Claude 24f816b6a3
Consolidate 22 sibling repos into layered organism structure
Place useful parts of the surrounding repos into sica-fondt by layer, per the
body model (Ada = membrane; brain/endocrine/capabilities/knowledge non-Ada):

- brain/        LLM reasoning + providers (dapr, hermes, MoMoA)
- capabilities/ REPRAG sidecars: hermes tools/skills, dapr tools, parallel
                dispatch, A51 channels, and the OSINT cluster
- knowledge/    LORAG corpus: 754 cyber-skills, agency personas, secure-coding,
                MITRE ATT&CK data
- reference/    defensive threat-reference (C3, shhbruh doc) + AdaYaml parser

License handling: AGPL sources (worldosint, advanced_evolution, mercury,
Reticulum) and GPL DeTTECT are SPEC-only clean-room/port descriptions — no
copyleft code copied. MIT/Apache/data parts copied as working trees.

Safety: shhbruh escape/persistence material and C3 covert-C2 kept as reference
only, not wired into the running organism. See CONSOLIDATION.md.

https://claude.ai/code/session_01UehUqEXXJJCsHoA4voCU5c
2026-06-10 06:53:01 +00:00

2.6 KiB

name description domain subdomain tags version author license nist_ai_rmf atlas_techniques nist_csf
detecting-azure-storage-account-misconfigurations 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for public access exposure, weak or long-lived SAS tokens, missing encryption at rest, disabled HTTPS-only traffic, and outdated TLS versions using the azure-mgmt-storage Python SDK. cybersecurity cloud-security
Azure
storage-accounts
blob-storage
ADLS
SAS-tokens
encryption
public-access
cloud-misconfiguration
azure-mgmt-storage
1.0 mahipal Apache-2.0
MEASURE-2.7
MAP-5.1
MANAGE-2.4
AML.T0070
AML.T0066
AML.T0082
PR.IR-01
ID.AM-08
GV.SC-06
DE.CM-01

Detecting Azure Storage Account Misconfigurations

Overview

Azure Storage accounts are a frequent target for attackers due to misconfigured public access, long-lived SAS tokens, missing encryption, and outdated TLS versions. This skill uses the azure-mgmt-storage Python SDK with StorageManagementClient to enumerate all storage accounts in a subscription, inspect their security properties, list blob containers for public access settings, and generate a risk-scored audit report identifying critical misconfigurations.

When to Use

  • When investigating security incidents that require detecting azure storage account misconfigurations
  • When building detection rules or threat hunting queries for this domain
  • When SOC analysts need structured procedures for this analysis type
  • When validating security monitoring coverage for related attack techniques

Prerequisites

  • Python 3.9+ with azure-mgmt-storage, azure-identity
  • Azure service principal with Reader role on target subscription
  • Environment variables: AZURE_CLIENT_ID, AZURE_TENANT_ID, AZURE_CLIENT_SECRET, AZURE_SUBSCRIPTION_ID

Key Detection Areas

  1. Public blob accessallow_blob_public_access enabled on storage account or individual containers set to Blob/Container access level
  2. HTTPS enforcementenable_https_traffic_only disabled, allowing unencrypted HTTP traffic
  3. Minimum TLS version — accounts accepting TLS 1.0 or TLS 1.1 instead of minimum TLS 1.2
  4. Encryption at rest — storage service encryption not enabled or missing customer-managed keys
  5. Network rules — default action set to Allow instead of Deny, exposing storage to all networks
  6. SAS token risks — account-level SAS with overly broad permissions or excessive lifetime

Output

JSON report with per-account findings, severity ratings (Critical/High/Medium/Low), and remediation recommendations aligned with CIS Azure Benchmark controls.