detecting-dll-sideloading-attacks

mukul975/Anthropic-Cybersecurity-Skills · updated May 25, 2026

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$npx skills install mukul975/Anthropic-Cybersecurity-Skills/detecting-dll-sideloading-attacks
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summary

Detect DLL side-loading attacks where adversaries place malicious DLLs alongside legitimate applications to hijack execution flow for defense evasion.

skill.md
name
detecting-dll-sideloading-attacks
description
Detect DLL side-loading attacks where adversaries place malicious DLLs alongside legitimate applications to hijack execution flow for defense evasion.
domain
cybersecurity
subdomain
threat-hunting
tags
- threat-hunting - mitre-attack - dll-sideloading - defense-evasion - t1574 - edr - proactive-detection
version
'1.0'
author
mahipal
license
Apache-2.0
d3fend_techniques
- File Metadata Consistency Validation - Content Format Conversion - File Content Analysis - Platform Hardening - File Format Verification
nist_csf
- DE.CM-01 - DE.AE-02 - DE.AE-07 - ID.RA-05

Detecting DLL Sideloading Attacks

When to Use

  • 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

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

  1. Identify Sideloading Targets: Research known vulnerable applications that load DLLs without full path qualification (LOLBAS, DLL-sideload databases).
  2. Monitor DLL Load Events: Query Sysmon Event ID 7 for DLL loads where the DLL path differs from the application's expected directory.
  3. Check DLL Signatures: Flag unsigned or untrusted DLLs loaded by signed executables.
  4. Detect Path Anomalies: Identify legitimate executables running from unusual locations (Temp, AppData, Public) that may be decoy wrappers.
  5. Hash Verification: Compare loaded DLL hashes against known-good versions and threat intel feeds.
  6. Correlate with Process Behavior: Check if the host process exhibits unusual behavior (network connections, child processes) after loading the suspicious DLL.
  7. Document and Remediate: Report sideloading instances, quarantine malicious DLLs, and update detection rules.

Key Concepts

ConceptDescription
T1574.002DLL Side-Loading
T1574.001DLL Search Order Hijacking
T1574.006Dynamic Linker Hijacking
T1574.008Path Interception by Search Order Hijacking
DLL Search OrderWindows DLL loading priority path
Side-LoadingPlacing malicious DLL where legitimate app loads it
Phantom DLLDLL that legitimate apps try to load but does not exist
DLL ProxyingMalicious DLL forwarding calls to legitimate DLL

Tools & Systems

ToolPurpose
SysmonEvent ID 7 DLL load monitoring
CrowdStrike FalconDLL load detection with process context
Microsoft Defender for EndpointDLL load anomaly detection
Process MonitorReal-time DLL load tracing
DLL Export ViewerVerify DLL export functions
SigcheckDigital signature verification
pe-sievePE analysis for proxied DLLs

Common Scenarios

  1. Legitimate App Wrapper: Adversary copies signed application (e.g., OneDrive updater) to temp folder alongside malicious DLL with same name as expected dependency.
  2. Phantom DLL Exploitation: Malicious DLL placed in PATH location where legitimate app searches for non-existent DLL.
  3. DLL Proxy Loading: Malicious version.dll proxies all exports to real version.dll while executing malicious code on DllMain.
  4. Software Update Hijack: Attacker replaces DLL in update staging directory before legitimate updater loads it.

Output Format

Hunt ID: TH-SIDELOAD-[DATE]-[SEQ]
Technique: T1574.002
Host Application: [Legitimate signed executable]
Sideloaded DLL: [Malicious DLL name and path]
Expected DLL Path: [Where DLL should legitimately be]
DLL Signed: [Yes/No]
App Location: [Expected/Anomalous]
Host: [Hostname]
Risk Level: [Critical/High/Medium/Low]
how to use detecting-dll-sideloading-attacks

How to use detecting-dll-sideloading-attacks on Cursor

AI-first code editor with Composer

1

Prerequisites

Before installing skills in Cursor, ensure your development environment meets these requirements:

  • Cursor installed and configured on your development machine
  • Node.js version 16.0+ with npm package manager (verify with node --version)
  • Active project directory or workspace where you want to add detecting-dll-sideloading-attacks
2

Execute installation command

Execute the skills CLI command in your project's root directory to begin installation:

$npx skills install mukul975/Anthropic-Cybersecurity-Skills/detecting-dll-sideloading-attacks

The skills CLI fetches detecting-dll-sideloading-attacks from GitHub repository mukul975/Anthropic-Cybersecurity-Skills and configures it for Cursor.

