This article contains possible Incident Responder interview questions and answers. However, before proceeding, ensure that you have considered the following questions/points.
In general, an incident is a violation of computer security policies, acceptable use policies, or standard computer security practices. Examples of incidents include:
Incident handling is the process of detecting, analyzing, and limiting the impact of incidents. For example, if an attacker breaks into a system via the Internet, the incident handling process should detect the breach. Incident handlers will then analyze the data and determine the level of severity of the attack. The incident will then be prioritized, and the incident handlers will take appropriate action to ensure that the progress of the incident is stopped and that the affected systems are returned to normal operation as quickly as possible.
The NIST Incident Response Lifecycle divides incident response down into four main phases: Preparation; Detection and Analysis; Containment, Eradication, and Recovery; and Post-Event Activity.
Incidents can be classified based on severity, impact, and likelihood of occurrence. Prioritization should consider factors such as potential damage, criticality of affected systems, and regulatory requirements.
Common sources include intrusion detection systems (IDS), security information, and event management (SIEM) solutions, antivirus software, firewalls, and user reports.
Common indicators include unusual network traffic patterns, unauthorized access attempts, unexpected system behavior, and malware infections.
An event is any observable occurrence in a system or network, while an incident is an event that has a negative impact on the confidentiality, integrity, or availability of information or IT services.
Indicators of compromise (IOCs) are artifacts or behaviors that indicate the presence of a security incident or compromise. These can include IP addresses, domain names, file hashes, registry keys, and network traffic patterns. IOCs are used to detect, investigate, and remediate security incidents.
Indicators of Attack (IOAs) are behavioral patterns or forensic artifacts observed within an organization's network or systems that suggest the presence of an active cyber attack. These indicators focus on detecting the tactics, techniques, and procedures (TTPs) used by attackers during different stages of an attack. Unlike Indicators of Compromise (IOCs), which are based on known patterns of malicious activity, IOAs provide insights into ongoing or potential attacks based on observed behaviors rather than predefined signatures or patterns. While IOCs are reactive and often indicate that a compromise has already occurred, IOAs enable proactive threat detection and response by identifying suspicious activities that indicate an attack is in progress.
An indicator of compromise (IOC) is any observable evidence or artifact that may indicate an ongoing or past security incident, such as suspicious network traffic patterns, unauthorized file modifications, or unusual system behavior. A signature is a specific pattern or characteristic associated with a known threat or vulnerability that can be used to detect and block malicious activity, often implemented in intrusion detection and prevention systems (IDS/IPS).
Proactive incident response involves implementing preventive measures and proactive monitoring to identify and mitigate security risks before they escalate into incidents. Reactive incident response, on the other hand, focuses on responding to security incidents after they have occurred, including detection, analysis, containment, eradication, and recovery activities.
Root cause analysis, sometimes referred to as RCA, is a formal effort to identify and document the root cause of an incident and then take preventative steps to ensure that the same problem doesn't happen again.
Packet analysis involves examining network packets to understand communication patterns, identify anomalies, and detect malicious activity. Tools such as Wireshark and tcpdump are commonly used to capture and analyze packets.
A command-and-control (C2) server is a remote server used by attackers to send commands to compromised systems and exfiltrate stolen data. Detecting and blocking C2 communications is critical for disrupting an attacker's control over compromised systems and preventing further data exfiltration or malicious activity. Techniques for detecting and blocking C2 communications include network traffic analysis, intrusion detection and prevention systems (IDPS), and endpoint security controls.
Intrusion detection involves monitoring network traffic and system logs for signs of unauthorized access, malicious activity, or security policy violations. Intrusion detection systems (IDS) analyze network traffic patterns and behavior to identify potential security threats and alert security teams in real time. IDS plays a crucial role in early threat detection, incident triage, and response coordination.
A honeypot is a decoy system or network designed to attract and deceive attackers, allowing security teams to observe and analyze their tactics, techniques, and procedures (TTPs). By deploying honeypots, organizations can gather threat intelligence, identify emerging attack trends, and improve incident response capabilities. By luring attackers away from critical systems, honeypots help reduce the risk of actual compromise and provide valuable insights for proactive threat mitigation.
Event log analysis involves establishing baseline behavior, identifying anomalies, and prioritizing alerts based on severity. Automated tools and correlation rules are used to streamline the analysis process. Once an incident is detected, further investigation, evidence gathering, and response actions are taken.
You can follow the Event Log Analysis course to get more details.
Methods for identifying anomalous activity in Windows event logs include focusing on critical events such as failed login attempts, account modifications, and privilege changes. Custom alerts and filters are created to quickly identify suspicious patterns that indicate security incidents, such as brute force attacks or data exfiltration attempts.
Event log correlation is essential for identifying relationships and patterns across multiple data sources. Correlating logs from multiple sources such as servers, endpoints, firewalls, and IDS/IPS systems provides a comprehensive view of security events. Correlation rules and SIEM platforms automate this process, facilitating real-time detection and response to security incidents.
When dealing with manipulated or altered logs, it is crucial to rely on backup and archival systems to preserve the original log data for forensic analysis. Tamper-evident logging mechanisms and log integrity monitoring using cryptographic hashes or digital signatures are implemented. Network-based logging and log forwarding to secure off-site locations also reduce the risk of tampering.
An example: Analysis of firewall logs and correlation with Windows event logs from the affected servers identified a compromised user account being used to exfiltrate data to an external IP address. Unauthorized access attempts and suspicious file transfers revealed by event log analysis led to the discovery and remediation of the breach before significant data loss occurred.
A timeline created during a digital forensics investigation is crucial for incident response because it helps reconstruct the sequence of events leading up to and during a security incident. By correlating timestamps from various sources such as system logs, network traffic, and user activity, the timeline provides insight into the attacker's actions, the timeline of the incident, and the affected systems. This information is invaluable for understanding the scope of the incident, identifying potential evidence, and formulating an effective response strategy.
Triage in digital forensics is similar to incident response's initial response phase, focusing on quickly identifying and prioritizing critical evidence while minimizing the impact of the incident. During triage, evidence is prioritized based on factors such as the severity of the incident, the potential impact on business operations, and the relevance to the investigation's objectives. The goal is to collect and preserve essential evidence promptly, allowing for immediate analysis and response actions to mitigate further damage and contain the incident.
Acquiring a forensic image of a digital device is a critical step in both digital forensics and incident response. Best practices include the use of write-blocking hardware or software to prevent alterations to the original data and ensure the integrity of the evidence. Tools such as EnCase, FTK Imager, and dd (Linux command) are commonly used for imaging. During incident response, the rapid acquisition of forensic images allows for the preservation of volatile evidence and facilitates analysis to determine the scope and impact of the incident.
Windows artifacts such as event logs, registry hives, prefetch files, link files (LNK), and user activity logs are commonly analyzed during digital forensics investigations and incident response. Event logs provide a chronological record of system events, while registry hives contain configuration and user data critical for understanding system activity. Prefetch files store metadata about application execution, and link files provide insight into recently accessed files and applications. Analyzing these artifacts helps reconstruct the attacker's actions, identify compromised systems, and determine the extent of the intrusion.
Volatile data collection involves capturing live system information such as running processes, network connections, open files, and system memory. In incident response, volatile data collection provides real-time insights into ongoing attacks, malware behavior, and active network connections. Analysis of volatile data helps identify malicious processes, detect unauthorized access, and gather evidence of attacker activity. By collecting volatile data promptly during incident response, responders can capture critical evidence before it gets lost due to system shutdowns or volatile memory clearing.
