Broadcom 250-580 Exam Dumps

In the Discovery phase of a cyber attack, attackers attempt to map the network, identify vulnerabilities, and gather information. Firewall and Intrusion Prevention System (IPS) are the most effective security controls to mitigate threats associated with this phase:

Firewall: The firewall restricts unauthorized network access, blocking suspicious or unexpected traffic that could be part of reconnaissance efforts.

IPS: Intrusion Prevention Systems detect and prevent suspicious traffic patterns that might indicate scanning or probing activity, which are common in the Discovery phase.

Together, these controls limit attackers' ability to explore the network and identify potential vulnerabilities.

In Symantec Endpoint Protection, the Discovery Agent designation is assigned to a computer responsible for identifying unmanaged devices within a network. This role is crucial for discovering endpoints that lack protection or are unmanaged, allowing the administrator to deploy agents or take appropriate action. Configuring a Discovery Agent facilitates continuous monitoring and helps ensure that all devices on the network are recognized and managed.

The Restricted Administrator role in the Integrated Cyber Defense Manager (ICDm) has the most limited permissions among the default roles. This role is intended for users who need access to basic functionality without any critical or high-level administrative capabilities, ensuring a lower risk of accidental or unauthorized changes.

Role of Restricted Administrator:

Restricted Administrators have highly constrained access, typically limited to viewing specific information and performing minimal actions.

Why Other Roles Are Incorrect:

Endpoint Console Domain Administrator (Option A) and Server Administrator (Option B) have broader permissions to manage endpoint settings and server configurations.

Limited Administrator (Option D) has more permissions than Restricted Administrator, though still not full access.

The Advanced Machine Learning feature in Symantec Endpoint Security (SES) uses a sophisticated model trained on a large dataset of known good and known bad files to detect malware effectively. Here's how it functions:

Training Model: The model is built from extensive data on benign and malicious files, allowing it to discern patterns that indicate a file's potential harm.

Predictive Malware Detection: Advanced Machine Learning can detect new and evolving malware strains without relying solely on traditional signature-based methods, offering proactive protection.

Real-Time Decision Making: When SES encounters a file, it consults this model to predict whether the file is likely harmful, enabling quick response to potential threats.

This feature strengthens SES's ability to detect malware dynamically, enhancing endpoint security through intelligent analysis of file attributes.

When creating a block list entry in Symantec Endpoint Detection and Response (SEDR), the SHA256 hash is a valid file attribute. SHA256 uniquely identifies files based on their content, making it a reliable attribute for ensuring that specific files, regardless of their names or creation dates, are accurately blocked. This hashing method helps prevent identified malicious files from executing, regardless of their locations or renaming attempts by attackers.