
response centers have completely different views on whether an advisory should
be published, on what to publish and on how the information included should be
organized. We present a scorecard as an exhaustive categorized list of
security-relevant metrics that helps an interested party to assess a security
advisory in a complete and efficient way, by following a clearly defined
sequence of conditional actions. Scorecard users should thus neither neglect
nor overreact in response to a potential security threat. Based on our
scorecard approach and the goal-question-metric technique, we also provide
prescriptive guidelines for collecting and disseminating system-specific
information related to a specific vulnerability. This paradigm is appropriate
for employment not only by end-users but also by security response centers as
an organized, stable and efficient scheme for publishing security advisories.
Categories and Subject Descriptors: D.4.6 Security and Privacy Protection, K.6.5
Security and Protection
Keywords: Vulnerability disclosure, Metrics, Applicability, Impact, Exploitation,
Countermeasures
Introduction
Bulletins of security
advisories typically include a description of a vulnerability, its possible
impact on specific targets and candidate solutions. These are published by
Security Response Centers, operating as independent organizations or as
specialized departments of software and hardware vendors, to help the
interested community operate their systems and networks in a secure manner. The
life-cycle of a security advisory starts form the ‘vulnerability disclosure’ i.e. the discovery of a security problem
after users’ reports or as a result of research and product evolution. The
product vendor decides on the necessary workaround, builds patches and fixes
and publishes a detailed ‘security
advisory’. At the same time the advisory may also appear in other
vendor-independent fora such as the reports of various Computer Emergency
Response Teams [1] and the Common Vulnerability and Exposures (CVE)
dictionary [2]. Various revisions of the
advisory may be published during its life-cycle, while the vendors release
relevant patches and workarounds or, at a later stage, incorporate a solution
into a major product release. A security advisory remains of interest to the
community during the life-cycle of the relevant vulnerability, until the number
of systems it can exploit shrinks to insignificance [3].
A security advisory is
usually judged by security experts and classified to a severity rating before
it is disclosed to the public. However, a basic vulnerability rating escalation
such as Critical, Moderate or Low risk and even a comparable value, is
insufficient for an end-user or a system administrator to assess the risk [4], since the vulnerability’s impact will typically
depend on specific product versions, system use profiles, configurations,
hardware platforms, functional conditions and local policies.
In fact it is quite
possible that an eventual victim will overlook or have difficulties to identify
a vulnerability disclosure that represents a significant risk or, on the other
side, she will invest significant resources to face a vulnerability that does
not introduce a real threat. The information overload regarding the vulnerabilities
and exploits, which is continuously increasing, is further worsening the
situation and is a separate and important threat by itself. According to
industry experience, attacks that impact systems rarely result from attackers’
exploitation of previously unknown vulnerabilities. Rather, as in the cases of
Nimda worm and the recent Windows RPC buffer overrun, attacks typically exploit
vulnerabilities for which solutions have long been available, but not applied.
It is in fact reported that over 90% of the security exploits are carried out
through vulnerabilities for which there are known patches [5].
The objective of the
paper is twofold: 1) to present our vulnerability
scorecard as practical guide that will help end users and system
administrators to efficiently manage and quickly assess impacts of a
vulnerability disclosure and 2) to provide prescriptive guidelines, based on a goal-question-metric approach, as a tool
for end-users to record useful information as well as for security response
centers to publish advisories in a way that will help their community
efficiently respond to them.
The (Un)readability of Security Bulletins
A quick survey of
various security bulletin boards showed that each has a completely different view
on what to publish, on what information to include and on how the data is
organized. In respect to the indicative volume of published advisories, we
recorded similar values for specific vendors, being 45 for Cisco, 72 for
Microsoft and 44 for FreeBSD, average per year, for the last 3 years.
