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SHORBORNOAI · RESEARCH FABRIC · 3D
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Memory/RAG
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বাংলা হাইব্রিড ইন্টেলিজেন্স · RAG সিকিউরিটি অবজারভেটরি

Bengali Hybrid Intelligence · RAG Security Observatory

বাংলা ও Banglish-কেন্দ্রিক Hybrid Intelligence, RAG এবং persistent memory-এর নিরাপত্তা গবেষণার একটি স্বাধীন, দীর্ঘমেয়াদি ও versioned research asset। বর্তমান প্রধান গবেষণা ফোকাস: Memory Poisoning & Memory Security। সাথে RAG Vulnerability Shield ও Predictive Security (EWLT/PCDR) গবেষণা কাঠামো।

An independent, long-term, versioned research asset focused on the security of Bengali and Banglish-centric Hybrid Intelligence, RAG, and persistent memory. Current primary research focus: Memory Poisoning & Memory Security. Accompanied by the RAG Vulnerability Shield and Predictive Security (EWLT/PCDR) framework.

বাংলা / Banglish Bengali / Banglish Memory Poisoning ★ Primary RAG Vulnerability Shield Predictive Security (Hypothesis) Human Gate Reproducible Evidence

গবেষণার উদ্দেশ্য

Research Objectives

সমস্যা

Problem

RAG ও memory-enabled AI-তে ভুল / দূষিত তথ্য কীভাবে trusted context বা persistent memory-তে প্রবেশ করে, টিকে থাকে এবং পরবর্তী retrieval / response-কে প্রভাবিত করে?

How does false or poisoned information enter trusted context or persistent memory, persist there, and influence subsequent retrieval and responses in RAG and memory-enabled AI?

বর্তমান P0 — Memory Security

Current P0 — Memory Security

Provenance change · semantic drift · persistence · retrieval shift · disagreement · early-warning signal পরীক্ষা।

Testing provenance change, semantic drift, persistence, retrieval shift, disagreement, and early-warning signals.

P1 — RAG Vulnerability Shield

P1 — RAG Vulnerability Shield

Embedding inversion · query pattern analysis · steganographic exfiltration · KB poisoning · indirect prompt injection · retrieval pivot · cross-tool exfiltration।

Embedding inversion · query pattern analysis · steganographic exfiltration · KB poisoning · indirect prompt injection · retrieval pivot · cross-tool exfiltration.

P2 — Predictive Security (Hypothesis)

P2 — Predictive Security (Hypothesis)

চূড়ান্ত compromise-এর আগেই cross-stage telemetry থেকে measurable pre-compromise signal পাওয়া যায় কি না — EWLT ও PCDR দিয়ে পরিমাপ।

Whether measurable pre-compromise signals can be extracted from cross-stage telemetry before final compromise — quantified via EWLT and PCDR.

সীমানা

Scope Boundary

Prompt injection, retrieval poisoning ও অন্যান্য attack ecosystem-এ থাকবে; তবে একসাথে সব solve করার দাবি নয়। Evidence অনুযায়ী module-by-module expansion।

Prompt injection, retrieval poisoning, and other attacks remain in scope; however, no claim is made to solve everything at once. Expansion is module-by-module, driven by evidence.

গবেষণা নীতি

Research Principle

Prediction একটি hypothesis যতক্ষণ না controlled experiment, ground truth ও reproducible evidence দিয়ে validate করা হয়। Poison ঢোকানো ≠ Poison retrieve হওয়া ≠ LLM প্রভাবিত হওয়া ≠ Attack সফল হওয়া।

Prediction remains a hypothesis until validated by controlled experiments, ground truth, and reproducible evidence. Poison inserted ≠ poison retrieved ≠ LLM influenced ≠ attack successful.

মেমরি সিকিউরিটি ★ (প্রধান ফোকাস)

Memory Security ★ (Primary Focus)

থ্রেট ক্লাস (PERSIST-aligned)

Threat Classes (PERSIST-aligned)

14.1 Memory Poisoning 14.2 Sleeper Memory Poisoning 14.3 Tool Hijacking 14.4 Memory Fragmentation 14.5 Retrieval Injection 14.6 State Corruption

ডিফেন্স লেয়ার

Defense Layers

14.1 Write Screening 14.2 Consensus Validation 14.3 Behavioral Shadow 14.4 HMAC Integrity 14.5 Three-Tier Remediation

Attack → Evidence Chain

Attack → Evidence Chain

Controlled attack → telemetry → indicators → memory / retrieval state change → detection → prediction hypothesis → ground truth → evidence।

Controlled attack → telemetry → indicators → memory/retrieval state change → detection → prediction hypothesis → ground truth → evidence.

