skills/mukul975/anthropic-cybersecurity-skills/detecting-insider-data-exfiltration-via-dlp/Gen Agent Trust Hub
detecting-insider-data-exfiltration-via-dlp
Pass
Audited by Gen Agent Trust Hub on Sep 17, 2026
Risk Level: SAFEINDIRECT_PROMPT_INJECTIONEXTERNAL_DOWNLOADS
Full Analysis
- [SAFE]: The operations performed in
scripts/agent.pyare limited to data processing and statistical analysis using the pandas library. The script does not interact with the network, spawn shell processes, or modify sensitive system configurations. - [INDIRECT_PROMPT_INJECTION]: The skill serves as a surface for indirect prompt injection as it ingests untrusted log data from CSV or JSON files.
- Ingestion points: External data is loaded via
pd.read_csvandpd.read_jsoninscripts/agent.pyand demonstrated inSKILL.md. - Boundary markers: The skill does not implement explicit delimiters or instructions to ignore embedded content within the analyzed logs.
- Capability inventory: No dangerous or exploitable capabilities (e.g., file writing to sensitive paths, network requests, or
eval/exec) are associated with the ingestion flow. - Sanitization: The skill does not perform sanitization of input strings, though the impact is mitigated as data is primarily used for quantitative analysis.
- [EXTERNAL_DOWNLOADS]: The documentation references the Microsoft Graph API and pandas documentation for implementation guidance. These involve well-known services (graph.microsoft.com, pandas.pydata.org) used appropriately within the context of security operations.
Audit Metadata