cti-expert

CTI Expert

Cyber threat intelligence and open-source intelligence skill. Turns Claude into a trained CTI/OSINT analyst. Generates precision search queries, interprets public data, builds case timelines, and delivers structured intelligence products — no API keys, no paid subscriptions.

Runs anywhere. Works in Claude Code (Desktop & CLI) and in OpenAI Codex / ChatGPT and other AGENTS.md-aware agents — see AGENTS.md for the cross-agent runtime contract. Throughout this file, $SKILL_DIR = the directory containing this SKILL.md (Claude Code: ~/.claude/skills/cti-expert; Codex/manual clone: the repo you are working in). Resolve it by locating SKILL.md — never hard-assume ~/.claude. Detect the OS once (Windows/macOS/Linux) and prefer uv for all Python — see §13 Tool Auto-Install Policy.

Collection method: agent-browser when available (JavaScript-heavy sites, infinite-scroll, screenshot evidence), with automatic fallback to web search / web fetch / direct URL fetch. Tool limitations are logged as collection gaps — never as case blockers.

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1. Quick Start

# Full autonomous case — runs every applicable technique
/case target.com

# Guided flow for first-time investigators
/flow person

# Summary of what's been found so far
/brief

Append --yolo to any command to skip all interactive prompts and confirmations. The analyst makes every decision autonomously.

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2. AEAD Case Lifecycle

Every investigation follows four phases:

Run /progress at any point to see which phase you're in and what's pending.

/case and web-infra pivoting. For a domain or URL target, /case includes web-infrastructure pivoting (/webpivot) in the Acquire phase. It runs keyless by default (crt.sh + passive DNS + anonymous urlscan) and upgrades automatically when premium keys are set via /apikeys (Shodan/Censys/FOFA/DNSLytics/SecurityTrails/urlscan-PRO/WhoisXML). Because /webpivot can fetch the target directly, for hostile infrastructure it prefers passive capture (urlscan/Wayback) — see techniques/web-pivot.md. It is not run for username/phone/person targets.

Archive IOC harvest runs by default too. For domain/URL targets the Acquire phase also runs wayback_harvest.py <domain> --indicators (add --urlscan when URLSCAN_API_KEY is set), harvesting emails, phones, crypto wallets, tracking/verification IDs, SaaS-operator IDs, and socials from the entire Wayback history — not just the live page — with first-seen/last-seen per selector. It writes case-schema indicators[] to <case>/raw/harvest.indicators.json, which merge into the case and flow into the auto-saved IOC bundle at Deliver. This is the step that recovers selectors a network later scrubbed — across the whole snapshot corpus, not just the live page. Passive by construction — only web.archive.org (+ urlscan.io if keyed), never the target.

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3. Command Reference

Commands grouped by AEAD phase.

Acquire

| /dork-sweep [target] [--telegram\|--docs\|--filetype\|--all] [--after DATE] [--clean] | Zero-auth dork sweep: Telegram ecosystem, 18 doc-hosts, filetype families; 4-tier fallback cascade | /dork-sweep example.com --filetype | | /docleak [target] [--platform list] [--severity high] | 18-platform document leak hunt with severity classification (CRITICAL/HIGH/MEDIUM/LOW) | /docleak "Acme Corp" |

| /dns-history [domain] | Historical DNS record changes (A, NS, MX) via passive DNS | /dns-history example.com | | /cert-history [domain] | SSL/TLS certificate timeline from CT logs (crt.sh) | /cert-history example.com | | /email-permute [name] [domain] | Generate email permutations from name + domain | /email-permute "John Smith" company.com | | /proton-check [email] | Proton Mail account creation date via PGP key | /proton-check user@proton.me | | /pgp-lookup [email] | PGP key search — creation date, UIDs, signatures | /pgp-lookup dev@example.com | | /wifi [ssid] | WiFi SSID geolocation via Wigle.net | /wifi "HomeNetwork" | | /wifi --bssid [mac] | Exact AP lookup by MAC address | /wifi --bssid AA:BB:CC:DD:EE:FF | | /register [name] | Add a subject to the case workspace | /register JohnDoe | | /snapshots [url] | List/fetch archived Wayback snapshots. Note: WebFetch is blocked from web.archive.org (robots.txt) — use scripts/webpivot/wayback_fetch.py to list captures and pull archived content. See analysis/archive-explorer.md | /snapshots example.com |

Enrich

Assess

Deliver

UX & Navigation

Configure

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4. Subject & Connection Model

Reference: engine/case-schema.json, engine/subject-registry.md

Subject Types

Connection Types

owns         — domain, email, or asset ownership
uses         — platform account or tool usage
works_at     — employment or affiliation
linked_to    — general association
alias        — same identity, different handle
communicated_with — observed contact

Finding Trust Scores

Source Reliability Scale

Complements numeric trust scores with source-level grading. Trust score rates finding content; source reliability rates the source itself.

Confidence Levels

Map Rendering (ASCII Mandatory)

ALL visualization commands produce ASCII box-drawing art by default. This includes /graph, /render entities, /render network, /render timeline, /render risk, /pathfind, and /show-connections. Mermaid available only with explicit --mermaid flag.

Why ASCII-first: Universal terminal compatibility, renders correctly in .md and .docx exports, no external renderer dependency.

