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SPECTRA

Security Policy, Emerging Cyber Threats, Research & AI

SPECTRA is an AI-automated monthly cybersecurity policy digest. It collects from 17 public government and industry sources, uses Claude to categorize and summarize items, and renders a branded PDF report -- all in a single scheduled task run.

Built for DoD/federal cybersecurity practitioners who need to stay current on policy, threats, and AI developments without manually scanning dozens of feeds.

What It Produces

A monthly PDF digest with seven sections:

Section What's Covered
Executive Summary Top 5 items by relevance
Policy & Compliance Agency actions, EOs, CISA directives, FedRAMP, CMMC
Publications & Standards NIST SPs, CISA guides, strategy docs
Threats & Incidents Breaches, APT campaigns, KEVs, ICS advisories
AI & Agentic Developments Frontier models, AI policy, agentic capabilities
Legislative Highlights Bills with significant movement only
Upcoming Conferences 5-10 events for the next 2-3 months

Each section is limited to the top 20 items by relevance score. Items are scored 1-10 based on direct impact to federal cyber practitioners.

Sources (17)

Government (8): NIST CSRC, CISA Alerts, CISA KEV Catalog, Federal Register API, Congress.gov API, Executive Orders, FedRAMP Notices, FedRAMP Changelog

Industry News (4): CyberScoop, Nextgov/FCW, Dark Reading, The Record

AI (5): OpenAI Blog, Google AI Blog, DeepMind Blog, The Verge AI, MIT Technology Review AI

All sources are public and unclassified. See src/collect/config.yaml for the full configuration.

Pipeline

SPECTRA architecture

The entire pipeline runs as a single Claude Code scheduled task. Claude reads the raw items, categorizes each into the appropriate section, writes a 2-3 sentence summary, scores relevance, consolidates duplicate stories, and assembles the markdown draft. No API key needed -- runs on the Claude Code subscription.

Setup

Prerequisites

  • Python 3.10+
  • Claude Code (for the scheduled curation task)

Install

git clone https://github.com/JAKSecurity/SPECTRA.git
cd SPECTRA
pip install -r requirements.txt

Run Manually

# 1. Collect from all sources
PYTHONPATH="." python -m src.collect.runner src/collect/config.yaml data/sources

# 2. Prep (load + dedup)
PYTHONPATH="." python -m src.curate.curate data/sources/2026-04 data/drafts/prepped_2026-04.json

# 3. Curate -- this step requires Claude Code (scheduled task handles it)
#    See the scheduled task SKILL.md for the full curation prompt

# 4. Render to PDF
PYTHONPATH="." python -m src.render.render data/drafts/2026-04-SPECTRA.md output/2026-04-SPECTRA.pdf

Automated Monthly Run

The spectra-monthly Claude Code scheduled task runs the full pipeline at 5AM on the 1st of each month. It collects sources, curates with AI, presents the draft for review, renders the PDF, and delivers via email and Discord.

Tests

python -m pytest tests/ -q

59 tests covering fetchers, prep/dedup, draft assembly, and PDF rendering.

Project Structure

src/
  collect/          Source fetcher modules and config
    config.yaml     Source URLs, types, category hints
    runner.py       Orchestrates fetchers, writes health report
    fetchers/       One module per source type (RSS, Federal Register API, etc.)
  curate/           Item loading, dedup, and draft assembly
  render/           PDF template and rendering (reportlab)
scripts/            Shell entry points for each stage
tests/              59 tests (pytest)
docs/               Design spec and backlog

License

MIT

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