alknet-firewall

alkdev/alknet-firewall

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Author	SHA1	Message	Date
glm-5.1	11620e8398	docs: resolve OQ-04, remove OQ-07, enrich OQ-03 with rolling windows - 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.	2026-06-13 05:47:44 +00:00
glm-5.1	cf464c2296	feat: initial architecture specification and research Phase 0→1 setup for alknet-firewall — a behavioral signal detection library that screens untrusted LLM inputs using small model activations. Architecture docs (5 specs, 10 ADRs, 7 open questions): - overview: vision, scope, dependencies, package structure - firewall: core API, alarm protocol, score composition, error handling - codebook: SVD basis, spline distributions, calibration, tensor format - model: activation extraction, model-agnostic interface, lazy loading - configuration: thresholds, model selection, detection tuning Research reports: - modern-python-project-setup: uv, pyproject.toml, src layout, ruff, CI - python-ml-packaging: optional PyTorch, HF Hub download, safetensors - llm-input-safety-landscape: threat taxonomy, defenses, academic evidence Agent role adaptations for Python project (replaced Rust conventions).	2026-06-13 05:17:40 +00:00

Author

SHA1

Message

Date

glm-5.1

11620e8398

docs: resolve OQ-04, remove OQ-07, enrich OQ-03 with rolling windows

- 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.

2026-06-13 05:47:44 +00:00

glm-5.1

cf464c2296

feat: initial architecture specification and research

Phase 0→1 setup for alknet-firewall — a behavioral signal detection
library that screens untrusted LLM inputs using small model activations.

Architecture docs (5 specs, 10 ADRs, 7 open questions):
- overview: vision, scope, dependencies, package structure
- firewall: core API, alarm protocol, score composition, error handling
- codebook: SVD basis, spline distributions, calibration, tensor format
- model: activation extraction, model-agnostic interface, lazy loading
- configuration: thresholds, model selection, detection tuning

Research reports:
- modern-python-project-setup: uv, pyproject.toml, src layout, ruff, CI
- python-ml-packaging: optional PyTorch, HF Hub download, safetensors
- llm-input-safety-landscape: threat taxonomy, defenses, academic evidence

Agent role adaptations for Python project (replaced Rust conventions).

2026-06-13 05:17:40 +00:00

2 Commits