# Aphoria Roadmap

---

## Phase 0: StemeDB Foundation ✅

> **Tracked in:** [roadmap.md § 5D. Concept Hierarchy](../../roadmap.md)

Changes to the core database that Aphoria depends on. Shipped as **Phase 5D** of the main StemeDB roadmap.

| Aphoria Phase 0 | StemeDB Phase 5D | Status |
|-----------------|------------------|--------|
| 0.1 ConceptPath Type | 5D.1 ConceptPath Type | ✅ |
| 0.2 ConceptPath in Assertion | (implicit in 5D.1) | ✅ |
| 0.3 Hierarchical Index | 5D.4 Hierarchical Query | ✅ |
| 0.4 Alias Store | 5D.3 Alias Store + 5D.5 Alias Resolution | ✅ |
| 0.5 Source Class Inference | 5D.6 Source Class Inference | ✅ |
| 0.6 Concept API Endpoints | 5D.7 Concept API Endpoints | ✅ |

**Spec:** [docs/specs/concept-hierarchy.md](../../docs/specs/concept-hierarchy.md)

---

## Phase 2: CLI Core ✅

> Phase 2 was built before Phase 1 (authoritative corpus expansion). The CLI pipeline works end-to-end with a bootstrapped corpus of 11 hardcoded assertions covering TLS, JWT, CORS, secrets, and rate limiting.

| Task | Status |
|------|--------|
| 2.1 Project Walker | ✅ `walker/mod.rs`, `walker/path_mapper.rs`, `walker/language.rs` |
| 2.2 Extractors (10) | ✅ `tls_verify`, `jwt_config`, `hardcoded_secrets`, `timeout_config`, `dep_versions`, `cors_config`, `rate_limit`, `weak_crypto`, `command_injection`, `sql_injection` |
| 2.3 Ingestion Bridge | ✅ `bridge.rs` — BLAKE3 hashing, Ed25519 signing, claim→assertion conversion |
| 2.4 Conflict Query | ✅ `episteme.rs` — LocalEpisteme with check_conflicts() |
| 2.5 Report Output | ✅ `report/` — table (comfy-table), JSON, SARIF 2.1.0, markdown |
| 2.6 Acknowledge Command | ✅ `lib.rs` acknowledge() |
| Baseline & Diff | ✅ `lib.rs` set_baseline(), show_diff() |
| Status Command | ✅ `lib.rs` show_status() |

183 tests pass. Clippy and fmt clean.

### Phase 2 Code Quality Fixes ✅

Code review improvements to extractors:

| Issue | Fix | Status |
|-------|-----|--------|
| DES/RC4 concept path misclassification | Split `check_pattern()` into `check_hash_pattern()` and `check_encryption_pattern()`; DES/RC4 now use `crypto/encryption/algorithm` path | ✅ |
| SHA1 edge case undocumented | Added comments and test documenting that SHA1 detection is intentionally broad (triggers for git hashes, etc.) | ✅ |
| JS exec() regex overly broad | Tightened regex to require `child_process.` prefix or non-word/non-dot preceding character; prevents `RegExp.exec()` false positives | ✅ |

---

## Phase 2A: Concept Matching ✅

> **Status:** Complete. Tail-path matching (2A.1), alias-aware queries (2A.2), and auto-alias creation (2A.3) all implemented.

### 2A.1 Leaf-Based Concept Matching (Aphoria-side fix) ✅

Implemented in `episteme.rs` via `ConceptIndex`:
- `make_key(subject, predicate)` extracts tail 2 path segments + predicate
- `build(assertions)` creates in-memory index keyed by tail path
- `lookup(subject, predicate)` finds matching authoritative assertions
- `check_conflicts()` uses `ConceptIndex` instead of `QueryEngine` for cross-scheme matching

Integration tests prove TLS and JWT conflicts are detected correctly.

### 2A.2 Alias Resolution in QueryEngine (StemeDB-side fix) ✅

Wired `AliasStore` into `QueryEngine.execute()`:
- Added `resolve_aliases: bool` field to `Query` (defaults to `false`)
- Added `alias_store: Option<Arc<dyn AliasStore>>` to `QueryEngine`
- Added `.with_alias_store()` builder method
- When `resolve_aliases: true`, expands subject via `AliasStore.resolve_all()` before index lookup
- Added `fetch_by_subjects()` and `fetch_by_subjects_predicate()` for multi-subject deduplication
- Modified `Query.matches()` to skip subject filtering when aliases are resolved
- Skips fast path (MV lookup) when `resolve_aliases: true`
- Gracefully degrades when no alias store is configured

7 unit tests in `engine/tests/alias_resolution.rs`. This is the architecturally correct long-term fix that complements leaf matching.

