Difference between revisions of "RBL"
| Line 6: | Line 6: | ||
* [https://apwg.org/ the Anti-Phishing Working Group's RBL], | * [https://apwg.org/ the Anti-Phishing Working Group's RBL], | ||
* [https://safebrowsing.google.com/ Google Safe Browsing], | * [https://safebrowsing.google.com/ Google Safe Browsing], | ||
| − | * [http://www.surbl.org/ SURBL], | + | * [http://www.surbl.org/ SURBL]'s feed is composed of domain names in unsolicited email messages and external blacklists, which are categorized into lists of phishing, malware, or spam activity.<ref>[http://www.surbl.org/lists Lists, SURBL]</ref> |
* [https://www.threatstop.com/ ThreatStop] | * [https://www.threatstop.com/ ThreatStop] | ||
* [[OpenPhish]], | * [[OpenPhish]], | ||
| Line 13: | Line 13: | ||
* [[URLHaus]], | * [[URLHaus]], | ||
* [[ThreatFox]], and | * [[ThreatFox]], and | ||
| − | * [[Spamhaus]]'s blocklist provides malicious domains obtained from URLs enumerated in spam email payloads, spammers, phishing, malware-related websites, or suspicious domain names that share patterns with domains involved in technical or content abuse.<ref>[https://www.spamhaus.org/ | + | * [[Spamhaus]]'s blocklist provides malicious domains obtained from URLs enumerated in spam email payloads, spammers, phishing, malware-related websites, or suspicious domain names that share patterns with domains involved in technical or content abuse.<ref>[https://www.spamhaus.org/dbl/ Spamhaus DBL]</ref> |
==History== | ==History== | ||
Revision as of 16:52, 4 February 2022
Reputation Block Lists, or RBLs, are lists of Domain Names, Universal Resource Locators (URLs), and/or Internet Protocol (IP) addresses that have been identified as posing security threats.[1] DNS reputation systems can detect malicious domains at the registration time (with PREDATOR) or domain activity phase (with EXPOSURE). They classify domains as either malicious or benign; however, they do not consider compromised domains. The blocklists represent activity such as spam, malware distribution, command-and-control, phishing, and/or intellectual property rights infringement. Intermediaries, such as internet service providers, use them to block malicious communications.
Overview
Commercial service providers, researchers, and non-profit organizations operate the most prominent RBLs that detect or receive notifications of security threats. Examples include:
- Cisco’s Talos email reputation system,
- the Anti-Phishing Working Group's RBL,
- Google Safe Browsing,
- SURBL's feed is composed of domain names in unsolicited email messages and external blacklists, which are categorized into lists of phishing, malware, or spam activity.[2]
- ThreatStop
- OpenPhish,
- PhishTank,
- Abuse.ch,
- URLHaus,
- ThreatFox, and
- Spamhaus's blocklist provides malicious domains obtained from URLs enumerated in spam email payloads, spammers, phishing, malware-related websites, or suspicious domain names that share patterns with domains involved in technical or content abuse.[3]
History
With the advent of email, email administrators began creating and sharing blocklists, which gave rise to some cases of false positives, which led to their creating a list of exceptions, known as allowlists.[4] In the early days, in some circles today, these lists were called blacklists and whitelists, but the racial implications of those terms, among many others, have led people to switch to block/allow.[5]
Then, in 1997 Paul Rand and Paul Vixie used the DNS protocol to access a blocklist to see whether a sending IP address had sent spam recently, and trademarked "Real-time Blackhole List" to refer to the blocklist. ISPs followed suit, which led to finer-tuned descriptions of the legitimacy of an IP address.[6]
In 2010, the Internet Research Task Force released Request for Comments 5782 in acknowledgment of network managers worldwide using DNSxLs (DNS block or allow lists) to filter traffic and to make sure such managers were on the same page as to the structure and usage of DNSxLs and the protocol to query them.[7]
As of April 2021, Intra2net's Blacklist Monitor ranked Distributed Checksum Clearinghouses or (DCC) as showing the highest rate of accuracy in filtering spam.[8]