When Defenders Turn Attackers: The BlackCat Insider Sentencing
Just caught the breaking news regarding the DoJ sentencing Ryan Goldberg and Kevin Martin to four years each. It’s a stark reminder that sometimes the biggest threats are already inside the perimeter or know exactly how to bypass the controls we design.
These weren't typical script kiddies; they were professionals who allegedly utilized their knowledge to facilitate BlackCat (ALPHV) attacks back in 2023. What worries me most is the efficiency gains they likely had. When you know the specific EDR bypasses or the legacy protocols the SOC is ignoring, the 'dwell time' drops significantly while the damage skyrockets.
If you're auditing your environment for similar risks—specifically regarding tools often abused by ransomware operators like BlackCat—you might want to hunt for rclone usage, which they frequently leveraged for exfiltration due to its speed and cloud support.
Here is a basic KQL query for Sentinel to hunt for suspicious rclone executions that deviate from standard admin behavior:
DeviceProcessEvents
| where Timestamp > ago(7d)
| where FileName =~ "rclone.exe"
| where ProcessCommandLine contains "copy" or ProcessCommandLine contains "sync"
| where InitiatingProcessFileName !in ~("explorer.exe", "cmd.exe", "powershell.exe")
| project Timestamp, DeviceName, AccountName, FolderPath, ProcessCommandLine
Given that these actors understood the defender's mindset, how is everyone handling the 'super-user' problem? Are you implementing strict Just-In-Time (JIT) access, or is it still mostly honor system based?
We moved to strict JIT access for all admin accounts about six months ago. It was a culture shock for the senior engineers, but the audit trails are invaluable. If one of our admins went rogue, they'd need a ticket approval and a manager's sign-off to even open a PowerShell session as admin. It doesn't stop everything, but it creates a friction point that's hard to bypass without raising flags in the SIEM.
Great query snippet. We actually caught something similar using Sigma rules last year. The scary part about BlackCat was their use of Rust to cross-compile payloads. If you have EDR, make sure your behavioral analysis is tuned for process masquerading. We saw them mimicking legitimate Windows update processes in the later stages of the infection.
This highlights why background checks need to go deeper than just criminal records. We audit for 'polyemployment' now—checking if senior staff are simultaneously working for 'security consulting' firms on the side. If you have access to the crown jewels and financial distress or a side gig that involves offensive tools, you're a high-risk profile regardless of your intentions.
It’s terrifying when defenders flip, but often they rely on "living off the land" to blend in. Beyond strict access, we hunt for anomalies in how standard tools are used during those approved sessions. We flag encoded PowerShell commands from admin accounts immediately. This KQL snippet helps us spot potential stagers or data exfiltration attempts that might look 'normal' to a basic filter:
DeviceProcessEvents
| where InitiatingProcessAccountName in~ ("AdminGroup")
| where FileName =~ "powershell.exe"
| where ProcessCommandLine contains " -enc "
While JIT and audits are great, we’ve had success layering honeytokens specifically for insider threat scenarios. Placing fake API keys in config files or dormant accounts creates a silent alarm that even a savvy admin might miss during a hasty exfiltration. If you want to try this, checking for access to these specific triggers in logs can be done via:
SecurityEvent | where EventID == 4663 and ObjectName contains "honey_token"
This helps distinguish between legitimate maintenance and malicious exploration.
Since insiders know exactly where the sensitive data lives, speed is their advantage. We’ve shifted focus to data egress baselines rather than just access controls. Even with JIT, if a privileged account suddenly triggers massive outbound traffic during off-hours, we auto-revoke. We use a KQL rule to catch these volume spikes immediately:
DeviceNetworkEvents
| where ActionType == "ConnectionAccepted"
| summarize SentBytes = sum(SentBytes) by DeviceName, bin(Timestamp, 1h)
| where SentBytes > 50000000
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