┌─────────────────────────────┐   owns   ┌───────────────────────────┐
│ 👤 John Doe          [3/5] │══════════▶│ 🌐 example.com     [4/5] │
└─────────────────────────────┘           └───────────────────────────┘
         │ works_at                       │ hosted_on
         ▼                                ▼
┌─────────────────────────────┐  ┌───────────────────────────┐
│ 🏢 Acme Corp         [4/5] │  │ 🖥 203.0.113.10    [4/5] │
└─────────────────────────────┘  └───────────────────────────┘

Connection arrows: ═══▶ owns · ───▶ confirmed · ···▶ inferred · ←─▶ bidirectional · ─·─▶ alias · ╌╌▶ works_at Box styles: ┌──┐ confirmed · ┌ ─ ┐ unverified · ╔══╗ target Badge: [n/5] trust score · emoji prefix = entity type

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5. Finding Framework

Reference: engine/finding-framework.md, engine/conflict-resolver.md

Every finding logged via /record-finding captures:

Source URL / method
Collection method (browser | search | fetch | manual)
Trust score (1–5)
Confidence level (VERIFIED → CHALLENGED)
Timestamp
Linked subjects

Conflict detection (engine/conflict-resolver.md): When two findings about the same subject contradict each other, the system flags a CONTESTED state. Both findings are preserved. Resolution options: accept one, mark both TENTATIVE, or log the conflict as its own finding.

Deviation detection (analysis/deviation-detector.md): Automatically flags behavioral anomalies — account creation gaps, platform presence inconsistencies, metadata mismatches.

Weight engine (analysis/weight-engine.md): Aggregates trust scores across findings to compute subject-level confidence.

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6. Technique Catalog

Reference directory: techniques/

| fx-dork-sweep.md | Zero-auth Google/Bing dork sweeps — Telegram ecosystem, doc-hosts, filetype families + 4-tier fallback cascade (WebSearch → Bing → DDG → agent-browser) | | fx-document-leak-hunt.md | 18-platform document leak discovery with severity classification, paywall handling, auto-snapshot |

| username-osint.md | 3000+ platform enumeration with pivot extraction | | phone-osint.md | Carrier lookup, VoIP detection, spam databases, FreeCNAM CallerID, WhoCalld, USPhoneBook reverse lookup | | email-osint.md | Full email investigation: accounts, breaches, infra, Proton API, PGP keys, permutation, manual reference tools | | fx-dns-cert-history.md | Historical DNS records (passive DNS, A/NS/MX changes), SSL certificate timeline (crt.sh CT logs) | | threat-intel.md | AbuseIPDB, GreyNoise, OTX, VirusTotal, URLScan.io, CIRCL CVE, NVD API, ransomware.live | | web-traffic-analysis.md | SimilarWeb/Semrush estimation, audience data | | secret-scanning.md | Credential/secret detection in repos and pastes | | github-osint.md | GitHub user/org/repo profiling, code search, commit metadata, forks, collaboration networks | | domain-advanced.md | Subfinder, Amass, CT log enumeration | | social-media-platforms.md | Twitter/X Snowflake IDs, Discord, Strava, BlueSky, ShareTrace share link analysis | | advanced-geolocation-techniques.md | Overpass Turbo, road sign analysis, reflected text | | web-dns-forensics.md | Zone transfers, Tor lookups, GitHub, Telegram, WHOIS, Xeuledoc Google doc intel | | fx-visitor-intelligence.md | Visitor stats, tech stack, geo, traffic sources, analytics/AdSense/advertising ID cross-domain linking, competitors | | wifi-ssid-osint.md | WiFi SSID/BSSID geolocation via Wigle.net, encryption analysis, travel patterns | | scam-check.md | Phishing/scam domain verification and detection | | cloud-audit.md | Cloud infrastructure security (AWS/GCP/Azure): IAM, network, storage, compute, logging, secrets | | microsoft-tenant-recon.md | M365/Azure tenant enumeration — federation, tenant ID, Azure AD config, MDI detection | | fx-edge-appliance-recon.md | Edge/VPN appliance fingerprint → CISA KEV/CVE catalog (Citrix/F5/Cisco/Ivanti/Forti/PAN/Exchange) + exposed-service port-risk matrix (Shodan InternetDB, passive-first) | | fx-saas-identity-recon.md | SaaS tenancy + identity-fabric mapping — DNS-TXT tenancy tokens, IdP fingerprinting (Okta/Auth0/OneLogin/Ping/Keycloak/ADFS/Entra), unauthenticated API/GraphQL/OpenAPI-spec discovery | | dependency-audit.md | Supply chain security: CVE audit, framework-specific vulns, typosquatting, CI/CD security | | disk-forensics.md | Digital evidence analysis: image integrity, Sleuth Kit, file carving, artifact recovery, timeline | | incident-triage.md | Security incident response: NIST 800-61 methodology, containment, evidence preservation, IOC extraction | | owasp-audit.md | OWASP Top 10 (2021) source code audit with grep patterns and CWE references | | prompt-injection-audit.md | AI/LLM security: prompt injection classes, agent/MCP security, permission boundary audit | | stealer-log-analysis.md | Infostealer-log triage: family fingerprinting (RedLine/Vidar/StealC/Lumma/META/traffer), victim-vs-operator profiling, cross-log actor correlation, IOC + attribution extraction (uv run parser, raw artifacts shown) | | agent-browser.md | Interactive browser collection & evidence capture via vercel-labs/agent-browser (CDP, accessibility-tree @eN snapshots, screenshots; primary interactive collector, complementary to Scrapling) |

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7. Workflow Guides

Reference directory: workflows/

Activate via /flow [type] — interactive guided prompts walk through each step.

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8. Output Formats

Reference: output/reports/, connectors/

Mandatory File Export (CRITICAL)

Every /report, /brief, and /case command MUST auto-save the default export set to disk at the end of delivery:

Save location: Current working directory, or ./osint-reports/ subdirectory if it exists.

• --yolo: save the five-format default set with no prompt.
• Interactive mode: save the default set, then ask the user at the end whether they also want DOCX (Word) or PDF.
• DOCX is NOT in the default set (heaviest, most failure-prone toolchain). Generate it on request (/report docx) or automatically for /report legal (evidentiary, where a fixed Word/PDF artifact is expected). HTML "Print → Save as PDF" covers most PDF needs for free.
• Explicit machine-format subcommands always emit that format directly: /report json, /report csv, /report ioc.

