Making passwords expire is an obsolete way of protecting user accounts – and may even be doing more harm that good. Not only do passwords that expire every 30 or 60 days create a headache for users who have to dream up a new one, and remember it, they may not improve security at all.
Now Microsoft has changed its stance, removing the recommendation that passwords should expire after a particular period that was previously part of its security guidelines for Windows 10 and Windows Server. Microsoft announced its intention to dump password expiry when the draft guidance was published, which my colleague Liam Tung wrote about.
As Microsoft explains: “Periodic password expiration is a defense only against the probability that a password (or hash) will be stolen during its validity interval and will be used by an unauthorized entity. If a password is never stolen, there’s no need to expire it. And if you have evidence that a password has been stolen, you would presumably act immediately rather than wait for expiration to fix the problem.” It goes on: “Periodic password expiration is an ancient and obsolete mitigation of very low value.”
Rather than depend on users tweaking passwords (and then writing them on a post-it note) companies should have a broader approach to authentication and security, it says. And it’s not saying that we are not changing requirements for minimum password length, history, or complexity. Taking password expiry out of its baseline means that companies can make their own decisions without being penalised by auditors, the company said.
“By removing it from our baseline rather than recommending a particular value or no expiration, organizations can choose whatever best suits their perceived needs without contradicting our guidance. At the same time, we must reiterate that we strongly recommend additional protections even though they cannot be expressed in our baselines,” it said.
Microsoft has been predicting the death of the password for more than a decade, and recently has been ramping up its efforts to make that come true. It has long argued that passwords are inconvenient, insecure and expensive to businesses. It argues that they should be replaced with multi-form authentication and biometrics (although biometrics have their own issues, too).
Microsoft is hardly alone in making this leap. The UK’s National Cyber Security Center (NCSC) recently published a set of best practices for passwords – warning that a bad strategy for passwords that puts too much pressure on users can make your business less secure, not more.
“Inevitably, users will devise their own coping mechanisms to cope with ‘password overload’. This includes re-using the same password across different systems, using simple and predictable password creation strategies, or writing passwords down where they can be easily found,” it warns.
SEE: Cybersecurity in an IoT and mobile world (ZDNet special report) | Download the report as a PDF (TechRepublic)
NCSC suggests that organisations reduce their reliance on passwords and use single sign-on or biometrics where available (although biometrics in particular come with their own risks). Monitoring password systems for unusual behaviour, using account throttling to defend against brute force attacks, and blacklisting common or guessable passwords are all good practice, it said. Multi-factor authentication for important or vulnerable accounts is good policy too.
But forcing regular password changes harms rather than improves security, it said. Users are likely to choose new passwords that are only minor variations of the old, and in any case a password that is stolen is generally used by hackers immediately, so resetting it up to 90 days later is rather a waste of time.
Despite security experts calling time on password expiration policies, it’s still common across many, if not most, organisations for passwords to expire after a relatively short period of time. Mostly that’s down to organisational inertia – there was a time when changing passwords regularly still seemed like a good idea, and the new approach hasn’t filtered down to the tech security team. There’s also a lot of caution around changing IT policies; nobody wants to be the one to change the status quo and then get blamed when it goes wrong.
But there are lots of companies that rely on an aggressive password expiry policy as pretty much their only defence against accounts being hijacked, whereas in reality security has to go well beyond that. At least for now, passwords still have their place, but making us all come up with new variations every few weeks may soon be a thing of the past.
Cloud Data Security
Data security has become an immutable part of the technology stack for modern applications. Protecting application assets and data against cybercriminal activities, insider threats, and basic human negligence is no longer an afterthought. It must be addressed early and often, both in the application development cycle and the data analytics stack.
The requirements have grown well beyond the simplistic features provided by data platforms, and as a result a competitive industry has emerged to address the security layer. The capabilities of this layer must be more than thorough, they must also be usable and streamlined, adding a minimum of overhead to existing processes.
To measure the policy management burden, we designed a reproducible test that included a standardized, publicly available dataset and a number of access control policy management scenarios based on real world use cases we have observed for cloud data workloads. We tested two options: Apache Ranger with Apache Atlas and Immuta. This study contrasts the differences between a largely role-based access control model with object tagging (OT-RBAC) to a pure attribute-based access control (ABAC) model using these respective technologies.
This study captures the time and effort involved in managing the ever-evolving access control policies at a modern data-driven enterprise. With this study, we show the impacts of data access control policy management in terms of:
- Dynamic versus static
In our scenarios, Ranger alone took 76x more policy changes than Immuta to accomplish the same data security objectives, while Ranger with Apache Atlas took 63x more policy changes. For our advanced use cases, Immuta only required one policy change each, while Ranger was not able to fulfill the data security requirement at all.
