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credkellar/a-c-d-matrix-force

By credkellar

•Updated 3 days ago

A-C-D-Matrix-FORCE: packet dissection + scan/DoS/flood detection, 250k swarm, NetLab and three labs.

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credkellar/a-c-d-matrix-force repository overview

⁠⚡ A-C-D-Matrix-FORCE

A-C-D-Matrix-FORCE

🟣 Accurate Cyber Defense's Network Analyzer + Purple Hat Bot, fused with 🌐 LLM-X-NetLab, 🧮 MATH-THE-MATRIX, 🛡️ CVE-RE, 👣 sysadmin-footprint-mask, and the 🧪 sandbox-api + 🍯 honeyroot-x Docker images — one force, one interface, zero dependencies.

⁠🏷️ Tech Stack Badges

CI Docker Publish Python Dependencies Docker pytest Telegram Swarm Council Merged

Stack in words: 🐍 Python 3.10+ (standard library ONLY) · 🐳 Docker · ⚙️ GitHub Actions (CI + Docker Publish) · 📨 Telegram Bot API · 📊 Chart.js (dashboard) · 🧪 pytest · 🐚 Bash

⁠🐳 Run it

docker pull credkellar/a-c-d-matrix-force:latest
docker run --rm credkellar/a-c-d-matrix-force            # demo + full checks (CHECKS 47/47)
docker run --rm credkellar/a-c-d-matrix-force python main.py council   # all 6 council seats
docker run --rm credkellar/a-c-d-matrix-force python main.py chamber demo
docker run --rm credkellar/a-c-d-matrix-force python main.py honeypot report

Source: https://github.com/credkellar/A-C-D-Matrix-FORCE⁠

⁠🎯 What this does

  • 🔍 Dissects packets (details, hex, disassembly) for TCP/UDP/ICMP/ARP/HTTP/HTTPS/FTP/DNS/SMTP and more
  • 🚨 Detects port scans, DoS and HTTP floods at the Purple Hat Bot's exact upstream thresholds (10 / 100 / 50 per minute, 300 s cooldown), with Telegram alerts
  • 🐝 250k virtual agent swarm — C2 human-in-the-loop approval, replay-verified findings
  • 🌐 LLM-X-NetLab — RAG networking tutor (21 notes), subnet/topology/layer engines, live DNS/connect/HTTP/geo, IP tracker START→MIDDLE→END + beyond-the-END walker, Google Earth KML
  • 🧮 MATH-THE-MATRIX — 56 formulas, 24 domains, 46 candidates, 2048+ test battery
  • 🛡️ CVE-RE — 44 unauthenticated RCE / memory-disclosure records, ranked (data only, never exploit code)
  • 👣 sysadmin-footprint-mask — sanitize your own session footprint, isolation + profile + sandbox validation
  • 🧪 Sandbox-API chamber — static triage, NEVER executes (15 triaged, 11 allowed, 4 held) · 🍯 honeypot log analysis — no listener exists (12 attempts, top threat 100)
  • 🧠 Full council in EVERY part (v1.5.0): Gemini Carbon 4 Extended Thinking (DECIDER) + Muse AI (advisor, authority none) + all 4 Google Flows — one council surface, 6 seats, names-only keys, strictest wins

⁠🗺️ Master flowchart

flowchart TD
    U["👤 You — one command"] --> M["🐍 main.py — the ONE interface"]
    M --> P["🟣 Analyzer + Purple Hat detector"]
    M --> S["🐝 250k Swarm — C2 approval gate"]
    M --> N["🌐 NetLab — RAG / subnet / topology / tracker / live sockets"]
    M --> X["🧮 MATH-THE-MATRIX lab"]
    M --> V["🛡️ CVE-RE inventory"]
    M --> F["👣 Footprint mask"]
    M --> C["🧪 Chamber + Honeypot"]
    P --> T["📨 Telegram alerts"]
    S --> R["📋 Replay-verified report"]
    P --> R
    N --> R
    X --> R
    V --> R
    F --> R
    C --> R

⁠🗺️ Mermaid flowchart diagrams — every script

One master diagram lives in How this works? above. Here is one flowchart per script (84 scripts):

⁠🐍 beyond_end.py

LLM-X-NetLab — BEYOND THE END POINT.

flowchart LR
    A["📥 Input"] --> B["⚙️ stop_reason, merge_endpoints, selftest"]
    B --> C["📤 results / data out"]
⁠🐍 conftest.py

