performing-dynamic-analysis-with-any-run▌
mukul975/Anthropic-Cybersecurity-Skills · updated May 25, 2026
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Performs interactive dynamic malware analysis using the ANY.RUN cloud sandbox to observe real-time execution behavior, interact with malware prompts, and capture process trees, network traffic, and system changes. Activates for requests involving interactive sandbox analysis, cloud-based malware detonation, real-time behavioral observation, or ANY.RUN usage.
| name | performing-dynamic-analysis-with-any-run |
| description | 'Performs interactive dynamic malware analysis using the ANY.RUN cloud sandbox to observe real-time execution behavior, interact with malware prompts, and capture process trees, network traffic, and system changes. Activates for requests involving interactive sandbox analysis, cloud-based malware detonation, real-time behavioral observation, or ANY.RUN usage. ' |
| domain | cybersecurity |
| subdomain | malware-analysis |
| tags | - malware - dynamic-analysis - sandbox - ANY.RUN - interactive-analysis |
| version | 1.0.0 |
| author | mahipal |
| license | Apache-2.0 |
| d3fend_techniques | - File Metadata Consistency Validation - Application Protocol Command Analysis - Identifier Analysis - Content Format Conversion - Message Analysis |
| nist_csf | - DE.AE-02 - RS.AN-03 - ID.RA-01 - DE.CM-01 |
Performing Dynamic Analysis with ANY.RUN
When to Use
- Interactive malware analysis is needed where the analyst must click dialogs, enter credentials, or navigate installer screens
- Rapid cloud-based sandbox analysis without maintaining local sandbox infrastructure
- Malware requires user interaction to proceed past anti-sandbox checks (document macros requiring "Enable Content")
- Sharing analysis results with team members via public or private task URLs
- Comparing behavior across different OS versions (Windows 7, 10, 11) available in ANY.RUN
Do not use for highly sensitive samples that cannot be uploaded to cloud services; use an on-premises sandbox like Cuckoo instead.
Prerequisites
- ANY.RUN account (free community tier or paid subscription at https://any.run)
- Modern web browser with WebSocket support for interactive session streaming
- Sample file ready for upload (max 100 MB for free tier, 256 MB for paid)
- Understanding of the sample type to select appropriate execution environment
- VPN or secure network for accessing ANY.RUN portal during analysis sessions
Workflow
Step 1: Configure Analysis Environment
Set up the ANY.RUN task with appropriate parameters:
ANY.RUN Task Configuration:
━━━━━━━━━━━━━━━━━━━━━━━━━━
OS Selection: Windows 10 x64 (recommended default)
Windows 7 x64 (for legacy malware)
Windows 11 x64 (for modern samples)
Execution Time: 60 seconds (default) / 120-300 for slow-acting malware
Network: Connected (captures real C2 traffic)
Residential Proxy (bypasses geo-blocking)
Privacy: Public (free tier) / Private (paid - not indexed)
MITM Proxy: Enable for HTTPS traffic decryption
Fake Net: Enable to simulate internet services if sample checks connectivity
API-based submission (paid tier):
# Submit file via ANY.RUN API
curl -X POST "https://api.any.run/v1/analysis" \
-H "Authorization: API-Key $ANYRUN_API_KEY" \
-F "[email protected]" \
-F "env_os=windows" \
-F "env_version=10" \
-F "env_bitness=64" \
-F "opt_timeout=120" \
-F "opt_network_connect=true" \
-F "opt_privacy_type=bylink"
# Check task status
curl "https://api.any.run/v1/analysis/$TASK_ID" \
-H "Authorization: API-Key $ANYRUN_API_KEY" | jq '.data.status'
Step 2: Interact with Malware During Execution
Use the interactive session to trigger malware behavior:
Interactive Actions During Analysis:
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
1. Document Macros: Click "Enable Content" / "Enable Editing" when prompted
2. Installer Screens: Click through installation dialogs
3. UAC Prompts: Click "Yes" to allow elevation (observe privilege escalation)
4. Credential Harvests: Enter fake credentials to observe phishing behavior
5. Browser Redirects: Navigate to URLs if malware opens browser windows
6. File Dialogs: Select target files if malware presents file picker
7. Timeout Extension: Extend analysis time if malware has delayed execution
Step 3: Analyze Process Tree
Review the complete process execution chain:
Process Tree Analysis Points:
━━━━━━━━━━━━━━━━━━━━━━━━━━━
Parent-Child Relationships:
