Hunting Credential Stuffing Attacks
Overview
Cybersecurity skill for hunting credential stuffing attacks. Follows industry best practices and security standards.
When to Use
Trigger phrases:
"hunting credential stuffing attacks"
"When investigating security incidents that require hunting credential stuffing a"
"When building detection rules or threat hunting queries for this domain"
"When SOC analysts need structured procedures for this analysis type"
When investigating security incidents that require hunting credential stuffing attacks
When building detection rules or threat hunting queries for this domain
When SOC analysts need structured procedures for this analysis type
When validating security monitoring coverage for related attack techniques
When NOT to Use
- When you lack proper authorization for testing
- For production systems without change management
- When the task requires legal or compliance expertise beyond technical scope
Prerequisites
- Familiarity with security operations concepts and tools
- Access to a test or lab environment for safe execution
- Python 3.8+ with required dependencies installed
- Appropriate authorization for any testing activities
Workflow
# Example: IOC detection
import re
IOC_PATTERNS = {
"ip": r"\b(?:\d{1,3}\.){3}\d{1,3}\b",
"domain": r"\b[a-z0-9-]+\.[a-z]{2,}\b",
"hash_md5": r"\b[a-f0-9]{32}\b",
"hash_sha256": r"\b[a-f0-9]{64}\b",
}
def extract_iocs(text: str) -> dict:
return {k: re.findall(v, text) for k, v in IOC_PATTERNS.items()}
- Define Detection Scope — Identify the specific credential stuffing attacks techniques or indicators to hunt. Map to MITRE ATT&CK tactics/techniques where applicable.
- Collect Baseline Data — Gather historical logs and establish normal behavior patterns for credential stuffing attacks.
- Build Detection Queries — Write detection rules, Sigma rules, or SIEM queries targeting credential stuffing attacks indicators.
- Execute Hunts — Run queries against the collected data, starting with broad filters and narrowing down.
- Triage Results — Investigate alerts, filter false positives, and validate findings against known-good behavior.
- Document Findings — Record confirmed detections, IOCs, and affected systems. Update detection rules based on findings.
Tools
- SIEM Platform — Central log aggregation and query execution
- Sigma Rules — Vendor-agnostic detection rule format
- MITRE ATT&CK Navigator — Technique mapping and coverage analysis
Process
- Reconnaissance — Gather target information, identify attack surface, enumerate services
- Analysis/Exploitation — Execute the technique, analyze results, document findings
- Reporting — Document IOCs, write findings, provide remediation recommendations
Verification
- All credential stuffing attacks procedures executed completely and documented
- Findings validated against multiple data sources
- False positives identified and filtered
- Results documented with evidence and timestamps
- Recommendations provided with risk-based prioritization
Anti-Rationalization Table
| Rationalization | Reality |
|---|---|
| "We are too small to be targeted" | Automated attacks target everyone. Size does not matter. |
| "Security slows us down" | A breach slows you down 100x more. Build security in from the start. |
| "We will fix it after launch" | Vulnerabilities in production are exploited within hours. Fix before deploy. |