Respectively, for the non vendor-specific informational postings we recorded 37
advisories for CERT, 734 for AusCert, 56 for Symantec and 1568 for CVE. The
unexpectedly high difference between the above numbers indicates that there is
no clear rule on what is considered as a security advisory and that there is
confusion between the terms ‘vulnerability disclosure’ and ‘security advisory’,
we described in the first paragraph of the present article.
As a typical example,
a first look into the following recent, apparently clear security advisories,
gave us a misleading impression for their effect on our systems:
The security advisory
SA-03:14.arp published by FreeBSD, affects all releases of FreeBSD systems,
independently of configuration, services running and software installed.
According to the advisory, it is possible for an attacker to cause the system
to hang by flooding it with ARP requests, which seemed as an urgent situation.
However, after reading through the 3 pages of the advisory, it became obvious
that there is no real concern for our FreeBSD system at home, since:
b) The attack may only originate from the local
network and not from the Internet; our system only communicates with the
Internet through a dial-up line and a packet filtering router.
In another case,
Microsoft published the MS02-030 security bulletin, applicable to systems
running SQL server 2000. The severity of the vulnerability was rated as
‘moderate’ by the vendor and it would not indicate an urgent threat for system
administrators. However, after a careful study of the 7 pages long advisory we
concluded that our web server which was configured to accept ad hoc URL queries
against a database frequently used by the academic community, was in real
danger for two reasons:
a)
An option called
SQLXML, which is not enabled by default, was in fact enabled and could allow an
attacker to run arbitrary code by injecting scripts through XML tags.
b) The subject system was providing critical
web-based applications to hundreds interested parties.
It is obvious that a
clear decision on the applicability and the severity of security advisories is
hardly drawn by a superficial study on them. A first conclusion on the impact
and on some applicability factors may be extracted by the detection of some
specific keywords within the summary of the advisory. We performed a rough
keyword classification in the collection of about 2600 advisories in the Common
Vulnerabilities and Exposures dictionary [2], as shown in Figure 1. However, there are other
important factors, including but not limited to the impact on the community
that uses the system, the exploitation preconditions, the solution requirements
and the solution impact, which are not obvious.
Figure 1. CVE keyword classification
The Metrics-based Scorecard
What is really missing
form the bulletin boards of the vendors and even from the organizations that
are exclusively focusing on handling emergency incidents, is a practical guide
for how one may read, evaluate and handle a security advisory. The advisories
are addressed to a heterogeneous community, being system or network
administrators and end-users, operating publicly used servers, critical
infrastructures, personal computers, network devices and other purpose-specific
systems. Any attempt by the vendor to conclude on the applicability and the
severity of the security advisory, would mislead an important portion of the
community.
A practical solution
to this problem is the definition of a series of metrics (the scorecard) that the interested party has to evaluate for a
specific security advisory, in order to conclude on the risk faced by a
specific system. The exhaustive scorecard presented in Table 1, contains nine
major categories of metrics, presented in a logical sequence, giving a complete
picture of the vulnerability and the relevant risk. An interested party has to
give values (answers) to the metrics in the order presented and in most cases
it will arrive at a conclusion before traversing the whole list.
The identified
categories are mutually exclusive and the items presented cover a wide spectrum
of security related attributes, although they may be further refined. Items 1
to 6 refer to the assessment of the applicability and the impact of the
advisory, while the items 7-9 refer to the implementation of the proposed
solution. More specifically, the target of a vulnerability is classified in
logical and physical items according to S.Gritzalis [6]. The items in the exploitation impact category
is a refined result of various listings, which either make a distinction
between hardware and software impact or presenting a classification according
to the effects on availability, integrity and confidentiality respectively or a
generic classification into misuse, exposure and denial-of-service [7, 8]. The metrics of the community impact are based on a
risk management analysis by S.Katsikas [9] and finally the solution requirements are partially
based on relevant taxonomies [10, 11].
|
Metrics
|
Short Description
|
Assessment phase |
1. Target |
|
·
Logical: o
Account o
Process o
Data ·
Physical: o
System infrastructure o
Network (local range) o
Internet (wide range) |
Logical targets
refer to informational and processing resources. Physical targets may refer
to hardware, to local area network infrastructure or, in a extreme case, to the entire Internet
infrastructure. |
|
2.
