Paloalto Networks Updated Practitioner Exam Questions and Answers by rae

XDR (Extended Detection and Response) uses machine learning (ML) to detect threats by identifying patterns and anomalies. XDR ingests data from multiple sources — including endpoints, networks, servers, and cloud workloads — to provide a unified and correlated view of threats across the environment.

An encoded string is a common technique used by attackers to obfuscate their malicious code or data. By decoding the string, a security operations engineer can reveal the true nature and intent of the attacker, and potentially discover indicators of compromise (IOCs) such as IP addresses, domain names, file names, etc. Decoding the string can also help the engineer to determine the type and severity of the incident, and the appropriate response actions. Therefore, decoding the string and continuing the investigation is the best option among the given choices. Saving the string to a new file and running it in a sandbox may be risky, as it could execute the malicious code and cause further damage. Running the string against VirusTotal may not yield any useful results, as the string may not be recognized by any antivirus engines. Appending the string to the investigation notes but not altering it may not provide any additional insight into the incident, and may delay the response process. References:

1: SANS Digital Forensics and Incident Response Blog | Strings, Strings, Are Wonderful Things

2: 5 Minute Forensics: Decoding PowerShell Payloads - Tevora

3: Known plaintext analysis of encoded strings - SANS Institute

4: Palo Alto Networks Certified Cybersecurity Entry-level Technician - Palo Alto Networks

5: 10 Palo Alto Networks PCCET Exam Practice Questions - CBT Nuggets

IDSs and IPSs also can be classified as knowledge-based (or signature-based) or behavior-based (or statistical anomaly-based) systems:

● A knowledge-based system uses a database of known vulnerabilities and attack profiles

to identify intrusion attempts. These types of systems have lower false-alarm rates than

behavior-based systems but must be continually updated with new attack signatures to

be effective.

● A behavior-based system uses a baseline of normal network activity to identify unusual

patterns or levels of network activity that may be indicative of an intrusion attempt.

These types of systems are more adaptive than knowledge-based systems and therefore

may be more effective in detecting previously unknown vulnerabilities and attacks, but they have a much higher false-positive rate than knowledge-based systems

Personally identifiable information (PII) is any data that can be used to identify someone. All information that directly or indirectly links to a person is considered PII1. Among PII, some pieces of information are more sensitive than others. Sensitive PII is sensitive information that directly identifies an individual and could cause significant harm if leaked or stolen2. Birthplace and name are examples of sensitive PII, as they can be used to distinguish or trace an individual’s identity, either alone or when combined with other information3. Login 10 and profession are not considered sensitive PII, as they are not unique to a person and do not reveal their identity. Login 10 is a non-sensitive PII that is easily accessible from public sources, while profession is not a PII at all, as it does not link to a specific individual4. References:

1: What is PII (personally identifiable information)? - Cloudflare

2: What is Personally Identifiable Information (PII)? | IBM

3: personally identifiable information - Glossary | CSRC

4: What Is Personally Identifiable Information (PII)? Types and Examples