This study exposed the limitations of extending legacy Hadoop security components into cloud use cases. Apache Ranger uses static policies in an OT-RBAC model for the Hadoop ecosystem with very limited support for attributes. The difference between it and Immuta’s attribute-based access control model (ABAC) became clear. By leveraging dynamic variables, nested attributes, and global row-level policies and row-level security, Immuta can be quickly implemented and updated in comparison with Ranger.
Using Ranger as a data security mechanism creates a high policy-management burden compared to Immuta, as organizations migrate and expand cloud data use—which is shown here to provide scalability, clarity, and evolvability in a complex enterprise’s data security and governance needs.
The chart in Figure 1 reveals the difference in cumulative policy changes required for each platform configuration.
Figure 1. Difference in Cumulative Policy Changes
The assessment and scoring rubric and methodology is detailed in the report. We leave the issue of fairness for the reader to determine. We strongly encourage you, as the reader, to discern for yourself what is of value. We hope this report is informative and helpful in uncovering some of the challenges and nuances of data governance platform selection. You are encouraged to compile your own representative use cases and workflows and review these platforms in a way that is applicable to your requirements.
GigaOm Radar for Data Loss Prevention
Data is at the core of modern business: It is our intellectual property, the lifeblood of our interactions with our employees, partners, and customers, and a true business asset. But in a world of increasingly distributed workforces, a growing threat from cybercriminals and bad actors, and ever more stringent regulation, our data is at risk and the impact of losing it, or losing access to it, can be catastrophic.
With this in mind, ensuring a strong data management and security strategy must be high on the agenda of any modern enterprise. Security of our data has to be a primary concern. Ensuring we know how, why, and where our data is used is crucial, as is the need to be sure that data does not leave the organization without appropriate checks and balances.
Keeping ahead of this challenge and mitigating the risk requires a multi-faceted approach. People and processes are key, as, of course, is technology in any data loss prevention (DLP) strategy.
This has led to a reevaluation of both technology and approach to DLP; a recognition that we must evolve an approach that is holistic, intelligent, and able to apply context to our data usage. DLP must form part of a broader risk management strategy.
Within this report, we evaluate the leading vendors who are offering solutions that can form part of your DLP strategy—tools that understand data as well as evaluate insider risk to help mitigate the threat of data loss. This report aims to give enterprise decision-makers an overview of how these offerings can be a part of a wider data security approach.
Key Criteria for Evaluating Data Loss Prevention Platforms
Data is a crucial asset for modern businesses and has to be protected in the same way as any other corporate asset, with diligence and care. Loss of data can have catastrophic effects, from reputational damage to significant fines for breaking increasingly stringent regulations.
While the risk of data loss is not new, the landscape we operate in is evolving rapidly. Data can leave data centers in many ways, whether accidental or malicious. The routes for exfiltration also continue to grow, ranging from email, USB sticks, and laptops to ever-more-widely-adopted cloud applications, collaboration tools, and mobile devices. This is driving a resurgence in the enterprise’s need to ensure that no data leaves the organization without appropriate checks and balances in place.
Keeping ahead of this challenge and mitigating the risk requires a multi-faceted approach. Policy, people, and technology are critical components in a data loss prevention (DLP) strategy.
As with any information security strategy, technology plays a significant role. DLP technology has traditionally played a part in helping organizations to mitigate some of the risks of uncontrolled data exfiltration. However, both the technology and threat landscape have shifted significantly, which has led to a reevaluation of DLP tools and strategy.
The modern approach to the challenge needs to be holistic and intelligent, capable of applying context to data usage by building a broader understanding of what the data is, who is using it, and why. Systems in place must also be able to learn when user activity should be classified as unusual so they can better interpret signs of a potential breach.
This advanced approach is also driving new ways of defining the discipline of data loss prevention. Dealing with these risks cannot be viewed in isolation; rather, it must be part of a wider insider risk-management strategy.
Stopping the loss of data, accidental or otherwise, is no small task. This GigaOM Key Criteria Report details DLP solutions and identifies key criteria and evaluation metrics for selecting such a solution. The corresponding GigOm Radar Report identifies vendors and products in this sector that excel. Together, these reports will give decision-makers an overview of the market to help them evaluate existing platforms and decide where to invest.
How to Read this Report
This GigaOm report is one of a series of documents that helps IT organizations assess competing solutions in the context of well-defined features and criteria. For a fuller understanding consider reviewing the following reports:
Key Criteria report: A detailed market sector analysis that assesses the impact that key product features and criteria have on top-line solution characteristics—such as scalability, performance, and TCO—that drive purchase decisions.
GigaOm Radar report: A forward-looking analysis that plots the relative value and progression of vendor solutions along multiple axes based on strategy and execution. The Radar report includes a breakdown of each vendor’s offering in the sector.
Solution Profile: An in-depth vendor analysis that builds on the framework developed in the Key Criteria and Radar reports to assess a company’s engagement within a technology sector. This analysis includes forward-looking guidance around both strategy and product.
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