Applicability – Scope |
||
·
Hardware architecture and platform ·
Version of installed firmware ·
Operating system and version ·
Software installed ·
Enabled feature ·
Configuration parameter ·
Peripherals and hardware specific software |
The applicability
of a security advisory, depends on hardware type, OS, software installed and
various configuration settings. It is usually clearly indicated in the text
provided by the advisory. |
|
3. Exploitation Preconditions |
||
·
Internet remotely exploitable ·
Intranet remotely exploitable ·
LAN shared medium exploitable ·
LAN switched medium exploitable ·
Registered user exploitable ·
Requires physical access |
The exploitation of
a vulnerability is usually performed remotely, either location independently
or only within specific logical or physical limits, such as an Intranet
logical area, a LAN or a switched LAN segment. In other cases the
exploitation may succeed only by normally registered users or by physical
access. |
|
4. Organizational Factors |
||
·
Comprehensiveness and completeness of
advisory description ·
Existence of an incident response team ·
Existence of prior risk analysis |
These factors may
considerably mitigate the impact of a vulnerability, by providing the means
for better information dissemination and response procedures. |
|
5. Exploitation Impact (Damage) |
||
·
Availability disruption (denial of service) ·
System or data integrity violation and loss
of data ·
Data disclosure and confidentiality breach ·
Privilege elevation ·
Stolen credentials ·
Code/script execution ·
Bypass of intended controls ·
Misuse of resources ·
Violation of system’s security policy ·
Affecting neighbor systems (spreading) ·
Erroneous transmission ·
Physical damage |
The first 5 items
refer to the basic security properties, i.e. the availability, the integrity
and the confidentiality of the information and the infrastructure.
Exploitation may also result to unauthorized action and system misuse, such
as the code execution and the bypass of authentication and authorization
controls. In other cases the exploitation may provoke spreading to neighbor
systems, erroneous transmission (e.g. network disruption, traffic
redirection, transmission out-of-sequence) or physical damage. |
|
6. Community Impact |
||
·
Financial loss – Labor time loss ·
Loss of trust ·
Personal abuse, defamation and humiliation ·
Unauthorized gain of political authority and
status ·
Blackmail and other criminal action ·
Action against the law ·
Effects on national security and defense ·
Effects on international relations |
Financial loss may
be direct theft, down-time cost or restoration cost. Loss of trust against
the information system is also a severe impact. The rest of the items refer
to illegal or criminal action and in more extreme cases on national and
international aspects. |
|
Implementation phase |
7. Solution Requirements |
|
·
No action ·
Workaround ·
Locate relevant security advisories by other
sources ·
Patch availability and installation ·
OS or application upgrade ·
Software development ·
Command execution ·
Configuration modification ·
Rebuilding of kernel or other executables ·
Configuration or installation of additional
protection measures ·
Enable logging of evidence data |
The solution
requirements focus on the solution implementation, such as patching and
configuring, according to the relevant security advisories. Additional
protection measures may be required, such as the use of ACLs, an IDS,
firewalls, cryptography, VPNs and antivirus applications. The collection of reliable evidence data,
by means of system logging, may be also a requirement of the solution. |
|
8. Solution Impact |
||
·
Cost in time and money for the establishment
of the countermeasures ·
Cost in time and money for regression testing
of the updated system. ·
Availability of the system while applying the
solution ·
Consequences on the functionality of the
organization ·
Time margin to take action |
The implementation
of a proposed solution is not costless. Cost in terms of money, labor time,
system availability and organization functionality is usually
significant. The time margin to take
action is also an issue and according to the severity of the impact it would
be immediate, short-term or long-term. |
|
9. Conclusions Impact |
||
·
Severity of the security advisory ·
Efficiency of the countermeasures ·
Need future plan for the protection of the
system ·
Need further communication with the vendor ·
Indication that attacks will be repeated or
increased |
The conclusions
that will arise after the assessment and the implementation phases of a
security advisory are either informational or indicating further action. |
Table 1. The Scorecard metrics
The value that will be
assigned to a metric heavily depends on the type and the usage of the target
system, being a server, a router/switch, a shared terminal, an online personal
computer, an offline PC and other networked devices. For example, a
Denial-of-Service attack will have completely different impact value on a mail
server with hundreds of users and on a personal computer, although they may
have the same operating system, hardware and configuration.
