Big Data. Big Decisions
InformationWeek
Special Coverage Series


Feds Identify Top 25 Software Vulnerabilities

Department of Homeland Security worked with non-profits and the private sector to come up with a list of the most worrisome threats and how organizations can mitigate them.

Inside DHS' Classified Cyber-Coordination Headquarters
(click image for larger view)
Slideshow: Inside DHS' Classified Cyber-Coordination Headquarters
The Department of Homeland Security on Monday announced detailed guidance for how software companies and others writing code can avoid the most widespread and serious vulnerabilities in software.

Working with technology research non-profit Mitre and security training organization the SANS Instittute, as well as a number of private sector organizations from Apple to Oracle, DHS' National Cyber Security Division drew up a list of software vulnerabilities called the Common Weakness Enumeration, developed a scoring system and risk analysis framework for evaluating the seriousness of the flaws and prioritizing the weaknesses, and released a top 25 list of the most dangerous software errors.

More Insights

Webcasts

More >>

White Papers

More >>

Reports

More >>

The list includes high-level overviews and examples of each of the vulnerabilities, common consequences of the problem, likely modes of detection and attack, and potential mitigations for each type of attack at various steps in the software development process.

Initiative leaders anticipate that the Common Weakness Enumeration, top 25 list, and scoring system will let users compare weaknesses, educate themselves, and prioritize their security efforts. This isn't the first release of the top 25 list or of the Common Weakness Enumeration, but is the first one to take as detailed and data-intensive look at the vulnerabilities, thus making it significantly more useful than previous versions, initiative leaders said on a conference call about the effort.

"This will allow agencies and organizations to take a tactical approach to addressing vulnerabilities." Will Pelgrin, director of the Multi-State Information Sharing and Analysis Center, a collaborative cybersecurity effort that includes state and local governments, said on the call. "I see this as a management tool to focus the team on things that are the greatest threat and that have the greatest consequences."

Atop this year's list are SQL injection flaws, which are the most serious due to their common nature and the ease and frequency of exploit online. Other top vulnerabilities include operating system command injection, classic buffer overflow, and cross-site scripting.

The effort is exemplary of the increasing frequency with which DHS is collaborating with the private sector on cybersecurity efforts. In addition to this initiative, for example, DHS' National Cybersecurity and Communications Integration Center has private sector reps working side by side with feds to uncover and address vulnerabilities in their systems, and the IT sector has worked on a major risk assessment effort with DHS.

"Whether you call it partnership or collaboration, the relationship between the government and the private sector has been on the increase," Joe Jarzombek, director for software assurance at the National Cyber Security Division, said on the call.

The scoring system takes into consideration the potential technical and business impacts of exploited weaknesses, the operational layer to which the attacker might gain access (i.e. application-level versus, say, network-level), the effectiveness of available mitigating controls, the privilege level needed to access the vulnerability, the likelihood of discovery and exploit of the weakness, and more.

What industry can teach government about IT innovation and efficiency. Also in the new, all-digital issue of InformationWeek Government: Federal agencies have to shift from annual IT security assessments to continuous monitoring of their risks. Download it now. (Free registration required.)



Related Reading




Currently we allow the following HTML tags in comments:

Single tags

These tags can be used alone and don't need an ending tag.