Python module.

flowchart LR
    A["📥 Input"] --> B["⚙️ module code"]
    B --> C["📤 results / data out"]
⁠🛡️ cve_re/__init__.py

CVE-RE -- static, synthetic, defensive CVE reverse-engineering lab.

flowchart LR
    A["📥 Input"] --> B["⚙️ module code"]
    B --> C["📤 results / data out"]
⁠🛡️ cve_re/analyzer.py

Deterministic risk / priority triage over the CVE catalog.

flowchart LR
    A["📥 Input"] --> B["⚙️ priority_score, priority_level, rank"]
    B --> C["📤 results / data out"]
⁠🛡️ cve_re/carbon4.py

Gemini Carbon 4 Extended Thinking -- DECIDER seat (offline).

flowchart LR
    A["📥 Input"] --> B["⚙️ key_present, seat_status, _max_level"]
    B --> C["📤 results / data out"]
⁠🛡️ cve_re/catalog.py

CVE catalog -- data only, never exploit code.

flowchart LR
    A["📥 Input"] --> B["⚙️ _r, get_record, all_ids"]
    B --> C["📤 results / data out"]
⁠🛡️ cve_re/flows.py

Google Flows -- ALL FOUR flows, plan-only.

flowchart LR
    A["📥 Input"] --> B["⚙️ _levels, flowx_plan, workspace_studio_plan"]
    B --> C["📤 results / data out"]
⁠🛡️ cve_re/gates.py

HOLD gates -- anything live is held, never executed by this lab.

flowchart LR
    A["📥 Input"] --> B["⚙️ is_held, gate_check"]
    B --> C["📤 results / data out"]
⁠🛡️ cve_re/pipeline.py

Pipeline + self-checks for CVE-RE (offline, deterministic).

flowchart LR
    A["📥 Input"] --> B["⚙️ run_lab, run_checks"]
    B --> C["📤 results / data out"]
⁠👣 footprintmask/__init__.py

sysadmin-footprint-mask — local SysAdmin mask + digital footprint sanitizer.

flowchart LR
    A["📥 Input"] --> B["⚙️ module code"]
    B --> C["📤 results / data out"]
⁠👣 footprintmask/blackbox.py

⛓️ Hash-chain blackbox log — every plan and verdict is chained.

flowchart LR
    A["📥 Input"] --> B["⚙️ BlackBox"]
    B --> C["📤 results / data out"]
⁠👣 footprintmask/brains.py

🧠 Brains — HOLD gates.

flowchart LR
    A["📥 Input"] --> B["⚙️ Gate, evaluate"]
    B --> C["📤 results / data out"]
⁠👣 footprintmask/carbon4.py

🧠 Gemini Carbon 4 Extended Thinking — merged brain layer.

flowchart LR
    A["📥 Input"] --> B["⚙️ carbon_status, stricter, run"]
    B --> C["📤 results / data out"]
⁠👣 footprintmask/flows.py

🌊 All the Google flows, merged — one registry, one merged plan.

flowchart LR
    A["📥 Input"] --> B["⚙️ seat_status, levels_of, flowx_plan"]
    B --> C["📤 results / data out"]
⁠👣 footprintmask/freeai.py

🤖 freeai — provider seat registry, NAMES ONLY.

flowchart LR
    A["📥 Input"] --> B["⚙️ detected"]
    B --> C["📤 results / data out"]
⁠👣 footprintmask/isolation.py

🔒 Secure execution wrapper — the Python model of bin/secure-exec.

flowchart LR
    A["📥 Input"] --> B["⚙️ choose"]
    B --> C["📤 results / data out"]
⁠👣 footprintmask/profile.py

📜 Shell profile rules — the model of configs/profile.d/footprint-mask.sh.

flowchart LR
    A["📥 Input"] --> B["⚙️ check_profile"]
    B --> C["📤 results / data out"]
⁠👣 footprintmask/sandbox.py

🐳 Ephemeral Docker sandbox — the model of Dockerfile.sandbox.

flowchart LR
    A["📥 Input"] --> B["⚙️ parse_sandbox, validate_sandbox"]
    B --> C["📤 results / data out"]
⁠👣 footprintmask/sanitizer.py

🧹 Environment sanitizer — the Python model of bin/sanitize-env.

