hermes-profiles

Systematically audit AWS S3 bucket permissions to identify publicly accessible buckets, overly permissive ACLs, misconfigured bucket policies, and missing encryption settings using AWS CLI, S3audit, and Prowler to enforce least-privilege data access controls.

Auditing Microsoft Entra ID (Azure Active Directory) configuration to identify risky authentication policies, overly permissive role assignments, stale accounts, conditional access gaps, and guest user risks using AzureAD PowerShell, Microsoft Graph API, and ScoutSuite.

This skill details how to conduct cloud security audits using Center for Internet Security benchmarks for AWS, Azure, and GCP. It covers interpreting CIS Foundations Benchmark controls, running automated assessments with tools like Prowler and ScoutSuite, remediating failed controls, and maintaining continuous compliance monitoring against CIS v5 for AWS, v4 for Azure, and v4 for GCP.

Auditing Google Cloud Platform IAM permissions to identify overly permissive bindings, primitive role usage, service account key proliferation, and cross-project access risks using gcloud CLI, Policy Analyzer, and IAM Recommender.

Auditing Kubernetes cluster RBAC configurations to identify overly permissive roles, wildcard permissions, dangerous ClusterRoleBindings, service account abuse, and privilege escalation paths using kubectl, rbac-tool, KubiScan, and Kubeaudit.

Auditing Terraform infrastructure-as-code for security misconfigurations using Checkov, tfsec, Terrascan, and OPA/Rego policies to detect overly permissive IAM policies, public resource exposure, missing encryption, and insecure defaults before cloud deployment.

Detect unusual API call patterns in AWS CloudTrail logs using boto3, statistical baselining, and behavioral analysis to identify credential compromise, privilege escalation, and unauthorized resource access.

Detecting exposed AWS credentials in source code repositories, CI/CD pipelines, and configuration files using TruffleHog, git-secrets, and AWS-native detection mechanisms to prevent credential theft and unauthorized account access.

Automate AWS GuardDuty threat detection findings processing using EventBridge and Lambda to enable real-time incident response, automatic quarantine of compromised resources, and security notification workflows.

Detect AWS IAM privilege escalation paths using boto3 and Cloudsplaining policy analysis to identify overly permissive policies, dangerous permission combinations, and least-privilege violations

Detect lateral movement in Azure AD/Entra ID environments using Microsoft Graph API audit logs, Azure Sentinel KQL hunting queries, and sign-in anomaly correlation to identify privilege escalation, token theft, and cross-tenant pivoting.

Detect and investigate Azure service principal abuse including privilege escalation, credential compromise, admin consent bypass, and unauthorized enumeration in Microsoft Entra ID environments.

Audit Azure Blob and ADLS storage accounts for public access exposure, weak or long-lived SAS tokens, missing encryption at rest, disabled HTTPS-only traffic, and outdated TLS versions using the azure-mgmt-storage Python SDK.

This skill teaches security teams how to deploy and operationalize Amazon GuardDuty for continuous threat detection across AWS accounts and workloads. It covers enabling protection plans for S3, EKS, EC2 runtime monitoring, and Lambda, interpreting finding severity levels, and building automated response workflows using EventBridge and Lambda.

Detect unauthorized modifications to running containers by monitoring for binary execution drift, file system changes, and configuration deviations from the original container image.

Container escape is a critical attack technique where an adversary breaks out of container isolation to access the host system or other containers. Detection involves monitoring for escape indicators

Detect container escape attempts in real-time using Falco runtime security rules that monitor syscalls, file access, and privilege escalation.

This skill teaches security teams how to detect and respond to unauthorized cryptocurrency mining operations in cloud environments. It covers identifying cryptomining indicators through compute usage anomalies, network traffic patterns to mining pools, GuardDuty CryptoCurrency findings, and runtime process monitoring on EC2, ECS, EKS, and Azure Automation workloads.

Detecting data exfiltration attempts from AWS S3 buckets by analyzing CloudTrail S3 data events, VPC Flow Logs, GuardDuty findings, Amazon Macie alerts, and S3 access patterns to identify unauthorized bulk downloads and cross-account data transfers.

Detects and prevents code injection attacks targeting serverless functions (AWS Lambda, Azure Functions, Google Cloud Functions) through event source poisoning, malicious layer injection, runtime command execution, and IAM privilege escalation via function modification. The analyst combines static analysis of function code, CloudTrail event correlation, runtime behavior monitoring, and IAM policy auditing to identify injection vectors across the expanded serverless attack surface including API Gateway, S3, SQS, DynamoDB Streams, and CloudWatch event triggers. Activates for requests involving Lambda security assessment, serverless injection detection, function event poisoning analysis, or serverless privilege escalation investigation.

Scans GitHub Actions workflows and CI/CD pipeline configurations for supply chain attack vectors including unpinned actions, script injection via expressions, dependency confusion, and secrets exposure. Uses PyGithub and YAML parsing for automated audit. Use when hardening CI/CD pipelines or investigating compromised build systems.

