Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
734 detections
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The following analytic identifies the creation of a new AWS IAM policy version that allows access to all resources. It detects this activity by analyzing AWS CloudTrail logs for the CreatePolicyVersion event with a policy document that grants broad permissions. This behavior is significant because it violates the principle of least privilege, potentially exposing the environment to misuse or abuse. If confirmed malicious, an attacker could gain extensive access to AWS resources, leading to unauthorized actions, data exfiltration, or further compromise of the AWS environment.
The following analytic detects the deletion of CloudWatch log groups in AWS, identified through `DeleteLogGroup` events in CloudTrail logs. This method leverages Amazon Security Lake logs parsed in the OCSF format. The activity is significant because attackers may delete log groups to evade detection and disrupt logging capabilities, hindering incident response efforts. If confirmed malicious, this action could allow attackers to cover their tracks, making it difficult to trace their activities and potentially leading to undetected data breaches or further malicious actions within the compromised AWS environment.
The following analytic detects when AWS S3 bucket versioning is suspended by a user. It leverages AWS CloudTrail logs to identify `PutBucketVersioning` events with the `VersioningConfiguration.Status` set to `Suspended`. This activity is significant because disabling versioning can prevent recovery of deleted or modified data, which is a common tactic in ransomware attacks. If confirmed malicious, this action could lead to data loss and hinder recovery efforts, severely impacting data integrity and availability.
The following analytic detects updates to the SAML provider in AWS. It leverages AWS CloudTrail logs to identify the `UpdateSAMLProvider` event, analyzing fields such as `sAMLProviderArn`, `sourceIPAddress`, and `userIdentity` details. Monitoring updates to the SAML provider is crucial as it may indicate a perimeter compromise of federated credentials or unauthorized backdoor access set by an attacker. If confirmed malicious, this activity could allow attackers to manipulate identity federation, potentially leading to unauthorized access to cloud resources and sensitive data.
The following analytic detects attempts to disable multi-factor authentication (MFA) for an AWS IAM user. It leverages Amazon Security Lake logs, specifically monitoring for `DeleteVirtualMFADevice` or `DeactivateMFADevice` API operations. This activity is significant as disabling MFA can indicate an adversary attempting to weaken account security to maintain persistence using a compromised account. If confirmed malicious, this action could allow attackers to retain access to the AWS environment without detection, potentially leading to unauthorized access to sensitive resources and prolonged compromise.
The analytic identifies multiple failed multi-factor authentication (MFA) requests to an AWS Console for a single user within a short timeframe (more than 10 failed MFA prompts within 5 minutes). This activity may indicate an adversary attempting to bypass MFA through 'MFA fatigue' attacks, where repeated authentication requests are sent to the user in hopes they will eventually approve one, leading to unauthorized access to the AWS environment.
The analytic identifies a spike in API activity related to the deletion of S3 buckets in an AWS environment. It uses AWS CloudTrail logs to detect anomalies by comparing current deletion activity against a historical baseline. Unusual spikes in S3 bucket deletions could indicate malicious actions such as data exfiltration or unauthorized data destruction, leading to significant data loss, disruption of services, and potential exposure of sensitive information. Immediate investigation is required to determine the legitimacy of the activity.
This analytic identifies potential privilege escalation activities within an organization's Active Directory (AD) environment by correlating multiple analytics from the "Active Directory Privilege Escalation" analytic story within a specified time frame. This is significant for a SOC as it helps identify coordinated attempts to gain elevated privileges, which could indicate a serious security threat. If confirmed malicious, this activity could allow attackers to gain unauthorized access to sensitive systems and data, leading to potential data breaches and further compromise of the network.
The following analytic detects `UpdateTrail` events within AWS CloudTrail logs, aiming to identify attempts by attackers to evade detection by altering logging configurations. By updating CloudTrail settings with incorrect parameters, such as changing multi-regional logging to a single region, attackers can impair the logging of their activities across other regions. This behavior is crucial for Security Operations Centers (SOCs) to identify, as it indicates an adversary's intent to operate undetected within a compromised AWS environment. The impact of such evasion tactics is significant, potentially allowing malicious activities to proceed without being logged, thereby hindering incident response and forensic investigations.
The following analytic identifies IAM users attempting to update or modify AWS Lambda code via the AWS CLI. It leverages CloudTrail logs to detect successful `UpdateFunctionCode` events initiated by IAM users. This activity is significant as it may indicate an attempt to gain persistence, further access, or plant backdoors within your AWS environment. If confirmed malicious, an attacker could upload and execute malicious code automatically when the Lambda function is triggered, potentially compromising the integrity and security of your AWS infrastructure.