As a result, complete
examination of certain security advisories under the perspectives of various
systems would be drawn upon a collection of quadratic vectors in the form:
{advisory, system usage, metric, value}
Since, in practice,
one deals with a single advisory or vulnerability and a single system at a
time, we may simplify the above approach by removing the two dimensions.
Consequently, the assignment of values to all or part of the abovementioned
metrics will result in a single scorecard
for a given vulnerability and a specific system.
A prior existence of a
“Risk Analysis” study [12] would add value to the assessment process, by
having:
Another practical
assumption is that all the metrics may be assigned discrete values. Discrete values such as Boolean (yes/no) or a
Low/High escalation give a more readable overall result that will lead the
investigator to a quick conclusion. Examples:
Countermeasures cost: High, Moderate, Low, None
Exploitation Impact: High, Moderate, Low, None
Applicability: All, Some, One, None
Time of action: Immediate, Short-term, Long-term,
N/A
Loss of data: Fully, Partially, None
The sequence of the evaluation of the
presented metrics for the assessment of a vulnerability disclosure, is also
important. As a general guide, the following sequence should be followed, where
the ([…]) notation indicates an optional part in the sequence:
[Event Detection à ] Security Advisory retrieval à Target à Applicability à Preconditions à Organizational factors [ à Exploitation Impact à Community Impact [ à Solution Requirements à Solution Impact [ à Solution Implementation à Conclusions ] ] ]
The following list
contains the conditions under which the distinct steps of the evaluation
process are executed. Figure 2 depicts the whole procedure in a UML sequence
diagram.
Figure 2. Action sequence for handling Security
Advisories
The Goal-Question-Metric Approach
The management of
systems security cannot only be seen by the perspective of some static
characteristics, but also by the perspectives of the emerging threats. Each and
every new vulnerability or exposure may pose different objectives for the
assessment and improvement of the security of a system. Various techniques
offer the opportunity to implement a quantitative and qualitative analysis of
the system’s security against a specific threat. The Goal-Question-Metric (GQM)
[13] technique and the Balanced Scorecard [14] framework are recommended for supporting process
improvements. Such quantitative approaches may be used either by the Response
Centers, as a practical guide for publishing advisories and by the end-user
wishing to efficiently handle a security advisory against a specific system.
The construction of a
practical guide for the assessment of the vulnerability disclosures may be
perfectly based on the Goal-Question-Metric technique that is a common analysis
tool in software engineering and in quality management. According to this
technique an involved party sets an objective, which cannot be directly
interpreted, but is described by a series of questions. Each question in turn
is answered by a series of metrics, which may be quantitative (obtain absolute
values) or qualitative (answered by a subjective judgment or by a comparable
value).
A goal is composed by
four parts:
A series of questions
and relevant metrics have to be constructed according to the characteristics
and the requirements of a specific system (object). For example, a question on
denial-of-service impact would probably appear in the case of a core mail
server, but not in the case of a home personal system. Examples on the
examination of two security advisories under the perspectives of two different
system types follow:
1st example: Goal: Assess (intention) the impact (issue) of
the vulnerability (object) described by CAN-2002-0187 (“Unchecked buffer in
SQLXML could lead to code execution”) against my personal Windows web server
(perspective).