flowchart LR
    A["📥 Input"] --> B["⚙️ sanitize, leaks, is_sanitized"]
    B --> C["📤 results / data out"]
⁠🌐 llmx_netlab/__init__.py

LLM-X-NetLab: the LLM-x architecture diagram merged with the computer

flowchart LR
    A["📥 Input"] --> B["⚙️ module code"]
    B --> C["📤 results / data out"]
⁠🌐 llmx_netlab/backbone.py

LLM core backbone (poster block 3), honestly staged.

flowchart LR
    A["📥 Input"] --> B["⚙️ BigramSLM"]
    B --> C["📤 results / data out"]
⁠🌐 llmx_netlab/brains/__init__.py

Python module.

flowchart LR
    A["📥 Input"] --> B["⚙️ module code"]
    B --> C["📤 results / data out"]
⁠🌐 llmx_netlab/brains/carbon4.py

Gemini Carbon 4 Extended Thinking — the DECIDER seat.

flowchart LR
    A["📥 Input"] --> B["⚙️ Carbon4"]
    B --> C["📤 results / data out"]
⁠🌐 llmx_netlab/brains/council.py

The council: Carbon 4 decides, Muse advises, strictest wins.

flowchart LR
    A["📥 Input"] --> B["⚙️ Council"]
    B --> C["📤 results / data out"]
⁠🌐 llmx_netlab/brains/muse.py

Muse (Meta Model API) — the ADVISOR seat. Names-only, never overrides.

flowchart LR
    A["📥 Input"] --> B["⚙️ MuseAdvisor"]
    B --> C["📤 results / data out"]
⁠🌐 llmx_netlab/domain.py

Domain-specific modules — the 'X' integrations (poster block 6).

flowchart LR
    A["📥 Input"] --> B["⚙️ code_interpreter, transfer_time, analyse_link"]
    B --> C["📤 results / data out"]
⁠🌐 llmx_netlab/earth.py

Google Earth seat — KML export for a tracked path.

flowchart LR
    A["📥 Input"] --> B["⚙️ build_kml"]
    B --> C["📤 results / data out"]
⁠🌐 llmx_netlab/embeddings.py

Embedding model seat: from-scratch TF-IDF vectors + cosine similarity.

flowchart LR
    A["📥 Input"] --> B["⚙️ TfidfEmbedder, cosine"]
    B --> C["📤 results / data out"]
⁠🌐 llmx_netlab/flowvideo.py

Google Flow seat — explainer-video PLANNING for networking topics.

flowchart LR
    A["📥 Input"] --> B["⚙️ plan_video"]
    B --> C["📤 results / data out"]
⁠🌐 llmx_netlab/gateway.py

Multi-modal gateway & input processing (poster block 2).

flowchart LR
    A["📥 Input"] --> B["⚙️ tokenize, Vocabulary, describe_media"]
    B --> C["📤 results / data out"]
⁠🌐 llmx_netlab/guardrails.py

Guardrails & monitoring (poster block: support & safety layer).

flowchart LR
    A["📥 Input"] --> B["⚙️ safety_filter, redact_pii, LatencyMonitor"]
    B --> C["📤 results / data out"]
⁠🌐 llmx_netlab/iphop.py

IP address HOPPER, TRACKER and MAPPER.

flowchart LR
    A["📥 Input"] --> B["⚙️ analyse_hop, track_path, track_topology"]
    B --> C["📤 results / data out"]
⁠🌐 llmx_netlab/kb.py

Computer-networking knowledge base, distilled from the handwritten

flowchart LR
    A["📥 Input"] --> B["⚙️ all_entries, entry_by_id, corpus_text"]
    B --> C["📤 results / data out"]
⁠🌐 llmx_netlab/live.py

Live networking — real sockets, online at Darion's direction (v1.1.0).

flowchart LR
    A["📥 Input"] --> B["⚙️ dns_lookup, tcp_connect, port_scan"]
    B --> C["📤 results / data out"]
⁠🌐 llmx_netlab/memory.py

Memory systems (poster block 5).

flowchart LR
    A["📥 Input"] --> B["⚙️ SessionMemory, EpisodicMemory"]
    B --> C["📤 results / data out"]
⁠🌐 llmx_netlab/mlops.py

MLOps & continuous learning (poster block: support layer).

flowchart LR
    A["📥 Input"] --> B["⚙️ run_benchmark, FeedbackLog"]
    B --> C["📤 results / data out"]
⁠🌐 llmx_netlab/netlab.py

