Account Use Policies help mitigate unauthorized access by configuring and enforcing rules that govern how and when accounts can be used. These policies include enforcing account lockout mechanisms, restricting login times, and setting inactivity timeouts. Proper configuration of these policies reduces the risk of brute-force attacks, credential theft, and unauthorized access by limiting the opportunities for malicious actors to exploit accounts. This mitigation can be implemented through the following measures: Account Lockout Policies: - Implementation: Configure account lockout settings so that after a defined number of failed login attempts (e.g., 3-5 attempts), the account is locked for a specific time period (e.g., 15 minutes) or requires an administrator to unlock it. - Use Case: This prevents brute-force attacks by limiting how many incorrect password attempts can be made before…
MITRE mitigation sourceAdversaryGraph public intelligence page
This page is part of Threat Matrix, the public browser workspace for the main AdversaryGraph platform. Use it for ATT&CK pivots, actor and technique context, similarity leads, detection coverage review, and analyst-ready investigation paths.
Validation disclaimer: TTP overlap, actor similarity, generated summaries, and coverage findings are investigation leads, not attribution proof or operational validation without analyst review.
Main AdversaryGraph project Documentation Malware Analysis GitHub
Serverless Execution
Adversaries may abuse serverless computing, integration, and automation services to execute arbitrary code in cloud environments. Many cloud providers offer a variety of serverless resources, including compute engines, application integration services, and web servers. Adversaries may abuse these resources in various ways as a means of executing arbitrary commands. For example, adversaries may use serverless functions to execute malicious code, such as crypto-mining malware (i.e. Resource Hijacking). Adversaries may also create functions that enable further compromise of the cloud environment. For example, an adversary may use the `IAM:PassRole` permission in AWS or the `iam.serviceAccounts.actAs` permission in Google Cloud to add Additional Cloud Roles to a serverless cloud function, which may then be able to perform actions the original user cannot. Serverless functions can also be invoked in response to cloud events (i.e. Event Triggered Execution), potentially enabling persistent execution over time. For example, in AWS environments, an adversary may create a Lambda function that automatically adds Additional Cloud Credentials to a user and a corresponding CloudWatch events rule that invokes that function whenever a new user is created. This is also possible in many cloud-based office application suites. For example, in Microsoft 365 environments, an adversary may create a Power Automate workflow that forwards all emails a user receives or creates anonymous sharing links whenever a user is granted access to a document in SharePoint. In Google Workspace environments, they may instead create an Apps Script that exfiltrates a user's data when they open a file.
Open detection, hunting, mitigation, and evidence workspace
Detection logic
Use behavior-focused telemetry and validate findings against surrounding activity.
Observed actors
Correlated CTI and IR reports
Cyber Knowledge context
Use these routes to move from the ATT&CK behavior into explanation, implementation, evidence handling, validation, and defensive operations. Relevance is generated from explicit identifiers/names and governed topic mappings; it is not attribution evidence.
Vulnerability Research & Exploit Development · Governed topic match · 57/100Module 5 — Cloud, containers, and Kubernetes
Red Team & Offensive Security · Tactic learning route · 24/100Static triage: strings, imports, resources, and capabilities
Malware Analysis & Reverse Engineering · Tactic learning route · 24/100Module 4 — Detection engineering and detection as code
Blue Team & Defensive Security · Tactic learning route · 24/100
MITRE mitigations
User Account Management involves implementing and enforcing policies for the lifecycle of user accounts, including creation, modification, and deactivation. Proper account management reduces the attack surface by limiting unauthorized access, managing account privileges, and ensuring accounts are used according to organizational policies. This mitigation can be implemented through the following measures: Enforcing the Principle of Least Privilege - Implementation: Assign users only the minimum permissions required to perform their job functions. Regularly audit accounts to ensure no excess permissions are granted. - Use Case: Reduces the risk of privilege escalation by ensuring accounts cannot perform unauthorized actions. Implementing Strong Password Policies - Implementation: Enforce password complexity requirements (e.g., length, character types). Require password expiration every 90…
MITRE mitigation sourceMITRE detection strategies and analytics
- AN1053 · Analytic 1053 — Correlate creation or modification of serverless functions (e.g., AWS Lambda, GCP Cloud Functions, Azure Functions) with anomalous IAM role assignments or permissions escalation events. Detect subsequent executions of newly created functions that perform unexpected actions such as spawning outbound network connections, accessing sensitive resources, or creating additional credentials.
- AN1054 · Analytic 1054 — Monitor for creation of new Power Automate flows or equivalent automation scripts that trigger on user or file events. Detect anomalous actions performed by these automations, such as email forwarding, anonymous link creation, or unexpected API calls to external endpoints.
- AN1055 · Analytic 1055 — Track creation or update of SaaS automation scripts (e.g., Google Workspace Apps Script). Detect when these scripts are bound to user events such as file opens or account modifications, and correlate with subsequent abnormal API calls that exfiltrate or modify user data.