detecting-dll-sideloading-attacks
Detect DLL side-loading attacks where adversaries place malicious DLLs alongside legitimate applications to hijack execution flow for defense evasion.
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Installation Guide
How to use detecting-dll-sideloading-attacks on Cursor
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Prerequisites
Before installing skills in Cursor, ensure your development environment meets these requirements:
- ›Cursor installed and configured on your machine
- ›Node.js 16+ with npm — verify with
node --version - ›Active project directory where you want to add
detecting-dll-sideloading-attacks
Run the install command
Execute the skills CLI command in your project's root directory to begin installation:
Fetches detecting-dll-sideloading-attacks from mukul975/Anthropic-Cybersecurity-Skills and configures it for Cursor.
Select Cursor when prompted
The CLI shows a list of agents. Use arrow keys and space to select Cursor:
Verify installation
Confirm successful installation by checking the skill directory location:
Restart Cursor to activate detecting-dll-sideloading-attacks. Access via /detecting-dll-sideloading-attacks in your agent's command palette.
Security 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 environment. Always review source, verify the publisher, and test in isolation before production.
Documentation
| 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
- Identify Sideloading Targets: Research known vulnerable applications that load DLLs without full path qualification (LOLBAS, DLL-sideload databases).
- Monitor DLL Load Events: Query Sysmon Event ID 7 for DLL loads where the DLL path differs from the application's expected directory.
- Check DLL Signatures: Flag unsigned or untrusted DLLs loaded by signed executables.
- Detect Path Anomalies: Identify legitimate executables running from unusual locations (Temp, AppData, Public) that may be decoy wrappers.
- Hash Verification: Compare loaded DLL hashes against known-good versions and threat intel feeds.
- Correlate with Process Behavior: Check if the host process exhibits unusual behavior (network connections, child processes) after loading the suspicious DLL.
- Document and Remediate: Report sideloading instances, quarantine malicious DLLs, and update detection rules.
Key Concepts
| Concept | Description |
|---|---|
| T1574.002 | DLL Side-Loading |
| T1574.001 | DLL Search Order Hijacking |
| T1574.006 | Dynamic Linker Hijacking |
| T1574.008 | Path Interception by Search Order Hijacking |
| DLL Search Order | Windows DLL loading priority path |
| Side-Loading | Placing malicious DLL where legitimate app loads it |
| Phantom DLL | DLL that legitimate apps try to load but does not exist |
| DLL Proxying | Malicious DLL forwarding calls to legitimate DLL |
Tools & Systems
| Tool | Purpose |
|---|---|
| Sysmon | Event ID 7 DLL load monitoring |
| CrowdStrike Falcon | DLL load detection with process context |
| Microsoft Defender for Endpoint | DLL load anomaly detection |
| Process Monitor | Real-time DLL load tracing |
| DLL Export Viewer | Verify DLL export functions |
| Sigcheck | Digital signature verification |
| pe-sieve | PE analysis for proxied DLLs |
Common Scenarios
- Legitimate App Wrapper: Adversary copies signed application (e.g., OneDrive updater) to temp folder alongside malicious DLL with same name as expected dependency.
- Phantom DLL Exploitation: Malicious DLL placed in PATH location where legitimate app searches for non-existent DLL.
- DLL Proxy Loading: Malicious version.dll proxies all exports to real version.dll while executing malicious code on DllMain.
- 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]
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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
Steps
- 1Install skill using provided installation command
- 2Test with simple use case relevant to your work
- 3Evaluate output quality and relevance
- 4Iterate on prompts to improve results
- 5Integrate 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
- 1Familiarize yourself with skill capabilities and limitations
- 2Start with low-risk, non-critical tasks
- 3Progress to more complex and valuable use cases
- 4Build expertise through regular use and experimentation
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Reviews
- PPratham Ware★★★★★Dec 20, 2024
detecting-dll-sideloading-attacks is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
- AAlexander 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.
- MMeera Verma★★★★★Dec 12, 2024
detecting-dll-sideloading-attacks has been reliable in day-to-day use. Documentation quality is above average for community skills.
- MMin 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.
- MMeera 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.
- XXiao 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.
- MMeera Mehta★★★★★Nov 23, 2024
detecting-dll-sideloading-attacks has been reliable in day-to-day use. Documentation quality is above average for community skills.
- AAlexander 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.
- AAma Agarwal★★★★★Nov 7, 2024
detecting-dll-sideloading-attacks fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
- FFatima 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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