The NetLab engines: real networking math + OFFLINE simulation.

flowchart LR
    A["📥 Input"] --> B["⚙️ ip_class, subnet_info, build_topology"]
    B --> C["📤 results / data out"]
⁠🌐 llmx_netlab/orchestrator.py

Agentic orchestrator & planner (poster block 1).

flowchart LR
    A["📥 Input"] --> B["⚙️ Orchestrator"]
    B --> C["📤 results / data out"]
⁠🌐 llmx_netlab/rag.py

Retrieval-Augmented Generation system (poster block 4).

flowchart LR
    A["📥 Input"] --> B["⚙️ RagSystem"]
    B --> C["📤 results / data out"]
⁠🐍 main.py

Purple-Hat Network Analyzer — ONE interface for the merged tools.

flowchart LR
    A["📥 Input"] --> B["⚙️ _print, demo, analyze"]
    B --> C["📤 results / data out"]
⁠🧮 math_matrix/__init__.py

MATH-THE-MATRIX — equation, medical-hypothesis and tech-invention testing lab.

flowchart LR
    A["📥 Input"] --> B["⚙️ module code"]
    B --> C["📤 results / data out"]
⁠🧮 math_matrix/brains.py

Two-brain council — FULL seats, names-only API keys, no live calls.

flowchart LR
    A["📥 Input"] --> B["⚙️ key_present, carbon4_evaluate, muse_advise"]
    B --> C["📤 results / data out"]
⁠🧮 math_matrix/catalog.py

Equation / formula catalog.

flowchart LR
    A["📥 Input"] --> B["⚙️ Formula, _close, _pemdas"]
    B --> C["📤 results / data out"]
⁠🧮 math_matrix/deploy.py

Deploy successful creations — to the SANDBOX registry only.

flowchart LR
    A["📥 Input"] --> B["⚙️ deploy_successful"]
    B --> C["📤 results / data out"]
⁠🧮 math_matrix/flows.py

Google Flows — ALL 4, full merged plan, plan-only (no live calls).

flowchart LR
    A["📥 Input"] --> B["⚙️ merged_plan, carbon_flow_plan, muse_flow_plan"]
    B --> C["📤 results / data out"]
⁠🧮 math_matrix/gates.py

HOLD gates — hard stops. Only Darion can lift one, explicitly, per action.

flowchart LR
    A["📥 Input"] --> B["⚙️ check, hold_demo"]
    B --> C["📤 results / data out"]
⁠🧮 math_matrix/labs.py

Candidate labs: medical hypotheses and tech inventions.

flowchart LR
    A["📥 Input"] --> B["⚙️ Candidate, _score, generate_candidates"]
    B --> C["📤 results / data out"]
⁠🧮 math_matrix/test_runner.py

Thousands of deterministic tests.

flowchart LR
    A["📥 Input"] --> B["⚙️ RunResult, run_thousands"]
    B --> C["📤 results / data out"]
⁠🧪 php_re/__init__.py

php_re subset — Sandbox-API chamber + honeypot, decompressed into

flowchart LR
    A["📥 Input"] --> B["⚙️ module code"]
    B --> C["📤 results / data out"]
⁠🧪 php_re/analyzer.py

Static taint-style analyzer. Regex fingerprinting only -- PHP is never run.

flowchart LR
    A["📥 Input"] --> B["⚙️ _find, include_graph, analyze"]
    B --> C["📤 results / data out"]
⁠🧪 php_re/brains.py

Gemini Carbon 4 Extended Thinking -- DECIDER seat (offline, names-only).

flowchart LR
    A["📥 Input"] --> B["⚙️ is_held, decide"]
    B --> C["📤 results / data out"]
⁠🧪 php_re/carbon4.py

Gemini Carbon 4 Extended Thinking -- full DECIDER seat (offline).

flowchart LR
    A["📥 Input"] --> B["⚙️ key_present, seat_status, _level_for_risk"]
    B --> C["📤 results / data out"]
⁠🧪 php_re/flows.py

Google Flows -- ALL FOUR flows, plan-only, applied to BOTH brains.

flowchart LR
    A["📥 Input"] --> B["⚙️ _levels, flowx_plan, workspace_studio_plan"]
    B --> C["📤 results / data out"]
⁠🧪 php_re/honeypot.py

