Closed
Conversation
Created detailed analysis of current and recommended loot files across all Azure CloudFox modules (whoami, inventory, rbac, storage, vms). Analysis includes: - Current loot file implementation status (2/5 modules) - 15+ recommended new loot files with actionable content - Detailed implementation guidance with code examples - Priority-based TODO list with 20+ tasks - 4-phase implementation roadmap Focus on actionable items: commands to execute, secrets/credentials, public IPs with access commands, privilege escalation paths, and enumeration next steps.
Analyzed all modules in azure/commands/ directory. KEY FINDINGS: - 64/72 modules (88.9%) already have loot files - EXCELLENT - 261 existing loot files across the codebase - Only 8 modules missing loot files (critical gaps) MODULES WITHOUT LOOT FILES: 🔴 CRITICAL (4): 1. aks.go - Kubernetes credential extraction 2. storage.go - Storage keys/SAS token commands 3. rbac.go - High-privilege RBAC enumeration 4. permissions.go - Dangerous permission abuse 🟡 HIGH (4): 5. federated-credentials.go - OIDC/GitHub exploitation 6. consent-grants.go - OAuth consent abuse 7. devops-agents.go - Agent token extraction 8. conditional-access.go - CA policy bypass TOP MODULES (Champions with 10 loot files): - vms.go - VM exploitation, snapshots, extensions - arc.go - Hybrid connectivity, certificates - automation.go - Runbooks, hybrid workers IMPLEMENTATION PLAN: - Phase 1 (Week 1-2): 4 critical modules, ~23 loot files - Phase 2 (Week 3): 4 high-priority modules, ~18 loot files - Total: ~40 new loot files to achieve 100% coverage Files: - docs/azure-loot-analysis/analysis.md - Comprehensive findings - docs/azure-loot-analysis/todo.md - Implementation roadmap
Implemented actionable loot file generation for 4 critical Azure security assessment modules. Loot files provide ready-to-execute commands, privilege escalation paths, and remediation guidance. Changes: - rbac.go: Added 4 loot files (high-privilege roles, service principals, enumeration commands, privilege escalation) - permissions.go: Added 4 loot files (dangerous permissions, service principal permissions, enumeration, privilege escalation paths) - consent-grants.go: Added 4 loot files (risky grants, external apps, user consent, remediation commands) - conditional-access.go: Added 4 loot files (weak policies, coverage gaps, bypass opportunities, remediation) Each module now generates context-aware loot files containing: - Specific attack/exploitation commands - Investigation and enumeration commands - Privilege escalation techniques based on discovered permissions - Remediation and hardening guidance Total: 16 loot file types across 4 modules, ~2500 lines of security-focused code
Comprehensive analysis of all Azure CloudFox loot files to identify non-actionable content that should be moved to standard output. Key findings: - 95%+ of loot files are properly actionable (commands/credentials/URLs) - Identified 5 non-actionable loot files that should be removed: 1. routes.go: route-custom-routes (just lists routes) 2. nsg.go: nsg-open-ports (just lists ports, redundant with nsg-targeted-scans) 3. arc.go: arc-machines (reformats table data) 4. arc.go: arc-identities (lists identity GUIDs) 5. hdinsight.go: hdinsight-identities (lists identity info) Documented decision criteria for actionable vs informational data: - Actionable: Commands, credentials, URLs, exploitation techniques - Informational: Simple lists, inventory, status, reformatted table data Provided specific code locations and examples for each finding. Included extensive examples of properly actionable loot files to keep. Recommendation: Remove 5 loot files to improve signal-to-noise ratio while keeping all 195+ actionable loot files unchanged.