Hardening Docker containers for production involves applying security best practices aligned with CIS Docker Benchmark v1.8.0 to minimize attack surface, prevent privilege escalation, and enforce leas

Harden the Docker daemon by configuring daemon.json with user namespace remapping, TLS authentication, rootless mode, and CIS benchmark controls.

Hardens Linux endpoints using CIS Benchmark recommendations for Ubuntu, RHEL, and CentOS to reduce attack surface, enforce security baselines, and meet compliance requirements. Use when deploying new Linux servers, remediating audit findings, or establishing security baselines for Linux infrastructure. Activates for requests involving Linux hardening, CIS benchmarks for Linux, server security baselines, or Linux configuration compliance.

Hardens Windows endpoints using CIS (Center for Internet Security) Benchmark recommendations to reduce attack surface, enforce security baselines, and meet compliance requirements. Use when deploying new Windows workstations or servers, remediating audit findings, or establishing organization-wide security baselines. Activates for requests involving Windows hardening, CIS benchmarks, GPO security baselines, or endpoint configuration compliance.

Hunt for adversary abuse of legitimate cloud services for C2, data staging, and exfiltration including abuse of Azure, AWS, GCP services, and SaaS platforms.

Hunt for supply chain compromise indicators including trojanized software updates, compromised dependencies, unauthorized code modifications, and tampered build artifacts.

Implement API abuse detection using token bucket, sliding window, and adaptive rate limiting algorithms to prevent DDoS, brute force, and credential stuffing attacks.

Implements security controls at the API gateway layer including authentication enforcement, rate limiting, request validation, IP allowlisting, TLS termination, and threat protection. The engineer configures API gateways (Kong, AWS API Gateway, Azure APIM, Apigee) to act as a centralized security enforcement point that validates, throttles, and monitors all API traffic before it reaches backend services. Activates for requests involving API gateway security, API management security, gateway authentication, or centralized API protection.

Implements secure API key generation, storage, rotation, and revocation controls to protect API authentication credentials from leakage, brute force, and abuse. The engineer designs API key formats with sufficient entropy, implements secure hashing for storage, enforces per-key scoping and rate limiting, monitors for leaked keys in public repositories, and builds key rotation workflows. Activates for requests involving API key management, API key security, key rotation policy, or API credential protection.

Implements API rate limiting and throttling controls using token bucket, sliding window, and fixed window algorithms to protect against brute force attacks, credential stuffing, resource exhaustion, and API abuse. The engineer configures per-user, per-IP, and per-endpoint rate limits using Redis-backed counters, API gateway plugins, or application middleware, and implements proper HTTP 429 responses with Retry-After headers. Activates for requests involving rate limiting implementation, API throttling setup, request quota management, or API abuse prevention.

Implement API schema validation using OpenAPI specifications and JSON Schema to enforce input/output contracts and prevent injection, data exposure, and mass assignment attacks.

Implement comprehensive API security testing using the 42Crunch platform to perform static audit and dynamic conformance scanning of OpenAPI specifications.

Implement API threat protection using Google Apigee policies including JSON/XML threat protection, OAuth 2.0, SpikeArrest, and Advanced API Security for OWASP Top 10 defense.

Implements application whitelisting using Windows AppLocker to restrict unauthorized software execution on endpoints, reducing attack surface from malware, unauthorized tools, and shadow IT. Use when enforcing application control policies, meeting compliance requirements for software restriction, or preventing execution of unsigned or untrusted binaries. Activates for requests involving AppLocker, application whitelisting, software restriction, or executable control.

Implementing AWS Config rules for continuous compliance monitoring of AWS resources, deploying managed and custom rules aligned to CIS and PCI DSS frameworks, configuring automatic remediation with SSM Automation, and aggregating compliance data across accounts.

Configure IAM permission boundaries in AWS to delegate role creation to developers while enforcing maximum privilege limits set by the security team.

Implement Amazon Macie to automatically discover, classify, and protect sensitive data in S3 buckets using machine learning and pattern matching for PII, financial data, and credentials detection.

Implements AWS Nitro Enclave-based confidential computing environments with cryptographic attestation, KMS policy integration using PCR-based condition keys, and secure vsock communication channels. The practitioner builds enclave images, configures attestation-aware KMS policies, validates attestation documents against the AWS Nitro PKI root of trust, and establishes isolated computation pipelines for processing sensitive data such as PII, cryptographic keys, and healthcare records. Activates for requests involving Nitro Enclave setup, enclave attestation validation, confidential computing on AWS, or KMS enclave policy configuration.

Implementing AWS Security Hub to aggregate security findings across AWS accounts, enable compliance standards like CIS AWS Foundations and PCI DSS, configure automated remediation with EventBridge and Lambda, and create custom security insights for organizational risk management.