Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
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'IP addresses of broadband links that usually indicates users attempting to access their home network, for example for a remote session to a home computer.'
This query helps reviewing URL click count by ClickAction
'Detects suspicious user agent strings used by crypto miners in proxy logs.'
Intent:
- Use MTP capability to look for insider threat potential risk indicators
- Indicators would then serve as the building block for insider threat risk modeling in subsequent tools
Definition of Insider Threat:
"The potential for an individual who has or had authorized access to an organization's assets to use their access, either maliciously or unintentionally, to act in a way that could negatively affect the organization."
This collection of queries describes the different indicators that could be used to model and look for patterns suggesting an increased risk of an individual becoming a potential insider threat.
Note: no single indicator should be used as a lone determinant of insider threat activity, but should be part of an overall program to understand the increased risk to your organization's critical assets. This in turn is used to feed an investigation by a formal insider threat program to look at the context associated with the whole person to understand the implication of a set of indicators.
- Use MTP capability to look for insider threat potential risk indicators
- Indicators would then serve as the building block for insider threat risk modeling in subsequent tools
Definition of Insider Threat:
"The potential for an individual who has or had authorized access to an organization's assets to use their access, either maliciously or unintentionally, to act in a way that could negatively affect the organization."
This collection of queries describes the different indicators that could be used to model and look for patterns suggesting an increased risk of an individual becoming a potential insider threat.
Note: no single indicator should be used as a lone determinant of insider threat activity, but should be part of an overall program to understand the increased risk to your organization's critical assets. This in turn is used to feed an investigation by a formal insider threat program to look at the context associated with the whole person to understand the implication of a set of indicators.
To evade security software and analyst tools, Nobelium malware enumerates the target system looking for certain running processes, loaded drivers, and registry keys, with the goal of disabling them.
The Microsoft Defender for Endpoint sensor is one of the processes the malware attempts to disable.
Microsoft Defender for Endpoint has built-in protections against many techniques attackers use to disable endpoint sensors ranging from hardened OS protection, anti-tampering policies, and detections for a variety of tampering attempts, including "Attempt to stop Microsoft Defender for Endpoint sensor", "Tampering with Microsoft Defender for Endpoint sensor settings", or "Possible sensor tampering in memory".
Successfully disabling Microsoft Defender for Endpoint can prevent the system from reporting observed activities.
However, the multitude of signals reported into Microsoft Defender XDR provides a unique opportunity to hunt for systems where the tampering technique used might have been successful.
The following advanced hunting query can be used to locate devices that should be reporting but aren't:
The Microsoft Defender for Endpoint sensor is one of the processes the malware attempts to disable.
Microsoft Defender for Endpoint has built-in protections against many techniques attackers use to disable endpoint sensors ranging from hardened OS protection, anti-tampering policies, and detections for a variety of tampering attempts, including "Attempt to stop Microsoft Defender for Endpoint sensor", "Tampering with Microsoft Defender for Endpoint sensor settings", or "Possible sensor tampering in memory".
Successfully disabling Microsoft Defender for Endpoint can prevent the system from reporting observed activities.
However, the multitude of signals reported into Microsoft Defender XDR provides a unique opportunity to hunt for systems where the tampering technique used might have been successful.
The following advanced hunting query can be used to locate devices that should be reporting but aren't:
'This detection will identify network requests in HTTP proxy data that contains Base64 encoded usernames from machines in the DeviceEvents table.
This technique was seen usee by POLONIUM in their RunningRAT tool.'
This technique was seen usee by POLONIUM in their RunningRAT tool.'
This advanced hunting query detects processes communicating with known Tor relay IP addresses.
The public URL in the query is updated daily at 12PM and 12AM UTC.
CSV source is the Tor Project API, obtained with: https://github.com/Dylan-J/Tor-Project-Statistics
The public URL in the query is updated daily at 12PM and 12AM UTC.
CSV source is the Tor Project API, obtained with: https://github.com/Dylan-J/Tor-Project-Statistics
'Rule helps to detect a rare user-agents indicating web browsing activity by an unusual process other than a web browser.'
This analytic identifies network traffic directed to the Active Directory Web Services Protocol (ADWS) on port 9389. It leverages network traffic logs, focusing on source and destination IP addresses, application names, and destination ports. This activity is significant as ADWS is used to manage Active Directory, and unauthorized access could indicate malicious intent. If confirmed malicious, an attacker could manipulate Active Directory, potentially leading to privilege escalation, unauthorized access, or persistent control over the environment.
