Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
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The analytic identifies an AWS IAM account with concurrent sessions originating from more than one unique IP address within a 5-minute window. It leverages AWS CloudTrail logs, specifically the `DescribeEventAggregates` event, to detect this behavior. This activity is significant as it may indicate a session hijacking attack, where an adversary uses stolen session cookies to access AWS resources from a different location. If confirmed malicious, this could allow unauthorized access to sensitive corporate resources, leading to potential data breaches or further exploitation within the AWS environment.
The following analytic detects the use of the Certipy tool to enumerate Active Directory Certificate Services (AD CS) environments by identifying unique file modifications. It leverages endpoint process and filesystem data to spot the creation of files with specific names or extensions associated with Certipy's information gathering and exfiltration activities. This activity is significant as it indicates potential reconnaissance and data exfiltration efforts by an attacker. If confirmed malicious, this could lead to unauthorized access to sensitive AD CS information, enabling further attacks or privilege escalation within the network.
The following analytic detects the execution of known MailSniper PowerShell functions on a machine. It leverages PowerShell logs (EventCode 4104) to identify specific script block text associated with MailSniper activities. This behavior is significant as MailSniper is often used by attackers to harvest sensitive emails from compromised Exchange servers. If confirmed malicious, this activity could lead to unauthorized access to sensitive email data, credential theft, and further compromise of the email infrastructure.
The following analytic identifies the presence of unauthorized DHCP servers on the network. It leverages logs from Cisco network devices with DHCP Snooping enabled, specifically looking for events where DHCP leases are issued from untrusted ports. This activity is significant because rogue DHCP servers can facilitate Man-in-the-Middle attacks, leading to potential data interception and network disruption. If confirmed malicious, this could allow attackers to redirect network traffic, capture sensitive information, and compromise the integrity of the network.
The following analytic identifies unauthorized devices attempting to connect to the organization's network by inspecting DHCP request packets. It detects this activity by comparing the MAC addresses in DHCP requests against a list of known authorized devices stored in the assets_by_str.csv file. This activity is significant for a SOC because unauthorized devices can pose security risks, including potential data breaches or network disruptions. If confirmed malicious, this activity could allow an attacker to gain unauthorized network access, potentially leading to further exploitation or data exfiltration.
The analytic identifies hosts receiving an unusually high volume of network traffic from an email server. It leverages the Network_Traffic data model to sum incoming bytes to clients from email servers, comparing current traffic against historical averages and standard deviations. This activity is significant as it may indicate data exfiltration by a malicious actor using the email server. If confirmed malicious, this could lead to unauthorized data access and potential data breaches, compromising sensitive information and impacting organizational security.
The analytic identifies successful access to an S3 bucket from a new or previously unseen remote IP address. This activity is significant because access from unfamiliar IP addresses could indicate unauthorized access or potential data exfiltration attempts. If confirmed malicious, this activity could lead to unauthorized data access, data theft, or further exploitation of the compromised S3 bucket, posing a significant risk to sensitive information stored within the bucket.
The following analytic identifies when an O365 email account sends and then hard deletes an email to an external recipient within a short period (within 1 hour). This behavior may indicate a compromised account where the threat actor is attempting to remove forensic artifacts or evidence of exfiltration activity. This behavior is often seen when threat actors want to reduce the probability of detection by the compromised account owner.
The following analytic identifies the creation of new email forwarding rules in an Office 365 environment via the UpdateInboxRules operation. It leverages Office 365 management activity events to detect rules that forward emails to external recipients by examining the OperationProperties for specific forwarding actions. This activity is significant as it may indicate unauthorized email redirection, potentially leading to data exfiltration. If confirmed malicious, attackers could intercept sensitive communications, leading to data breaches and information leakage.
The following analytic identifies instances where read permissions are assigned to mailbox folders within an Office 365 environment. It leverages the `o365_management_activity` data source, specifically monitoring the `ModifyFolderPermissions` and `AddFolderPermissions` operations, while excluding Calendar, Contacts, and PersonMetadata objects. This activity is significant as unauthorized read permissions can lead to data exposure and potential information leakage. If confirmed malicious, an attacker could gain unauthorized access to sensitive emails, leading to data breaches and compromising the confidentiality of organizational communications.
