Blacklist (computing) explained

In computing, a blacklist, disallowlist, blocklist, or denylist is a basic access control mechanism that allows through all elements (email addresses, users, passwords, URLs, IP addresses, domain names, file hashes, etc.), except those explicitly mentioned. Those items on the list are denied access. The opposite is a whitelist, allowlist, or passlist, in which only items on the list are let through whatever gate is being used. A greylist contains items that are temporarily blocked (or temporarily allowed) until an additional step is performed.

Blacklists can be applied at various points in a security architecture, such as a host, web proxy, DNS servers, email server, firewall, directory servers or application authentication gateways. The type of element blocked is influenced by the access control location.[1] DNS servers may be well-suited to block domain names, for example, but not URLs. A firewall is well-suited for blocking IP addresses, but less so for blocking malicious files or passwords.

Example uses include a company that might prevent a list of software from running on its network, a school that might prevent access to a list of websites from its computers, or a business that wants to ensure their computer users are not choosing easily guessed, poor passwords.

Examples of systems protected

Blacklists are used to protect a variety of systems in computing. The content of the blacklist is likely needs to be targeted to the type of system defended.[2]

Information systems

An information system includes end-point hosts like user machines and servers. A blacklist in this location may include certain types of software that are not allowed to run in the company environment. For example, a company might blacklist peer to peer file sharing on its systems. In addition to software, people, devices and Web sites can also be blacklisted.[3]

Email

Most email providers have an anti-spam feature that essentially blacklists certain email addresses if they are deemed unwanted. For example, a user who wearies of unstoppable emails from a particular address may blacklist that address, and the email client will automatically route all messages from that address to a junk-mail folder or delete them without notifying the user.

An e-mail spam filter may keep a blacklist of email addresses, any mail from which would be prevented from reaching its intended destination. It may also use sending domain names or sending IP addresses to implement a more general block.

In addition to private email blacklists, there are lists that are kept for public use, including:

Web browsing

The goal of a blacklist in a web browser is to prevent the user from visiting a malicious or deceitful web page via filtering locally. A common web browsing blacklist is Google's Safe Browsing, which is installed by default in Firefox, Safari, and Chrome.

Usernames and passwords

Blacklisting can also apply to user credentials. It is common for systems or websites to blacklist certain reserved usernames that are not allowed to be chosen by the system or website's user populations. These reserved usernames are commonly associated with built-in system administration functions. Also usually blocked by default are profane words and racial slurs.

Password blacklists are very similar to username blacklists but typically contain significantly more entries than username blacklists. Password blacklists are applied to prevent users from choosing passwords that are easily guessed or are well known and could lead to unauthorized access by malicious parties. Password blacklists are deployed as an additional layer of security, usually in addition to a password policy, which sets the requirements of the password length and/or character complexity. This is because there are a significant number of password combinations that fulfill many password policies but are still easily guessed (i.e., Password123, Qwerty123).

Distribution methods

Blacklists are distributed in a variety of ways. Some use simple mailing lists. A DNSBL is a common distribution method that leverages the DNS itself. Some lists make use of rsync for high-volume exchanges of data.[6] Web-server functions may be used; either simple GET requests may be used or more complicated interfaces such as a RESTful API.

Examples

Usage considerations

As expressed in a recent conference paper focusing on blacklists of domain names and IP addresses used for Internet security, "these lists generally do not intersect. Therefore, it appears that these lists do not converge on one set of malicious indicators."[8] [9] This concern combined with an economic model[10] means that, while blacklists are an essential part of network defense, they need to be used in concert with whitelists and greylists.

External links

Notes and References

  1. Book: Introduction to Information Security: A Strategic-Based Approach. Newnes. 2013-11-12. 9781597499729. en. Timothy. Shimeall. Jonathan. Spring.
  2. Web site: Domain Blacklist Ecosystem - A Case Study. insights.sei.cmu.edu. 17 June 2015 . 2016-02-04.
  3. Book: Rainer, Watson. Introduction to Information Systems. 2012. Wiley Custom Learning Solutions. 978-1-118-45213-4.
  4. Web site: 反垃圾邮件联盟 . 2015-08-10 . https://web.archive.org/web/20150811034525/http://www.anti-spam.org.cn/?locale=en_US . 2015-08-11 . dead .
  5. Web site: Fabelsources - Blacklist.
  6. Web site: Guidelines. www.surbl.org. 2016-02-04.
  7. Web site: B.I.S.S. Forums - FAQ - Questions about the Blocklists . Bluetack Internet Security Solutions . dead . https://web.archive.org/web/20081020052855/http://www.bluetack.co.uk/forums/index.php?autocom=faq&CODE=02&qid=18 . 2008-10-20 . 2015-08-01 .
  8. Book: 2015-01-01. 13–22. Leigh. Metcalf. Jonathan M.. Spring. Proceedings of the 2nd ACM Workshop on Information Sharing and Collaborative Security . Blacklist Ecosystem Analysis . 10.1145/2808128.2808129. 9781450338226. 4720116.
  9. Book: Springer International Publishing. 2014-09-17. 9783319113784. 1–21. Lecture Notes in Computer Science. 10.1007/978-3-319-11379-1_1. en. Marc. Kührer. Christian. Rossow. Thorsten. Holz. Research in Attacks, Intrusions and Defenses . Paint It Black: Evaluating the Effectiveness of Malware Blacklists . 8688 . 12276874. Angelos. Stavrou. Herbert. Bos. Georgios. Portokalidis.
  10. Spring. Jonathan M.. 2013-09-17. Modeling malicious domain name take-down dynamics: Why eCrime pays. 2013 ECrime Researchers Summit (eCRS 2013). https://ieeexplore.ieee.org/xpl/conhome/6802823/proceeding. IEEE. 1–9. 10.1109/eCRS.2013.6805779. 978-1-4799-1158-5. 10.1.1.645.3543. 8812531.