NIST Recommends Some Common-Sense Password Rules

NIST’s second draft of its “SP 800-63-4“—its digital identify guidelines—finally contains some really good rules about passwords:

The following requirements apply to passwords:

  1. lVerifiers and CSPs SHALL require passwords to be a minimum of eight characters in length and SHOULD require passwords to be a minimum of 15 characters in length.
  2. Verifiers and CSPs SHOULD permit a maximum password length of at least 64 characters.
  3. Verifiers and CSPs SHOULD accept all printing ASCII [RFC20] characters and the space character in passwords.
  4. Verifiers and CSPs SHOULD accept Unicode [ISO/ISC 10646] characters in passwords. Each Unicode code point SHALL be counted as a signgle character when evaluating password length.

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The State of Ransomware

Palo Alto Networks published its semi-annual report on ransomware. From the Executive Summary:

Unit 42 monitors ransomware and extortion leak sites closely to keep tabs on threat activity. We reviewed compromise announcements from 53 dedicated leak sites in the first half of 2024 and found 1,762 new posts. This averages to approximately 294 posts a month and almost 68 posts a week. Of the 53 ransomware groups whose leak sites we monitored, six of the groups accounted for more than half of the compromises observed.

In February, we reported a 49% increase year-over-year in alleged victims posted on ransomware leak sites. So far, in 2024, comparing the first half of 2023 to the first half of 2024, we see an even further increase of 4.3%. The higher level of activity observed in 2023 was no fluke…

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People-Search Site Removal Services Largely Ineffective

Consumer Reports has a new study of people-search site removal services, concluding that they don’t really work:

As a whole, people-search removal services are largely ineffective. Private information about each participant on the people-search sites decreased after using the people-search removal services. And, not surprisingly, the removal services did save time compared with manually opting out. But, without exception, information about each participant still appeared on some of the 13 people-search sites at the one-week, one-month, and four-month intervals. We initially found 332 instances of information about the 28 participants who would later be signed up for removal services (that does not include the four participants who were opted out manually). Of those 332 instances, only 117, or 35%, were removed within four months…

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On Secure Voting Systems

Andrew Appel shepherded a public comment—signed by twenty election cybersecurity experts, including myself—on best practices for ballot marking devices and vote tabulation. It was written for the Pennsylvania legislature, but it’s general in nature.

From the executive summary:

We believe that no system is perfect, with each having trade-offs. Hand-marked and hand-counted ballots remove the uncertainty introduced by use of electronic machinery and the ability of bad actors to exploit electronic vulnerabilities to remotely alter the results. However, some portion of voters mistakenly mark paper ballots in a manner that will not be counted in the way the voter intended, or which even voids the ballot. Hand-counts delay timely reporting of results, and introduce the possibility for human error, bias, or misinterpretation…

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Facebook’s Extensive Surveillance Network

Consumer Reports is reporting that Facebook has built a massive surveillance network:

Using a panel of 709 volunteers who shared archives of their Facebook data, Consumer Reports found that a total of 186,892 companies sent data about them to the social network. On average, each participant in the study had their data sent to Facebook by 2,230 companies. That number varied significantly, with some panelists’ data listing over 7,000 companies providing their data. The Markup helped Consumer Reports recruit participants for the study. Participants downloaded an archive of the previous three years of their data from their Facebook settings, then provided it to Consumer Reports…

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Breaking Laptop Fingerprint Sensors

They’re not that good:

Security researchers Jesse D’Aguanno and Timo Teräs write that, with varying degrees of reverse-engineering and using some external hardware, they were able to fool the Goodix fingerprint sensor in a Dell Inspiron 15, the Synaptic sensor in a Lenovo ThinkPad T14, and the ELAN sensor in one of Microsoft’s own Surface Pro Type Covers. These are just three laptop models from the wide universe of PCs, but one of these three companies usually does make the fingerprint sensor in every laptop we’ve reviewed in the last few years. It’s likely that most Windows PCs with fingerprint readers will be vulnerable to similar exploits…

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Security Risks of AI

Stanford and Georgetown have a new report on the security risks of AI—particularly adversarial machine learning—based on a workshop they held on the topic.

Jim Dempsey, one of the workshop organizers, wrote a blog post on the report:

As a first step, our report recommends the inclusion of AI security concerns within the cybersecurity programs of developers and users. The understanding of how to secure AI systems, we concluded, lags far behind their widespread adoption. Many AI products are deployed without institutions fully understanding the security risks they pose. Organizations building or deploying AI models should incorporate AI concerns into their cybersecurity functions using a risk management framework that addresses security throughout the AI system life cycle. It will be necessary to grapple with the ways in which AI vulnerabilities are different from traditional cybersecurity bugs, but the starting point is to assume that AI security is a subset of cybersecurity and to begin applying vulnerability management practices to AI-based features. (Andy Grotto and I have vigorously argued …

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