-
AWS Bedrock AgentCore with Public Network Browser or Code Interpreter Sandbox
Oct 7, 2026 · Domain: Cloud Data Source: AWS Data Source: Amazon Web Services Platform: AWS Data Source: AWS CloudTrail Service: AWS Bedrock Service: AWS IAM Use Case: Threat Detection Tactic: Privilege Escalation Tactic: Persistence Rule Type: Custom Query (KQL) Resources: Investigation Guide Domain: GenAI Mitre Atlas: AML.T0012 Mitre Atlas: AML.T0103 ·Detects the successful creation of an Amazon Bedrock AgentCore Browser or Code Interpreter with an execution IAM role and public network access. These sandboxes run agent-generated code or automated browsing on the caller's behalf, and the attached role lets the sandbox call other AWS services. Public network mode removes the sandbox's network containment, so a sandbox steered by prompt injection, malicious tool output, or code-execution abuse can reach the internet and pivot into other AWS resources with the role's permissions. Review the role scope and whether public egress is required.
Read More -
GCP Vertex AI Caller Activity From High Number of Countries
Oct 7, 2026 · Domain: GenAI Domain: Cloud Data Source: GCP Vertex AI Data Source: GCP Data Source: Google Cloud Platform Platform: GCP Service: GCP Vertex AI Use Case: Threat Detection Tactic: Credential Access Tactic: Initial Access Threat: Impossible Travel Threat: LLMjacking Threat: Unauthorized AI Usage Mitre Atlas: AML.T0012 Mitre Atlas: AML.T0091 Mitre Atlas: AML.T0091.000 Resources: Investigation Guide Rule Type: ES|QL ·Detects Vertex AI authenticated caller activity for the same client.user.email from at least three countries and three source IPs within a four-hour interval. That pattern can indicate stolen user or service-account credentials reused from multiple regions, including VPN or cloud egress and return trips where first and last locations are close.
Read More -
GCP Vertex AI Caller Impossible Travel
Oct 7, 2026 · Domain: GenAI Domain: Cloud Data Source: GCP Vertex AI Data Source: GCP Data Source: Google Cloud Platform Platform: GCP Service: GCP Vertex AI Use Case: Threat Detection Tactic: Credential Access Tactic: Initial Access Threat: Impossible Travel Threat: LLMjacking Threat: Unauthorized AI Usage Mitre Atlas: AML.T0012 Mitre Atlas: AML.T0091 Mitre Atlas: AML.T0091.000 Resources: Investigation Guide Rule Type: ES|QL ·Detects the same Vertex AI authenticated caller (client.user.email) generating aiplatform audit activity from geographically distant source IPs within a short window at an impossible travel speed. That pattern can indicate a stolen user or service-account credential used from multiple regions. Related: GCP Vertex AI Caller Activity From High Number of Countries covers slower multi-country reuse without a high-speed hop.
Read More -
The organization admin role controls organization settings, integrations, membership, and security configuration in Anthropic Claude for Enterprise. Membership role changes are reported as
claude_user_role_updatedwithanthropic.audit.current_role. An attacker can promote a compromised or newly invited account to org admin to turn initial access into durable control-plane access. From admin, they can disable SSO, mint admin API keys for automation, start data exports, and weaken audit logging. Workspace-scopedrole_assignment_grantedgrants (for example bareadminon a workspace) are out of scope for this rule.
Read More -
Primary ownership is the highest administrative authority in an Anthropic organization, covering billing, membership, and organization-wide settings. Transferring ownership to an attacker-controlled account can lock out the legitimate administrator from recovery paths that depend on the original owner. Attackers often do this after role escalation so defenders cannot reverse earlier privilege changes through normal administration.
Read More -
AWS Bedrock Foundation Model Access Enabled or Entitlement Granted
Oct 7, 2026 · Domain: Cloud Domain: GenAI Data Source: AWS Data Source: AWS CloudTrail Data Source: Amazon Web Services Data Source: AWS Bedrock Data Source: Amazon Bedrock Use Case: Threat Detection Tactic: Persistence Resources: Investigation Guide Noise: Low Performance: Fast Profile: Recommended Threat: Unauthorized AI Usage Rule Type: Custom Query (KQL) Platform: AWS Service: AWS Bedrock Mitre Atlas: AML.T0012 Mitre Atlas: AML.T0040 ·Identifies when access to an Amazon Bedrock foundation model is enabled at the account level, either by granting a foundation-model entitlement, submitting a use case for model access, or creating a foundation-model agreement (accepting the EULA). These account-level "model access" actions unlock a foundation model so that it can subsequently be invoked. Adversaries or a compromised principal may enable model access to abuse expensive models (LLMjacking), to establish a durable ability to invoke models within the account, or to bypass organizational controls. This activity is distinct from changes to a resource-based model invocation policy and is identified by the Bedrock control-plane API calls that grant model entitlements and agreements.