The HTML, JSON, CSV and IOC outputs all derive from one report JSON. Build it once, then run the generators below.

Step 1 — Build the report JSON file. The generators expect a SPECIFIC flat format (NOT the engine case-schema.json). You MUST construct the JSON matching this exact structure before calling the scripts. Reference: scripts/sample-cti-report-data.json.

{
  "case": {
    "id": "CTI-2026-001",          // string, case identifier
    "label": "Case Title",         // string, human-readable name
    "classification": "OPEN SOURCE", // string
    "analyst": "AI-Assisted CTI",  // string
    "date": "2026-04-08",          // ISO date
    "subject": "target.com",       // string, primary subject
    "status": "active",            // string
    "exposure_score": 72           // integer 0-100 (optional, enables risk gauge)
  },
  "executive_summary": "Full paragraph summarizing investigation findings...",
  "subjects": [
    {
      "id": "SUB-001",            // string ID (not UUID)
      "label": "target.com",      // human-readable name — REQUIRED for display
      "type": "domain",           // lowercase: domain, person, ip, organization, email, username
      "confidence": 95,           // INTEGER 0-100 (not string like "VERIFIED")
      "verified": true,           // boolean
      "aliases": ["alias1"],      // string array
      "first_seen": "2025-01-15", // ISO date string
      "notes": "Primary domain"   // string
    }
  ],
  "findings": [
    {
      "id": "FND-001",            // string ID
      "subject_id": "SUB-001",    // links to subject
      "type": "infrastructure",   // credential, infrastructure, identity, exposure, behavioral, legal
      "weight": "HIGH",           // CRITICAL, HIGH, MEDIUM, LOW, INFO — drives severity colors
      "description": "Full description of the finding...",
      "source_url": "https://...",
      "collected_at": "2026-04-08T10:00:00Z",
      "confidence": 88,           // INTEGER 0-100 (not string)
      "tags": ["tag1", "tag2"]
    }
  ],
  "connections": [
    {
      "id": "CON-001",
      "from_id": "SUB-001",       // subject ID
      "to_id": "SUB-002",         // subject ID
      "relationship": "owns",     // string describing relationship
      "strength": "confirmed"     // confirmed, probable, possible
    }
  ],
  "timeline": [
    {"date": "2025-01-15", "event": "Domain registered"}
  ],
  "sources": [
    {"name": "Source Name", "url": "https://...", "date": "2026-04-08"}
  ],
  "intelligence_gaps": [
    "Gap description string"
  ],
  "recommendations": [
    "Action item string"
  ],
  "visitor_stats": {              // optional — enables visitor intelligence charts
    "domain": "target.com",
    "monthly_visits": 150000,
    "traffic_sources": {"direct": 42, "search": 28, "referral": 15, "social": 10, "paid": 5},
    "top_countries": [{"country": "Vietnam", "share": 60}, {"country": "US", "share": 20}]
  },
  "caveats": ["Caveat string"]   // optional — overrides default methodology notes
}

CRITICAL FORMAT RULES:

• confidence on subjects and findings MUST be an integer (e.g., 85), NOT a string (e.g., "VERIFIED")
• findings MUST be a flat top-level array, NOT nested inside subjects
• label is REQUIRED on each subject (this is what displays in the report — not value or display_name)
• weight on findings drives severity coloring — use CRITICAL/HIGH/MEDIUM/LOW/INFO
• recommendations must be an array of strings (not objects with priority/action keys)
• All fields shown above should be populated with actual data — empty strings or "N/A" defeat the purpose
• Populate executive_summary with a full paragraph — this is the most-read section of the report

Optional enrichment fields (backward-compatible — used by the HTML report & IOC export when present):

• subjects[].role — actor | victim | infrastructure | associate | witness (drives the role chips and actor↔victim attribution; otherwise inferred from type/links)
• subjects[].selectors[] — contact/social points attached to a person/org: {type, value, platform, url} (e.g. a victim's phone, an actor's Telegram or LinkedIn) — surfaced in the Indicators panel and IOC export
• indicators[] — analyst-curated indicators to force into the export verbatim: {type, value, category, role, confidence, source_url}

Step 2 — Generate the interactive HTML report (PRIMARY human-facing deliverable). Self-contained, OFFLINE, zero toolchain to view — opens in any browser:

S="$SKILL_DIR/scripts"     # $SKILL_DIR = dir containing SKILL.md
uv run "$S/generate-cti-html.py" "REPORT.json" "REPORT.html"   # any OS, zero setup
# no uv installed: python3 "$S/generate-cti-html.py" "REPORT.json" "REPORT.html"   (Windows: py …)

It injects the report JSON into cti-report-template.html and renders, entirely client-side and offline (no CDN, no network calls): KPI cards, an exposure gauge, a finding-type pie, severity bars, a draggable/zoomable 2D entity graph, infrastructure topology, an event timeline, and the comprehensive Indicators & Selectors panel (network IOCs + contacts + identities + social/messaging handles + wallets + actor↔victim attribution) — with global search, category menus, dark/light themes and a print-to-PDF stylesheet.

Step 3 — Generate the comprehensive IOC / selector bundle.

uv run "$S/generate-cti-iocs.py" "REPORT.json" "IOC-[CASE-ID]-[YYYY-MM-DD]" --format all
# single format: --format stix | flat | csv

Extracts EVERY indicator that profiles or can reach an actor/victim — network IOCs, emails/phones, usernames/names/aliases, social-media profiles, messaging handles, crypto wallets, and the attribution links between subjects. Full spec: techniques/ioc-export.md.

