geo-infer-sec
Security and threat detection for geospatial systems. Use when implementing spatial access control, anomaly detection on access patterns, geospatial threat assessment, security auditing, or spatial data anonymization.
Best use case
geo-infer-sec is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Security and threat detection for geospatial systems. Use when implementing spatial access control, anomaly detection on access patterns, geospatial threat assessment, security auditing, or spatial data anonymization.
Teams using geo-infer-sec should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/GEO-INFER-SEC/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How geo-infer-sec Compares
| Feature / Agent | geo-infer-sec | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Security and threat detection for geospatial systems. Use when implementing spatial access control, anomaly detection on access patterns, geospatial threat assessment, security auditing, or spatial data anonymization.
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
# GEO-INFER-SEC
## Instructions
### Core Capabilities
- **Access control**: Role-based and spatial-boundary-based authorization (RBAC + SBAC)
- **Threat detection**: Anomaly detection on spatial access patterns, behavioral profiling
- **Confidence scoring**: Dynamic confidence computation (uses real `calculated_confidence`)
- **Audit logging**: Security event tracking with spatial context, chain of evidence
- **Data protection**: Spatial data anonymization, k-anonymity, differential privacy
- **Integrity**: Data integrity verification, tampering detection
### Key Imports
```python
from geo_infer_sec.core.integrated_security import IntegratedSecurityEngine
from geo_infer_sec.core.access_control import SpatialAccessController
from geo_infer_sec.core.threat_detection import ThreatAnalyzer
from geo_infer_sec.core.anonymization import SpatialAnonymizer
```
## Examples
```python
from geo_infer_sec.core.integrated_security import IntegratedSecurityEngine
engine = IntegratedSecurityEngine()
result = engine.assess_threat(
request=api_request,
user_context=user_profile,
spatial_context=request_location
)
print(f"Confidence: {result.confidence_score}") # Real computed value
```
## Guidelines
- `confidence_score` uses real `calculated_confidence` — not hardcoded
### Integrations
- Integrates with API for endpoint security
- Test: `uv run python -m pytest GEO-INFER-SEC/tests/ -v`