3

Select Cursor when prompted

The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:

◆ Which agents do you want to install to?
│ ── Universal (.agents/skills) ── always included ────
│ • Amp
│ • Antigravity
│ • Cline
│ • Codex
│ ●Cursor(selected)
│ • Cursor
│ • Windsurf
4

Verify installation

Confirm successful installation by checking the skill directory location:

.cursor/skills/detecting-dll-sideloading-attacks

Reload or restart Cursor to activate detecting-dll-sideloading-attacks. Access the skill through slash commands (e.g., /detecting-dll-sideloading-attacks) or your agent's skill management interface.

Security & Verification Notice

We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.

Skills execute code in your development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.

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Use Cases

Task Automation & Efficiency

Automate repetitive workflows and reduce manual effort

Example

Generate reports, summarize documents, draft communications

Save 3-5 hours per week on routine tasks

Knowledge Enhancement

Learn new skills, understand complex topics, get expert guidance

Example

Explain concepts, provide examples, suggest learning resources

Accelerate learning and skill development by 2x

Quality Improvement

Enhance output quality through reviews, suggestions, and refinements

Example

Review drafts, suggest improvements, catch errors

Improve work quality by 30-40% with less effort

Implementation Guide

Prerequisites

  • Claude Desktop or compatible AI client with skill support
  • Clear understanding of task or problem to solve
  • Willingness to iterate and refine outputs

Time Estimate

15-45 minutes depending on use case complexity

Installation Steps

  1. 1.Install skill using provided installation command
  2. 2.Test with simple use case relevant to your work
  3. 3.Evaluate output quality and relevance
  4. 4.Iterate on prompts to improve results
  5. 5.Integrate into regular workflow if valuable

Common Pitfalls

  • Expecting perfect results without iteration
  • Not providing enough context in prompts
  • Using skill for tasks outside its intended scope
  • Accepting outputs without review and validation

Best Practices

✓ Do

  • +Start with clear, specific prompts
  • +Provide relevant context and constraints
  • +Review and refine all outputs before using
  • +Iterate to improve output quality
  • +Document successful prompt patterns

✗ Don't

  • Don't use without understanding skill limitations
  • Don't skip validation of outputs
  • Don't share sensitive information in prompts
  • Don't expect skill to replace human judgment

💡 Pro Tips

  • Be specific about desired format and style
  • Ask for multiple options to choose from
  • Request explanations to understand reasoning
  • Combine AI efficiency with human expertise

When to Use This

✓ Use When

Use when skill capabilities match your task, clear ROI on time saved, and you can validate outputs. Best for repetitive tasks, learning, and quality improvement.

✗ Avoid When

Avoid when task requires deep expertise you can't validate, involves sensitive decisions, or when learning process is more valuable than speed of completion.

Learning Path

  1. 1Familiarize yourself with skill capabilities and limitations
  2. 2Start with low-risk, non-critical tasks
  3. 3Progress to more complex and valuable use cases
  4. 4Build expertise through regular use and experimentation

Discussion

Product Hunt–style comments (not star reviews)
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general reviews

Ratings

4.760 reviews
  • Pratham Ware· Dec 20, 2024

    detecting-dll-sideloading-attacks is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.

  • Alexander Nasser· Dec 16, 2024

    I recommend detecting-dll-sideloading-attacks for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.

  • Meera Verma· Dec 12, 2024

    detecting-dll-sideloading-attacks has been reliable in day-to-day use. Documentation quality is above average for community skills.

  • Min Bansal· Dec 8, 2024

    Keeps context tight: detecting-dll-sideloading-attacks is the kind of skill you can hand to a new teammate without a long onboarding doc.

  • Meera Smith· Dec 4, 2024

    Solid pick for teams standardizing on skills: detecting-dll-sideloading-attacks is focused, and the summary matches what you get after install.

  • Xiao Sethi· Nov 27, 2024

    We added detecting-dll-sideloading-attacks from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.

  • Meera Mehta· Nov 23, 2024

    detecting-dll-sideloading-attacks has been reliable in day-to-day use. Documentation quality is above average for community skills.

  • Alexander Desai· Nov 11, 2024

    Useful defaults in detecting-dll-sideloading-attacks — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.

  • Ama Agarwal· Nov 7, 2024

    detecting-dll-sideloading-attacks fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.

  • Fatima Flores· Nov 3, 2024

    Solid pick for teams standardizing on skills: detecting-dll-sideloading-attacks is focused, and the summary matches what you get after install.

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