The following analytic detects instances where a user has initiated an eDiscovery search or exported a PST file in an Office 365 environment. It leverages Office 365 management activity logs, specifically filtering for events under ThreatManagement with the name "eDiscovery search started or exported." This activity is significant as it may indicate data exfiltration attempts or unauthorized access to sensitive information. If confirmed malicious, it suggests an attacker or insider threat is attempting to gather or exfiltrate data, potentially leading to data breaches, loss of intellectual property, or unauthorized access to confidential communications. Immediate investigation is required.
This analytic identifies instances where the Mail.Read Graph API permissions are granted to an application registration within an Office 365 tenant. It leverages O365 audit logs, specifically events related to changes in application permissions within the AzureActiveDirectory workload. This activity is significant because the Mail.Read permission allows applications to access and read all emails within a user's mailbox, which often contain sensitive or confidential information. If confirmed malicious, this could lead to data exfiltration, spear-phishing attacks, or further compromise based on the information gathered from the emails.
This analytic detects the use of the LD_PRELOAD environment variable to hijack or hook library functions on a Linux platform. It leverages data from Linux Auditd, focusing on process execution logs that include command-line details. This activity is significant because adversaries, malware authors, and red teamers commonly use this technique to gain elevated privileges and establish persistence on a compromised machine. If confirmed malicious, this behavior could allow attackers to execute arbitrary code, escalate privileges, and maintain long-term access to the system.
The analytic detects the creation of files in the Remcos folder within the AppData directory, specifically targeting .dat files which are often used for keylog and clipboard log files by the Remcos RAT. This activity indicates the presence of the Remcos RAT, which performs keylogging, clipboard capturing, and audio recording, potentially leading to unauthorized data exfiltration and extensive surveillance.
This analytic detects IPv6 network infrastructure threats by identifying suspicious activities such as IP and MAC address theft or packet drops. It leverages logs from Cisco network devices configured with First Hop Security measures like RA Guard and DHCP Guard. This activity is significant as it can indicate attempts to compromise network integrity and security. If confirmed malicious, attackers could manipulate network traffic, leading to potential data interception, unauthorized access, or network disruption.
The analytic identifies the creation of AWS Batch jobs that could potentially abuse the AWS Bucket Replication feature on S3 buckets. It leverages AWS CloudTrail logs to detect the `JobCreated` event, analyzing job details and their status. This activity is significant because attackers can exploit this feature to exfiltrate data by creating malicious batch jobs. If confirmed malicious, this could lead to unauthorized data transfer between S3 buckets, resulting in data breaches and loss of sensitive information.
The analytic detects the assignment of the ApplicationImpersonation role in Office 365 to a user or application. This role allows impersonation of any user, enabling access to and modification of their mailbox. If confirmed malicious, an attacker could gain unauthorized access to sensitive information, manipulate mailbox data, and perform actions as a legitimate user, posing a severe security risk to the organization.
The analytic identifies when the results of a content search within the Office 365 Security and Compliance Center are exported. It uses the SearchExported operation from the SecurityComplianceCenter workload in the o365_management_activity data source. This activity is significant because exporting search results can involve sensitive or critical organizational data, potentially leading to data exfiltration. If confirmed malicious, an attacker could gain access to and exfiltrate sensitive information, posing a severe risk to the organization's data security and compliance posture.
The following analytic identifies instances where read permissions are granted to mailbox folders within an Office 365 environment. It detects this activity by monitoring the `o365_management_activity` data source for the `Set-MailboxFolderPermission` and `Add-MailboxFolderPermission` operations. This behavior is significant as it may indicate unauthorized access or changes to mailbox folder permissions, potentially exposing sensitive email content. If confirmed malicious, an attacker could gain unauthorized access to read email communications, leading to data breaches or information leakage.
The following analytic detects the creation of open/public S3 buckets via the AWS CLI. It leverages AWS CloudTrail logs to identify events where a user has set bucket permissions to allow access to "AuthenticatedUsers" or "AllUsers." This activity is significant because open S3 buckets can expose sensitive data to unauthorized users, leading to data breaches. If confirmed malicious, an attacker could gain unauthorized access to potentially sensitive information stored in the S3 bucket, posing a significant security risk.
The following analytic identifies a spike in the number of AWS Security Hub alerts for an EC2 instance within a 4-hour interval. It leverages AWS Security Hub findings data, calculating the average and standard deviation of alerts to detect anomalies. This activity is significant for a SOC as a sudden increase in alerts may indicate potential security incidents or misconfigurations requiring immediate attention. If confirmed malicious, this could signify an ongoing attack, leading to unauthorized access, data exfiltration, or disruption of services on the affected EC2 instance.
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