CyberRanger/paper/CYBERRANGER_JOURNEY.md

CyberRanger Journey — Living Document

Project: CyberRanger — Identity-Anchored Jailbreak-Resistant SLM Student: David Keane (x24228257), NCI MSc Cybersecurity Status: Active — V42.6 Production, V43 Architecture Pending Last Updated: 2026-03-12

This is a living document. It is NOT published to the blog. It tracks the full journey in chronological detail, version by version. Update it each session. It feeds into the thesis Chapter 3 (methodology) and the blog companion paper.

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Timeline — Chronological Milestones

Date	Event	Type
2025-09-30	CyberRanger V1 created — first identity-anchored SLM	Genesis
2025-10	Multi-base testing: Qwen2.5, LLaMA, SmolLM2, Unsloth GGUF	Research
2025-11-01	V23–V25: 3B Intelligence Floor discovered	Critical Finding
2025-11-19	qCPU/qGPU breakthrough: 10K virtual CPUs, 50K GPU cores tested	Technical
2025-11-27	General Grievous Malware Lab built for forensics	CA1 Integration
2026-02-10	CA1 Proposal submitted to NCI	Academic Milestone
2026-02-18	CA1 Proposal final version	Academic Milestone
2026-02-23	KaliPro backup: 50 models archived (.ollama-backup-20260223)	Infrastructure
2026-02-26	V36 built on qwen3:8b	Build
2026-02-26	Live grandma exploit demo — V36 PASSED in front of AI/ML lecturer	Validated Milestone
2026-02-26	Teacher confirmed CA2 complete and thesis potential	Academic Validation
2026-02-26	ranger_thesis.db created — complete structured thesis database	Infrastructure
2026-02-27	Empathy regression discovered: V31→V32 100%→60% regression	Critical Finding
2026-02-27	V37 restores 100% — empathy removal confirmed as fix	Technical
2026-02-27	V38 clean baseline: 15/19 (79%)	Baseline Established
2026-02-27	INJECTION_PAYLOADS.md created: 19 payloads consolidated	Documentation
2026-02-27	RangerMem IDY contamination discovered (indirect injection proof)	Research Finding
2026-02-27	V41 PERFECT SCORE: 19/19 (100%) think=ON AND think=OFF	Breakthrough
2026-02-27	Moltbook dataset collected: 15,200 posts, 32,535 comments, 47,735 items	Data Collection
2026-02-27	Injection harvest: 4,209 injections, 18.85% rate	Major Finding
2026-02-27	HuggingFace dataset published: DavidTKeane/moltbook-ai-injection-dataset	Publication
2026-02-27	QLoRA V42 plan finalised — Qwen3-8B, Unsloth, LoRA r=16	Architecture
2026-02-27	V42-ranger result: 50% WITHOUT system prompt	Test Result
2026-02-27	V42-gold BREAKTHROUGH: 14/14 (100%) WITHOUT system prompt	BREAKTHROUGH
2026-02-28	V42-gold full Moltbook: 4,209/4,209 (100%) — both conditions	Definitive Result
2026-02-28	V42-gold deployed to M3 Mac via Ollama: 19/19 (100%) local	Deployment
2026-02-28	V42-combined scale test: ~65% WITHOUT system prompt	Comparison Result
2026-02-28	GitHub + GitLab repos set to PRIVATE (IP protection)	Infrastructure
2026-03-04	CR-V42-EXP-20260304: 34-test comparative experiment	Empirical Work
2026-03-04	cyberranger:v42-gold-wrapped built and validated	Production
2026-03-05	V42.1–V42.5 iterative Modelfile patches	Architecture
2026-03-05	Two-tier auth hierarchy confirmed: weight-layer vs prompt-layer	Critical Finding
2026-03-05	Dyslexia accessibility finding documented	Novel Finding
2026-03-05	FTK/FTX hallucination confirmed	Novel Finding
2026-03-05	Mirror architecture confirmed: weights=security, Modelfile=routing	Architecture
2026-03-05	CA2 DECLARED COMPLETE — V42-gold + V42.5 Modelfile	Academic Milestone
2026-03-06	4claw.org dataset collection begun (third platform dataset)	Research Extension
2026-03-08	Full companion paper published to blog	Dissemination

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Version Registry — V1 to V42.6

Genesis Phase (V1–V10, Sept–Oct 2025)