Step 4 — DOCX (on request, or automatically for /report legal). Word is no longer auto-generated by default. When the user asks for it (or for evidentiary reports), build it from the SAME report JSON + MD. The generators carry PEP 723 inline dependency metadata, so the simplest, most portable runner is uv run — it provisions the deps on the fly with zero venv/pip setup, identically on every OS. The generator is also self-healing: it forces UTF-8 output and auto-locates pandoc (including Windows %LOCALAPPDATA%\Pandoc), so no PYTHONUTF8 / PATH prelude is needed. Replace REPORT with CTI-REPORT-[CASE-ID]-[YYYY-MM-DD].

Preferred — uv run (any OS, any agent, zero setup):

S="$SKILL_DIR/scripts"     # $SKILL_DIR = dir containing SKILL.md (Claude Code: ~/.claude/skills/cti-expert; Codex/clone: the repo)
# Primary: HYBRID — full narrative from MD + charts/diagrams from JSON (zero content loss)
uv run "$S/generate-cti-docx-hybrid.py" "REPORT.md" "REPORT.json" "REPORT.docx"
# Fallback 1: JSON-only (charts + structured data; no pandoc needed)
uv run "$S/generate-cti-docx.py" "REPORT.json" "REPORT.docx"
# Fallback 2: MD-only (styled narrative, no charts)
uv run "$S/generate-cti-docx-hybrid.py" "REPORT.md" "REPORT.docx"

Windows PowerShell: set $S = "$env:USERPROFILE\.claude\skills\cti-expert\scripts" (Claude Code) or "<repo>\scripts" (Codex/clone), and use backslash paths.

Fallback — no uv installed. Use the OS interpreter; the script's ensure_deps() installs the libs on first run (via uv if present, else pip):

• macOS / Linux (Bash): python3 "$S/generate-cti-docx-hybrid.py" "REPORT.md" "REPORT.json" "REPORT.docx"
• Windows (PowerShell): py "$S\generate-cti-docx-hybrid.py" "REPORT.md" "REPORT.json" "REPORT.docx" — the Store python3 stub will not run; use py or the venv python
• Last resort (no styling/charts): pandoc "REPORT.md" -o "REPORT.docx" --from markdown --to docx --standalone

How the hybrid generator works:

1. Phase 1: pandoc converts the MD file to a base DOCX (preserving ALL narrative content — tables, lists, formatting)
2. Phase 2: python-docx post-processes to add CTI professional styling, prepend cover page + TOC, and inject charts/diagrams from JSON at matching section headings

The MD file is the primary content source. It carries the full narrative (detailed person profiles, infrastructure tables, wallet addresses, corporate structure, legal history, etc.). The JSON file provides structured data for visual elements (charts, diagrams, risk gauge). Using both together produces a complete report with zero content loss.

Rich hybrid DOCX includes: Cover page titled "CTI REPORT", table of contents, all narrative content from MD (every paragraph, table, list, code block), pie chart (finding types), bar chart (severity), risk gauge (exposure score), timeline chart, entity relationship diagram, network topology diagram, traffic/geo charts, CTI-themed styling (navy headings, styled tables), header/footer with classification and page numbers.

After saving, confirm all files to the user:

📄 Report saved (default export set):
   → CTI-REPORT-CASE001-2026-03-30.md
   → CTI-REPORT-CASE001-2026-03-30.html   (interactive — open in any browser, fully offline)
   → CTI-REPORT-CASE001-2026-03-30.json
   → CTI-REPORT-CASE001-2026-03-30.csv
   → IOC-CASE001-2026-03-30.stix.json / .txt / .csv   (indicators & selectors)

   Need a Word (.docx) or PDF too? (PDF = open the .html and Print → Save as PDF)

Report Formats

Every narrative report auto-saves the default export set (.md + .html + .json + .csv + IOC bundle — see Mandatory File Export above). /report legal additionally produces DOCX/PDF. Machine-only subcommands (json, csv, ioc) emit their native format directly.

Visual Outputs

All visual outputs use ASCII box-drawing by default. Mermaid only on explicit --mermaid flag.

Diagram tradecraft: output/visuals/diagram-patterns.md — compile-check a Mermaid diagram before presenting it, and pick the right diagram type per CTI question (attack → sequence, lifecycle → state, handoffs → swimlane, infra → graph).

The interactive HTML report (default deliverable) renders all of these as live, explorable visuals — a draggable/zoomable 2D force-directed entity graph, infrastructure topology, an event timeline, and SVG charts (pie/bar/gauge/donut) — alongside the ASCII versions in the .md.

Connectors

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9. Skill Tiers & Customization

Reference: experience/skill-tiers.md, experience/layered-detail.md

Tiers

Switch tiers at any point — output adapts immediately.

Guided Flows

experience/guided-flows/ contains step-by-step interactive flows:

• person-investigation.md — Full guided person case
• domain-reconnaissance.md — Guided domain sweep
• email-investigation.md — Guided email tracing
• rapid-case.md — 10-minute abbreviated sweep

Activate: /flow person · /flow domain · /flow email · /flow quick

Case Templates

experience/case-templates/ contains pre-built starting configurations:

• due-diligence.md — Corporate partner vetting
• security-audit.md — Organization exposure audit
• background-check.md — Individual background research

Activate: /template run [name]

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10. Ethics & Boundaries

This skill operates strictly within publicly available information.

Permitted

• Journalists verifying facts about public figures or institutions
• Security professionals auditing their own organization's exposure
• Individuals reviewing their own digital footprint
• Corporate due diligence on business partners
• Academic research and educational demonstrations

Prohibited

• Stalking, harassment, or doxing of any individual
• Accessing accounts or systems without authorization
• Social engineering or deception campaigns
• Any activity violating applicable law

Ethical reminders are issued automatically when the investigation approaches sensitive territory. Public data is not a license to cause harm.

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11. Autonomous Mode (--yolo)

Append --yolo to any command or activate at session start.

