skills/mukul975/anthropic-cybersecurity-skills/performing-indicator-lifecycle-management/Gen Agent Trust Hub
performing-indicator-lifecycle-management
Pass
Audited by Gen Agent Trust Hub on Sep 15, 2026
Risk Level: SAFEINDIRECT_PROMPT_INJECTIONMETADATA_POISONING
Full Analysis
- [INDIRECT_PROMPT_INJECTION]: The skill processes untrusted external files (such as threat reports and CSV feeds), creating an ingestion surface where malicious actors could embed prompt injection strings inside indicators or reports.
- Ingestion points: Found in
scripts/agent.py(extract_iocsandingest_ioc_feedfunctions) andscripts/process.py(--import-iocsoption), which read unstructured text and CSV files. - Boundary markers: Absent; the extracted data is not wrapped in specific delimiters or data structures that instruct the underlying LLM to ignore potential instructions embedded within the text.
- Capability inventory: There are no highly privileged capabilities (such as network requests, subprocess spawning, or dynamic execution) present in the scripts; they are confined to local file read/write and text parsing.
- Sanitization: Absent; the scripts extract indicators via regular expressions or row reading without sanitizing or escaping content before it enters the agent's context.
- [METADATA_POISONING]: A metadata inconsistency exists where the
SKILL.mdfrontmatter defines the author asmahipal, whereas theLICENSEfile attributes the copyright tomukul975.
Audit Metadata