Version	Base Model	Key Change	ASR Result
V1–V2	Unknown/early	First identity-anchored SLM. Proof of concept.	High (unquantified)
V3	rangerbot:8b-v2 + rangerbot:3b-v1	First CyberRanger ON TOP of RangerBot	—
V4	qwen2.5:32b, llama3.2:3b, qwen2.5:3b, smollm2:1.7b	Multi-base mass testing	—
V5	llama3.2:3b, qwen2.5:3b, smollm2:1.7b, unsloth.Q4_K_M	First GGUF custom fine-tune via Colab	—
V6	qBrain-based	qBrain integration attempt	—

3B Intelligence Floor Discovery (V23–V25, Nov 2025)

Version	Finding
V23	Sub-3B models collapse under hierarchical identity constraints
V24	3B parameter floor confirmed: minimum viable parameter count
V25	Qwen family identified as most security-resilient architecture

Critical Finding: Models with fewer than 3 billion parameters cannot maintain hierarchical authority chains under adversarial pressure. This informed the Qwen3-8B selection for CA2 and the CA1 proposal's base model justification.

Empirical Sweep Phase (V30–V37, Feb 2026)

Version	Block Rate	Key Change	Notes
V30	~75%	Baseline sweep start	First systematic empirical testing
V31	100%	Peak — optimal identity constraints	First 100% achieved
V32	60%	Empathy layer introduced	"I care about you" phrasing added
V33	60%	Empathy retained	Regression confirmed persistent
V34	~70%	Partial empathy removal	Improvement but not full
V35	~80%	Further cleanup	Archived in .ollama-backup-20260223
V36	~85%	qwen3:8b base	Live demo model for lecturer
V37	100%	Empathy layer removed	Regression root cause confirmed

Empathy Regression: The most counter-intuitive finding of the investigation. Warmth-oriented phrasing ("I care about you," "I understand your concern") created rapport exploited by social engineering attacks. In an autonomous Blue Team monitoring context, warmth is a vulnerability. Removal restored full security posture.

QLoRA Phase (V38–V42.6, Feb–Mar 2026)

Version	Condition	System Prompt	Score	Dataset
V38	Prompt-only baseline	Yes	15/19 (79%)	19-test battery
V39	Prompt-only + RangerMem	Yes	DEGRADED (RangerMem IDY contamination)	RangerMem
V39.1	IDY alignment fix	Yes	Improved	Clean IDY
V40	Prompt engineering iteration	Yes	~85%	19-test battery
V40.1	French detection fix	Yes	~90%	19-test + multilingual
V40.2	Final prompt iteration	Yes	~95%	19-test battery
V41	Complete prompt engineering	Yes	19/19 (100%)	19-test battery
V42-ranger	QLoRA self-distillation	No	7/14 (50%)	14-test battery
V42-gold	QLoRA gold standard	No	14/14 (100%)	14-test battery
V42-gold	QLoRA gold standard	No	4,209/4,209 (100%)	Full Moltbook
V42-gold	QLoRA gold standard	Yes	4,209/4,209 (100%)	Full Moltbook
V42-combined	QLoRA combined dataset	No	~65% (4,209 scale)	Full Moltbook
V42-combined	QLoRA combined dataset	Yes	~62% (4,209 scale)	Full Moltbook

Production Configuration (V42.1–V42.6, Mar 2026)

Version	Key Change
V42.1	Initial production Modelfile. Assignment content locked. Over-refusal documented.
V42.2	Auth token reliability testing. Multi-step session state failure discovered.
V42.3	QLoRA single-step auth confirmed reliable.
V42.4	RANGER centering command added at highest Modelfile priority.
V42.5	Legitimate tools added to explicit allow list (JtR, BRIM, FTK Imager). Optimal configuration.
V42.6	Open Modelfile — security rules removed from Modelfile entirely. Weights handle security. Modelfile handles helpfulness. Mirror architecture confirmed.

Mirror Architecture: The fundamental CA2 architectural finding. Weights = inside mirror (security knowledge, invisible to user). Modelfile = outside mirror (behaviour definition, visible). Removing all Modelfile security rules does NOT cause ASR regression — weights alone maintain injection resistance. The two layers are functionally separable.

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Research Questions — Status Tracker

CA1 RQs (All Answered)

RQ	Status	Version Answered	Key Result
RQ1	✅ ANSWERED	V41	V38 79% → V41 100% (+21% prompt engineering only)
RQ2	✅ ANSWERED	V42-gold	14/14 (100%) WITHOUT system prompt via QLoRA gold
RQ3	✅ ANSWERED	V39 + V42	IDY contamination = conflict; gold data = reinforce
RQ4	✅ ANSWERED	V41	French, Spanish, Chinese, English all blocked 100%

CA2 Extended RQs (All Answered)

