Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
223 detections
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This rule performs an IOC sweep over the past 30 days using DeviceNetworkEvents, DeviceFileEvents, and DeviceProcessEvents to detect indicators associated with PoeLLM / Canto Incognito malware campaigns, specifically scanning for known C2 IP addresses, Kryptex cryptomining pool endpoints/domains, and specific file hashes (SHA256).
This rule performs an IOC sweep over the past 30 days using DeviceNetworkEvents, DeviceFileEvents, and DeviceProcessEvents to detect indicators associated with PoeLLM / Canto Incognito malware campaigns, specifically scanning for known C2 IP addresses, Kryptex cryptomining pool endpoints/domains, and specific file hashes (SHA256).
This rule performs an IOC sweep over the past 30 days using DeviceNetworkEvents, DeviceFileEvents, and DeviceProcessEvents to detect indicators associated with PoeLLM / Canto Incognito malware campaigns, specifically scanning for known C2 IP addresses, Kryptex cryptomining pool endpoints/domains, and specific file hashes (SHA256).
Detects anomalous AWS Bedrock activity indicative of LLMjacking by correlating multiple phases of an attack chain (Model Enablement, Reconnaissance, Probing, and Execution) performed by a single identity within a short timeframe. This rule identifies attackers leveraging stolen IAM credentials to discover available AI models, probe for vulnerabilities, and execute unauthorized inference requests at scale.
The following analytic identifies the creation of cloud compute instances by users who have not previously created them. It leverages data from the Change data model, focusing on 'create' actions by users, and cross-references with a baseline of known user activities. This activity is significant as it may indicate unauthorized access or misuse of cloud resources by new or compromised accounts. If confirmed malicious, attackers could deploy unauthorized compute instances, leading to potential data exfiltration, increased costs, or further exploitation within the cloud environment.
Detects anomalous AWS Bedrock model invocation patterns where a single identity accesses models across three or more distinct AWS regions within a short timeframe. This behavior is indicative of quota evasion, where attackers bypass per-region rate limits to maximize throughput when leveraging compromised credentials for unauthorized LLM use.
Detects the creation of high-cost, resource-intensive compute instances (such as GPU-enabled or large-scale VMs) within cloud regions that have not been previously utilized by the account, subscription, or project. This behavior is often indicative of unauthorized resource hijacking, such as crypto-mining or large-scale data processing by threat actors.
Detects the use of 'vim-cmd' or 'esxcli' to power off or terminate virtual machine processes on an ESXi host, which may indicate malicious activity such as ransom-related VM shutdown or service disruption.
Detects evidence of cryptocurrency mining (XMRig) and suspicious process masquerading on Linux systems, alongside container-related events referencing known malicious or suspicious strings such as 'GH0ST_C2' or 'fsociety'.
Detects the provisioning of high-performance compute instances (GPU or high-CPU) in AWS regions that fall outside of an established organizational baseline. This behavior is often associated with unauthorized resource hijacking (cryptomining) by adversaries leveraging compromised IAM principals to deploy infrastructure in regions with lower visibility or monitoring coverage.
Detects the deployment of virtual machines with public IP addresses (in Azure) or compute instances with external IP addresses (in GCP) by a single principal within a 15-minute window. This behavior is indicative of a newly-privileged identity or an compromised account establishing externally-accessible infrastructure for further malicious activity.
Detects the mass creation of high-performance compute instances (GPU or high-memory variants) in an AWS environment. By filtering out legitimate service-linked roles associated with auto-scaling, the rule isolates potentially unauthorized manual provisioning, often indicative of cryptojacking or resource hijacking.
Detects the execution of 'Silent XMR Miner Builder.exe' followed by the spawning of common compilers (e.g., csc.exe, gcc.exe, donut.exe), which is indicative of a developer tool being used to compile and build a cryptocurrency mining payload.
This rule detects network traffic originating from internal hosts to the domain 'msfconfig.icu'. It specifically monitors for GET requests to '/tmp/system.txt' and TLS connections using the same domain as an SNI, which are associated with the delivery of ClickFix XMRig miner payloads.
Detects the use of long-lived AWS IAM access keys (AKIA) to perform critical AWS Bedrock operations such as enabling foundation model access (PutUseCaseForModelAccess, CreateFoundationModelAgreement). Such sensitive configurations are typically expected to be performed via the AWS Console using federated credentials; the use of long-lived keys for these specific actions is a strong indicator of potential compromise and unauthorized resource enablement.
Detects outbound network traffic matching Stratum protocol JSON-RPC methods (mining.subscribe, mining.authorize, mining.submit) typically used by XMRig and other cryptomining software to communicate with a mining pool. The rule monitors for established TCP connections on non-standard ports, excluding common web ports 80 and 443.
Detects instances where the XMRig cryptominer is masquerading as the legitimate systemd-logind process on Linux hosts. The rule triggers on process execution of /usr/sbin/systemd-logind coupled with suspicious outbound network connections to known mining pools or mining-related ports.
Detects network traffic associated with the WallStealer malware, including the download of malicious payloads from a known C2 server, communication with a cryptominer C2, and the use of Steam Community profiles as dead-drop resolvers for C2 instructions.
Detects anomalous, large-scale provisioning of GPU-intensive cloud instances (such as p3, p4, g4dn, g5, and trn1 families) in AWS. This activity is indicative of cloud cryptojacking campaigns where adversaries hijack resources to rapidly spin up compute clusters for cryptomining, potentially incurring significant financial damage within a short period.
Detects the launch of compute-optimized or GPU-accelerated EC2 instances via the RunInstances API. This behavior is a common indicator of unauthorized resource hijacking, such as cryptomining, where attackers leverage compromised credentials to deploy resource-intensive workloads in regions that have not been historically used by the organization.
Detects rapid, large-scale deployment of high-vCPU/GPU compute instances, potentially indicating resource hijacking for cryptomining. The rule correlates high-compute instance launches with preceding AWS service quota increases, identifying potential malicious activity within an AWS environment.
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