Read More -
AWS Bedrock Unauthorized Foundation Model Access Attempt
Oct 7, 2026 · Domain: Cloud Domain: GenAI Data Source: AWS Data Source: AWS CloudTrail Data Source: Amazon Web Services Data Source: AWS Bedrock Data Source: Amazon Bedrock Use Case: Threat Detection Tactic: Persistence Resources: Investigation Guide Noise: Unknown Performance: Fast Threat: Unauthorized AI Usage Threat: LLMjacking Rule Type: Custom Query (KQL) Platform: AWS Service: AWS Bedrock Mitre Atlas: AML.T0012 Mitre Atlas: AML.T0040 ·Identifies failed, access-denied attempts to enable account-level access to an Amazon Bedrock foundation model, either by granting a foundation-model entitlement, submitting a use case for model access, or creating a foundation-model agreement (accepting the EULA). These account-level "model access" actions unlock a foundation model so that it can subsequently be invoked. A principal that is repeatedly denied when attempting these actions may be a compromised or under-privileged identity probing for the ability to unlock expensive models (LLMjacking) or to establish a durable ability to invoke models. Unlike the companion rule that detects successful model-access grants, this rule surfaces the attempt itself, which is a high-signal indicator of credential boundary-testing even though access was not granted.
Read More -
Microsoft Foundry Subscription Key Impossible Travel
Oct 5, 2026 · Data Source: Microsoft Foundry Use Case: Threat Detection Mitre Atlas: AML.T0091 Mitre Atlas: AML.T0012 Resources: Investigation Guide Tactic: Credential Access Tactic: Initial Access Rule Type: ES|QL Platform: Azure Domain: Cloud Domain: GenAI Service: Azure API Management Threat: Impossible Travel ·Detects the same API Management subscription key calling Microsoft Foundry from source IPs in two or more countries, far enough apart and fast enough that the hop is not physical travel. Calls are grouped by apim_subscription_id. Requests with no subscription key are ignored, because those are unauthenticated calls and share no key.
Read More -
Anthropic User Activity From High Number of Countries
Oct 5, 2026 · Domain: GenAI Domain: Identity Platform: Anthropic Data Source: Anthropic Audit Logs Use Case: Identity and Access Audit Use Case: Threat Detection Resources: Investigation Guide Rule Type: ES|QL Tactic: Credential Access Tactic: Initial Access Mitre Atlas: AML.T0012 Threat: Impossible Travel ·Detects Anthropic activity for the same user email from at least three countries and two unique user agents within a four-hour interval. This highly unusual activity may indicate leaked session cookies being abused by a remote adversary using a VPN.
Read More -
Detects successful Anthropic audit activity where the user agent matches scripting HTTP clients, offensive scanners, or automation libraries (for example curl, python-requests, Go-http-client, axios, nuclei). Browser and first-party Claude clients normally present recognizable browser or product user agents; raw HTTP library agents on successful control-plane or product activity often indicate scripted access, stolen-session reuse, or unauthorized automation. Known benign automation patterns (axios or Go HTTP clients on file upload/delete, trusted device enrollment, and environment creation) are excluded.
Read More -
Detects successful Anthropic magic link or SSO sign-ins for the same user email from source IP addresses whose query-time geo-locations (via IP_LOCATION) are separated by at least 1,000 km, with implied travel faster than 800 km/h, within a 24-hour window. That pattern can indicate account sharing, VPN or proxy egress mismatches, or an adversary authenticating from a geography far from the legitimate user's baseline.
Read More -
Detects when a Claude project owner or editor role is granted through a
role_assignment_grantedevent. Project owners and editors can access project chats, artifacts, and knowledge bases that may hold sensitive data. An attacker with organization access can grant these roles to persist access to high-value project content without holding organization admin privileges.
Read More -
Detects successful Anthropic audit activity for the same user email from source IP addresses whose query-time geo-locations (via IP_LOCATION) span at least two countries, are separated by at least 500 km, and imply travel faster than 800 km/h within a short (~15-minute) lookback. Unlike login-only impossible travel, this rule covers any successful user-actor activity and can surface session cookie replay or concurrent session reuse when no new authentication events appear.
