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Introduction:
A sophisticated criminal campaign is actively targeting Snowflake customer instances with stolen credentials, leading to massive data theft and extortion. This attack leverages previously infected machines and information-stealing malware to bypass security controls, highlighting a critical shift in cloud-based threat vectors. Understanding the attack chain and implementing robust mitigation strategies is no longer optional for any organization utilizing cloud data warehousing solutions.
Learning Objectives:
- Decipher the complete attack chain used in the Snowflake credential theft campaign.
- Implement immediate hardening steps for your Snowflake environment, including MFA and network policies.
- Master forensic commands to detect Indicators of Compromise (IoCs) within your Snowflake instance and endpoints.
You Should Know:
- The Attack Chain: From Info-Stealer Malware to Data Exfiltration
The campaign’s success hinges on a multi-stage process that bypasses traditional perimeter defenses. It begins not with a direct attack on Snowflake, but with the compromise of user endpoints.
Stage 1: Initial Infection. User machines are infected with information-stealer malware (e.g., Vidar, Raccoon, Lumma) through phishing or malicious downloads.
Stage 2: Credential Harvesting. The malware harvests cached credentials from browsers, including those for Snowflake, and often contains a cryptobot component.
Stage 3: Credential Sale. Stolen credentials are sold on cybercriminal forums.
Stage 4: Direct Login. Attackers use these credentials to directly log into Snowflake customer instances, often from unfamiliar IPs.
Stage 5: Data Theft & Extortion. Once inside, they exfiltrate valuable data and contact the victim company to demand a ransom.
2. Immediate Hardening: Enforcing Multi-Factor Authentication (MFA)
The single most effective mitigation for this attack vector is the universal enforcement of MFA. A password alone is insufficient.
Snowflake SQL Command:
-- Create a network policy to restrict logins (prerequisite for certain MFA enforcement)
CREATE NETWORK POLICY trusted_ips
ALLOWED_IP_LIST = ('192.168.1.0/24','203.0.113.100')
BLOCKED_IP_LIST = ('')
COMMENT = 'Restrict logins to corporate IP range';
-- Apply the network policy to your account (requires ACCOUNTADMIN role)
ALTER ACCOUNT SET NETWORK_POLICY = trusted_ips;
-- Enforce MFA for a specific user
ALTER USER jdoe SET MFA_CACHE_FOR_SESSION = FALSE;
ALTER USER jdoe SET DISABLED = FALSE;
Step-by-step guide explaining what this does and how to use it:
1. Assess Your Users: First, identify users without MFA using `DESC USER
2. Create a Network Policy: The `CREATE NETWORK POLICY` command defines a list of approved IP addresses (e.g., your corporate network/VPN). This prevents logins from unknown locations, even with valid credentials.
3. Apply the Policy: The `ALTER ACCOUNT` command activates the network policy globally. This is a critical step to block attacker access.
4. Enforce MFA Per User: The `ALTER USER` commands ensure that MFA is required for every session and that the account is active. MFA should be mandated for all users, especially those with high privileges.
3. Digital Forensics: Querying Snowflake Login History
Snowflake maintains detailed login history logs. Proactively querying these is essential for identifying suspicious activity.
Snowflake SQL Command:
-- Query login history for the last 30 days, looking for failed logins and unusual clients
SELECT
USER_NAME,
CLIENT_IP,
REPORTED_CLIENT_TYPE,
EVENT_TIMESTAMP,
IS_SUCCESS,
ERROR_CODE,
ERROR_MESSAGE
FROM
SNOWFLAKE.ACCOUNT_USAGE.LOGIN_HISTORY
WHERE
EVENT_TIMESTAMP > DATEADD(day, -30, CURRENT_TIMESTAMP())
AND (IS_SUCCESS = 'NO'
OR CLIENT_IP NOT IN ('192.168.1.0/24') -- Replace with your trusted IP range
OR REPORTED_CLIENT_TYPE IN ('SNOWFLAKE_UI', 'JDBC', 'ODBC') -- Filter for common clients, look for anomalies
)
ORDER BY
EVENT_TIMESTAMP DESC;
Step-by-step guide explaining what this does and how to use it:
1. Access the View: This query uses the `ACCOUNT_USAGE.LOGIN_HISTORY` view, which provides a consolidated view of logins across your account.
2. Filter for Anomalies: The `WHERE` clause filters for three key indicators: failed logins (IS_SUCCESS = 'NO'), logins from untrusted IPs, and logins from specific client types that an attacker might use.
3. Analyze Results: Pay close attention to `ERROR_CODE` and `ERROR_MESSAGE` for failed attempts. A high volume of failures for a single user may indicate a targeted credential-stuffing attack. Logins from unexpected countries or IPs are immediate red flags.
4. Endpoint Detection: Hunting for Information-Stealer Malware
The attack originates on the endpoint. System administrators must be able to hunt for IoCs related to info-stealers.
Linux Command (to check for suspicious processes and network connections):
List all established network connections, filtering for unknown processes sudo netstat -tunap | grep ESTABLISHED Check for recently modified executable files in common user directories (potential malware drops) find /home /tmp -name ".exe" -o -name ".sh" -type f -mtime -7 2>/dev/null Scan for known IoCs (hashes, domains) using a custom list with grep grep -r "malicious-domain.com" /etc/hosts /var/log/
Windows Command (using PowerShell):
Get a list of all established network connections and the owning process Get-NetTCPConnection -State Established | Select-Object LocalAddress, LocalPort, RemoteAddress, RemotePort, OwningProcess | Format-Table Get the process associated with the connection Get-Process -Id <OwningProcessId> Check for run keys in the registry where malware persists Get-ItemProperty -Path "HKLM:\Software\Microsoft\Windows\CurrentVersion\Run", "HKCU:\Software\Microsoft\Windows\CurrentVersion\Run"
Step-by-step guide explaining what this does and how to use it:
1. Network Reconnaissance: The `netstat` and `Get-NetTCPConnection` commands show all active network connections. Correlate unknown remote IPs with the process ID (PID) to identify malicious callouts.
