Vibe Hacking: AI-Driven Data Extortion

Query 1: Detecting AI-Generated Tunneling Tools Masquerading

• Behavior Targeted: Masquerading a custom TCP proxy or obfuscated Chisel binary as a legitimate Microsoft binary (MSBuild.exe, devenv.exe, cl.exe) to evade detection.
• MITRE ATT&CK: T1036
• Expected Results: High-fidelity alerts on binaries that share the name of a known development tool but are executed from a non-standard system path.
• False Positive Likelihood: Medium – Legitimate software often runs development tools, but path and execution context should make tuning simple.

Splunk (SPL)

// Query description: Detect process creation where the process name is a common Microsoft dev tool 
// but the execution path is not a known, legitimate system directory.
// Tuning guidance: Exclude known, trusted paths (e.g., all Visual Studio, system32, .NET Framework paths).
index=winsecurity sourcetype=sysmon_process_create OR index=edr_logs 
| rename CommandLine as cmd, Image as process_path, ParentImage as parent_process
| where match(process_path, "(?i)cl\.exe$|(?i)devenv\.exe$|(?i)msbuild\.exe$") 
    AND NOT match(process_path, "(?i)C:\\(Windows|Program Files|Microsoft\.NET)")
| table _time, host, user, process_path, cmd, parent_process
              

Microsoft Defender/Sentinel (KQL)

// Query description: Search DeviceProcessEvents for common development tools executed from suspicious paths.
// Data Tables: DeviceProcessEvents
// Tuning guidance: Refine the NOT IN list with known, approved paths in your organization's environment.
DeviceProcessEvents
| where FileName in ("msbuild.exe", "devenv.exe", "cl.exe")
| where not(FolderPath has_any("Program Files", @"C:\Windows\Microsoft.NET", @"C:\Program Files (x86)\Microsoft Visual Studio"))
| project Timestamp, DeviceName, InitiatingProcessFileName, FolderPath, ProcessCommandLine, AccountName
| order by Timestamp desc
              

Query 2: Detecting AI-Augmented Credential Harvesting / Enumeration

• Behavior Targeted: Automated password spraying or systematic credential enumeration (Kerberos attacks) followed by rapid access to multiple critical assets.
• MITRE ATT&CK: T1558
• Expected Results: A cluster of unsuccessful logon attempts (Event ID 4625) immediately preceding a successful logon (Event ID 4624) to a critical server.
• False Positive Likelihood: Low – A high-volume, rapid failure/success pattern targeting critical infrastructure is usually malicious.

Splunk (SPL)

// Query description: Correlate multiple logon failures (4625) to a single successful logon (4624) within a short window.
// Tuning guidance: Adjust the 'fail_count' and time range (e.g., 30 minutes) based on acceptable baseline for your environment.
index=winsecurity EventCode=4625 | stats count as fail_count by IpAddress | rename IpAddress as source_ip 
| where fail_count > 100 // High volume failure threshold
| join source_ip [
    search index=winsecurity EventCode=4624 // Successful logon
    | where LogonType IN (2, 3, 10) // Interactive, Network, RemoteInteractive
    | fields _time, source_ip, TargetUserName
]
| eval time_diff = abs(_time - relative_time(now(), "-30m")) 
| where time_diff < 1800 // Within 30 minutes (1800 seconds)
| table _time, source_ip, TargetUserName, fail_count
| sort - fail_count
                

Microsoft Defender/Sentinel (KQL)

// Query description: Identify IP addresses with a high number of failed logons followed by success within a short time frame.
// Data Tables: SecurityEvent, DeviceLogonEvents
// Tuning guidance: Baseline failed logon thresholds (EventID 4625) and ensure logons are to high-value targets (e.g., Domain Controllers).
let failed_logons = SecurityEvent
| where EventID == 4625
| summarize FailedAttempts = count() by IpAddress, bin(TimeGenerated, 1h);

let successful_logons = DeviceLogonEvents
| where LogonType in ("Interactive", "Network", "RemoteInteractive")
| summarize Successes = count() by IpAddress, bin(TimeGenerated, 1h);

failed_logons
| join kind=inner successful_logons on IpAddress, TimeGenerated
| where FailedAttempts > 50 
| project TimeGenerated, IpAddress, FailedAttempts, Successes
| order by TimeGenerated desc
                

Query 3: Monitoring for Network Tunneling (High-Volume Outbound)

• Behavior Targeted: Exfiltration and C2 over custom TCP proxies or obfuscated tunnels that rely on communicating with an external C2 IP.
• MITRE ATT&CK: T1041
• Expected Results: Anomalous, high-volume outbound network sessions to a previously unseen external IP or domain, especially if the process is one of the known masqueraded binaries.
• False Positive Likelihood: Medium – Requires tuning against cloud services or CDN traffic but can highlight long-running, unusual sessions.

Splunk (SPL)

// Query description: Identify persistent, long-running outbound network connections from suspicious processes.
// Tuning guidance: Baseline standard network sessions and exclude known corporate proxy and VPN targets.
index=firewall_logs OR index=netflow_logs 
| where dest_port!=80 AND dest_port!=443 AND bytes_out > 0 
| stats count as connection_count, sum(bytes_out) as total_data_out, avg(duration) as avg_duration, values(app) as applications by dest_ip, 
  src_ip 
| where connection_count > 50 AND avg_duration > 600 // Check for high count, long-running connections (e.g., >10 min)
| table dest_ip, src_ip, total_data_out, connection_count, avg_duration, applications
| sort - total_data_out
                

Microsoft Defender/Sentinel (KQL)

// Query description: Look for outbound connections from internal devices to suspicious, persistent external IPs.
// Data Tables: DeviceNetworkEvents
// Tuning guidance: Exclude known secure/trusted network destinations. Filter by common tunneling ports if known.
DeviceNetworkEvents
| where RemoteIPType == "Public"
| summarize TotalConnections = count(), TotalBytesSent = sum(TotalBytesSent), Destinations = dcount(RemoteIP) by DeviceName, 
  InitiatingProcessFileName, RemoteIP
| where TotalConnections > 100 
| where InitiatingProcessFileName has_any ("msbuild.exe", "devenv.exe", "cl.exe") or InitiatingProcessFileName contains "proxy" 
| project Timestamp, DeviceName, InitiatingProcessFileName, RemoteIP, TotalConnections, TotalBytesSent
| order by TotalBytesSent desc
                

Query 4: Detect AI-Assisted Credential Harvesting

• Behavior Targeted: Unauthorized cross-domain logins and account enumeration
• MITRE ATT&CK: T1078
• Expected Results: List of accounts with abnormal login patterns for investigation
• False Positive Likelihood: Medium – Normal service accounts may trigger some matches

Splunk (SPL)

// Detect unusual cross-domain logins
index=security EventCode=4624 OR EventCode=4648
| stats count by Account_Name, Logon_Workstation, Source_Network_Address
| where count > 5
              

Microsoft Defender/Sentinel (KQL)

// Detect abnormal logons
// Data Tables: SecurityEvent
SecurityEvent
| where EventID == 4624 or EventID == 4648
| summarize count() by Account, Computer, IpAddress
| where count_ > 5