Read More -
AWS Bedrock AgentCore Execution Role Used Outside Its Runtime
Oct 1, 2026 · Domain: Cloud Data Source: AWS Data Source: AWS CloudTrail Data Source: Amazon Web Services Data Source: AWS Bedrock Data Source: Amazon Bedrock Use Case: Threat Detection Tactic: Privilege Escalation Tactic: Credential Access Resources: Investigation Guide Noise: Low Performance: Fast Profile: Recommended Threat: Unauthorized AI Usage Threat: LLMjacking Rule Type: New Terms Platform: AWS Domain: GenAI Service: AWS Bedrock Mitre Atlas: AML.T0012 Mitre Atlas: AML.T0098 ·Identifies an Amazon Bedrock AgentCore execution role (an AssumedRole identity whose role name begins with "AgentCore-" or contains "BedrockAgentCore") making an AWS API call to a service it has not previously called. AgentCore runtimes normally interact only with Bedrock inference, AgentCore data-plane, and observability services (CloudWatch Logs, X-Ray, CloudWatch metrics), so an execution role suddenly calling STS, EC2, IAM, Secrets Manager, or other services is a strong indicator that the role's temporary credentials were exfiltrated from the agent's microVM (for example, via the Code Interpreter instance-metadata-service credential theft) and are being used outside the runtime for reconnaissance, privilege escalation, or lateral movement. Because the stolen credentials are recorded in CloudTrail under the execution role's own identity, the anomalous service usage, not the identity, is the detectable signal.
Read More -
AWS Bedrock AgentCore Resource Created with IAM Execution Role
Oct 1, 2026 · Domain: Cloud Data Source: AWS Data Source: Amazon Web Services Platform: AWS Data Source: AWS CloudTrail Service: AWS Bedrock Service: AWS IAM Tactic: Privilege Escalation Tactic: Persistence Rule Type: Custom Query (KQL) Resources: Investigation Guide Domain: GenAI Mitre Atlas: AML.T0012 Mitre Atlas: AML.T0103 ·Detects the creation of an AWS Bedrock AgentCore resource (code interpreter, agent runtime, browser, or harness) with an IAM execution role attached. When an attacker with iam:PassRole permission creates an AgentCore resource and attaches a privileged role, subsequent invocations inside that resource execute as the attached role — enabling privilege escalation to roles that trust bedrock-agentcore.amazonaws.com.
Read More -
AWS Bedrock API Key Phantom User Activity Outside Bedrock
Oct 1, 2026 · Domain: Cloud Domain: GenAI Data Source: AWS Data Source: AWS CloudTrail Data Source: Amazon Web Services Data Source: AWS IAM Data Source: AWS Bedrock Data Source: Amazon Bedrock Use Case: Threat Detection Tactic: Privilege Escalation Resources: Investigation Guide Noise: Medium Performance: Fast Profile: Recommended Threat: Unauthorized AI Usage Rule Type: Custom Query (KQL) Platform: AWS Service: AWS IAM Service: AWS Bedrock Mitre Atlas: AML.T0012 Mitre Atlas: AML.T0055 ·Identifies an Amazon Bedrock API key phantom user (an IAM user whose name starts with "BedrockAPIKey-") acting as the caller of a non-Bedrock API request, such as IAM, STS, EC2, VPC, or KMS calls. These users are provisioned by AWS to back a Bedrock bearer token and carry the AmazonBedrockLimitedAccess managed policy, which also grants IAM, VPC, and KMS reconnaissance. A phantom user performing activity outside of Bedrock indicates its credentials are being used beyond their intended scope, which is the privilege-escalation path realized: an attacker who created standard IAM access keys for the phantom user is now using them for reconnaissance or lateral movement outside the Bedrock authentication boundary.