Question |
Metric |
Value |
Question A: (General factors) Is the vulnerability
disclosure well described and documented? |
||
|
Metric
A1: Comprehensiveness |
Good |
Metric
A2: Completeness |
High |
|
Question B: (Applicability and Preconditions) Is my
system in danger? |
||
|
Metric
B1: Microsoft SQL server 2000 installed |
Yes |
Metric
B2: Connectivity to the Internet |
Partial |
|
Metric
B3: XML queries through http enabled |
Yes |
|
Metric
B4: Privileged user only exploitable |
Yes |
|
Question C: (Target) Which system objects are in
danger? |
||
|
Metric
C1: Logical targets |
Data |
Metric
C2: Physical targets |
None |
|
Question D: (Exploitation Impact) Is the risk high? |
||
|
Metric
D1: Code execution |
High |
Metric
D2: Data modification and loss |
High |
|
Metric
D4: Credentials stolen |
No |
|
Question E: (Solution Impact) Do I have to take
immediate action or leave it for next working day? |
||
|
Metric
E1: Severity rating by the vendor |
Moderate |
Metric
E2: Number of people using the server |
<10 |
|
Question F: (Conclusions Impact) Is the protection
against the vulnerability really needed? |
||
|
Metric
F1: Subjective reply based on metrics A to E |
Not
urgently |
Table 2. Unchecked buffer in SQLXML could lead to code
execution – GQM analysis
2nd example: Goal: Protect (intention) the border router (perspective)
of the national tax information system from the vulnerability (issue) described
in Cisco security advisory (object) with ID 44020 “Cisco IOS interface blocked
by IPv4 packets” released on July 16th 2003.
Question |
Metric |
Value |
Question A (Target): What is the target of the
threat? |
||
|
Metric A1: Parts of system infrastructure
affected. |
All interfaces of border router |
Question B (Applicability): Is the current
configuration of the router tolerant against the threat? |
||
|
Metric B1: Current version of IOS |
Vulnerable |
Metric B2: Protocol Independent Multicast
(PIM) enabled |
Yes, higher risk |
|
Metric B3: Existence of Ethernet Interface
that possibly affects neighbor systems through ARP |
Yes |
|
Question C (Preconditions): Are the additional
preconditions for the exploitation of the vulnerability satisfied? |
||
|
Metric C1: IPv4 enabled |
Yes |
Metric C2: No ACL blocks TCP protocols 53,
55, 77 and 103 |
Yes |
|
Question D (Exploitation Impact): What is the
maximum exploitation impact? |
||
|
Metric D1: Denial of Service |
High |
Metric D2: Affecting neighbor systems |
Yes |
|
Metric D3: Code execution |
No |
|
Question E (Community Impact): What will be the
consequences of a possible attack to the citizens? |
||
|
Metric E1: Financial Loss |
Likely |
Metric E2: Loss of Trust |
High |
|
Metric E3: Criminal action |
No |
|
Question F (Solution Requirements): What is the
immediate action needed? |
||
|
Metric F1: IOS upgrade |
Yes |
Metric F2: ACL update |
Yes |
|
Question G (Solution Impact): What are the effects
of the solution implementation? |
||
|
Metric G1: Cost in money |
zero |
Metric G2: Down time |
10 minutes |
|
Metric G3: Impact to other systems |
None |
|
Metric G4: Consequences to the functionality
of public services, if applied on low-traffic time |
Low |
|
Metric
G5: Rate {Cost of impact / Cost of solution} |
High |
Table 3. Cisco IOS interface blocked by IPv4 packets -
GQM analysis
Ideally, a security
advisory published by a vendor should be accompanied with a
Goal-Question-Metric list, such as the ones presented above, containing the
most relevant to the advisory metrics and the estimated values. This will help
an interested party to identify the required data in a more organized fashion
and thus to come quickly to a conclusion on the faced risk. In any case, at
least two GQM lists should be presented separately in respect to the two
extreme situations, where an affected system is either a personal system or a
critical widely used infrastructure.