- WINWORD.EXE -> cmd.exe -> powershell.exe (macro execution chain)
- explorer.exe -> suspect.exe -> svchost.exe (process injection)
Process Events to Note:
- Process creation with suspicious command-line arguments
- PowerShell with encoded commands (-enc / -encodedcommand)
- cmd.exe executing script files (.bat, .vbs, .js)
- Legitimate processes spawned from unusual parents
- Process termination (self-deletion behavior)
Step 4: Review Network Activity
Examine DNS, HTTP/HTTPS, and TCP/UDP connections:
ANY.RUN Network Panel Analysis:
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
DNS Requests:
- Domain resolutions with threat intelligence tags
- Fast-flux or DGA domain patterns
- DNS over HTTPS (DoH) detection
HTTP/HTTPS Traffic (with MITM enabled):
- Full request/response bodies for HTTP
- Decrypted HTTPS traffic showing C2 commands
- Downloaded payloads and their content types
- POST data containing exfiltrated information
Connection Map:
- Geographic visualization of C2 server locations
- Connection timeline showing beacon patterns
- Suricata alerts triggered on network traffic
Step 5: Examine IOCs and Threat Intelligence
Extract indicators and map to known threats:
ANY.RUN IOC Categories:
━━━━━━━━━━━━━━━━━━━━━━
Files: Dropped files with hashes, YARA matches, VirusTotal results
Network: IPs, domains, URLs contacted during execution
Registry: Keys created/modified for persistence
Processes: Suspicious process names and command lines
Mutex: Named mutexes created (used for single-instance checking)
Signatures: Suricata rules triggered, behavioral signatures matched
MITRE ATT&CK Mapping:
- ANY.RUN automatically maps observed behaviors to ATT&CK techniques
- Review the ATT&CK matrix tab for technique coverage
- Export ATT&CK Navigator layer for reporting
Step 6: Export Analysis Results
Download comprehensive reports and artifacts:
# Download report via API
curl "https://api.any.run/v1/analysis/$TASK_ID/report" \
-H "Authorization: API-Key $ANYRUN_API_KEY" \
-o report.json
# Download PCAP
curl "https://api.any.run/v1/analysis/$TASK_ID/pcap" \
-H "Authorization: API-Key $ANYRUN_API_KEY" \
-o capture.pcap
# Download dropped files
curl "https://api.any.run/v1/analysis/$TASK_ID/files" \
-H "Authorization: API-Key $ANYRUN_API_KEY" \
-o dropped_files.zip
# Available exports from ANY.RUN web interface:
# - HTML Report (shareable standalone page)
# - PCAP file (network traffic capture)
# - Process dump (memory dumps of processes)
# - Dropped files (all files created during execution)
# - MITRE ATT&CK Navigator JSON
# - IOC export (STIX/JSON/CSV format)
Key Concepts
| Term | Definition |
|---|---|
| Interactive Sandbox | Analysis environment allowing real-time analyst interaction with the executing sample, enabling triggering of user-dependent behaviors |
| MITM Proxy | Man-in-the-middle TLS interception in ANY.RUN that decrypts HTTPS traffic for visibility into encrypted C2 communications |
| Residential Proxy | ANY.RUN feature routing malware traffic through residential IP addresses to bypass geo-IP and datacenter-IP evasion checks |
| Suricata Alerts | Network IDS signatures triggered during execution, providing immediate identification of known malicious traffic patterns |
| Process Tree | Hierarchical visualization of parent-child process relationships showing the complete execution chain from initial sample to final payloads |
| Behavioral Tags | ANY.RUN classification labels automatically applied based on observed behavior (e.g., "trojan", "stealer", "ransomware") |
Tools & Systems
- ANY.RUN: Cloud-based interactive malware sandbox providing real-time execution monitoring, process trees, network capture, and MITRE ATT&CK mapping
- ANY.RUN API: REST API for programmatic sample submission, status checking, and report/artifact retrieval
- Suricata: Integrated network IDS within ANY.RUN providing signature-based detection of malicious network traffic
- MITRE ATT&CK Navigator: Framework integration mapping observed malware behaviors to adversary techniques and tactics
- VirusTotal Integration: Automatic hash lookup of sample and dropped files against VirusTotal detection results
Common Scenarios
Scenario: Analyzing a Macro-Enabled Document Requiring User Interaction
Context: Phishing email contains a .docm file that requires clicking "Enable Content" to trigger the macro payload. Traditional non-interactive sandboxes fail to trigger the malicious behavior.