Read More -
AWS Bedrock API Key Used for Destructive or Anti-Recovery Action
Oct 1, 2026 · Domain: Cloud Data Source: AWS Data Source: Amazon Web Services Data Source: AWS CloudTrail Data Source: AWS Bedrock Data Source: Amazon Bedrock Use Case: Threat Detection Tactic: Impact Tactic: Defense Evasion Resources: Investigation Guide Noise: Unknown Performance: Normal Profile: Recommended Threat: Unauthorized AI Usage Rule Type: ES|QL Platform: AWS Domain: GenAI Service: AWS Bedrock Mitre Atlas: AML.T0012 ·Identifies an Amazon Bedrock API key (bearer token) being used to perform a destructive or anti-recovery control-plane action, such as deleting a guardrail, deleting a custom or imported model, removing provisioned throughput, or disabling model invocation logging. Bedrock API keys are bearer credentials intended for model invocation (InvokeModel, Converse); using one to delete Bedrock resources or disable logging is inconsistent with that purpose and is characteristic of LLMjacking or sabotage following key theft. Every Bedrock API key call is identifiable in CloudTrail by "additionalEventData.callWithBearerToken" being true. The rule matches regardless of outcome, because a destructive attempt via a bearer token is suspicious even when denied.
Read More -
AWS Bedrock Resource-Based Policy Modified or Deleted
Oct 1, 2026 · Domain: Cloud Domain: GenAI Data Source: AWS Data Source: AWS CloudTrail Data Source: Amazon Web Services Data Source: AWS Bedrock Data Source: Amazon Bedrock Use Case: Identity and Access Audit Resources: Investigation Guide Tactic: Persistence Noise: Unknown Performance: Fast Profile: Recommended Threat: Unauthorized AI Usage Rule Type: New Terms Platform: AWS Service: AWS Bedrock Mitre Atlas: AML.T0012 ·Detects modification or deletion of resource-based access policies on AWS Bedrock resources via the PutResourcePolicy and DeleteResourcePolicy API calls. Resource-based policies govern which principals (including external accounts) may access Bedrock resources such as agents, knowledge bases, and custom models. An adversary may attach a resource policy granting an external or unexpected principal access to a Bedrock resource to establish persistence or enable cross-account access, or may delete an existing policy to weaken access controls. These changes should be validated for principal ownership and least-privilege intent.
Read More -
AWS Bedrock Unauthorized Resource-Based Policy Modification Attempt
Oct 1, 2026 · Domain: Cloud Domain: GenAI Data Source: AWS Data Source: AWS CloudTrail Data Source: Amazon Web Services Data Source: AWS Bedrock Data Source: Amazon Bedrock Use Case: Identity and Access Audit Resources: Investigation Guide Tactic: Persistence Noise: Unknown Performance: Fast Threat: Unauthorized AI Usage Rule Type: Custom Query (KQL) Platform: AWS Service: AWS Bedrock Mitre Atlas: AML.T0012 ·Detects failed, access-denied attempts to modify or delete resource-based access policies on AWS Bedrock resources via the PutResourcePolicy and DeleteResourcePolicy API calls. Resource-based policies govern which principals (including external accounts) may access Bedrock resources such as agents, knowledge bases, and custom models. A principal that is repeatedly denied when attempting to attach or remove these policies may be a compromised or under-privileged identity probing for the ability to grant external or cross-account access, or to weaken existing access controls. Unlike the companion rule that detects successful changes, this rule surfaces the attempt itself, which is a high-signal indicator of credential boundary-testing even though no change occurred.
Read More -
AWS IAM Credentials Added to a Bedrock API Key Phantom User
Oct 1, 2026 · Domain: Cloud Data Source: AWS Data Source: Amazon Web Services Data Source: AWS IAM Data Source: AWS Bedrock Data Source: Amazon Bedrock Use Case: Threat Detection Tactic: Privilege Escalation Tactic: Persistence Resources: Investigation Guide Noise: Unknown Performance: Fast Profile: Recommended Threat: Unauthorized AI Usage Rule Type: ES|QL Platform: AWS Domain: GenAI Service: AWS IAM Service: AWS Bedrock Mitre Atlas: AML.T0012 ·Identifies standard IAM credentials being added to an Amazon Bedrock API key phantom user, whose user name starts with "BedrockAPIKey-": either a long-term access key (CreateAccessKey) or a console password / login profile (CreateLoginProfile, UpdateLoginProfile). When a long-term Bedrock API key is generated through the AWS Console, AWS silently provisions a "BedrockAPIKey-
" IAM user with the AmazonBedrockLimitedAccess managed policy. That user is intended only to back a Bedrock bearer token and should never hold standard programmatic keys or interactive console access. Adding either converts a Bedrock-scoped identity into general-purpose IAM credentials that inherit the policy's Bedrock control-plane and IAM, VPC, and KMS reconnaissance permissions and that persist after the Bedrock API key is revoked. This is the privilege-escalation and persistence pivot documented for Bedrock API key phantom users, and there is no legitimate workflow that produces it.
Read More