Case study: Testing the repeatability of
scoring reports
A key issue that adds
value to our proposed solution is the repeatability
of the scoring reports. The rating of a security advisory, based on our
scorecard, is characterized as repeatable when a different observer can rely on
this rating without undertaking
a detailed examination of the security advisory. An efficient exploitation of our proposal that
produces highly repeatable scoring reports will reduce the complexity of
judging risk and the work factor that is necessary to examine a vulnerability
disclosure and its related security advisories. High repeatability of scoring reports may also contribute to the automation and the
scalability of intrusion detection procedures [15].
As a case study, we
used historical data of vulnerability disclosures from the CVE dictionary to
apply our metrics-based scorecard. The objective of the case study was to
collect results on the effort required to quantify the scorecard metrics, on
the accuracy of the drawn conclusion and on the repeatability of the results of
the scoring procedure. We examined 200 CVE entries covering a 5-month period
within 2002,[1] having also
added some extra entries applicable to NetBSD systems. To collect the data
necessary to perform the case study, we extracted the vulnerability
descriptions from the CVE dictionary and located the related security
advisories from product vendors. We studied each advisory up to the point where
a clear conclusion regarding its applicability could be drawn, recording the
metrics of our scorecard.[2]
This procedure was repeated for three different systems: a) An Intel-based
system with Microsoft Windows 2000, serving as a database and Internet web
server for a medium-size University b) A Cisco router (7500 series) serving as
a university’s border router. c) An ARM-based NetBSD network appliance periodically
connected to the Internet.
In brief, we initially
found 35 applicable entries for the Windows system; 18 entries out of the 35
were found to be non-applicable at a later step, due to specific configuration
parameters. For 7 entries out of the 35 the assessment stopped at an
intermediate step, mainly because their impact proved to be not important (e.g.
a browser vulnerability has impact on workstations but not on servers). For 10
entries the complete assessment and the resolution implementation steps were
carried out. Similarly, it was necessary to perform all assessment and
resolution implementation steps for approximately 25% of the vulnerabilities
applicable to the Cisco and NetBSD systems.
Our experiments
focused on our basic research question: the repeatability of a scoring report
under multiple observers. Toward this objective, we repeated the scoring
procedure for the Windows 2000 system (against the 35 applicable
vulnerabilities) under four additional perspectives,2 in order to
examine whether a different observer may rely on an existing precompiled
scoring report or has to read through the complete security advisory. The
perspectives under which the study was preformed were:
Assuming that the
examined systems have similar applicability factors, in terms of platforms and
basic configuration, a high percentage of the scoring reports proved to be
repeatable in many cases, as summarized in Table 4. Each value in Table 4
(percentage and absolute number) represents the number of scoring reports that were
found to be repeatable between two different observing perspectives. The order
of the observations does not affect the result and therefore the resulting
matrix is symmetric (aij = aji). The diagonal of the
table is shaded since it corresponds to comparisons between the same
observations.
Observation Perspective |
DB & Web Server |
Mail Server |
Intranet File Server |
Workstation Lekkas |
Workstation Spinellis |
DB & Web Server |
|
97% (34) |
94% (33) |
57% (20) |
57% (20) |
Mail Server |
97% (34) |
|
91% (32) |
54% (19) |
54% (19) |
Intranet File Server |
94% (33) |
91% (32) |
|
57% (20) |
57% (20) |
Workstation Lekkas |
57% (20) |
54% (19) |
57% (20) |
|
94% (33) |
Workstation Spinellis |
57% (20) |
54% (19) |
57% (20) |
94% (33) |
|
Table 4. Repeatability of scoring reports under
multiple observations
The results of the
case study show a total repeatability of the scoring reports when observed
under the perspective of Internet servers, high repeatability between Internet
and Intranet servers, partial repeatability between servers and workstations
and high repeatability between different workstations. By further analyzing the
results, we have concluded that the different scorings recorded between
Internet and Intranet servers are due to different exploitation preconditions
of a vulnerability and specifically the dependency on whether the vulnerability
is remotely or locally (and usually by authenticated users) exploitable. On the
other hand, the majority of the differences between servers and workstations derive
from the need of local user intervention for the exploitation of a
vulnerability (e.g. opening a document or interacting with a remote site) which
is common on a workstation but not probable on a server. The number of
non-repeatable reports between the two workstations was very small and was
caused by applicability differences, something which in most cases was obvious
by just reading the title of the vulnerability.