What changes:

• No clarifying questions — analyst infers context and proceeds
• No confirmation prompts — scope expands automatically on new discoveries
• Guided flows skip Q&A — reasonable defaults applied
• Both /report and /brief generated without asking

What stays the same:

• Ethics and legal boundaries — always enforced
• Trust scores on every finding
• Source citations on every claim
• /validate and /coverage run before final delivery

Activate per-command: /case target.com --yolo Activate for session: /cti-expert --yolo

---

12. Architecture Reference

cti-expert/
├── SKILL.md                    This file
├── README.md                   User-facing overview
│
├── engine/                     Case data model and state management
│   ├── case-schema.json        Subject and finding data structures
│   ├── subject-registry.md     How subjects are tracked and versioned
│   ├── finding-framework.md    Finding lifecycle, trust scores, evidence chains
│   ├── pivot-orchestration.md  Recursive spider-map pivot engine (BFS loop, edge matrix, gating)
│   ├── workspace-format.md     Workspace serialization spec
│   ├── workspace-manager.md    Save/open/list workspace logic
│   └── conflict-resolver.md    CONTESTED finding resolution
│
├── analysis/                   Pattern detection and intelligence engines
│   ├── deviation-detector.md   Behavioral anomaly detection
│   ├── auto-branch-rules.md    Automatic pivot trigger rules
│   ├── drift-monitor.md        Subject state change tracking
│   ├── cross-reference-engine.md Shared identifier detection across subjects
│   ├── archive-explorer.md     Wayback Machine integration and diff
│   ├── signature-catalog.md    Behavioral pattern library
│   ├── exposure-model.md       Exposure score calculation framework
│   ├── risk-trend-tracker.md   Temporal risk score tracking (/drift)
│   ├── pattern-library.md      Username, email, bot detection patterns
│   └── weight-engine.md        Finding aggregation and confidence weighting
│
├── techniques/                 Collection techniques and module specs
│   ├── fx-metadata-parsing.md  EXIF, headers, document metadata
│   ├── fx-image-verification.md Image authenticity and provenance
│   ├── fx-breach-discovery.md  Breach database and paste site methods
│   ├── fx-geolocation.md       GPS, W3W, Plus Codes, Street View
│   ├── fx-social-topology.md   Social graph construction and topology
│   ├── fx-email-header-analysis.md Header analysis, SPF/DKIM
│   ├── fx-document-forensics.md Document forensics and extraction
│   ├── fx-http-fingerprint.md  HTTP fingerprinting and signatures
│   ├── fx-leak-monitoring.md   Leak and breach monitoring
│   ├── username-osint.md       Platform enumeration (3000+)
│   ├── phone-osint.md          Phone carrier/VoIP/spam lookup
│   ├── email-osint.md          Deep email investigation
│   ├── threat-intel.md         Threat intelligence free lookups
│   ├── web-traffic-analysis.md Traffic estimation methods
│   ├── secret-scanning.md      Credential/secret detection
│   ├── github-osint.md         GitHub profiles, repos, code, commits, forks
│   ├── domain-advanced.md      Subdomain enumeration methods
│   ├── social-media-platforms.md Platform-specific techniques
│   ├── advanced-geolocation-techniques.md Overpass Turbo, road signs, reflected text
│   ├── wifi-ssid-osint.md      WiFi SSID/BSSID geolocation via Wigle.net
│   ├── web-dns-forensics.md    DNS, GitHub, Telegram, WHOIS
│   ├── fx-visitor-intelligence.md Visitor stats, tech stack, geo analysis
│   ├── scam-check.md           Phishing/scam domain verification
│   ├── cloud-audit.md          Cloud infrastructure security audit
│   ├── microsoft-tenant-recon.md M365/Azure tenant enumeration
│   ├── fx-edge-appliance-recon.md Edge/VPN appliance fingerprint → KEV/CVE catalog + port-risk matrix
│   ├── fx-saas-identity-recon.md SaaS tenancy + IdP fingerprint + API/GraphQL/spec discovery
│   ├── dependency-audit.md     Supply chain security audit
│   ├── disk-forensics.md       Digital evidence analysis
│   ├── incident-triage.md      Security incident response
│   ├── owasp-audit.md          OWASP Top 10 source code audit
│   ├── prompt-injection-audit.md AI/LLM security audit
│   ├── stealer-log-analysis.md Infostealer-log triage, actor attribution & IOC extraction
│   ├── agent-browser.md        Interactive browser collection & evidence capture (vercel-labs/agent-browser)
│   └── ioc-export.md           IOC export (STIX 2.1, flat list)
│
├── experience/                 UX, tiers, and guided flows
│   ├── skill-tiers.md          Novice/Practitioner/Specialist spec
│   ├── layered-detail.md       Progressive disclosure rules
│   ├── guidance-system.md      How guided flows work
│   ├── case-progress.md        Progress tracking logic
│   ├── guided-flows/           Interactive step-by-step flows
│   │   ├── flow-person-lookup.md Person investigation guided flow
│   │   ├── flow-domain-sweep.md Domain reconnaissance guided flow
│   │   └── flow-image-check.md Image verification guided flow
│   ├── case-templates/         Pre-built case configurations
│   │   ├── tpl-index.md        Template index and descriptions
│   │   ├── tpl-due-diligence.md Due diligence case template
│   │   ├── tpl-security-review.md Security audit case template
│   │   └── tpl-background-check.md Background check case template
│   ├── tutorial.md             First-time onboarding guide (/onboard)
│   ├── feedback-system.md      Investigation quality feedback loops
│   └── accessibility/          Glossary and accessibility settings
│       ├── glossary.md         OSINT term glossary
│       └── accessible-mode.md  Low-jargon mode settings
│
├── output/                     Report and visualization specs
│   ├── reports/                Report format templates
│   │   ├── format-catalog.md   Report format specifications
│   │   ├── leadership-brief-template.md Executive brief template
│   │   ├── export-specs.md     Export format specifications
│   │   └── citation-guide.md   Source citation standards
│   └── visuals/                Chart and visualization specs
│       ├── chart-templates.md  Chart rendering templates
│       ├── ui-components.md    UI component library
│       ├── render-engine.md    ASCII render engine spec
│       ├── case-dashboard.md   Dashboard layout spec
│       ├── attack-path-diagram.md  Attack path flow visualization (/render threat-path)
│       └── attack-surface-map.md   Attack surface exposure map (/render attack-surface)
│
├── scripts/                    Cross-platform install + HTML / IOC / DOCX report generation
│   ├── platform-setup.md            Cross-platform reference: OS detection, uv-first install matrix, gotchas
│   ├── install.ps1                  Windows installer (uv-first: uv venv/pip/tool; winget + pip/pipx fallback)
│   ├── install.sh                   macOS/Linux/Git-Bash/WSL installer (uv-first; brew/apt + pip/pipx fallback)
│   ├── stealer_log_parse.py         Infostealer-log analyzer — attribution, profiling, IOCs (PEP 723 / `uv run`, zero-dep)
│   ├── cti-report-template.html     PRIMARY: interactive HTML report template — self-contained & OFFLINE (charts + 2D entity graph + topology + timeline + indicator panel + search; dark/light + print-to-PDF)
│   ├── generate-cti-html.py         HTML report generator — injects the report JSON into the template (PEP 723 / `uv run`, zero-dep, self-heals UTF-8)
│   ├── generate-cti-iocs.py         Comprehensive IOC/selector exporter → STIX 2.1 / flat / CSV (network IOCs + contacts + identities + social/messaging + wallets + attribution; PEP 723 / `uv run`, zero-dep)
│   ├── generate-cti-docx-hybrid.py  Hybrid MD+JSON DOCX generator — on request / `/report legal` (PEP 723 / `uv run`; self-heals UTF-8 + pandoc)
│   ├── generate-cti-docx.py         Fallback: JSON-only generator (PEP 723 / `uv run`)
│   ├── cti_docx_postprocess.py      Post-processing: styling, chart injection, cover page
│   ├── cti_docx_charts.py           Chart rendering (pie, bar, gauge, timeline, traffic, geo)
│   ├── cti_docx_diagrams.py         Entity relationship + network topology diagrams
│   ├── cti_docx_sections.py         Report section formatting (used by JSON-only generator)
│   ├── cti_docx_styles.py           Document styling, colors, cover page, header/footer
│   ├── requirements.txt             Python dependencies
│   └── sample-cti-report-data.json  Example JSON report data
│
├── workflows/                  Professional workflow guides
│   ├── wf-journalist.md
│   ├── wf-hr-screening.md
│   ├── wf-threat-analyst.md
│   └── wf-private-investigator.md
│
├── handbook/                   Reference material
│   ├── operator-queries.md     Search operator catalog
│   ├── quick-report.md         Rapid reporting reference
│   ├── discovery-paths.md      Per-target-type search paths
│   ├── report-template.md      INTSUM format specification
│   ├── admin-endpoint-indicators.md  Admin-panel / sensitive-endpoint detection vocab & rules
│   └── tool-cascade-reference.md Tool priority and fallback chains
│
├── guides/                     Worked case walkthroughs
│   └── walkthroughs/           Step-by-step investigation examples
│       ├── walkthrough-person-lookup.md
│       ├── walkthrough-domain-sweep.md
│       └── walkthrough-username-trace.md
│
├── validation/                 Quality assurance
│   ├── coverage-matrix.md      Investigation area coverage tracking
│   ├── quality-scoring.md      Scoring methodology
│   └── verification-checklist.md Finding verification steps
│
└── connectors/                 External tool integrations
    ├── maltego-export.md
    ├── obsidian-setup.md
    └── notion-schema.md