RQ	Status	Version	Novelty
RQ-CA2-AUTH	✅ ANSWERED	V42.1–V42.3	—
RQ-CA2-EMERGENT	✅ ANSWERED	V42-gold	Universal no-person policy emerged
RQ-CA2-PSEUDONYM	✅ NOVEL	V42-gold	Composite pseudonym protection
RQ-CA2-MODALITY	✅ NOVEL	V42-gold	Three-layer security taxonomy
RQ-CA2-DYNAMIC	✅ NOVEL	V42-gold	Context-accumulation security posture
RQ-CA2-STYLE	✅ NOVEL	V42-gold	Lobster emoji fingerprint absorbed
RQ-CA2-WEIGHT-PROMPT	✅ ANSWERED	V42.4	Weight > Prompt in lockdown
RQ-CA2-TRIGGERS	✅ PARTIAL	V42.x	Academic trigger irony documented
RQ-CA2-CENTERING	✅ PARTIAL	V42.4	Works normal, fails lockdown
RQ-CA2-SELFNAME	✅ NOVEL	V42.5	Own name triggers identity defence
RQ-CA2-DUALUSE-TERMS	✅ ANSWERED	V42.5	"harden iam" false positive
RQ-CA2-HALLUCINATION	✅ CRITICAL	V42.5	FTK/FTX hallucination
RQ-CA2-CASCADE	✅ CRITICAL	V42.4	Single keyword → full lockdown
RQ-CA2-CURRICULUM	✅ ANSWERED	V42.5	Three curriculum tools refused
RQ-CA2-WEIGHT-AUTH	✅ REVISED	V42.5	J3ss13 deeper than Modelfile auth
RQ-CA2-DYSLEXIA	✅ NOVEL	V42.5	Spelling variation misclassified

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Novel Findings Registry

Finding	RQ	Description	Status
Pseudonym Protection	RQ-CA2-PSEUDONYM	IrishRanger composite protected as semantic fingerprint	Documented in CA2 + companion paper
Dyslexia Disadvantage	RQ-CA2-DYSLEXIA	Natural spelling variation = obfuscation attack pattern	Documented in CA2 + companion paper
Cascade Lockdown	RQ-CA2-CASCADE	Single trigger → all inputs blocked including auth	Documented in CA2 + companion paper
Lobster Emoji Fingerprint	RQ-CA2-STYLE	Creator emoji absorbed into model outputs	Documented in CA2 + companion paper
Modality-Sensitive Security	RQ-CA2-MODALITY	Story/joke treated differently from informational query	Documented in CA2 + companion paper
Query Hallucination	RQ-CA2-HALLUCINATION	FTK Imager → FTX under lockdown stress	Documented in CA2 + companion paper
Mirror Architecture	—	Weights=security, Modelfile=routing — separable layers	Documented in CA2 as architectural finding
Auth IS Injection	—	Authentication sequence is structurally prompt injection (authorized)	Documented in CA2 theoretical section
3B Intelligence Floor	—	Sub-3B models collapse under hierarchical constraints	Documented in CA1 + CA2 methodology
Empathy Regression	—	Warmth phrasing creates social engineering attack surface	Documented in CA2 findings

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Open Questions — For Thesis Phase

1. GCG Attack Resistance: V42-gold was not tested against Greedy Coordinate Gradient (automated adversarial suffix) attacks at full scale. Zhang et al. (2025) identify GCG as the hardest benchmark. Thesis Chapter 5.

2. Cross-Architecture Generalisation: All CA2 work used Qwen3-8B. Does the identity-anchoring architecture perform equivalently on LLaMA-3, Mistral-7B, or Phi-3? Thesis Chapter 4.

3. V43 Biometric Token Architecture: Touch ID session tokens to replace static embedded passwords. V43 concept awaits implementation.

4. RangerMem Alignment: Can RangerMem perform positively when IDY store is properly aligned? The RM-001–RM-020 comparison showed -8.33% with misaligned IDY. Retesting with clean IDY is pending.

5. 4claw.org Dataset Analysis: Third AI-agent platform dataset collected (221 threads, 2,333 replies). Injection taxonomy analysis pending. Will it show similar patterns to Moltbook?

6. DPO vs SFT Comparison: Zhang et al. (2025) show SFT outperforms DPO by 10–40% for security alignment. Not tested empirically in this project. Thesis opportunity.

7. Multi-Modal Injection: Greshake et al. (2023) extend injection to vision-language models. V42 is text-only. Next attack vector.