We can now argue that
the targeted pre-processing of our scorecard under three main perspectives,
results in highly repeatable reports and may substantially increase the
efficiency of the relevant security advisories. The perspectives were based on
the different usages of each system: an Internet server, an appliance not
directly connected to the Internet, serving a local community (Intranet server)
and a workstation, partially connected to the Internet. It is also possible to
identify different categorizations of system usage, depending on the type of
the device. For example, a relevant categorization for a network device would
be a) Border router, b) Access server and c) LAN equipment. A sample simplified
scoring report for a specific vulnerability is shown in Table 5.
CVE-2002-0650 |
The keep-alive
mechanism for Microsoft SQL Server 2000 allows remote attackers to cause a
denial of service (bandwidth consumption) via a "ping" style packet
to the Resolution Service (UDP port 1434) with a spoofed IP address of
another SQL Server system, which causes the two servers to exchange packets
in an infinite loop. |
||
Perspective: |
Internet Server |
Intranet Server |
Workstation |
Target |
System, Network, Internet |
System, Network |
System, Network |
Applicability |
SQL server installed and enabled |
SQL server installed and enabled |
SQL server installed and enabled |
Preconditions |
remotely exploitable |
Spreading by neighbor systems |
Spreading by neighbor systems |
Organizational |
Advisory existed long before current massive exploits |
Advisory existed long before
current massive exploits |
Automatic system update does not download the patch |
Damage |
DOS – System and Network disruption |
System disruption and low risk of LAN disruption |
Low impact. No data disclosure or code execution |
Community Impact |
High - Financial loss |
Important |
None |
Solution Requirements |
patch installation or ACL
blocking port 1434 |
Patch installation |
Patch installation |
Solution Impact |
Server needs restarting. Remote connections disabled if ACL enabled |
Server needs restarting |
None |
Conclusions |
Critical situation. Need further observation |
Important risk. |
Not a critical situation. |
Table 5. Reducing work factor in the
examination of security advisories: A simplified precompiled scorecard for the
basic system usage perspectives
Conclusions
The security
advisories regarding specific product vulnerabilities are published by product
vendors and by independent organizations. They usually contain significant
amount of data, but rarely follow specific rules on the organization of the
information. The overall assessment of the advisory by an interested party is a
difficult task since it depends on various parameters, such as its
applicability, the preconditions and the impact of the vulnerability
exploitation, probable community impacts and the requirements of the solution.
Furthermore, one must take into account the type and the usage of the subject
system, in order to draw up a clear conclusion.
A list of metrics (a
Scorecard) grouped into major categories will help the interested party to
record the information included in a security advisory in a more productive way
that gives a clear picture of the risk faced by a system, among other
information such as the solution impact. The collection of the metrics’ values
becomes a straightforward procedure, since we describe it as a conditional
sequence of clearly defined steps. The Goal-Question-Metric technique gives a
practical solution for collecting all the information relevant to a security
advisory, by building up a list of questions and relevant metrics, against a
specific target system. The case study we performed against 200 CVE entries
demonstrated that the publication of pre-processed scorecards for a small
number of basic system usage perspectives can significantly increase the
repeatability of the proposed scoring reports. Consequently, the effort spent by
users and administrators for examining a security advisory can be significantly
reduced. This paradigm can be used as a guide by vendors and CERTs toward a
more stable and valuable security advisory publication scheme.
References