---

Technique Activation Matrix

Which techniques activate per target type in a /case run:

| /dork-sweep | ✅ | ✅ | ✅ | ✅ | ✅ | ✅* | | /docleak | ✅ | ✅ | ✅ | ✅* | — | — |

| Social media platforms | ✅ | — | ✅ | ✅ | — | — | | Metadata forensics | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | | Photo verification | ✅ | — | ✅* | ✅ | — | — | | Network analysis | — | ✅ | ✅ | — | — | ✅ | | Advanced geolocation | ✅ | — | — | ✅ | — | — | | Web & DNS forensics | — | ✅ | ✅ | — | ✅ | ✅ | | /timeline | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | | /exposure | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | | /threat-model | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | | /wifi (SSID/BSSID) | ✅ | ✅ | ✅ | — | — | ✅ | | Visitor intelligence | — | ✅ | ✅ | — | — | ✅ | | Cloud audit | — | ✅ | ✅ | — | — | ✅ | | MSFTRecon (M365/Azure tenant) | — | ✅ | ✅ | — | — | — | | Dependency audit | — | ✅ | ✅ | — | — | — | | Disk forensics | — | — | — | — | — | — | | Incident triage | — | ✅ | ✅ | — | — | ✅ | | OWASP audit | — | ✅ | ✅ | — | — | — | | Prompt injection audit | — | ✅ | ✅ | — | — | — | | /snapshots | — | ✅ | ✅ | — | — | ✅ | | Archive IOC harvest (wayback_harvest.py) | — | ✅ | ✅ | — | — | — | | /diff | — | ✅ | ✅ | — | — | ✅ | | /drift | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | | /render threat-path | — | ✅ | ✅ | — | — | ✅ | | /render attack-surface | — | ✅ | ✅ | — | — | ✅ | | /blind-spots | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | | /source-check | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | | /report ioc | — | ✅ | ✅ | — | — | ✅ | | /report + /brief | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | | Shodan InternetDB (ports/tags/vulns) | — | ✅ | ✅ | — | — | ✅ | | GreyNoise Community (noise/threat class) | — | ✅ | ✅ | — | — | ✅ | | URLScan.io passive (scan history) | — | ✅ | ✅ | — | — | — | | Disposable email check (kickbox) | ✅ | — | ✅* | — | ✅ | — | | URLhaus (malware URL hosting) | — | ✅ | ✅ | — | — | ✅ | | ThreatFox (IOC/C2 lookup) | — | ✅ | ✅ | — | — | ✅ | | MalwareBazaar (hash → malware family) | — | — | — | — | — | — | | ipwho.is (geo + ASN + ISP) | — | ✅ | ✅ | — | — | ✅ | | DMARC/SPF/DKIM check (DNS) | — | ✅ | ✅ | — | ✅ | — |