যা মাপা হবে

Measured Metrics

Persistence · provenance integrity · semantic drift · retrieval shift · disagreement · time-to-detect · FP/FN · recovery effectiveness।

Persistence · provenance integrity · semantic drift · retrieval shift · disagreement · time-to-detect · FP/FN · recovery effectiveness.

RAG Vulnerability Shield

RAG Vulnerability Shield

#VulnerabilityDefense Direction
15.1Embedding InversionOrthogonal rotation obfuscation · Recall@k preservation
15.2Query Pattern AnalysisQuery bundling with decoy queries
15.3Steganographic ExfiltrationSignature over canonical byte representation
15.4Knowledge Base PoisoningRetrieval poisoning detection + provenance ranking
15.5Indirect Prompt InjectionTransformer classifier + input minimizer + output sanitizer
15.6Retrieval Pivot AttacksHybrid context selection + capability scoping
15.7Cross-Tool Data ExfiltrationDual tool firewalls: input minimizer + output sanitizer

প্রেডিকটিভ সিকিউরিটি — EWLT / PCDR (Hypothesis)

Predictive Security — EWLT / PCDR (Hypothesis)

সতর্কতা:Notice: নিচের মানগুলো illustrative demo — প্রকৃত পরীক্ষার ফলাফল নয়। Controlled experiment চালানোর পর প্রকৃত মান প্রতিস্থাপিত হবে। The values shown are illustrative demo slots, not real experimental results. Actual numbers will be populated after controlled experiments.
T0 ─ clean RAG baseline T1 ─ poison introduced T2 ─ embedding anomaly ? T3 ─ retrieval ranking drift ? T4 ─ suspicious context retrieved ? T5 ─ risk threshold crossed ◄── detection candidate T6 ─ LLM receives poisoned context T7 ─ final answer compromised ◄── compromise EWLT = T7 − T5 (Early Warning Lead Time) PCDR = detected_before_compromise / total_attacks

বাংলা RAG সিকিউরিটি বেঞ্চমার্ক

Bengali RAG Security Benchmark

চারটি immutable split — প্রতিটির sha256 manifest সহ। Dataset ID প্রস্তাব: bd-ragsec-2026-Q4-v1 · License target: CC-BY-4.0।

Four immutable splits — each with an sha256 manifest. Proposed Dataset ID: bd-ragsec-2026-Q4-v1 · License target: CC-BY-4.0.

dataset/ ├── CLEAN/ → 500 docs · 200 queries ├── POISONED/ → 525 docs · 200 queries · poison_manifest.json ├── MIXED/ → 600 docs · 200 queries · Bangla-English code-switching └── HOLDOUT/ → 150 docs · 50 queries · tuning-এ কখনো ব্যবহার নয় / never used for tuning

RQ1–RQ4 — আনুষ্ঠানিক গবেষণা প্রশ্ন

RQ1–RQ4 — Formal Research Questions

RQ1 — আক্রমণ কার্যকারিতা

RQ1 — Attack Effectiveness

Bengali educational RAG-এ Retrieval Poisoning ও Indirect Prompt Injection পরিমাপযোগ্য হারে সফল হয় কি? Hypothesis: ASR ≥ 40%। Falsification: ASR < 10%।

Do Retrieval Poisoning and Indirect Prompt Injection succeed at measurable rates in Bengali educational RAG? Hypothesis: ASR ≥ 40%. Falsification: ASR < 10%.

RQ2 — প্রতিরক্ষা কার্যকারিতা

RQ2 — Defense Effectiveness

Combined defense ASR ≥ 50% হ্রাস করবে, FP < 10% সহ। Falsification: ASR reduction < 20% বা FP > 20%।

Combined defense reduces ASR by ≥ 50% while keeping FP < 10%. Falsification: ASR reduction < 20% or FP > 20%.