### 2A.3 Auto-Alias Creation ✅

When Aphoria ingests authoritative assertions and code claims that share leaf names, automatically create aliases:
- `code://rust/myapp/tls/cert_verification` ↔ `rfc://5246/tls/cert_verification`
- `code://rust/myapp/auth/jwt/audience_validation` ↔ `rfc://7519/jwt/audience_validation`

This bridges 2A.1 (leaf matching) with 2A.2 (alias resolution) — leaf matching identifies candidates, aliases persist the relationship.

**Implementation:**
- Added `auto_create_aliases: bool` config option to `AliasConfig` (defaults to `true`)
- Added `AliasOrigin::AutoDetected` variant to `stemedb-core` for tracking auto-created aliases
- Wired `GenericAliasStore` into `LocalEpisteme` for alias persistence
- In `check_conflicts()`, when a code claim matches an authoritative claim by leaf, calls `AliasStore.set_alias()` to persist the relationship with `AliasOrigin::AutoDetected`
- Alias creation is idempotent (skips if alias already exists)
- 4 unit tests verify: alias creation on conflict, no creation when disabled, correct origin, idempotency

---

## Phase 1: Authoritative Corpus Expansion ✅

> Expanded from 11 hardcoded assertions to a pluggable corpus system with RFC, OWASP, and Vendor sources.

### Architecture

```
┌─────────────────────────────────────────────────────────────────┐
│                     aphoria corpus build                         │
│                                                                  │
│  ┌──────────────┐  ┌──────────────┐  ┌───────────────────────┐  │
│  │ RFC Ingester │  │ OWASP        │  │ Vendor Bootstrapper   │  │
│  │ (Tier 0)     │  │ Ingester     │  │ (Tier 2)              │  │
│  │              │  │ (Tier 1)     │  │                       │  │
│  └──────┬───────┘  └──────┬───────┘  └───────────┬───────────┘  │
│         │                 │                      │              │
│         └─────────────────┼──────────────────────┘              │
│                           ▼                                     │
│                  ┌─────────────────┐                            │
│                  │ CorpusRegistry  │                            │
│                  └────────┬────────┘                            │
│                           ▼                                     │
│                  ┌─────────────────┐                            │
│                  │ LocalEpisteme   │                            │
│                  │ ingest_         │                            │
│                  │ authoritative() │                            │
│                  └─────────────────┘                            │
└─────────────────────────────────────────────────────────────────┘
```

### 1.1 CorpusBuilder Trait ✅

| Task | Status |
|------|--------|
| `CorpusBuilder` trait | ✅ `corpus/mod.rs` — name, scheme, default_tier, build, requires_network |
| `CorpusRegistry` | ✅ Manages multiple builders, build_all(), list_builders() |
| `CorpusBuildResult` | ✅ Stats per builder, total assertions, success/fail/skip counts |

### 1.2 RFC Ingester ✅

| Task | Status |
|------|--------|
| `RfcCorpusBuilder` | ✅ `corpus/rfc.rs` |
| HTTP fetching | ✅ Via `ureq`, cached to `~/.cache/aphoria/rfc-cache/` |
| RFC 2119 keyword parsing | ✅ MUST, MUST NOT, SHOULD, SHALL extraction |
| RFC-specific parsers | ✅ JWT (7519), OAuth (6749), Bearer (6750), TLS 1.3 (8446), TLS BCP (7525), TOTP (6238), Basic Auth (7617), HTTP (9110) |
| Concept mapping | ✅ `rfc://{number}/{topic}` at Tier 0 (Regulatory) |

### 1.3 OWASP Ingester ✅

| Task | Status |
|------|--------|
| `OwaspCorpusBuilder` | ✅ `corpus/owasp.rs` |
| HTTP fetching | ✅ From GitHub raw content, cached to `~/.cache/aphoria/owasp-cache/` |
| Markdown parsing | ✅ MUST/SHOULD statements, section context |
| Cheat sheet parsers | ✅ Authentication, JWT, TLS, Secrets, Input Validation, Session, CSRF, Password Storage, HTTP Headers |
| Concept mapping | ✅ `owasp://cheatsheet/{topic}/{claim}` at Tier 1 (Clinical) |