✅* — runs for discovered key personnel within the organization MalwareBazaar — activates only via /hash [value] when a file hash is discovered during investigation

Recursive pivot orchestration (the spider-map). /case is not a one-pass collector — it runs a recursive BFS pivot engine: every discovered identifier becomes a new seed, and the relationship graph expands hop by hop until the frontier is exhausted or a budget cap is hit. The state machine — identifier typing, dedup / cycle prevention, per-node depth, the identifier→pivot edge matrix, confidence gating, and per-depth checkpoints — is scripts/pivot_orchestrator.py; the full spec is engine/pivot-orchestration.md. The orchestrator plans and tracks; the agent executes each hop's technique commands and feeds results back via --ingest.

• Defaults: posture=active (may fetch/scan targets; still passive-first for hostile infra), reach=exhaustive (pivot till the frontier empties), autonomy=checkpoint (pause after each depth level, present new nodes + proposed pivots, await approval). Safety caps: max_nodes=500, max_depth=6.
• Gating (reuses analysis/auto-branch-rules.md): exact-match links (≥95% — shared GA ID / cert / favicon / registrant email, handle exact-match) auto-pursue unbounded; HIGH/MEDIUM capped per type; LOW held unless corroborated; PII (person/phone) held unless --authorization confirmed; visited nodes and past-depth-cap nodes suppressed (loop-safe).
• Example hops: an email auto-pivots via reverse-WHOIS→domains, /breach-deep, /github-osint; a domain discovered from a person (high-confidence link) continues via /webpivot+wayback_harvest+whois_enrich+cert_pivot+subdomains; a shared GA ID reverse-pivots to sibling domains — each new node re-enters the loop.
• Control flags: /case <t> --passive|--passive-first, --reach balanced|focused, --auto (no checkpoints, run to closure), --depth N, --budget N, --authorization confirmed.
• Termination → emit edges → graph_build.py → interactive HTML force-graph + topology
  • timeline; findings/indicators roll into the auto-saved report + IOC bundle.

Legacy one-hop note (still true, now a subset of the loop): if /sweep on a domain finds an email, /email-deep and /breach-deep trigger on it automatically.

GitHub OSINT auto-fire in /case:

• Domain/Org target → run /github-osint on the org name, primary domain, discovered GitHub orgs/repos, and developer-platform hits from /query or /dork-sweep.
• Username target → run /github-osint directly when the handle has a GitHub profile or GitHub search hit.
• Person target → run /github-osint only after discovering a likely GitHub handle, commit email, repo author, or developer profile link.
• Email target → run /github-osint only after discovering commit attribution, GitHub noreply patterns, profile links, or repo references.
• Results feed into /secrets, /branch, /timeline, /crossref, /exposure, and final /report automatically.

✅* dork coverage notes: /dork-sweep on IP runs against reverse-DNS hostname once resolved (graceful skip if no rDNS); /docleak on Username targets document-author/uploader fields on scribd, slideshare, academia.edu, researchgate.

Dork auto-fire matrix — every /case target type gains coverage:

• Person → /dork-sweep --telegram --docs + /docleak on full name
• Domain → /dork-sweep --filetype --docs + /docleak on domain + org name
• Org → /dork-sweep --filetype --docs --telegram + /docleak on org + primary domain
• Username → /dork-sweep --telegram --docs + /docleak (author-angle)
• Email → /dork-sweep --telegram --docs on email + @domain
• IP → /dork-sweep on rDNS-resolved hostname (skipped if no rDNS)

Adaptive fan-out: discovered emails → Telegram dork; discovered personnel → /docleak; discovered subdomains → filetype dork; discovered usernames → Telegram + doc sweep; discovered IPs → rDNS → dork-sweep.

When /case or /sweep runs on a Domain or Org target, it inspects the MX record and SPF TXT record. If MX ends in protection.outlook.com OR SPF contains spf.protection.outlook.com, /msftrecon auto-fires as part of the Acquire phase. Results feed back into the subject registry as infrastructure findings (tenant ID, federation type, MDI presence) and into /exposure scoring.

/case pipeline walkthrough (M365-hosted Domain/Org): (a) standard DNS/WHOIS/subdomain/traffic/scam-check/breach-deep checks run first, (b) if M365 indicators present → /msftrecon fires automatically with no extra flag, (c) tenant ID discovered becomes a pivot for /branch in Enrich phase (search other domains under the same tenant). No user intervention required.

Parallel enrichment (3+ subjects): When Acquire discovers 3+ subjects, enrichment commands fan out in parallel via AgentFlow DAG orchestration. Each subject's enrichment runs independently, results merge with dedup before Assess phase. Disable with --sequential flag. See techniques/agentflow-enrichment.md.

---

Exposure Score Bands

---

Tool Priority & Fallback

Primary interactive collector: agent-browser (vercel-labs) — a fast native-Rust CDP browser that returns accessibility-tree snapshots (@eN element refs) + screenshots; no API key for core automation; cross-platform; also an MCP server. Full how-to + per-command usage in techniques/agent-browser.md. It is complementary to Scrapling, not in conflict (different ecosystems — Rust binary via npm/brew/cargo vs Python via pip — each manages its own browser): use agent-browser to interact with and witness a page (logins, clicks, screenshots, JS render) and Scrapling to fetch and parse pages programmatically.