<br> Defines a single line break

<hr> Defines a horizontal line

Matching tags

These require an ending tag - e.g. <i>italic text</i>

<a> Defines an anchor

<b> Defines bold text

<big> Defines big text

<blockquote> Defines a long quotation

<caption> Defines a table caption

<cite> Defines a citation

<code> Defines computer code text

<em> Defines emphasized text

<fieldset> Defines a border around elements in a form

<h1> This is heading 1

<h2> This is heading 2

<h3> This is heading 3

<h4> This is heading 4

<h5> This is heading 5

<h6> This is heading 6

<i> Defines italic text

<p> Defines a paragraph

<pre> Defines preformatted text

<q> Defines a short quotation

<samp> Defines sample computer code text

<small> Defines small text

<span> Defines a section in a document

<s> Defines strikethrough text

<strike> Defines strikethrough text

<strong> Defines strong text

<sub> Defines subscripted text

<sup> Defines superscripted text

<u> Defines underlined text

BYTE encourages readers to engage in spirited, healthy debate, including taking us to task. However, BYTE moderates all comments posted to our site, and reserves the right to modify or remove any content that it determines to be derogatory, offensive, inflammatory, vulgar, irrelevant/off-topic, racist or obvious marketing/SPAM. BYTE further reserves the right to disable the profile of any commenter participating in said activities.

Disqus Tips To upload an avatar photo, first complete your Disqus profile. | View the list of supported HTML tags you can use to style comments. | Please read our commenting policy.

Follow InformationWeek

By The Numbers

What Are Your Primary Concerns About Using Big Data Software?

Base: 417 respondents at organizations using or planning to deploy data analytics, BI or statistical analysis software
Data: InformationWeek 2013 Analytics, Business Intelligence and Information Management Survey of 541 business technology professionals, October 2012

What Do You Think?

What's your attitude about SQL analysis on top of Hadoop?
We want fast, standard SQL analysis capabilities on Hadoop ASAP
Hadoop is for unstructured data; SQL is for relational databases
We'll give SQL on Hadoop a try, but relational DBs will remain the mainstay
Given strong SQL support on Hadoop, we'd nix the data warehouse
We're not interested in Hadoop
No opinion



Related Content

From Our Sponsor

Five Big Data Challenges and How to Overcome Them with Visual Analytics

Five Big Data Challenges and How to Overcome Them with Visual Analytics

Business leaders often need a visual snapshot of data to quickly grasp and use it. This paper identifies five challenges in presenting data and how visual analytics can resolve them. Solutions are suggested to overcome the challenges of: speed, data clarity, data quality, displaying meaningful results, and dealing with outliers.

Game-Changing Analytics: How IT Executives Can Use Analytics to Create Innovation and Business Success

Game-Changing Analytics: How IT Executives Can Use Analytics to Create Innovation and Business Success

Today's competitive advantage requires a deeper understanding of your business, your market and your customers. As an IT executive, you can drive that knowledge transformation. In this white paper, learn how to make decisions as a strategic business leader and three steps to begin an analytics initiative within your enterprise.

Data Visualization Techniques: From Basics to Big Data with SAS Visual Analytics

Data Visualization Techniques: From Basics to Big Data with SAS Visual Analytics

High-performance data visualization turns sophisticated analyses into meaningful graphics, leading to faster and smarter decision making. In this white paper, learn how visual analytics can transform big data, with additional features such as real-time functionality, mobile compatibility, robust applications for technical groups and accessibility for nontechnical users.

Big Data: Lessons from the Leaders

Big Data: Lessons from the Leaders

Financial performance, competitive advantage, operational efficiency, strategic decision making - every business goal can extract value from big data, and the time for doubt or inaction has long passed. In this Economist Intelligence Unit report, in-depth interviews with data pioneers reveal the link between the effective use of big data and the bottom line among other results.

Decision-Driven Data Management: A Strategy for Better Decisions with Better Data

Decision-Driven Data Management: A Strategy for Better Decisions with Better Data

Which came first, the data or the decision? This white paper makes the case for having a decision in mind, then tailoring big data's volume, variety and velocity to achieve business results such as overcoming customer dissatisfaction or creating well-informed strategies in real time.

Informationweek Reports

Research: The Big Data Management Challenge

Research: The Big Data Management Challenge

The challenge of big data is real, but most organizations don't differentiate 'big data' from traditional data, and nearly 90% of respondents to our survey use conventional databases as the primary means of handling data. We'll help you understand what constitutes big data (it's not just size) and the numerous management challenges it poses.