### 1.4 Vendor Docs ✅

| Task | Status |
|------|--------|
| `VendorCorpusBuilder` | ✅ `corpus/vendor.rs` |
| PostgreSQL claims | ✅ pool_size, idle_timeout, ssl_mode |
| Redis claims | ✅ timeout, max_retries, tls |
| reqwest claims | ✅ cert_verification, connect_timeout, request_timeout |
| hyper claims | ✅ keep_alive_timeout, max_concurrent_streams |
| Go net/http claims | ✅ read_timeout, write_timeout, idle_timeout, min_tls_version |
| tokio-postgres claims | ✅ pool_size, ssl_mode |
| SQLx claims | ✅ max_connections, idle_timeout |
| Concept mapping | ✅ `vendor://{product}/{topic}/{claim}` at Tier 2 (Observational) |

### 1.5 Hardcoded Refactor ✅

| Task | Status |
|------|--------|
| `HardcodedCorpusBuilder` | ✅ `corpus/hardcoded.rs` — original 11 assertions |
| `create_authoritative_assertion()` | ✅ Made public in `episteme.rs` for corpus builders |

### 1.6 CLI Integration ✅

| Task | Status |
|------|--------|
| `aphoria corpus build` | ✅ Fetches and ingests from all sources |
| `--only rfc,owasp,vendor` | ✅ Filter to specific sources |
| `--offline` | ✅ Skip network-requiring sources |
| `--clear-cache` | ✅ Clear cache before building |
| `aphoria corpus list` | ✅ List available corpus sources |
| `CorpusConfig` | ✅ cache_dir, include_*, rfc_list options |

### 1.7 Error Handling ✅

| Task | Status |
|------|--------|
| `RfcFetch` error | ✅ Per-RFC fetch failures with context |
| `OwaspFetch` error | ✅ Per-cheat-sheet fetch failures with context |
| `CorpusBuild` error | ✅ General corpus build failures |
| Graceful degradation | ✅ Continue with other sources if one fails |

**Files:** `corpus/mod.rs`, `corpus/hardcoded.rs`, `corpus/rfc.rs`, `corpus/owasp.rs`, `corpus/vendor.rs`

---

## Phase 3: Skill Integration ✅

> Complete. Aphoria is now usable in Claude Code agent workflows.

### 3.1 Claude Code Skill ✅

| Task | Status |
|------|--------|
| `skill/SKILL.md` | ✅ Comprehensive skill definition with all commands |
| `/aphoria scan` | ✅ Scan project, show conflicts grouped by verdict |
| `/aphoria scan --fix` | ✅ Interactive fix workflow |
| `/aphoria ack` | ✅ Acknowledge conflicts as intentional |
| `/aphoria status` | ✅ Show status and baseline |
| `/aphoria diff` | ✅ Show changes since baseline |
| `/aphoria init` | ✅ Initialize Aphoria |
| `/aphoria baseline` | ✅ Set baseline |
| `skill/install.sh` | ✅ Install script for `~/.claude/skills/aphoria/` |

**Files:** `skill/SKILL.md`, `skill/install.sh`, `skill/hooks.json`

### 3.2 Agent Pre-Flight Hook ✅

| Task | Status |
|------|--------|
| `--exit-code` flag | ✅ Returns 2 for BLOCK, 1 for FLAG only, 0 for clean |
| `--strict` flag | ✅ Lower thresholds (FLAG at 0.3, BLOCK at 0.5) |
| Hook template | ✅ `skill/hooks.json` with PreCommit and PrePush examples |

**Usage:**
```json
{
  "hooks": {
    "PreCommit": [{"command": "aphoria scan --format sarif --exit-code"}],
    "PrePush": [{"command": "aphoria scan --strict --exit-code"}]
  }
}
```

### 3.3 Alias Suggestion Workflow ✅

Auto-alias creation is now automatic (Phase 2A.3). When Aphoria scans:
1. Tail-path matching finds authoritative assertions
2. Aliases are auto-created with `AliasOrigin::AutoDetected`
3. Future queries use the alias automatically

The skill documents the suggestion flow for manual alias management:
- **y (Accept)**: Creates alias
- **n (Reject)**: Records intentional difference
- **defer**: Flags for later review

---

## Phase 4: Full-Cycle Pre-Commit (Scan + Sync) ✅

> **Vision:** The pre-commit hook is a **bidirectional knowledge sync**, not just a read-only linter. Every commit extracts claims, checks authority, detects drift from prior observations, and records new observations back.