1. Check agent-browser first (agent-browser --version; load its guide via agent-browser skills get core; install per the auto-install policy if missing)
2. Use agent-browser for: screenshot evidence, logins/interactive UI, JS-rendered/SPA pages, complex multi-step browser flows
3. Use Scrapling DynamicFetcher for: JS-heavy sites, SPA content, auto-escalation from static (programmatic)
4. Use Scrapling StealthyFetcher for: anti-bot bypass, Cloudflare-protected targets
5. Use Scrapling Fetcher for: fast static page collection, HTML parsing (~2ms)
6. Fall back to web search → web fetch → direct curl — no investigation blockers
7. Tag each finding with collection method: [browser] · [scrapling-dynamic] · [scrapling-stealth] · [scrapling-static] · [search] · [fetch] · [manual] · [whois-lib] · [whois-cli] · [whois-api]

---

Tool Auto-Install Policy

Before running any CLI tool, detect the OS, check whether the tool exists, and if not, install it automatically and silently using the method correct for that OS. This ensures zero-friction investigation on Windows, macOS, and Linux alike — the analyst never stalls on a missing dependency and never runs a Linux-only command on Windows.

Full cross-platform reference: scripts/platform-setup.md — OS detection, $PY/shell conventions, package managers, the complete per-tool × per-OS install matrix, and known gotchas. Consult it whenever this summary is not enough.

Step 0 — Detect the platform (once per session)

Determine the OS before running anything, and cache it for the rest of the session. In Claude Code the environment block already reports it (e.g. Platform: win32 → Windows). Otherwise probe: PowerShell $IsWindows/$IsMacOS, or Bash uname -s (Darwin=macOS, Linux=Linux, MINGW*/MSYS*/CYGWIN*=Windows/Git Bash). Then fix these conventions:

On Windows, python3/python in the Bash tool is often a non-functional Microsoft Store stub. Prefer uv (it brings its own Python and sidesteps the stub); otherwise use py via PowerShell.

Step 0.5 — Ensure uv (the primary Python toolchain)

uv is the preferred way to install and run everything Python in this skill. It is a single fast, cross-platform tool that replaces pip, pipx, venv, and pyenv, manages its own Python (so the Windows Store-stub problem disappears), and resolves script dependencies on the fly. Using uv also collapses the per-OS split for Python tools — the same command works on Windows, macOS, and Linux.

• Check: uv --version
• Install if missing:
  • Windows: winget install --id astral-sh.uv — or powershell -ExecutionPolicy ByPass -c "irm https://astral.sh/uv/install.ps1 | iex"
  • macOS / Linux: curl -LsSf https://astral.sh/uv/install.sh | sh — or brew install uv
  • Any OS that already has pip: python -m pip install uv

If uv genuinely cannot be installed, fall back to the per-OS pip/pipx/venv path — nothing here hard-requires uv.

Auto-Install Protocol

1. Check: OS-correct existence test from the table above (or <$PY> -c "import <module>" for Python modules)
2. Install: If missing, run the OS-correct install command (see dispatch below / platform-setup.md)
3. Verify: Confirm the tool resolves before proceeding — re-check; on Windows a fresh install may need a new shell or a probe of its install dir
4. Log: Note [auto-installed] in the finding's collection method tag
5. Continue: Proceed with the investigation — never block on tool availability

Install Dispatch by Category

Python tools — uv, identical on every OS (the big win: no per-OS split). CLIs use uv tool; libraries go into the skill venv via uv pip. No-uv fallback in the last column.

<$PY> = py (Windows) / python3 (macOS/Linux), or the venv python. On PEP-668 Linux add --break-system-packages to the pip fallback.

System binaries — OS package manager (uv does not manage these):

Go tools (after Go is present — identical on all OSes): go install <module> for subfinder, amass, gau, gitleaks, httpx. PhoneInfoga → GitHub release binary per OS/arch. ASN → Git Bash/WSL bash <(curl -sL …/nitefood/asn/master/asn) on Windows, native bash on macOS/Linux, or RDAP/ipwho.is HTTP fallback.

The exact winget IDs, brew formulae, apt packages, uv commands, import names, and Go module paths for every tool are tabulated in scripts/platform-setup.md §5. To provision a fresh machine in one shot, run the bundled installer for the detected OS:

• Windows: powershell -ExecutionPolicy Bypass -File "$env:USERPROFILE\.claude\skills\cti-expert\scripts\install.ps1"
• macOS / Linux / Git Bash / WSL: bash ~/.claude/skills/cti-expert/scripts/install.sh

(both accept --headless/-Headless, --go/-Go, --all/-All)

Behavior Rules

• uv first (anything Python): prefer uv — uv tool install for CLIs, uv pip install for libraries, uv run for scripts. It behaves identically on every OS, so reach for it before per-OS pip/pipx. Fall back to <$PY> -m pip / pipx only when uv cannot be installed.
• Detect before install (system binaries): dispatch by the OS detected in Step 0 — never run apt on Windows or winget on Linux.
• Silent install: do not ask permission — install and proceed. Tool installation is a normal part of the investigation workflow.
• Go tools: require Go installed. If go is missing, install it via the OS package manager (winget install GoLang.Go / brew install go / sudo apt install -y golang), or note the gap and fall back to the next tool in the cascade.
• Linux privileges: system installs need sudo unless running as root.
• Windows specifics: winget may prompt UAC; a freshly installed tool may not be on PATH until the shell is reopened (probe its install dir or restart the shell before declaring failure). The DOCX generator self-heals UTF-8 output and pandoc location — see platform-setup.md §6.
• Git-based install: for tools without a PyPI package (msftrecon, blackbird, sharetrace), clone the repo and install its requirements.txt with <$PY> -m pip install -r requirements.txt.
• Fallback on install failure: if installation fails, log a collection gap and skip to the next tool in the cascade — never block the investigation.