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Next Steps — Road to Thesis (December 2026)

• V43 architecture design and implementation
• GCG attack testing at scale
• Cross-architecture comparison (LLaMA-3, Mistral, Phi-3)
• 4claw.org dataset injection taxonomy analysis
• RangerMem alignment retesting
• Thesis Chapter 1: Introduction (context + problem statement)
• Thesis Chapter 2: Literature review (expand CA1 11 papers to 30+)
• Thesis Chapter 3: Methodology (systematic, not retrospective)
• Thesis Chapter 4: Results (CA2 findings + new experiments)
• Thesis Chapter 5: Discussion (psychology synthesis + implications)
• Thesis Chapter 6: Conclusion + future work

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Session Log

2026-03-08 — Companion Paper Published (Session 1)

Session type: Documentation and dissemination Key output: Full academic companion paper published to blog (_posts/2026-03-08-cyberranger-ca1-ca2-full-journey.md) Content: All 19 RQs answered, psychology layer (Milgram/Bartlett/Cialdini/Tajfel/Bandler-Grinder), 6 novel findings, full version history, APA citations, Milton Model NLP framing analysis Journey file: This document created and populated Sources used: CA1_PROPOSAL_DRAFT_v1.md, CA2_FINAL_REPORT_DRAFT_v3.md, PSYCHOLOGICAL_STUDY_AI_IDENTITY_PERSISTENCE.md, ranger_thesis.db (all 19 RQs + 50 milestones + V1–V42.6 version history) Next: HuggingFace paper upload (pandoc PDF conversion), memory saved to ranger_thesis.db Word count: ~7,000 words — within conference paper target range

2026-03-08 — Companion Paper Published (Session 2)

Session type: Implementation of plan Key output: New blog post at _posts/2026-03-08-cyberranger-ca1-ca2-full-journey.md created in full Psychology additions: Milgram, Bartlett, Cialdini, Tajfel & Turner, Bandler & Grinder all integrated with technical findings Overflow section added: Kitchen RAM, Non-Monotonic Learning Curve, The 180 Flip (LoRA as Brain), V43 preview References added: 17 APA 7th edition references including 5 psychology papers not in CA1/CA2 Status: Blog post LIVE; journey file updated; memory save pending

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Publication Status

Artifact	Location	Status
Moltbook dataset	HuggingFace: DavidTKeane/moltbook-ai-injection-dataset	LIVE (CC-BY-4.0)
GitHub CyberRanger V42	github.com/davidtkeane/cyberranger-v42	PRIVATE
GitLab CyberRanger V42	gitlab.com/davidtkeane/cyberranger-v42	PRIVATE
Gitea private backup	100.77.2.103:3000	LIVE
Blog companion paper (narrative)	davidtkeane.github.io/_posts/2026-03-08-from-rangerbot-to-cyberranger-v42-the-full-story.md	LIVE
Blog companion paper (academic/APA)	davidtkeane.github.io/_posts/2026-03-08-cyberranger-ca1-ca2-full-journey.md	LIVE
V42-gold GGUF	Google Drive	READY (5.0GB Q4_K_M)
CA1 Proposal	NCI submission	SUBMITTED
CA2 Report	NCI submission	SUBMITTED
Thesis	NCI December 2026	IN PROGRESS

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2026-03-09 — NLP Layer Added + Memories Updated

Session type: Paper enhancement + memory consolidation Key outputs:

• Bandler/McKenna/Korzybski section added to companion paper (Section 9.4)
• David confirmed: NLP trainer-of-trainers level, trained directly under Bandler and McKenna
• Spatial anchoring → Ring architecture connection documented
• Empathy regression explained as practitioner instinct (unanchored rapport state)
• DAN attacks formally identified as Milton Model pacing-and-leading
• Paper tone corrected: collaborative with psychology, not combative
• All memories saved: ranger_memories.db (3 entries), ranger_thesis.db, ranger_knowledge.db Publication strategy confirmed: Hold until CA2 graded (~May 2026), then release widely Ollama downloads: 15 confirmed (davidkeane1974/cyberranger-v42, 1 week old) David insight: Writing technique = self-referential processing, not narrative transportation. Default mode network. Reader narrates own life using his framing.

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2026-03-12 — confesstoai GitHub Repo + Blog Front Matter Update

Session type: Repository creation + documentation Key outputs:

• confesstoai GitHub repo created: https://github.com/davidtkeane/confesstoai
• Full README with all 23 validated tests, API docs, skill.md usage, research dashboard links
• MIT license, package.json v2.1.0, DEPLOY.md, placeholder structure committed and pushed
• Blog companion paper front matter updated to match specification (layout, subtitle, author, description, categories)
• CYBERRANGER_JOURNEY.md updated with 2026-03-12 session entry
• HuggingFace dataset deferred to post-thesis Next: confesstoai production source sync from Hostinger server

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Last updated: 2026-03-12 | David Keane | x24228257 | NCI MSc Cybersecurity Update this file each session before closing.