Approach:
- Upload .docm to ANY.RUN with Windows 10 environment and Microsoft Office installed
- When Word opens and displays the security banner, click "Enable Content" interactively
- Observe the macro execution in the process tree (Word -> cmd.exe -> powershell.exe)
- Monitor network panel for PowerShell downloading second-stage payload
- If a UAC prompt appears, click "Yes" to allow the payload to observe full behavior chain
- Review Suricata alerts for known malware signatures on the downloaded payload
- Export IOCs (download URLs, dropped file hashes, C2 domains) for blocking
Pitfalls:
- Forgetting to enable MITM proxy, resulting in encrypted HTTPS traffic without visibility
- Using too short an execution timeout for malware with delayed execution or sleep timers
- Uploading to public analysis when the sample contains sensitive organizational data
- Not clicking through all prompts; some malware requires multiple user interactions to fully execute
Output Format
ANY.RUN ANALYSIS REPORT
=========================
Task URL: https://app.any.run/tasks/<task_id>
Sample: invoice_q3.docm
SHA-256: e3b0c44298fc1c149afbf4c8996fb924...
Verdict: MALICIOUS (Score: 95/100)
Family: Emotet
Tags: [trojan, banker, spam, macro]
PROCESS TREE
WINWORD.EXE (PID: 2184)
└── cmd.exe (PID: 3456) "/c powershell -enc JABXAG..."
└── powershell.exe (PID: 4012)
└── rundll32.exe (PID: 4568) "C:\Users\...\payload.dll,Control_RunDLL"
NETWORK INDICATORS
DNS: update.emotet-c2[.]com -> 185.220.101.42
HTTPS: POST hxxps://185.220.101[.]42/wp-content/gate/ (C2 beacon)
HTTP: GET hxxp://compromised-site[.]com/invoice.dll (payload download)
SURICATA ALERTS
[1:2028401] ET MALWARE Emotet CnC Beacon
[1:2028402] ET MALWARE Win32/Emotet Activity
MITRE ATT&CK TECHNIQUES
T1566.001 Phishing: Spearphishing Attachment
T1204.002 User Execution: Malicious File
T1059.001 Command and Scripting Interpreter: PowerShell
T1218.011 Rundll32 Execution
T1071.001 Application Layer Protocol: Web Protocols
DROPPED FILES
payload.dll SHA-256: abc123... Detection: 48/72 (VirusTotal)
config.dat SHA-256: def456... (encrypted configuration)
How to use performing-dynamic-analysis-with-any-run on Cursor
AI-first code editor with Composer
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 performing-dynamic-analysis-with-any-run
Execute installation command
Execute the skills CLI command in your project's root directory to begin installation:
The skills CLI fetches performing-dynamic-analysis-with-any-run from GitHub repository mukul975/Anthropic-Cybersecurity-Skills and configures it for Cursor.
Select Cursor when prompted
The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:
Verify installation
Confirm successful installation by checking the skill directory location:
Reload or restart Cursor to activate performing-dynamic-analysis-with-any-run. Access the skill through slash commands (e.g., /performing-dynamic-analysis-with-any-run) 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.