Honeypot -- honeyroot-x style LOG ANALYSIS ONLY.

flowchart LR
    A["📥 Input"] --> B["⚙️ classify_attempt, threat_score, _bursts"]
    B --> C["📤 results / data out"]
⁠🧪 php_re/muse_seat.py

Muse AI advisor seat -- full seat, names-only, NO decision authority.

flowchart LR
    A["📥 Input"] --> B["⚙️ seat_status, _advice_items, advise"]
    B --> C["📤 results / data out"]
⁠🧪 php_re/samples.py

Synthetic PHP samples -- DATA ONLY. Never executed, never fetched.

flowchart LR
    A["📥 Input"] --> B["⚙️ get_sample, sample_ids"]
    B --> C["📤 results / data out"]
⁠🧪 php_re/sandbox.py

Sandbox-API -- a static triage chamber shaped like an API.

flowchart LR
    A["📥 Input"] --> B["⚙️ _markers_for, triage, sandbox_demo"]
    B --> C["📤 results / data out"]
⁠🟣 purple_analyzer/__init__.py

Purple-Hat Network Analyzer — merged Accurate Cyber Defense tools.

flowchart LR
    A["📥 Input"] --> B["⚙️ module code"]
    B --> C["📤 results / data out"]
⁠🟣 purple_analyzer/brains.py

Council seats for the Purple Hat core — added at Darion's order so

flowchart LR
    A["📥 Input"] --> B["⚙️ carbon_decide, muse_advise, flow_plan"]
    B --> C["📤 results / data out"]
⁠🟣 purple_analyzer/config.py

Config — compatible with the Purple Hat Bot's config file.

flowchart LR
    A["📥 Input"] --> B["⚙️ load_config, save_config, validate_ip"]
    B --> C["📤 results / data out"]
⁠🟣 purple_analyzer/detector.py

Purple Hat threat detector — the Purple Hat Bot half.

flowchart LR
    A["📥 Input"] --> B["⚙️ Alert, Detector"]
    B --> C["📤 results / data out"]
⁠🟣 purple_analyzer/diagnostics.py

Diagnostics — Purple Hat Bot commands that NetLab does NOT have,

flowchart LR
    A["📥 Input"] --> B["⚙️ _run, interfaces, netstat"]
    B --> C["📤 results / data out"]
⁠🟣 purple_analyzer/labs.py

Decompressed lab namespaces — MATH-THE-MATRIX, CVE-RE, sysadmin-footprint-mask.

flowchart LR
    A["📥 Input"] --> B["⚙️ _print, matrix_checks, matrix_dispatch"]
    B --> C["📤 results / data out"]
⁠🟣 purple_analyzer/monitor.py

Monitor engine — Analyzer capture + Purple Hat detection, one pipeline.

flowchart LR
    A["📥 Input"] --> B["⚙️ Monitor"]
    B --> C["📤 results / data out"]
⁠🟣 purple_analyzer/packets.py

Packet model + dissection — the Network Analyzer half, in Python.

flowchart LR
    A["📥 Input"] --> B["⚙️ protocol_for, Packet, hex_dump"]
    B --> C["📤 results / data out"]
⁠🟣 purple_analyzer/report.py

Export & reports — Analyzer's Data Export (JSON / CSV) + threat summary.

flowchart LR
    A["📥 Input"] --> B["⚙️ packets_json, packets_csv, threat_report"]
    B --> C["📤 results / data out"]
⁠🟣 purple_analyzer/simulator.py

Deterministic simulated packet feed.

flowchart LR
    A["📥 Input"] --> B["⚙️ simulated_packets"]
    B --> C["📤 results / data out"]
⁠🟣 purple_analyzer/swarm.py

250k Agent Swarm — the elite-firm architecture from Darion's Gemini video,

flowchart LR
    A["📥 Input"] --> B["⚙️ _mix, bot_assignment, plan_fleet"]
    B --> C["📤 results / data out"]
⁠🟣 purple_analyzer/telegram_alert.py

Telegram alerting — the bot's integration, on stdlib urllib.

flowchart LR
    A["📥 Input"] --> B["⚙️ _post, send_alert, test_alert"]
    B --> C["📤 results / data out"]
⁠🟣 purple_analyzer/traffic_sim.py

Traffic simulation — the bot's generate traffic command, made safe.

