Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
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This query calculates device uptime based on periodic DeviceInfo which is recorded every 15 minutes regardless of device's network connectivity and uploaded once device gets online. If its interval is over 16 minutes, we can consider device is turned off.Calculated uptime may include up to 30 minutes gap. Devices may be turned on up to 15 minutes earlier than the "timestamp", and may be turned off up to 15 minutes later than the "LastTimestamp". When the single independent DeviceInfo without any sequential DeviceInfo within 16 minutes before or after is recorded, "DurationAtLeast" will be displayed as "00.00:00:00".
Query #1 - Find the machines on which this file was seen.
TODO - set file hash to be a SHA1 hash of your choice...
TODO - set file hash to be a SHA1 hash of your choice...
This query uses the public MDE GitHub repo as a source to estimate the time that an agent build remains supported
based on the time it was uploaded. Please note that the timestamps used in this query are meant to estimate the
support period and will likely not represent the actual expiration of the package which will be based on the build.
If you would like an estimate of support, uncomment the extend statement to get an idea of what is \ is not
supported and an idea of how long support will remain for current agents.
This query currently only supports GA builds, not preview builds.
based on the time it was uploaded. Please note that the timestamps used in this query are meant to estimate the
support period and will likely not represent the actual expiration of the package which will be based on the build.
If you would like an estimate of support, uncomment the extend statement to get an idea of what is \ is not
supported and an idea of how long support will remain for current agents.
This query currently only supports GA builds, not preview builds.
wifikeys
KQL
Detect if someone run netsh and try to expose WPA keys in clear text
@mattiasborg82.
Blog.sec-labs.com.
@mattiasborg82.
Blog.sec-labs.com.
Find devices connected to a monitored network.
Please Note line 5 needs to have a monitored network name put in place or commented out to pull everything.
Please Note line 5 needs to have a monitored network name put in place or commented out to pull everything.
Looking for high volume queries against a given RemoteIP, per DeviceName, RemotePort and Process.
Please change the Timestamp window according your preference/objective, as also the subnet ranges that you want to analyze against.
Please change the Timestamp window according your preference/objective, as also the subnet ranges that you want to analyze against.
This query searches for not onboarded devices with a specific Suffix
This query will count the number of devices in Defender ATP based
on their DNS suffix. For a full list of devices with the DNS
suffix, comment out or remove the last line.
on their DNS suffix. For a full list of devices with the DNS
suffix, comment out or remove the last line.
'This hunting query identifies users joining a meeting from a time zone that a user has not been observed from in the last 30 days.'
List alerts flagging attempts to delete backup files.
One of the challenges in making an AppLocker policy is knowing where applications
launch from. This query normalizes process launch paths through aliasing, then
counts the number of processes launched from that path, how many distinct machines it
was launched on, and how many distinct file names \ hashes these processes had. The
path is broken into subfolders to help simplify analysis.
launch from. This query normalizes process launch paths through aliasing, then
counts the number of processes launched from that path, how many distinct machines it
was launched on, and how many distinct file names \ hashes these processes had. The
path is broken into subfolders to help simplify analysis.
Services
KQL
Gets the service name from the registry key.
Surfaces suspicious spoolsv.exe behavior likely related to CVE-2021-1675
Original Sigma Rule: https://github.com/Neo23x0/sigma/blob/master/rules/apt/apt_sofacy_zebrocy.yml.
Questions via Twitter: @janvonkirchheim.
Questions via Twitter: @janvonkirchheim.
The query checks for suspicious Tomcat process launches associated with likely exploitation of Confluence - CVE-2022-26134
Read more here:.
https://confluence.atlassian.com/doc/confluence-security-advisory-2022-06-02-1130377146.html
https://nvd.nist.gov/vuln/detail/CVE-2022-26134
Tags: #exploit #CVE-2022-26134
Read more here:.
https://confluence.atlassian.com/doc/confluence-security-advisory-2022-06-02-1130377146.html
https://nvd.nist.gov/vuln/detail/CVE-2022-26134
Tags: #exploit #CVE-2022-26134
'This detection highlights executables deployed to hosts via either the Default Domain or Default Domain Controller Policies. These policies apply to all hosts or Domain Controllers and best practice is that these policies should not be used for deployment of files.