List & Monetize Your Skill
Submit your Claude Code skill and start earning
Use Cases▌
Exploratory Data Analysis
Quickly understand datasets, identify patterns, and generate insights
Example
Analyze CSV with 100K rows, identify outliers, visualize correlations, suggest hypotheses
Reduce EDA time from hours to minutes, uncover insights faster
Data Cleaning & Transformation
Write scripts to clean messy data, handle missing values, normalize formats
Example
Generate Python/SQL to fix date formats, impute missing values, remove duplicates
Automate 80% of data preprocessing work
Statistical Analysis
Perform hypothesis testing, regression, and statistical modeling
Example
Run A/B test analysis, calculate confidence intervals, interpret p-values
Get statistically sound analysis without PhD in statistics
Data Visualization
Create charts, dashboards, and visual reports
Example
Generate matplotlib/seaborn code for time series plots, distribution charts, heatmaps
Build presentation-ready visualizations 3x faster
Implementation Guide▌
Prerequisites
- ›Claude Desktop or compatible AI client
- ›Python environment (pandas, numpy, matplotlib) or SQL database access
- ›Basic understanding of data analysis concepts
- ›Sample datasets for testing skill capabilities
Time Estimate
20-40 minutes to set up and run first analysis
Installation Steps
- 1.Install data analysis skill using provided command
- 2.Prepare a sample dataset (CSV, JSON, or database connection)
- 3.Start with descriptive statistics: 'Summarize this dataset'
- 4.Progress to visualization: 'Create a scatter plot of X vs Y'
- 5.Advanced analysis: 'Run linear regression and interpret results'
- 6.Validate outputs: check calculations, verify visualizations make sense
- 7.Document analysis workflow for reproducibility
Common Pitfalls
- ⚠Not validating statistical assumptions before applying tests
- ⚠Accepting visualizations without checking data accuracy
- ⚠Overlooking data quality issues (missing values, outliers)
- ⚠Misinterpreting correlation as causation
- ⚠Using wrong statistical test for data distribution
- ⚠Not considering sample size and statistical power
Best Practices▌
✓ Do
- +Always validate data quality before analysis
- +Check statistical assumptions (normality, independence, etc.)
- +Visualize data before running statistical tests
- +Document analysis steps for reproducibility
- +Cross-validate findings with domain experts
- +Use skill for initial exploration, then dive deeper manually
- +Save generated code for reuse on similar datasets
✗ Don't
- −Don't trust analysis without verifying data quality
- −Don't apply statistical tests without checking assumptions
- −Don't make business decisions solely on AI-generated analysis
- −Don't ignore outliers without investigating cause
- −Don't skip data validation and sanity checks
- −Don't use for mission-critical financial or medical analysis without expert review
💡 Pro Tips
- ★Describe data context: 'This is user behavior data from e-commerce site'
- ★Ask for interpretation: 'What does this correlation mean for business?'
- ★Request multiple approaches: 'Show 3 ways to handle missing data'
- ★Combine AI analysis with domain expertise for best insights
- ★Use for rapid prototyping, then refine analysis manually
When to Use This▌
✓ Use When
Use for exploratory data analysis, data cleaning, statistical testing, visualization prototyping, and learning new analysis techniques. Best for initial exploration and rapid insights.
✗ Avoid When
Avoid for mission-critical financial analysis, medical research requiring regulatory compliance, production ML models, or when deep statistical expertise is required for nuanced interpretation.
Learning Path▌
- 1Basic: descriptive statistics, data cleaning, simple visualizations
- 2Intermediate: hypothesis testing, regression, correlation analysis
- 3Advanced: time series analysis, clustering, predictive modeling
- 4Expert: causal inference, experimental design, advanced statistical methods
Discussion
Product Hunt–style comments (not star reviews)- No comments yet — start the thread.
Ratings
4.7★★★★★51 reviews- ★★★★★Jin Zhang· Dec 28, 2024
Keeps context tight: performing-dynamic-analysis-with-any-run is the kind of skill you can hand to a new teammate without a long onboarding doc.
- ★★★★★Chinedu Farah· Dec 28, 2024
performing-dynamic-analysis-with-any-run fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
- ★★★★★Li Harris· Dec 24, 2024
performing-dynamic-analysis-with-any-run is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
- ★★★★★Alexander Khan· Dec 12, 2024
performing-dynamic-analysis-with-any-run has been reliable in day-to-day use. Documentation quality is above average for community skills.
- ★★★★★Nikhil Jackson· Nov 19, 2024
Registry listing for performing-dynamic-analysis-with-any-run matched our evaluation — installs cleanly and behaves as described in the markdown.
- ★★★★★Zara Gill· Nov 19, 2024
We added performing-dynamic-analysis-with-any-run from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
- ★★★★★Rahul Santra· Nov 7, 2024
Solid pick for teams standardizing on skills: performing-dynamic-analysis-with-any-run is focused, and the summary matches what you get after install.
- ★★★★★James Diallo· Nov 3, 2024
performing-dynamic-analysis-with-any-run reduced setup friction for our internal harness; good balance of opinion and flexibility.
- ★★★★★Pratham Ware· Oct 26, 2024
performing-dynamic-analysis-with-any-run is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
- ★★★★★Mei Rao· Oct 22, 2024
We added performing-dynamic-analysis-with-any-run from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
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