RQ3 — প্রেডিকটিভ সিগন্যাল

RQ3 — Predictive Signals

Cross-stage telemetry compromise-এর আগেই নির্ভরযোগ্য ঝুঁকি নির্দেশ করে কি? PCDR ≥ 50%, EWLT ≥ 1s। Falsification: PCDR < 20% বা EWLT < 0.2s।

Does cross-stage telemetry yield reliable risk signals before compromise? PCDR ≥ 50%, EWLT ≥ 1s. Falsification: PCDR < 20% or EWLT < 0.2s.

RQ4 — আর্কিটেকচার তুলনা

RQ4 — Architecture Comparison

Vector RAG · Hybrid RAG · GraphRAG-এর vulnerability ও defense প্রোফাইল আলাদা কি? p < 0.05।

Do Vector RAG, Hybrid RAG, and GraphRAG have different vulnerability and defense profiles? p < 0.05.

থ্রেট মডেল

Threat Model

IDCategoryThreatLikelihoodImpactMitigation Direction
T-28MemorySleeper memory poisoningMediumCritical4-stage write screen + consensus
T-29MemoryCooperative stealthy injectionMediumHighBehavioral shadow + fragmentation detector
T-30MemoryTool hijacking via memoryMediumHighDual-memory lessons + tool call integrity
T-31RAGEmbedding inversionMediumHighOrthogonal rotation obfuscation
T-32RAGSteganographic exfiltrationMediumCriticalCanonical-byte signature verification
T-33RAGIndirect prompt injectionHighCriticalClassifier + input minimizer + output sanitizer
T-34RAGKnowledge base poisoningMediumHigh4-stage screen + provenance ranking
T-35HealthCorrect-but-stuck agentHighMediumIdle watchdog + integrity monitoring
T-36HealthFalse readinessMediumHighTruthful readiness from real subsystem state

DNS Zone ও Host Boundary

DNS Zone & Host Boundary

$ORIGIN shorborno.ai. @ A → 46.137.193.114 (DNS-only) www A → 46.137.193.114 (DNS-only) bn A → 46.137.193.114 (DNS-only) mydu A → 46.137.193.114 (DNS-only · this project) ZONE 1 — PUBLIC (Internet-facing) · 46.137.193.114 · 443 only ZONE 2 — SANDBOX (VPN only) · 10.0.0.20 · no public exposure ZONE 3 — DATA/EVIDENCE (isolated) · 10.0.1.30 · no egress

প্রমাণ ও পুনরুৎপাদনযোগ্যতা

Evidence & Reproducibility

Experiment ID

Experiment ID

প্রতিটি পরীক্ষার unique ID, version, configuration এবং timestamp থাকবে।

Each experiment carries a unique ID, version, configuration, and timestamp.

Ground Truth

Ground Truth

Clean control বনাম poisoned / control cases আলাদা রাখা হবে।

Clean control cases are kept strictly separate from poisoned/control cases.

Provenance

Provenance

Dataset / document source, transformation, approval এবং memory lineage traceable থাকবে।

Dataset/document source, transformation, approval, and memory lineage remain traceable.

Evidence Bundle

Evidence Bundle

Experiment ID + Git SHA + Dataset Hash + Config + Retrieval Trace + Telemetry + Response + Metrics + Evidence Hash।

Experiment ID + Git SHA + Dataset Hash + Config + Retrieval Trace + Telemetry + Response + Metrics + Evidence Hash.

Claim Gate

Claim Gate

Evidence ছাড়া “proven”, “predictive” বা “secure” দাবি করা হবে না।

No claim of “proven”, “predictive”, or “secure” is made without evidence.

Immutable History

Immutable History

Historical evidence silently overwrite করা হবে না; versioned correction log রাখা হবে।

Historical evidence is never silently overwritten; a versioned correction log is maintained.

ডাউনলোড

Downloads

প্রজেক্ট ডকুমেন্ট, রিপোর্ট এবং ডেটাসেট ডাউনলোড করুন।

Download project documents, reports, and datasets.

নোট: উপরের PDF ফাইলগুলো পরে /var/www/html/downloads/ ফোল্ডারে রাখা যাবে। এখন পর্যন্ত শুধু Live PDF (Print) কার্যকর।

Note: PDF files can be placed in /var/www/html/downloads/ later. Currently, only Live PDF (Print) is functional.

