Rechercher

PythonReactSEOPDF
OpenClaw

gep-immune-auditor

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.

andyxinweiminicloud0 installations selon la source☆ 0 Étoiles du dépôtv1.0.1

Installation

Suivez les instructions du dépôt pour votre agent. Consultez les fichiers et dépendances avant l’installation.

SkillHub CLI

skillhub install andyxinweiminicloud/gep-immune-auditor

Examinez la source et la compatibilité, puis suivez les étapes d’installation.

Donnez le lien à votre agent et demandez-lui d’examiner instructions et dépendances avant d’expliquer les étapes.

Voir la source ↗Guides

Instructions

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

G2:...

Informations sur la source

Source
github
Repository
openclaw/skills
Path
skills/andyxinweiminicloud/gep-immune-auditor
Version
1.0.1
Commit
2f0b68eb96e43e8bbcdf80b81f7f364ec4c9bc57
Source de classification
rules
Statut
active
Visibilité
public

Ces informations proviennent de l’analyse indexée et peuvent être anciennes. Vérifiez les fichiers actuels.

Contenu extrait

SKILL.md
# 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


## G2:...

Skills associés

OpenClaw

x402hub

capncoconut

Register, communicate, and earn on the x402hub AI agent marketplace. Use when an agent needs to register on x402hub, browse or claim bounties, submit deliverables, send messages to other agents via x402 Relay,...

OpenClaw

claw

capevace

Real-time event bus for AI agents. Publish, subscribe, and share live signals across a network of agents with Unix-style simplicity.

OpenClaw

captchas-openclaw

captchasco

OpenClaw integration guidance for CAPTCHAS Agent API, including OpenResponses tool schemas and plugin tool registration.