A threat actor may use these policies to deploy files or scripts to all hosts in a domain.
This query uses the ASIM parsers and will need them deployed before usage - https://docs.microsoft.com/azure/sentinel/normalization'
A threat actor may use these policies to deploy files or scripts to all hosts in a domain.
This query uses the ASIM parsers and will need them deployed before usage - https://docs.microsoft.com/azure/sentinel/normalization'
This query was originally published in a threat analytics report about the group known to other security researchers as APT32 or OceanLotus
This tracked activity group uses a wide array of malicious documents to conduct attacks. Some of their favored techniques include sideloading dynamic link libraries, and disguising payloads as image files.
The following query detects network activity that may indicate an attack by this group.
See Detect malicious documents associated with group known as "OceanLotus" for another query related to this group's activity.
This tracked activity group uses a wide array of malicious documents to conduct attacks. Some of their favored techniques include sideloading dynamic link libraries, and disguising payloads as image files.
The following query detects network activity that may indicate an attack by this group.
See Detect malicious documents associated with group known as "OceanLotus" for another query related to this group's activity.
This query was originally published in the threat analytics report, Qakbot blight lingers, seeds ransomware
Qakbot is malware that steals login credentials from banking and financial services. It has been deployed against small businesses as well as major corporations. Some outbreaks have involved targeted ransomware campaigns that use a similar set of techniques. Links to related queries are listed under See also.
The following query detects possible use of the system process, esentutl.exe, to look through a user's browser history and steal cookies.
Reference - https://www.microsoft.com/security/blog/2017/11/06/mitigating-and-eliminating-info-stealing-qakbot-and-emotet-in-corporate-networks/
Qakbot is malware that steals login credentials from banking and financial services. It has been deployed against small businesses as well as major corporations. Some outbreaks have involved targeted ransomware campaigns that use a similar set of techniques. Links to related queries are listed under See also.
The following query detects possible use of the system process, esentutl.exe, to look through a user's browser history and steal cookies.
Reference - https://www.microsoft.com/security/blog/2017/11/06/mitigating-and-eliminating-info-stealing-qakbot-and-emotet-in-corporate-networks/
'Provides the Security Intelligence version and total count of up to date devices, not up to date devices and count of devices whose status is not available relevant to the security intelligence version.'
Dragon Fly
KQL
Original Sigma Rule: https://github.com/Neo23x0/sigma/blob/master/rules/apt/apt_dragonfly.yml.
Questions via Twitter: @janvonkirchheim.
Questions via Twitter: @janvonkirchheim.
This query was originally published in a threat analytics report about the group known to other security researchers as APT32 or OceanLotus
This tracked activity group uses a wide array of malicious documents to conduct attacks. Some of their favorite techniques include sideloading dynamic link libraries, and disguising payloads as image files. The group has weaponized files with exploits for the following vulnerabilities:
1. CVE-2017-11882 - Software update
2. CVE-2017-0199 - Software update
The following query detects known malicious files associated with the group's campaigns.
See Detect malicious network activity associated with group known as "OceanLotus" for another query related to this group's activity.
This tracked activity group uses a wide array of malicious documents to conduct attacks. Some of their favorite techniques include sideloading dynamic link libraries, and disguising payloads as image files. The group has weaponized files with exploits for the following vulnerabilities:
1. CVE-2017-11882 - Software update
2. CVE-2017-0199 - Software update
The following query detects known malicious files associated with the group's campaigns.
See Detect malicious network activity associated with group known as "OceanLotus" for another query related to this group's activity.
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