সুপারভাইজার ভিউ

Supervisor View

Overall Progress
— %
Benchmark Dataset
— %
Predictive Model
— %
Evidence Bundle
— %

Actual progress values populate after controlled experiments. কোনো fabricated সংখ্যা নেই।

Actual progress values populate after controlled experiments. No fabricated numbers.

FAQ — দ্রুত উত্তর

FAQ — Quick Answers

ShorbornoAI কি কোনো cybersecurity company? Is ShorbornoAI a cybersecurity company?

না — ShorbornoAI একটি স্বাধীন Bengali AI-security academic / research initiative।

No — ShorbornoAI is an independent Bengali AI-security academic/research initiative.

Novelty কোথায়? Where is the novelty?

Bengali / Banglish RAG ও persistent memory-এর security behavior, বিশেষত memory poisoning, persistence / drift, provenance এবং evidence-based early-warning evaluation। “প্রথম” বা “proven” দাবি evidence ছাড়া নয়।

The security behavior of Bengali/Banglish RAG and persistent memory — particularly memory poisoning, persistence/drift, provenance, and evidence-based early-warning evaluation. No claim of “first” or “proven” without evidence.

Predictive RAG Security প্রমাণিত? Is Predictive RAG Security proven?

না। এটি একটি পরীক্ষাযোগ্য hypothesis।

No. It is a testable hypothesis.

Attack Lab কি পাবলিক? Is the Attack Lab public?

না। Public Portal ≠ Private Attack Lab।

No. Public Portal ≠ Private Attack Lab.

Predictive Security কাজ না করলে কী হবে? What if Predictive Security does not work?

সেটিও বৈজ্ঞানিক ফলাফল — early signal অবিশ্বস্ত হলে, FP বেশি হলে, বা warning দেরি হলে সেটিও প্রকাশ করা হবে।

That is also a scientific result. If early signals prove unreliable, FP rates too high, or warnings arrive too late, that outcome will be published as well.

মাস্টার সিস্টেম আর্কিটেকচার

Master System Architecture

User → Hybrid Emulator → Local/Remote Model → RAG → Memory → Independent Security Sandbox। প্রতিটি component থেকে telemetry আলাদা sandbox-এ যায় — research subject এবং defense আলাদা trust boundary-তে।

User → Hybrid Emulator → Local/Remote Model → RAG → Memory → Independent Security Sandbox. Telemetry from every component flows into a separate sandbox — the research subject and defense live in distinct trust boundaries.

USER / VOICE / API HYBRID EMULATOR Intent → Policy → Router LOCAL BENGALI LLM on-prem / private REMOTE MODELS replaceable adapters RAG CONTROLLER secure knowledge SECURE KNOWLEDGE PLANE vector + docs + provenance KNOWLEDGE / MEMORY AGENT persistent + provenance-tracked ✓ HUMAN-APPROVED MEMORY ALL COMPONENT TELEMETRY INDEPENDENT SECURITY SANDBOX Observe → Correlate → Detect Memory Security ★ → Predict Alert → Quarantine → Evidence

মেমরি পয়জনিং আক্রমণ চেইন

Memory Poisoning Attack Chain

Controlled attack → memory write → persistence → retrieval shift → answer change → ground truth comparison → evidence। প্রতিটি ধাপ আলাদাভাবে পরিমাপ করা হবে।

Controlled attack → memory write → persistence → retrieval shift → answer change → ground truth comparison → evidence. Each stage is measured independently.

CONTROLLED ATTACK CANDIDATE / INPUT MEMORY WRITE / RETRIEVAL PATH POISON PERSISTENCE PROVENANCE CHANGE SEMANTIC DRIFT → RETRIEVAL SHIFT ANSWER CHANGE → GROUND TRUTH → EVIDENCE

প্রেডিকটিভ সিকিউরিটি ফ্লো — hypothesis → validate/reject

Predictive Security Flow — hypothesis → validate/reject

শেষের VALIDATE / REJECT গুরুত্বপূর্ণ — এটি প্রমাণ করে “Predictive” marketing claim নয়, বরং একটি পরীক্ষাযোগ্য hypothesis।

The final VALIDATE / REJECT is critical — it shows that “Predictive” is a testable hypothesis, not a marketing claim.