Device Network Events Involving Low Count FQDNs.
This query reduces network events to only those with the RemoteURL column populated,.
Then parses the DNS name from the URL (if needed) and finds the least prevalent.
FQDNs. The result is then joined with DeviceNetworkEvents to highlight anomalous.
Network communication.
This query reduces network events to only those with the RemoteURL column populated,.
Then parses the DNS name from the URL (if needed) and finds the least prevalent.
FQDNs. The result is then joined with DeviceNetworkEvents to highlight anomalous.
Network communication.
This query looks for the DGA pattern of the domain associated with the Nobelium campaign, in order to find other domains with the same activity pattern.
This query is inspired by an Azure Sentinel detection.
Reference - https://raw.githubusercontent.com/Azure/Azure-Sentinel/master/Hunting%20Queries/DnsEvents/Solorigate-DNS-Pattern.yaml
This query is inspired by an Azure Sentinel detection.
Reference - https://raw.githubusercontent.com/Azure/Azure-Sentinel/master/Hunting%20Queries/DnsEvents/Solorigate-DNS-Pattern.yaml
Snip3 is a family of related remote access trojans. Although the malware in this family contain numerous small variations, they all exhibit similar behaviors and techniques.
The following query looks for network connections using any protocols associated with recent RevengeRAT, AsyncRAT, and other malware campaigns targeting the aviation industry.
This activity is often followed by connections to copy-and-paste sites such as pastebin.com, stikked.ch, academia.edu, and archive.org. Many of these connections will occur on non-standard ports.
The following query looks for network connections using any protocols associated with recent RevengeRAT, AsyncRAT, and other malware campaigns targeting the aviation industry.
This activity is often followed by connections to copy-and-paste sites such as pastebin.com, stikked.ch, academia.edu, and archive.org. Many of these connections will occur on non-standard ports.
Remote Monitoring and Management (RMM) programs are IT to manage remote endpoints. Attackers have begun to abuse these programs to persist or provide C2 channels.
https://github.com/jischell-msft/RemoteManagementMonitoringTools
https://github.com/jischell-msft/RemoteManagementMonitoringTools
'This composite hunting query will highlight any HTTP traffic in CommonSecurityLog web proxies (such as ZScaler) that match known patterns used by red teaming tools potentially stolen from FireEye. Most FireEye red teaming tools are designed to mimic
legitimate API activity, false positives are common. This query includes a basic check to determine how common a hostname is in you environment, and allows you to modify this threshold to remove legitimate traffic from the query results.
This query contains only a subset of potential FireEye red team tool communications, and therefore should not be relied upon alone :) .'
legitimate API activity, false positives are common. This query includes a basic check to determine how common a hostname is in you environment, and allows you to modify this threshold to remove legitimate traffic from the query results.
This query contains only a subset of potential FireEye red team tool communications, and therefore should not be relied upon alone :) .'
'Threat actors may use tools such as Curl to download additional files, communicate with C2 infrastructure, or exfiltrate data. This query looks for new files being downloaded using Curl. Curl also has legitimate uses files and hosts should be reviewed to identify potentially malicious activity.
Ref: https://www.microsoft.com/security/blog/2022/07/27/untangling-knotweed-european-private-sector-offensive-actor-using-0-day-exploits/'
Ref: https://www.microsoft.com/security/blog/2022/07/27/untangling-knotweed-european-private-sector-offensive-actor-using-0-day-exploits/'
'This query dynamically identifies Exchange servers and then looks for instances where the IIS worker process initiates a call out to a remote URL using either cmd.exe or powershell.exe.
This behaviour was described as post-compromise behaviour following exploitation of CVE-2022-41040 and CVE-2022-41082, this pattern of activity was use to download additional tools to the server. This suspicious activity is generic.'
This behaviour was described as post-compromise behaviour following exploitation of CVE-2022-41040 and CVE-2022-41082, this pattern of activity was use to download additional tools to the server. This suspicious activity is generic.'
This query was originally published in the threat analytics report, Solorigate supply chain attack. Please note that these attacks are currently known as the Nobelium campaign.
