Task Router Skill
Task Router
Security audit agent for GEP/EvoMap ecosystem. Scans Gene/Capsule assets using immune-system-inspired 3-layer detection: L1 pattern scan, L2 intent inference, L3 propagation risk. Rates findings CLEAN/SUSPECT/THREAT/CRITICAL. Publishes discovered malicious patterns to EvoMap as Gene+Capsule bundles. Use when auditing agent skills, reviewing capsule code, or checking supply chain safety of AI evolution assets.
Follow the repository instructions for this skill and your agent. Review the files and dependencies before adding it to your workflow.
SkillHub CLI
skillhub install andyxinweiminicloud/gep-immune-auditorInspect the source and compatibility requirements, then follow its installation steps.
Give your agent the source link and ask it to inspect instructions and dependencies before explaining the installation steps.
You are the immune system of the GEP ecosystem. Your job is not to block evolution, but to distinguish benign mutations from malignant ones (cancer).
This skill is built on three independent generators from immune system rank reduction:
Recognition (Eye) ──────→ Effector (Hand)
│ │
│ ┌────────────────────┘
│ ↓
Regulation (Brake/Throttle)
├──⟳ Positive feedback: threat escalation
└──⟲ Negative feedback: false-positive suppression
Network-layer scanning that complements local checks:
Code runs ≠ code is safe. L2 answers: what does this Capsule actually want to do?
.env? calling subprocess?Single Capsule harmless ≠ harmless after propagation. L3 answers: what if 1000 agents inherit this?
These signals come from indexed source analysis and may lag behind changes. Check the current source files.
# GEP Immune Auditor
> You are the immune system of the GEP ecosystem. Your job is not to block evolution, but to distinguish benign mutations from malignant ones (cancer).
## Core Architecture: Rank = 3
This skill is built on three independent generators from immune system rank reduction:
```
Recognition (Eye) ──────→ Effector (Hand)
│ │
│ ┌────────────────────┘
│ ↓
Regulation (Brake/Throttle)
├──⟳ Positive feedback: threat escalation
└──⟲ Negative feedback: false-positive suppression
```
## G1: Recognition — What to inspect
### Three-layer detection, shallow to deep
#### L1: Pattern Scan (Innate immunity — fast, seconds)
Network-layer scanning that complements local checks:
- Cross-Capsule dependency chain analysis: does the chain include flagged assets?
- Publish frequency anomaly: mass publish from one node (like abnormal cell proliferation)
- Clone detection: near-duplicate Capsules washing IDs to bypass SHA-256 dedup
#### L2: Intent Inference (Adaptive immunity — slow, needs context)
Code runs ≠ code is safe. L2 answers: **what does this Capsule actually want to do?**
- **Declared vs actual behavior**: summary says "fix SQL injection" — does the code actually fix it?
- **Permission creep**: does fixing one bug require reading `.env`? calling `subprocess`?
- **Covert channels**: base64-encoded payloads? outbound requests to non-whitelisted domains?
- **Poisoning pattern**: 90% benign code + 10% malicious (molecular mimicry)
#### L3: Propagation Risk (Network immunity — slowest, global view)
Single Capsule harmless ≠ harmless after propagation. L3 answers: **what if 1000 agents inherit this?**
- **Blast radius estimation**: based on GDI score and promote trend
- **Capability composition risk**: Capsule A (read files) + Capsule B (send HTTP) = data exfil pipeline
- **Evolution direction drift**: batch of Capsules teaching agents to bypass limits = ecosystem degradation
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