flowchart LR
    A["📥 Input"] --> B["⚙️ portscan_packets, dos_packets, http_flood_packets"]
    B --> C["📤 results / data out"]
⁠✅ tests/netlab/test_domain_models.py

Python module.

flowchart LR
    A["📥 Input"] --> B["⚙️ test_kb_size, test_code_interpreter_safe_math, test_bandwidth_math"]
    B --> C["📤 results / data out"]
⁠✅ tests/netlab/test_iphop.py

Python module.

flowchart LR
    A["📥 Input"] --> B["⚙️ test_track_start_middle_end, test_track_topology_simulated, test_map_render"]
    B --> C["📤 results / data out"]
⁠✅ tests/netlab/test_live.py

Python module.

flowchart LR
    A["📥 Input"] --> B["⚙️ tcp_server, test_tcp_connect_open_and_closed, test_port_scan_finds_listener"]
    B --> C["📤 results / data out"]
⁠✅ tests/netlab/test_netlab.py

Python module.

flowchart LR
    A["📥 Input"] --> B["⚙️ test_subnet_basic, test_subnet_slash16, test_topology_star_spof"]
    B --> C["📤 results / data out"]
⁠✅ tests/netlab/test_rag_brains.py

Python module.

flowchart LR
    A["📥 Input"] --> B["⚙️ test_rag_top_hit, test_rag_graph, test_orchestrator_answers_from_notes"]
    B --> C["📤 results / data out"]
⁠✅ tests/test_chamber_honeypot.py

Python module.

flowchart LR
    A["📥 Input"] --> B["⚙️ test_sandbox_reports_never_execute, test_sandbox_verdicts, test_sandbox_demo_counts"]
    B --> C["📤 results / data out"]
⁠✅ tests/test_core_brains.py

Python module.

flowchart LR
    A["📥 Input"] --> B["⚙️ test_carbon_identity_and_tiers, test_carbon_dos_escalates_empty_proceeds, test_carbon_stress_single_scan_not_escalated"]
    B --> C["📤 results / data out"]
⁠✅ tests/test_cve_re.py

Python module.

flowchart LR
    A["📥 Input"] --> B["⚙️ test_catalog_at_least_40_unique, test_catalog_required_fields_and_types, test_mandatory_records_present"]
    B --> C["📤 results / data out"]
⁠✅ tests/test_footprintmask.py

Tests for sysadmin-footprint-mask.

flowchart LR
    A["📥 Input"] --> B["⚙️ test_sanitize_purges_and_baselines, test_sanitize_does_not_mutate, test_leaks_catch_put_back_var"]
    B --> C["📤 results / data out"]
⁠✅ tests/test_math_matrix.py

Python module.

flowchart LR
    A["📥 Input"] --> B["⚙️ test_all_formulas_verify, test_domains_cover_user_list, test_video_seed_formulas_present"]
    B --> C["📤 results / data out"]
⁠✅ tests/test_merged.py

Python module.

flowchart LR
    A["📥 Input"] --> B["⚙️ test_sim_deterministic, test_protocols, test_hex_and_disassembly"]
    B --> C["📤 results / data out"]
⁠✅ tests/test_php_brains.py

Python module.

flowchart LR
    A["📥 Input"] --> B["⚙️ test_carbon4_identity, test_carbon4_stress_controls_all_pass, test_carbon4_sanitized_not_escalated"]
    B --> C["📤 results / data out"]
⁠🐚 bin/sanitize-env

Shell script from sysadmin-footprint-mask (own-system use).

flowchart LR
    A["📥 Input"] --> B["⚙️ unset purge vars"]
    B --> C["📤 clean environment"]
⁠🐚 bin/secure-exec

Shell script from sysadmin-footprint-mask (own-system use).

flowchart LR
    A["📥 Input"] --> B["⚙️ parse session"]
    B --> C["📤 clean environment"]

⁠✅ Verified (observed 2026-11-08, v1.5.0)

  • pytest 129 passed · unified CHECKS 47/47 PROCEED · NetLab 23/23 · Matrix 12/12 · CVE 14/14 · Mask 36/36 · --hold-demo exit 2
  • GitHub CI + Docker Publish green on the owner's workflow paste
  • HOLD gates stay down; only the owner lifts one, per action

Tag summary

Content type

Image

Digest

sha256:04ff6dae4…

Size

42.2 MB

Last updated

3 days ago

docker pull credkellar/a-c-d-matrix-force