For more information on how to respond to the Log4j vulnerabilities using Splunk products, please see our Log4Shell response overview page. Like most cybersecurity teams, the Splunk Threat Research Team (STRT) has been heads-down attempting to understand, simulate, and detect the Log4j attack vector. This post shares detection opportunities STRT found in different stages of successful Log4Shell exploitation.
Is it just me or is the announcement of a significant CVE becoming a holiday tradition? Discovered on December 9, 2021 by Minecraft players, the Apache Log4Shell vulnerability is a uniquely insidious because it infects servers which are traditionally well insulated from attacks and perceived as unreachable by an intruder and not at risk for CVEs. Log4Shell is an entirely different can of works that proves this assumption wrong.
We recently discussed some methods for detecting the Log4j exploit, and we’ve now developed another method that everyone running Zeek® or a Corelight sensor can use. Our new approach is based on the rarity of legitimate downloads of Java via LDAP. Zeek does not currently have a native LDAP protocol analyzer (though one is available if you are running Spicy). This will not stop you from detecting this exploit downloading Java over LDAP, though. To see how, read on.
In quick succession in December, The Apache Software Foundation released information on two critical vulnerabilities in its Log4j Java-based library. The first vulnerability CVE-2021-44228, also known as Log4Shell or LogJam, was reported as an unauthenticated remote code execution (RCE) vulnerability. By exploiting how the library logs error messages, it could lead to a complete system takeover.
The United States Department of Homeland Security (DHS) is inviting security researchers to uncover vulnerabilities and hack into its systems, in an attempt to better protect itself from malicious attacks.
Log4Shell is a high severity vulnerability (CVE-2021-44228) impacting Apache Log4j versions 2.0 to 2.14.1. It was discovered by Chen Zhaojun of Alibaba Cloud Security Team and disclosed via the project´s GitHub repository on December 9, 2021.
