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Removes outdated section (#6635)
* Removes outdated section * removes broken link
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docs/detections/detection-engine-intro.asciidoc

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@@ -84,52 +84,8 @@ In addition, the following support restrictions are in place:
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<<detections-permissions-section>> provides detailed information on all the
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permissions required to initiate and use the Detections feature.
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[discrete]
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[[malware-prevention]]
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== Malware prevention
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Malware, short for malicious software, is any software program designed to damage or execute unauthorized actions on a
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computer system. Examples of malware include viruses, worms, Trojan horses, adware, scareware, and spyware. Some
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malware, such as viruses, can severely damage a computer's hard drive by deleting files or directory information. Other
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malware, such as spyware, can obtain user data without their knowledge.
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Malware may be stealthy and appear as legitimate executable code, scripts, active content, and other software. It is also
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often embedded in non-malicious files, non-suspicious websites, and standard programs — sometimes making the root
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source difficult to identify. If infected and not resolved promptly, malware can cause irreparable damage to a computer
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network.
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For information on how to enable malware protection on your host, see <<malware-protection, Malware Protection>>.
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[discrete]
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[[machine-learning-model]]
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=== Machine learning model
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To determine if a file is malicious or benign, a machine learning model looks for static attributes of files (without executing
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the file) that include file structure, layout, and content. This includes information such as file header data, imports, exports,
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section names, and file size. These attributes are extracted from millions of benign and malicious file samples, which then
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are passed to a machine-learning algorithm that distinguishes a benign file from a malicious one. The machine learning
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model is updated as new data is procured and analyzed.
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[discrete]
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=== Threshold
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A malware threshold determines the action the agent should take if malware is detected. The Elastic Agent uses a recommended threshold level that generates a balanced number of alerts with a low probability of undetected malware. This threshold also minimizes the number of false positive alerts.
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[discrete]
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[[ransomware-prevention]]
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== Ransomware prevention
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Ransomware is computer malware that installs discreetly on a user's computer and encrypts data until a specified amount of money (ransom) is paid. Ransomware is usually similar to other malware in its delivery and execution, infecting systems
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through spear-phishing or drive-by downloads. If not resolved immediately, ransomware can cause irreparable damage to an entire computer network.
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Behavioral ransomware prevention on the Elastic Endpoint detects and stops ransomware attacks on Windows systems by analyzing data from low-level system processes, and is effective across an array of widespread ransomware families — including those targeting the system’s master boot record.
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For information on how to enable ransomware protection on your host, see <<ransomware-protection>>.
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NOTE: Ransomware prevention is a paid feature and is enabled by default if you have a https://www.elastic.co/pricing[Platinum or Enterprise license].
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[float]
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=== Resolve UI error messages
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== Resolve UI error messages
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Depending on your privileges and whether detection system indices have already
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been created for the {kib} space, you might get one of these error messages when you

docs/getting-started/configure-integration-policy.asciidoc

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[[malware-protection]]
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== Malware protection
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{elastic-defend} malware prevention detects and stops malicious attacks by using a <<machine-learning-model, machine learning model>>
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{elastic-defend} malware prevention detects and stops malicious attacks by using a machine learning model
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that looks for static attributes to determine if a file is malicious or benign.
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By default, malware protection is enabled on Windows, macOS, and Linux hosts.

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