Claude 24f816b6a3
Consolidate 22 sibling repos into layered organism structure
Place useful parts of the surrounding repos into sica-fondt by layer, per the
body model (Ada = membrane; brain/endocrine/capabilities/knowledge non-Ada):

- brain/        LLM reasoning + providers (dapr, hermes, MoMoA)
- capabilities/ REPRAG sidecars: hermes tools/skills, dapr tools, parallel
                dispatch, A51 channels, and the OSINT cluster
- knowledge/    LORAG corpus: 754 cyber-skills, agency personas, secure-coding,
                MITRE ATT&CK data
- reference/    defensive threat-reference (C3, shhbruh doc) + AdaYaml parser

License handling: AGPL sources (worldosint, advanced_evolution, mercury,
Reticulum) and GPL DeTTECT are SPEC-only clean-room/port descriptions — no
copyleft code copied. MIT/Apache/data parts copied as working trees.

Safety: shhbruh escape/persistence material and C3 covert-C2 kept as reference
only, not wired into the running organism. See CONSOLIDATION.md.

https://claude.ai/code/session_01UehUqEXXJJCsHoA4voCU5c
2026-06-10 06:53:01 +00:00

160 lines
5.4 KiB
Python

#!/usr/bin/env python3
"""
Trivy Container Scanning Report Aggregator
Processes Trivy JSON scan results and generates consolidated
vulnerability reports across multiple container images.
"""
import json
import os
import sys
import subprocess
from datetime import datetime
from collections import defaultdict
def run_trivy_scan(image: str, output_file: str) -> dict:
cmd = [
"trivy", "image",
"--format", "json",
"--output", output_file,
"--severity", "CRITICAL,HIGH,MEDIUM,LOW",
image,
]
result = subprocess.run(cmd, capture_output=True, text=True)
if result.returncode not in (0, 1):
print(f"Trivy scan failed for {image}: {result.stderr}")
return {}
with open(output_file) as f:
return json.load(f)
def parse_trivy_results(scan_data: dict) -> dict:
summary = {
"vulnerabilities": [],
"severity_counts": defaultdict(int),
"fixable_count": 0,
"packages_affected": set(),
}
for result in scan_data.get("Results", []):
target = result.get("Target", "")
target_type = result.get("Type", "")
for vuln in result.get("Vulnerabilities", []):
entry = {
"id": vuln.get("VulnerabilityID"),
"severity": vuln.get("Severity", "UNKNOWN"),
"package": vuln.get("PkgName"),
"installed_version": vuln.get("InstalledVersion"),
"fixed_version": vuln.get("FixedVersion"),
"title": vuln.get("Title", ""),
"target": target,
"target_type": target_type,
}
summary["vulnerabilities"].append(entry)
summary["severity_counts"][entry["severity"]] += 1
summary["packages_affected"].add(entry["package"])
if entry["fixed_version"]:
summary["fixable_count"] += 1
summary["packages_affected"] = list(summary["packages_affected"])
summary["severity_counts"] = dict(summary["severity_counts"])
return summary
def generate_fleet_report(images: list) -> dict:
report = {
"generated_at": datetime.utcnow().isoformat() + "Z",
"total_images": len(images),
"total_vulnerabilities": 0,
"total_critical": 0,
"total_fixable": 0,
"severity_summary": defaultdict(int),
"top_cves": defaultdict(int),
"image_reports": [],
}
for i, image in enumerate(images):
print(f"Scanning {i+1}/{len(images)}: {image}")
output_file = f"/tmp/trivy_scan_{i}.json"
scan_data = run_trivy_scan(image, output_file)
if not scan_data:
continue
parsed = parse_trivy_results(scan_data)
vuln_count = len(parsed["vulnerabilities"])
report["total_vulnerabilities"] += vuln_count
report["total_critical"] += parsed["severity_counts"].get("CRITICAL", 0)
report["total_fixable"] += parsed["fixable_count"]
for sev, count in parsed["severity_counts"].items():
report["severity_summary"][sev] += count
for vuln in parsed["vulnerabilities"]:
report["top_cves"][vuln["id"]] += 1
report["image_reports"].append({
"image": image,
"total_vulnerabilities": vuln_count,
"severity_counts": parsed["severity_counts"],
"fixable": parsed["fixable_count"],
"critical_vulns": [
v for v in parsed["vulnerabilities"] if v["severity"] == "CRITICAL"
],
})
report["severity_summary"] = dict(report["severity_summary"])
top_sorted = sorted(report["top_cves"].items(), key=lambda x: x[1], reverse=True)[:20]
report["top_cves"] = dict(top_sorted)
return report
def print_fleet_report(report: dict) -> None:
print(f"\n{'='*60}")
print(f"Container Fleet Vulnerability Report")
print(f"Generated: {report['generated_at']}")
print(f"{'='*60}")
print(f"Images scanned: {report['total_images']}")
print(f"Total vulnerabilities: {report['total_vulnerabilities']}")
print(f"Total critical: {report['total_critical']}")
print(f"Total fixable: {report['total_fixable']}")
print(f"\nSeverity Breakdown:")
for sev in ["CRITICAL", "HIGH", "MEDIUM", "LOW", "UNKNOWN"]:
count = report["severity_summary"].get(sev, 0)
if count:
print(f" {sev:12s}: {count}")
print(f"\nImages by Risk (sorted by critical count):")
for img in sorted(
report["image_reports"],
key=lambda x: x["severity_counts"].get("CRITICAL", 0),
reverse=True,
):
crits = img["severity_counts"].get("CRITICAL", 0)
print(f" {img['image']:50s} | Critical: {crits} | Total: {img['total_vulnerabilities']}")
def main():
images_env = os.environ.get("SCAN_IMAGES", "")
if images_env:
images = [i.strip() for i in images_env.split(",") if i.strip()]
else:
images = [
"python:3.11-slim",
"node:20-alpine",
"nginx:latest",
"golang:1.22-alpine",
]
print("No SCAN_IMAGES env var set, using default image list")
report = generate_fleet_report(images)
print_fleet_report(report)
output = f"container_scan_report_{datetime.utcnow().strftime('%Y%m%d_%H%M%S')}.json"
with open(output, "w") as f:
json.dump(report, f, indent=2, default=str)
print(f"\nReport saved to: {output}")
if __name__ == "__main__":
main()