The analytic detects cloud provisioning activities originating from previously unseen regions. It leverages cloud infrastructure logs to identify events where resources are started or created, and cross-references these with a baseline of known regions. This activity is significant as it may indicate unauthorized access or misuse of cloud resources from unfamiliar locations. If confirmed malicious, this could lead to unauthorized resource creation, potential data exfiltration, or further compromise of cloud infrastructure.
This analytic detects AWS `DeleteTrail` events within CloudTrail logs, specifically leveraging Amazon Security Lake logs parsed in the Open Cybersecurity Schema Framework (OCSF) format. The purpose is to identify when a CloudTrail is deleted. This activity is significant because adversaries may delete CloudTrail logs to evade detection and operate with stealth. If confirmed malicious, this action could allow attackers to cover their tracks, making it difficult to trace their activities and investigate other potential compromises within the AWS environment.
The analytic identifies a single source IP failing to authenticate into the AWS Console with 30 unique valid users within 10 minutes. It leverages CloudTrail logs to detect multiple failed login attempts from the same IP address. This behavior is significant as it may indicate a Password Spraying attack, where an adversary attempts to gain unauthorized access or elevate privileges by trying common passwords across many accounts. If confirmed malicious, this activity could lead to unauthorized access, data breaches, or further exploitation within the AWS environment.
The analytic detects when an EC2 snapshot is shared publicly by analyzing AWS CloudTrail events. This detection method leverages CloudTrail logs to identify modifications in snapshot permissions, specifically when the snapshot is shared outside the originating AWS account. This activity is significant as it may indicate an attempt to exfiltrate sensitive data stored in the snapshot. If confirmed malicious, an attacker could gain unauthorized access to the snapshot's data, potentially leading to data breaches or further exploitation of the compromised information.
The analytic detects multiple failed attempts to assume an AWS IAM role, indicating a potential brute force attack. It leverages AWS CloudTrail logs to identify `MalformedPolicyDocumentException` errors with a status of `failure` and filters out legitimate AWS services. This activity is significant as repeated failures to assume roles can indicate an adversary attempting to guess role names, which is a precursor to unauthorized access. If confirmed malicious, this could lead to unauthorized access to AWS resources, potentially compromising sensitive data and services.
The analytic identifies `GetPasswordData` API calls in AWS CloudTrail logs from Amazon Security Lake. This activity is significant as it indicates an attempt to retrieve encrypted administrator passwords for running Windows instances. Attackers could gain unauthorized access to administrative credentials, potentially leading to full control over affected instances and further compromise of the AWS environment.
The following analytic detects cloud provisioning activities originating from previously unseen cities. It leverages cloud infrastructure logs and compares the geographic location of the source IP address against a baseline of known locations. This activity is significant as it may indicate unauthorized access or misuse of cloud resources from an unexpected location. If confirmed malicious, this could lead to unauthorized resource creation, potential data exfiltration, or further compromise of cloud infrastructure.
The following analytic identifies the creation of open/public S3 buckets in AWS. It detects this activity by analyzing AWS CloudTrail events for `PutBucketAcl` actions where the access control list (ACL) grants permissions to all users or authenticated users. This activity is significant because open S3 buckets can expose sensitive data to unauthorized access, leading to data breaches. If confirmed malicious, an attacker could read, write, or fully control the contents of the bucket, potentially leading to data exfiltration or tampering.
The analytic detects unauthorized container uploads to AWS Elastic Container Service (ECR) by monitoring AWS CloudTrail events. It identifies instances where a new container is uploaded by a user not previously recognized as authorized. This detection is crucial for a SOC as it can indicate a potential compromise or misuse of AWS ECR, which could lead to unauthorized access to sensitive data or the deployment of malicious containers. By identifying and investigating these events, organizations can mitigate the risk of data breaches or other security incidents resulting from unauthorized container uploads. The impact of such an attack could be significant, compromising the integrity and security of the organization's cloud environment.
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 identifies unsuccessful login attempts to the AWS Management Console using a specific user identity. It leverages AWS CloudTrail logs to detect failed authentication events associated with the AWS ConsoleLogin action. This activity is significant for a SOC because repeated failed login attempts may indicate a brute force attack or unauthorized access attempts. If confirmed malicious, an attacker could potentially gain access to AWS account services and resources, leading to data breaches, resource manipulation, or further exploitation within the AWS environment.
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