xalgord Hunting For Living Off The Cloud Techniques
When to Use
- When proactively hunting for indicators of hunting for living off the cloud techniques in the environment
- After threat intelligence indicates active campaigns using these techniques
- During incident response to scope compromise related to these techniques
- When EDR or SIEM alerts trigger on related indicators
- During periodic security assessments and purple team exercises
Detection Gaps & Validation
- Reputation-based detection is useless here. C2 over trusted SaaS — Discord/Slack/Telegram webhooks, Microsoft Graph API, Google Drive, Notion, Pastebin — terminates at high-reputation domains your allowlists already trust (T1102/T1567/T1537). Block volume/beacon-timing analysis and JA3/JARM, not domain reputation.
- OAuth/refresh-token abuse leaves no malware on disk; the access looks like a normal API client.
- Cloud-native C2 (Azure Functions, AWS Lambda) originates from provider IP ranges indistinguishable from legitimate cloud egress.
- TLS hides the payload — without inspection you only have destination + timing; lean on periodicity/jitter analysis to surface beacons to SaaS endpoints.
- Validate the hunt fires: simulate exfil to a Telegram bot (
api.telegram.org/bot.../sendDocument) or a Graph API upload, then confirm EDR/proxy network telemetry and your beacon-detection logic flag the periodic SaaS traffic. - FP tuning: legitimate corporate use of the exact same SaaS. Baseline per-user/per-host normal destinations and data volume, and alert on deviation rather than the service itself.
Prerequisites
- EDR platform with process and network telemetry (CrowdStrike, MDE, SentinelOne)
- SIEM with relevant log data ingested (Splunk, Elastic, Sentinel)
- Sysmon deployed with comprehensive configuration
- Windows Security Event Log forwarding enabled
- Threat intelligence feeds for IOC correlation
Workflow
- Formulate Hypothesis: Define a testable hypothesis based on threat intelligence or ATT&CK gap analysis.
- Identify Data Sources: Determine which logs and telemetry are needed to validate or refute the hypothesis.
- Execute Queries: Run detection queries against SIEM and EDR platforms to collect relevant events.
- Analyze Results: Examine query results for anomalies, correlating across multiple data sources.
- Validate Findings: Distinguish true positives from false positives through contextual analysis.
- Correlate Activity: Link findings to broader attack chains and threat actor TTPs.
- Document and Report: Record findings, update detection rules, and recommend response actions.
Key Concepts
| Concept | Description |
|---|---|
| T1102 | Web Service |
| T1567 | Exfiltration Over Web Service |
| T1537 | Transfer Data to Cloud Account |
Tools & Systems
| Tool | Purpose |
|---|---|
| CrowdStrike Falcon | EDR telemetry and threat detection |
| Microsoft Defender for Endpoint | Advanced hunting with KQL |
| Splunk Enterprise | SIEM log analysis with SPL queries |
| Elastic Security | Detection rules and investigation timeline |
| Sysmon | Detailed Windows event monitoring |
| Velociraptor | Endpoint artifact collection and hunting |
| Sigma Rules | Cross-platform detection rule format |
Common Scenarios
- Scenario 1: C2 over Discord webhooks for command delivery
- Scenario 2: Data exfiltration to Telegram bot API
- Scenario 3: Malware using Azure Functions for dynamic C2
- Scenario 4: Staging stolen data on Google Docs or Notion pages
Output Format
Hunt ID: TH-HUNTIN-[DATE]-[SEQ]
Technique: T1102
Host: [Hostname]
User: [Account context]
Evidence: [Log entries, process trees, network data]
Risk Level: [Critical/High/Medium/Low]
Confidence: [High/Medium/Low]
Recommended Action: [Containment, investigation, monitoring]