Implemented Phase 1 of loot file cleanup recommendations to remove non-actionable loot files that contain simple lists/inventory data instead of actionable commands, credentials, or exploitation techniques. Files modified: - routes.go: Removed route-custom-routes (just listed route details) - nsg.go: Removed nsg-open-ports (duplicated data, nsg-targeted-scans has commands) - arc.go: Removed arc-machines and arc-identities (reformatted table data) - hdinsight.go: Removed hdinsight-identities (just listed identity GUIDs) All changes: - Removed loot file entries from LootMap initialization - Removed loot file content generation code - Auto-formatted files with gofmt for proper syntax Impact: - Reduces noise in loot file output - Keeps loot files focused on actionable security data only - Maintains all 195+ actionable loot files unchanged - No loss of information - data still in standard table output Related: docs/azure-loot-analysis/loot-cleanup-recommendations.md
Added comprehensive, realistic multi-step exploitation examples to aks-pod-exec-commands loot file: SCENARIO 1: Automated Privilege Escalation Chain - Complete workflow that automatically enumerates all pods - Extracts service account tokens from running pods - Tests each token's permissions against Kubernetes API - Identifies tokens that can list secrets (high-value targets) - No more generic placeholders - real automation scripts SCENARIO 2: Container Escape via Privileged Pod - Complete pod manifest for container escape - Includes hostNetwork, hostPID, and privileged settings - Mounts host root filesystem at /host - Provides chroot command for immediate host access Benefits: - Replaces generic <POD-NAME> placeholders with actual enumeration - Provides copy-paste ready exploitation workflows - Demonstrates realistic attack chains - Shows how to pivot from pod access to cluster compromise Related: Phase 2 Enhancement - Add detailed exploitation examples
Added three complete exploitation scenarios to storage loot files: 1. Automated bulk data exfiltration using azcopy with SAS token generation 2. Soft-deleted blob recovery for deleted data forensics 3. Connection string extraction from web apps/functions to find storage credentials Replaces basic SAS token examples with full end-to-end attack chains.
Added four complete database exploitation scenarios: 1. Automated SQL Database data extraction with credential retrieval from Key Vault 2. PostgreSQL/MySQL data exfiltration using connection strings from App Services 3. CosmosDB data extraction via REST API with master keys 4. Automated credential harvesting from Key Vaults, App Services, and Function Apps Each scenario includes complete workflows from credential discovery through firewall manipulation, database connection, data extraction, and cleanup.
…nbTDxXvATUGKXmoU91 Claude/cloudfox azure new 01 qlt tnb t dx xv atugk xmo u91
Identified 7 high-value Azure modules that would benefit from enhanced exploitation scenarios: High Priority (7-9/10): - vms.go (9/10): VM takeover, disk snapshots, password resets - keyvaults.go (9/10): Credential harvesting, soft-deleted secret recovery - webapps.go (8/10): Kudu exploitation, connection strings, backups - databricks.go (8/10): Notebook secret scanning, cluster hijacking - functions.go (7/10): Master key extraction, code download - automation.go (7/10): Hybrid worker compromise, runbook exploitation Medium Priority (5-6/10): - logicapps.go (6/10): Workflow analysis, API connections Includes detailed enhancement potential, example scenarios, and estimated effort for each module. Total estimated effort: 15-22 hours for all 7 modules.
Created three key documents: 1. **gold-standard-analysis.md** (20KB) - Detailed analysis of acr.go, vms.go, storage.go, aks.go - Gold standard patterns for all 8 aspects (entry point, struct, processing, etc.) - Complete compliance checklist - Anti-patterns to avoid - Migration path with effort estimates 2. **audit-results.md** (6KB) - Automated compliance audit of all 72 Azure modules - Pattern-by-pattern scoring (InitCtx, BaseModule, RunSubEnum, etc.) - Categorization: COMPLIANT (44), PARTIAL (14), NON-COMPLIANT (8) 3. **audit-summary-and-plan.md** (13KB) - Executive summary: 61% already compliant! - 3-phase implementation plan (3 weeks, 42.5 hours) - Phase 1: Quick wins (14 modules, 10.5 hours) - Phase 2: DevOps overhaul (6 modules, 23 hours) - Phase 3: Final cleanup (4 modules, 9 hours) - Detailed risk mitigation and testing strategy Key Findings: - 44 modules (61%) fully compliant - NO WORK NEEDED - 14 modules (19%) need minor updates (1-3 patterns) - 8 modules (11%) need major refactor (DevOps suite + 2 others) - Total effort: 42.5 hours to achieve 100% standardization - Expected code reduction: ~65,000 lines across 24 modules Ready for implementation with clear prioritization and effort estimates.
…nbTDxXvATUGKXmoU91 Claude/cloudfox azure new 01 qlt tnb t dx xv atugk xmo u91
This file contains hidden or bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment
2 participants
Add this suggestion to a batch that can be applied as a single commit.This suggestion is invalid because no changes were made to the code.Suggestions cannot be applied while the pull request is closed.Suggestions cannot be applied while viewing a subset of changes.Only one suggestion per line can be applied in a batch.Add this suggestion to a batch that can be applied as a single commit.Applying suggestions on deleted lines is not supported.You must change the existing code in this line in order to create a valid suggestion.Outdated suggestions cannot be applied.This suggestion has been applied or marked resolved.Suggestions cannot be applied from pending reviews.Suggestions cannot be applied on multi-line comments.Suggestions cannot be applied while the pull request is queued to merge.Suggestion cannot be applied right now. Please check back later.
Card
GCP rework
Details
GCP rework and initialization