llm-council
Pass
Audited by Gen Agent Trust Hub on Oct 26, 2026
Risk Level: SAFEINDIRECT_PROMPT_INJECTIONDYNAMIC_EXECUTIONCOMMAND_EXECUTIONMETADATA_POISONING
Full Analysis
- [METADATA_POISONING]: The skill metadata (SKILL.md) identifies the author as 'DAIR.AI' and describes the source as 'official', which contradicts the identified skill author 'sickn33'. This inconsistency can lead to misjudgment of the skill's origin and trust level.
- [INDIRECT_PROMPT_INJECTION]: The core council-of-models architecture processes untrusted outputs from multiple LLMs as inputs to other LLMs, creating a surface for injection attacks.
- Ingestion points: Phase 2 and Phase 3 scripts in
references/detailed-guide.mdingest outputs from Phase 1 (independent model responses). - Boundary markers: The scripts use basic text-based delimiters (e.g.,
=== Response A ===or[Model Name's Rankings]) to separate inputs. - Capability inventory: The skill has access to
Bash, allowing it to execute scripts that performNetworkrequests to Fireworks AI andWritesession data to the/tmpdirectory. - Sanitization: There is no evidence of escaping, filtering, or validation of the content generated by the participant LLMs before it is interpolated into the prompts for the ranking and synthesis models.
- [DYNAMIC_EXECUTION]: The skill relies on complex Python scripts defined within markdown files that are executed dynamically via shell here-docs (
python3 << 'PYEOF'). These scripts orchestrate the multi-phase API interaction and local file management. - [COMMAND_EXECUTION]: The workflow extensively uses the
Bashtool to perform environment variable checks, manage local session directories in/tmp, and execute the Python orchestration scripts.
Audit Metadata