skills/mukul975/anthropic-cybersecurity-skills/detecting-business-email-compromise-with-ai/Gen Agent Trust Hub
detecting-business-email-compromise-with-ai
Pass
Audited by Gen Agent Trust Hub on Sep 22, 2026
Risk Level: SAFEMETADATA_POISONINGINDIRECT_PROMPT_INJECTION
Full Analysis
- [SAFE]: The Python scripts
scripts/agent.pyandscripts/process.pyperform static linguistic and behavioral analysis on provided text inputs. The analysis is local, uses standard libraries (re, math, collections), and lacks any network operations, dynamic execution, or persistence mechanisms. - [METADATA_POISONING]: A discrepancy was identified between the author declared in
SKILL.md("mahipal") and the copyright holder in theLICENSEfile ("mukul975"). This appears to be a clerical error in the documentation rather than a deceptive attempt to obfuscate the skill's origin. - [INDIRECT_PROMPT_INJECTION]: The skill processes untrusted email content through its detection engine, creating a potential attack surface for indirect prompt injection.
- Ingestion points: Email text is ingested via the
--fileargument inagent.pyand via JSON files inprocess.py. - Boundary markers: None are implemented to distinguish email content from system instructions.
- Capability inventory: The associated scripts are restricted to file reading and printing analysis results to standard output; they cannot execute commands, access sensitive system files, or make network calls.
- Sanitization: No input sanitization is performed on the ingested text, though it is only used for regex-based feature extraction and statistical scoring.
Audit Metadata