Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
390 detections
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Detects when a large number of virtual machines are powered off by a single user or initiator within a short timeframe, which can be an indicator of malicious availability interruption or virtualization disruption (such as ransomware preparation).
Detects deletion of a managed resource from the vault following privileged access to
it. Removing the resource destroys the record of which credentials existed and who
held them, which is both destructive and a way of covering the preceding access.
Treat the deletion as evidence tampering rather than as routine housekeeping unless
a decommissioning record exists.
Onboarding: PAM360 is ingested via Syslog (Bloo extractor 879).
Integration guide: https://bloo.io/docs/hypercloud/syslog-connector
BQL (Bloo Query Language):
stream=audit where sourcename='PAM360' and action='RESOURCE_DELETED'
| groupby user, targetuser, srcip, message
it. Removing the resource destroys the record of which credentials existed and who
held them, which is both destructive and a way of covering the preceding access.
Treat the deletion as evidence tampering rather than as routine housekeeping unless
a decommissioning record exists.
Onboarding: PAM360 is ingested via Syslog (Bloo extractor 879).
Integration guide: https://bloo.io/docs/hypercloud/syslog-connector
BQL (Bloo Query Language):
stream=audit where sourcename='PAM360' and action='RESOURCE_DELETED'
| groupby user, targetuser, srcip, message
Detects a single account deleting a large number of files on the NAS. On shared
storage this is either ransomware working through the share, a destructive insider,
or an attacker removing backups before encrypting the primary estate.
NAS appliances rarely carry endpoint agents, so their own logs are frequently the
only place this is visible.
Onboarding: DISKSTATION-NAS is ingested via Syslog (Bloo extractor 826).
Integration guide: https://bloo.io/docs/hypercloud/syslog-connector
BQL (Bloo Query Language):
stream=documents where sourcename='DISKSTATION-NAS' and action='DELETED'
| duration 10m
| groupby user, srcip
| select user, srcip, count(*) as cnt
| having cnt > 50
storage this is either ransomware working through the share, a destructive insider,
or an attacker removing backups before encrypting the primary estate.
NAS appliances rarely carry endpoint agents, so their own logs are frequently the
only place this is visible.
Onboarding: DISKSTATION-NAS is ingested via Syslog (Bloo extractor 826).
Integration guide: https://bloo.io/docs/hypercloud/syslog-connector
BQL (Bloo Query Language):
stream=documents where sourcename='DISKSTATION-NAS' and action='DELETED'
| duration 10m
| groupby user, srcip
| select user, srcip, count(*) as cnt
| having cnt > 50
Detects the Shai-Hulud supply chain attack dead-man's switch: a gh-token-monitor persistence component followed by a recursive forced deletion of the user home directory, or the presence of the specific kill-switch string in a command line.
A BTP subaccount entity was deleted from the global account
Detects the rare 'AssumeRoot' event in AWS STS followed by high-impact administrative or destructive API calls within a one-hour window. This behavior often indicates an adversary attempting to gain elevated, privileged access to perform unauthorized actions such as disabling logging, deleting infrastructure, or modifying IAM policies.
The following analytic detects the use of the 'dd' command to overwrite files on a Linux system. It leverages data from Linux Auditd telemetry, focusing on process execution logs that include command-line details. This activity is significant because adversaries often use the 'dd' command to destroy or irreversibly overwrite files, disrupting system availability and services. If confirmed malicious, this behavior could lead to data destruction, making recovery difficult and potentially causing significant operational disruptions.
The following analytic detects the use of the 'dd' command to overwrite files on a Linux system. It leverages data from Endpoint Detection and Response (EDR) agents, focusing on process execution logs that include command-line details. This activity is significant because adversaries often use the 'dd' command to destroy or irreversibly overwrite files, disrupting system availability and services. If confirmed malicious, this behavior could lead to data destruction, making recovery difficult and potentially causing significant operational disruptions.
Detects malicious attempts to delete or modify the access control settings of centralized cloud audit log storage, such as S3 buckets, Azure Log Analytics workspaces, or GCP log buckets. These actions aim to impair visibility into an adversary's activities, a common step in anti-forensics and data destruction workflows.
Detects high-volume or multi-type destructive operations against cloud backup, snapshot, and recovery infrastructure, including the disabling of immutability policies or soft-delete protections. This activity is consistent with ransomware actors attempting to eliminate recovery options before encrypting data.
Detects a service principal or application identity performing a burst of deletion operations across multiple Azure resource types, such as Storage Accounts, SQL Databases, Key Vaults, and Function Apps. This behavior is indicative of malicious activity, including potential cloud environment destruction or 'agentic' destructive operations similar to those observed in the Storm-3168 (JADEPUFFER) threat activity.
Detects mass device management actions (e.g., remote wipe, retire, or delete) performed via the Microsoft Intune console by a user who has simultaneously exhibited risky sign-in behavior, potentially indicating a compromised administrative account.
Detects unauthorized attempts to modify or delete AWS CloudTrail logs stored in S3, or changes to the S3 bucket lifecycle configuration that would shorten the log retention period. This activity is indicative of an adversary attempting to clear their tracks or hinder audit capabilities.
Detects instances where a file is downloaded or exfiltrated, followed by the deletion or alteration of its version history within a 7-day window. This behavior is consistent with post-theft activities aimed at obfuscating access logs or sanitizing stolen data by removing original versioning markers, often observed in insider threat or compromised account scenarios.
Detects a suspicious volume of cloud resource deletions occurring within a short 15-minute window, specifically targeting multiple storage accounts and SQL database/server instances. This behavior is indicative of a malicious actor or an automated script attempting to disrupt business operations or destroy data.
Detects a burst of file delete or overwrite operations initiated by a configured AI agent service identity. This behavior, if deviating from established baselines, may indicate a compromised agent performing malicious destructive activities such as mass data deletion or ransomware-style file destruction.
Detects anomalous, high-volume file deletion, modification, or resource deletion operations performed by an identified AI agent service account within a short timeframe. This behavior is indicative of a compromised AI agent being leveraged for mass data destruction, ransomware activity, or disruptive configuration changes.
Detects high-velocity, automated-paced burst of deletion operations spanning multiple distinct Azure resource types (Storage, SQL, Key Vault, Web Sites) within a 15-minute window. This behavior is indicative of agentic AI-orchestrated cloud resource destruction, contrasting with typical administrative lifecycle management.
Detects execution of common Windows utilities used by adversaries post-encryption to hinder system recovery and clear forensic evidence. This includes disabling the Windows Recovery Environment (ReAgentC), wiping disk free space (Cipher), clearing DNS caches, and clearing Windows Event Logs via Wevtutil or PowerShell.
Detects a service principal attempting to delete multiple Azure SQL databases in a short timeframe, resulting in failures. This pattern is characteristic of malicious data destruction activity, such as that observed in Storm-3168 (JADEPUFFER) campaigns, but accounts for the possibility of misconfigured infrastructure-as-code pipelines by requiring a high volume of failed requests across distinct resources.
Detects a precursor pattern identified as JADEPUFFER, where a failed 'ListKeys' operation (indicating an attempt to discover or access keys for a non-existent storage account) is immediately followed by a burst of destructive delete operations on critical cloud resources (e.g., storage, databases, key vaults) by the same actor.
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