What are examples of evidence of compromises from inside network in conjunction with Bot- infected systems?

An active bot infection on an internal system generates specific network traffic that serves as evidence of compromise. This includes outbound communication attempts from the infected host to a remote Command and Control (C&C) server, which is how the bot receives instructions. Furthermore, many modern bots use Domain Generation Algorithms (DGA) to locate their C&C servers, leading to a high volume of DNS queries for non-existent or rapidly changing domains. This combination of outbound C&C traffic and anomalous DNS activity are hallmark indicators of a bot-infected system operating from within the network.

B. This describes a SYN flood, a type of Denial-of-Service attack. The traffic is inbound from external sources, not evidence of a compromise originating from inside.
C. A security audit report showing missing patches indicates vulnerabilities or weaknesses. It is a precursor to a potential compromise, not evidence that one has already occurred.
D. An IPS alert for a blocked external attack shows a successful prevention action against an external threat, not an active, successful compromise originating from an internal host.

1. Check Point R81.10 Threat Prevention Administration Guide, "Anti-Bot" Chapter, Page 1. The guide states, "The Anti-Bot Software Blade detects bot-infected machines, prevents bot damages by blocking bot C&C (Command and Control) communications...". This confirms that C&C communication is the primary indicator detected.

2. Check Point Security Administration R81.10 Guide, "The Check Point Solution" Chapter, "Threat Prevention" Section. It describes how the Anti-Bot blade provides "post-infection detection" by identifying communications between infected clients and C&C centers.

3. Alauthaman, M., Al-Tawil, M., Al-Saba, M., & Al-Hadramy, S. (2021). "A Comprehensive Survey on Botnet Detection and Classification". IEEE Access, 9, 161239-161272. Section IV-A, "DNS-Based Detection," details how anomalous DNS query patterns, such as those generated by DGAs, are a key method for identifying botnet activity. https://doi.org/10.1109/ACCESS.2021.3125380

4. MIT OpenCourseWare, 6.858 Computer Systems Security, Fall 2014. Lecture 15, "Malware," discusses the architecture of botnets, emphasizing the critical role of the C&C channel for command dissemination and how monitoring for this traffic is a primary detection strategy.