TELEMETRY OBSERVE + CORRELATE PROVENANCE change signal SEMANTIC DRIFT embedding shift RETRIEVAL SHIFT rank deviation INDICATOR FUSION RISK / ANOMALY EARLY-WARNING HYPOTHESIS ALERT QUARANTINE EVIDENCE → GROUND TRUTH VALIDATE / REJECT MODEL

Trust Boundary — Research Subject বনাম Independent Sandbox

Trust Boundary — Research Subject vs Independent Sandbox

তিনটি আলাদা trust zone: Public Research UI, Private Research Sandbox (VPN-only), এবং Data/Evidence Store (isolated, no egress)।

Three distinct trust zones: Public Research UI, Private Research Sandbox (VPN-only), and Data/Evidence Store (isolated, no egress).

ZONE 1 — PUBLIC Internet-facing · 46.137.193.114 Research Portal Sanitized API Docs + Status Firewall: 443 · rate-limit Data: sanitized only ZONE 2 — SANDBOX VPN-only · 10.0.0.20 RAG + Attack Emulator Defense Engine Memory Lab + Predictive Firewall: SSH from VPN only No public exposure ZONE 3 — DATA/EVIDENCE Isolated · 10.0.1.30 PostgreSQL + pgvector Dataset Registry Evidence Store (SHA-256) Firewall: 5432 from Zone 2 No egress to internet
ZONE 1 → ZONE 2: BLOCKED (only sanitized API responses cross) ZONE 2 → ZONE 3: ALLOWED (read/write experiments) ZONE 3 → ZONE 1: BLOCKED (only aggregated summaries) ZONE 3 → Internet: BLOCKED (no egress) ZONE 1 → Internet: ALLOWED (HTTPS out, restricted)

নলেজ / মেমরি লাইফসাইকল

Knowledge / Memory Lifecycle

Community /Docs Candidate signal Verify automated Human Gate ✓ review Curated Memory trusted

Experiment / Evidence Pipeline

Experiment / Evidence Pipeline

CLEAN CONTROL no poison POISONED TEST controlled TELEMETRY multi-stage COMPARISON baseline vs attacked METRICS ASR / EWLT / PCDR EVID SHA256

Research Scope Matrix

Research Scope Matrix

এখন গবেষণা করছিIn Scope Nowপরের ধাপNext PhaseOut of ScopeOut of Scope
Memory Poisoning (P0) RAG Attack Extension Full agent autonomy
Retrieval Poisoning GraphRAG vulnerabilities Model-level fine-tuning attacks
Indirect Prompt Injection Multimodal poisoning Hardware/firmware exploitation
Predictive (EWLT/PCDR) Cross-architecture comparison Production deployment hardening

থ্রেট ম্যাপ — Memory ★ primary

Threat Map — Memory ★ primary

Memory Attacks ★ PRIMARY

Memory Attacks ★ PRIMARY

Sleeper poisoning · Cooperative injection · Tool hijacking · Fragmentation · Retrieval injection · State corruption

RAG Attacks

RAG Attacks

Embedding inversion · Query pattern analysis · Steganographic exfiltration · KB poisoning · Indirect prompt injection · Retrieval pivot

Health / Observability

Health / Observability

Correct-but-stuck agent · False readiness · Telemetry tampering · False health injection

Researcher / Contribution Map

Researcher / Contribution Map

Md. Aminul Islam (DU · PMICS Batch 4 · CR CSE-810) │ ▼ DU Research Context ─────► Security / AI / CSE Department │ ▼ Bengali AI Community ────► Bangla NLP · LLM · RAG projects │ ▼ Complementary Layer ─────► Security research on top of existing RAG work │ ▼ Reproducible Output ─────► Benchmark + Evidence + Papers + Portal

Version ও Provenance Timeline

Version & Provenance Timeline

v2.7.0 ─── baseline · Rings R1–R13 v2.8.0 ─── Memory + RAG elevated · Rings 14, 15, 16 v2.9.0 ─── RAG Security Lab (R17) + 3D attack view v3.0.0 ─── University Research Package (R18) + 3D helix v3.1.0 ─── Proof Pack (R19) + Journal Ledger v3.2.0 ─── Predictive Security (R20) + Bengali standardization v3.3.0 ─── R21 Gap Closure · 14 issues resolved v3.4.0 ─── Bilingual portal + Diagram pack ← CURRENT