feat: enrich 209 skills with MITRE ATLAS, D3FEND, and NIST AI RMF frontmatter

Added structured security framework mappings to SKILL.md frontmatter across all applicable skills:
- atlas_techniques: MITRE ATLAS v5.5 AML.TXXXX IDs (81 skills, AI-targeted attack techniques)
- d3fend_techniques: MITRE D3FEND v1.3 defensive technique labels (139 skills, mapped from ATT&CK IDs)
- nist_ai_rmf: NIST AI RMF 1.0 subcategory IDs (85 skills, AI risk management functions)

Also updates ATTACK_COVERAGE.md with coverage statistics for all three frameworks.

skills/analyzing-cloud-storage-access-patterns/SKILL.md

@@ -1,16 +1,25 @@
 ---
 name: analyzing-cloud-storage-access-patterns
-description: >-
-  Detect abnormal access patterns in AWS S3, GCS, and Azure Blob Storage by analyzing CloudTrail
-  Data Events, GCS audit logs, and Azure Storage Analytics. Identifies after-hours bulk downloads,
-  access from new IP addresses, unusual API calls (GetObject spikes), and potential data exfiltration
-  using statistical baselines and time-series anomaly detection.
+description: Detect abnormal access patterns in AWS S3, GCS, and Azure Blob Storage by analyzing CloudTrail Data Events, GCS
+  audit logs, and Azure Storage Analytics. Identifies after-hours bulk downloads, access from new IP addresses, unusual API
+  calls (GetObject spikes), and potential data exfiltration using statistical baselines and time-series anomaly detection.
 domain: cybersecurity
 subdomain: cloud-security
-tags: [analyzing, cloud, storage, access]
-version: "1.0"
+tags:
+- analyzing
+- cloud
+- storage
+- access
+version: '1.0'
 author: mahipal
 license: Apache-2.0
+atlas_techniques:
+- AML.T0024
+- AML.T0056
+nist_ai_rmf:
+- MEASURE-2.7
+- MAP-5.1
+- MANAGE-2.4
 ---