glm-5.1
11620e8398
- OQ-04 resolved: thresholds are both model-specific (shipped with codebook) and user-overridable. Inspired by platonic representation hypothesis — calibrated models converge on similar behavioral patterns. - OQ-07 removed: Rust port is an alknet project concern, not relevant to the Python package architecture. Removed from overview.md Phase 3. - OQ-03 enriched: rolling window token screening for granular detection in documents (PDF→markdown use case, academic paper injection detection). Upgraded from low to medium priority. - OQ-01 updated: likely path is PyTorch first, ONNX export by default. - OQ-05 updated: needs deep dive into guardrail landscape. - Updated threshold description in configuration.md with platonic representation context.
70 lines
3.9 KiB
Markdown
70 lines
3.9 KiB
Markdown
---
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status: draft
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last_updated: 2026-06-13
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---
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# alknet-firewall — Architecture
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## Current State
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**Phase 0→1 (Exploration → Architecture)** — The project has a working PoC
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demonstrating that behavioral signals from small language models can detect
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adversarial inputs. The core detection logic (~1,745 lines) works reasonably
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well but lacks tests, has excessive codebook size, and needs extraction from
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the research codebase into a properly structured Python package.
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This project extracts and productionizes the behavioral signal detection
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approach from the metaspline research project. A ~125M parameter model
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(SmolLM2-135M) processes untrusted inputs and produces hidden state
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activations. SVD-based dimensionality reduction on these activations reveals
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behavioral patterns — normal inputs cluster in expected regions while
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adversarial inputs produce anomalous activation signatures. The system
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raises "behavioral alarms" without needing to know specific attack types.
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## Architecture Documents
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| Document | Status | Description |
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|----------|--------|-------------|
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| [overview.md](overview.md) | Draft | Vision, scope, package structure, dependencies |
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| [firewall.md](firewall.md) | Draft | Core firewall API, input screening, alarm protocol |
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| [codebook.md](codebook.md) | Draft | SVD basis, detection parameters, codebook compilation |
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| [model.md](model.md) | Draft | Model loading, activation extraction, model-agnostic design |
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| [configuration.md](configuration.md) | Draft | Thresholds, model selection, detection tuning |
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| [open-questions.md](open-questions.md) | Active | Unresolved questions tracker with OQ-IDs |
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## ADR Table
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| ADR | Title | Status |
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|-----|-------|--------|
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| [001](decisions/001-python-uv.md) | Python with uv | Accepted |
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| [002](decisions/002-behavioral-signals.md) | Behavioral Signal Detection (Not Text Classification) | Accepted |
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| [003](decisions/003-small-model-detector.md) | Small Model (~125M) as Detector | Accepted |
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| [004](decisions/004-svd-based-detection.md) | SVD-Based Anomaly Detection | Accepted |
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| [005](decisions/005-safetensors-only.md) | Safetensors-Only Model Loading | Accepted |
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| [006](decisions/006-optional-pytorch.md) | PyTorch as Optional Dependency | Accepted |
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| [007](decisions/007-runtime-model-download.md) | Runtime Model Download via HuggingFace Hub | Accepted |
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| [008](decisions/008-three-level-alarm.md) | Three-Level Alarm System | Accepted |
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| [009](decisions/009-last-token-extraction.md) | Last-Token Activation Extraction | Accepted |
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| [010](decisions/010-monotonic-spline-distributions.md) | Monotonic Spline Distributions | Accepted |
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## Open Questions
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See [open-questions.md](open-questions.md) for the full tracker.
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| OQ | Question | Priority | Status |
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|----|----------|----------|--------|
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| OQ-01 | Should ONNX Runtime be a supported inference backend in Phase 1? | medium | open |
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| OQ-02 | What is the minimum viable codebook — can the 1,245-line codebook be compressed? | high | open |
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| OQ-03 | Should the firewall support streaming/chunked input screening? | medium | open |
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| ~~OQ-04~~ | ~~Should detection thresholds be per-model or globally configurable?~~ | ~~medium~~ | **resolved** (both: model-specific defaults, user-overridable) |
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| OQ-05 | How should the firewall integrate with existing guardrail systems? | medium | open |
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| OQ-06 | Should file-based configuration use TOML or YAML? | low | open |
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## Document Lifecycle
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| Status | Meaning | Transitions |
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|--------|---------|-------------|
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| `draft` | Under active development. May change significantly. | → `reviewed` when open questions are resolved |
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| `reviewed` | Architecture is final. Implementation may begin. Changes require review. | → `stable` when implementation is complete |
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| `stable` | Locked. Changes require review and may warrant an ADR. | → `deprecated` when superseded |
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| `deprecated` | Superseded. Kept for reference. | Removed when no longer referenced | |