2. File System Hunting: The `find` command on Linux searches for recently dropped executables or scripts in user-writable areas. On Windows, use `Get-ChildItem` with `-LastWriteTime` filters.
3. Persistence Mechanism Check: Info-stealers often establish persistence. The PowerShell command checks common Windows Registry “Run” keys for unauthorized entries.
5. Leveraging CSPM for Continuous Cloud Security Monitoring
A Cloud Security Posture Management (CSPM) tool can automatically detect misconfigurations that make your Snowflake instance a target.
Example CSPM Detection Rule (Pseudocode):
Rule: snowflake-mfa-disabled Description: "Alert if any Snowflake user does not have MFA enabled." Resource: snowflake.user Condition: mfa_enabled == false Severity: HIGH
Step-by-step guide explaining what this does and how to use it:
1. Define Security Policies: Translate your security requirements into machine-readable rules. The example rule checks for users without MFA.
2. Automate Scans: Configure your CSPM to continuously scan your Snowflake account against these rules. This provides ongoing assurance rather than a point-in-time check.
3. Integrate with SIEM/SOAR: Forward alerts from the CSPM to your Security Information and Event Management (SIEM) system. This allows for automated ticketing or even automatic remediation actions, such as temporarily disabling a user account.
6. Incident Response: Rapid User Session Termination
If you detect a compromised account, you must be able to terminate its sessions immediately to prevent further data exfiltration.
Snowflake SQL Command:
-- Identify active sessions for a specific user SELECT FROM TABLE(INFORMATION_SCHEMA.CURRENT_USER_SESSIONS()) WHERE USER_NAME = 'SUSPECT_USER'; -- Terminate a user's active session using the SESSION_ID SELECT SYSTEM$ABORT_SESSION(<session_id>); -- As a last resort, immediately disable the user account ALTER USER suspect_user SET DISABLED = TRUE;
Step-by-step guide explaining what this does and how to use it:
1. Investigate: Use the `CURRENT_USER_SESSIONS()` function to list all active sessions for the potentially compromised user. Note the SESSION_ID.
2. Abort Session: The `SYSTEM$ABORT_SESSION()` function is the fastest way to log a user out of their current session, cutting off an active attacker.
3. Contain: Follow up by disabling the user account entirely with ALTER USER ... DISABLED. This prevents any new logins until the incident is fully contained and investigated.
7. API Security: Auditing Snowflake API Usage
Attackers may use the Snowflake REST API with stolen credentials. Auditing this activity is crucial.
Snowflake SQL Command:
-- Query the query history to see all executed commands, including those from the API SELECT QUERY_ID, USER_NAME, WAREHOUSE_NAME, QUERY_TEXT, EXECUTION_STATUS, START_TIME FROM SNOWFLAKE.ACCOUNT_USAGE.QUERY_HISTORY WHERE START_TIME > DATEADD(hour, -6, CURRENT_TIMESTAMP()) AND USER_NAME = 'SUSPECT_USER' AND EXECUTION_STATUS = 'SUCCESS' ORDER BY START_TIME DESC;
Step-by-step guide explaining what this does and how to use it:
1. Focus on Recent Activity: This query looks at the last 6 hours of successful query history for a specific user. Narrowing the timeframe is critical during an active investigation.
2. Analyze Query Text: Scrutinize the `QUERY_TEXT` column for data exfiltration patterns. Look for large `SELECT ` statements on sensitive tables, `COPY INTO` commands pointing to external stages, or the use of `UNLOAD` commands.
3. Correlate with Logins: Cross-reference the `START_TIME` of suspicious queries with the `LOGIN_HISTORY` to confirm the client used was the REST API from an untrusted IP.
What Undercode Say:
- The perimeter has dissolved. This campaign proves that the corporate network is no longer the perimeter; the identity of the user (and their endpoint) is the new primary attack surface. Defending a cloud service like Snowflake requires a defense-in-depth strategy that extends to every user’s laptop.
- Credential management is the weakest link. The attack did not exploit a zero-day vulnerability in Snowflake’s code. It exploited the perennial weak link: reusable, static passwords stored in an insecure manner on user endpoints. This shifts significant responsibility onto the customer’s security hygiene.
The sophistication of this attack lies in its simplicity. By leveraging the underground economy for stolen credentials, threat actors have created a highly scalable and efficient attack model. They are not breaking down the fortress gates; they are using a copied key. This incident should serve as a global wake-up call for all SaaS and cloud platform customers. It underscores the absolute necessity of MFA, strict network policies, and robust endpoint detection and response (EDR) controls. The convergence of credential theft, cloud infrastructure, and extortion represents the new normal in cybercrime.
Prediction:
The Snowflake campaign is a blueprint that will be rapidly adopted by other ransomware and extortion groups. We predict a significant rise in similar attacks targeting other major SaaS platforms (e.g., Salesforce, ServiceNow, AWS Console) and data-intensive cloud services. Criminal groups will refine their automation, using bots to test vast lists of stolen credentials against these services’ login portals directly. This will lead to a new wave of mass data extortion events, forcing a fundamental industry-wide shift away from password-only authentication towards phishing-resistant MFA and broader adoption of zero-trust principles for all enterprise applications.
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IT/Security Reporter URL:
Reported By: Nir Roitman – Hackers Feeds
Extra Hub: Undercode MoN
Basic Verification: Pass ✅