Microsoft detects the 2020 SolarWinds supply chain attack implant and its other components as part of a campaign by the Nobelium activity group. Nobelium is the threat actor behind the attack against SolarWinds, which was previously referred to as Solorigate.
Nobelium silently added malicious code to legitimate software updates for Orion, which is IT monitoring software provided by SolarWinds. In this way, malicious dynamic link libraries (DLLs) were distributed to SolarWinds customers.
The following query detects events when Nobelium received a DNS response after launching a lookup request to known command-and-control infrastructure.
More Nobelium-related queries can be found listed under the See also section of this document.
References:
https://msrc-blog.microsoft.com/2020/12/13/customer-guidance-on-recent-nation-state-cyber-attacks/
https://www.microsoft.com/security/blog/2020/12/18/analyzing-solorigate-the-compromised-dll-file-that-started-a-sophisticated-cyberattack-and-how-microsoft-defender-helps-protect/
Microsoft detects the 2020 SolarWinds supply chain attack implant and its other components as part of a campaign by the Nobelium activity group. Nobelium is the threat actor behind the attack against SolarWinds, which was previously referred to as Solorigate.
Nobelium silently added malicious code to legitimate software updates for Orion, which is IT monitoring software provided by SolarWinds. In this way, malicious dynamic link libraries (DLLs) were distributed to SolarWinds customers.
The following query detects events when Nobelium received a DNS response after launching a lookup request to known command-and-control infrastructure.
More Nobelium-related queries can be found listed under the See also section of this document.
References:
https://msrc-blog.microsoft.com/2020/12/13/customer-guidance-on-recent-nation-state-cyber-attacks/
https://www.microsoft.com/security/blog/2020/12/18/analyzing-solorigate-the-compromised-dll-file-that-started-a-sophisticated-cyberattack-and-how-microsoft-defender-helps-protect/
'Detects suspicious user agent strings used by known hack tools'
This query is a function that consumes the publicly available Azure IP address list and checks a list of remote IP addresses against it to see if they are Azure IP addresses or not.
To use this, replace the demo portion of the query (DeviceNetworkEvents | take 10000) with your query with the column name of the IP address to check named RemoteIP. The function will add a new column to the end called IsAzure denoting if the IP address range is in the published list or not.
Please note that over time the URL to the Azure IP address list may need to be updated.
To use this, replace the demo portion of the query (DeviceNetworkEvents | take 10000) with your query with the column name of the IP address to check named RemoteIP. The function will add a new column to the end called IsAzure denoting if the IP address range is in the published list or not.
Please note that over time the URL to the Azure IP address list may need to be updated.
Intent:
- Use MTP capability to look for insider threat potential risk indicators
- Indicators would then serve as the building block for insider threat risk modeling in subsequent tools
Definition of Insider Threat:
"The potential for an individual who has or had authorized access to an organization's assets to use their access, either maliciously or unintentionally, to act in a way that could negatively affect the organization."
This collection of queries describes the different indicators that could be used to model and look for patterns suggesting an increased risk of an individual becoming a potential insider threat.
Note: no single indicator should be used as a lone determinant of insider threat activity, but should be part of an overall program to understand the increased risk to your organization's critical assets. This in turn is used to feed an investigation by a formal insider threat program to look at the context associated with the whole person to understand the implication of a set of indicators.
- Use MTP capability to look for insider threat potential risk indicators
- Indicators would then serve as the building block for insider threat risk modeling in subsequent tools
Definition of Insider Threat:
"The potential for an individual who has or had authorized access to an organization's assets to use their access, either maliciously or unintentionally, to act in a way that could negatively affect the organization."
This collection of queries describes the different indicators that could be used to model and look for patterns suggesting an increased risk of an individual becoming a potential insider threat.
Note: no single indicator should be used as a lone determinant of insider threat activity, but should be part of an overall program to understand the increased risk to your organization's critical assets. This in turn is used to feed an investigation by a formal insider threat program to look at the context associated with the whole person to understand the implication of a set of indicators.
Remote Monitoring and Management (RMM) programs are IT to manage remote endpoints. Attackers have begun to abuse these programs to persist or provide C2 channels.
https://github.com/jischell-msft/RemoteManagementMonitoringTools
https://github.com/jischell-msft/RemoteManagementMonitoringTools
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