Detecting Dll Sideloading Attacks

Detecting Dll Sideloading Attacks

Overview

Cybersecurity skill for detecting dll sideloading attacks. Follows industry best practices and security standards.

When to Use

Trigger phrases:

• "detecting dll sideloading attacks"

• "Detect DLL side-loading attacks where adversaries place malicious DLLs alongside"

• When investigating potential DLL hijacking in enterprise environments

• After EDR alerts on unsigned DLLs loaded by signed applications

• When hunting for APT persistence using legitimate application wrappers

• During incident response to identify trojanized applications

• When threat intel indicates DLL sideloading campaigns targeting specific software

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

• EDR with DLL load monitoring (CrowdStrike, MDE, SentinelOne)
• Sysmon Event ID 7 (Image Loaded) with hash verification
• Application whitelisting or DLL integrity monitoring
• Software inventory of legitimate applications and expected DLL paths
• Code signing verification capabilities

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()}

1. Define Detection Scope — Identify the specific dll sideloading attacks techniques or indicators to hunt. Map to MITRE ATT&CK tactics/techniques where applicable.
2. Collect Baseline Data — Gather historical logs and establish normal behavior patterns for dll sideloading attacks.
3. Build Detection Queries — Write detection rules, Sigma rules, or SIEM queries targeting dll sideloading attacks indicators.
4. Execute Hunts — Run queries against the collected data, starting with broad filters and narrowing down.
5. Triage Results — Investigate alerts, filter false positives, and validate findings against known-good behavior.
6. 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

1. Reconnaissance — Gather target information, identify attack surface, enumerate services
2. Analysis/Exploitation — Execute the technique, analyze results, document findings
3. Reporting — Document IOCs, write findings, provide remediation recommendations

Verification

• All dll sideloading 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