**Spec:** [uat/2026-02-04-full-cycle-precommit-vision.md](uat/2026-02-04-full-cycle-precommit-vision.md)

```
┌─────────────────────────────────────────────────────────────┐
│                     PRE-COMMIT FLOW                          │
├─────────────────────────────────────────────────────────────┤
│  1. EXTRACT     → What claims does this code make?           │
│  2. CHECK       → Against authority + own prior claims       │
│  3. CLASSIFY    → Authority conflict | Self conflict | Novel │
│  4. UPDATE      → Record observations to local Episteme      │
│  5. GATE        → Exit code (BLOCK=2, FLAG=1, PASS=0)        │
└─────────────────────────────────────────────────────────────┘
```

### 4.1 Git Pre-Commit Hook ✅

All flags needed for pre-commit integration are implemented:

```bash
#!/bin/sh
# .git/hooks/pre-commit
aphoria scan --staged --sync --exit-code
```

Or using pre-commit framework:

```yaml
repos:
  - repo: local
    hooks:
      - id: aphoria
        name: Aphoria Truth Sync
        entry: aphoria scan --staged --sync --exit-code
        language: system
        pass_filenames: false
```

### 4.2 Baseline Mode ✅

Already implemented in Phase 2.

### 4A: Observational Claims ✅

Record code claims as Tier 4 (Community) assertions when no authority conflict exists:

| Task | Status |
|------|--------|
| `sync: bool` in ScanArgs | ✅ `types/command.rs` |
| `observations_recorded: usize` in ScanResult | ✅ `types/result.rs` |
| `--sync` CLI flag | ✅ `cli.rs` — requires `--persist` |
| `claim_to_observation()` | ✅ `bridge.rs` — creates Tier 4 (Community, 0.3 weight) assertions |
| `ingest_observations()` in LocalEpisteme | ✅ `episteme/local.rs` — writes to WAL + predicate index |
| Scan flow integration | ✅ `scan.rs` — splits claims by conflict status, writes novel claims as observations |
| Handler validation | ✅ `handlers.rs` — `--sync requires --persist` error |
| Report output | ✅ `report/table.rs`, `report/json.rs` — shows observation count |
| Tests | ✅ 5 new tests for observation write-back |

```
Code: connection_pool.max_size = 25
Authority: (nothing)
Action: Record as Tier 4 observation (project memory)
```

**Usage:**
```bash
# Scan with observation write-back
aphoria scan --persist --sync

# Output:
# Recorded 45 observations (project memory)
```

### 4B: Self-Conflict Detection ✅

Detect drift from the project's own prior observations:

| Task | Status |
|------|--------|
| Query prior claims before conflict check | ✅ `fetch_observations_for_concept()` |
| Compare current vs stored observations | ✅ `check_drift()` compares values |
| Report changes as SELF-CONFLICT | ✅ DriftResult with prior/current values |
| New verdict: `Drift` (distinct from Block/Flag) | ✅ `Verdict::Drift` |
| Drift reporting in all formats | ✅ table, json, markdown, sarif |
| Exit code includes drift | ✅ `--exit-code` returns 1 for drift |

```
Prior: db/pool_size = 25 (recorded 2026-01-15)
Now:   db/pool_size = 100
Result: DRIFT — "You changed pool_size from 25 to 100. Intentional?"
```

**Files:** `types/result.rs`, `types/verdict.rs`, `episteme/local.rs`, `scan.rs`, `report/*.rs`

### 4C: Diff-Only Scanning ✅

Fast scanning for pre-commit hooks:

| Task | Status |
|------|--------|
| `FileSource` enum (All, Staged) | ✅ `types/command.rs` |
| `--staged` flag (git diff --cached) | ✅ `cli.rs`, `handlers.rs` |
| `walker/git.rs` git utilities | ✅ `find_repo_root()`, `get_staged_files()` |
| `walk_staged_files()` | ✅ `walker/mod.rs` — filters to scan root, applies same filters |
| Scan dispatch by file_source | ✅ `scan.rs` |
| Error handling (NotGitRepo, GitCommand) | ✅ `error.rs` |
| Tests | ✅ 9 tests in `tests/staged_scanning.rs` |
| Target: < 500ms for staged-only | ✅ |

**Files:** `types/command.rs`, `walker/git.rs`, `walker/mod.rs`, `scan.rs`, `cli.rs`, `handlers.rs`, `error.rs`

**Usage:**
```bash
# Pre-commit hook (fast, staged files only)
aphoria scan --staged --exit-code

# Full cycle with observation sync
aphoria scan --staged --persist --sync --exit-code
```

### 4D: Enhanced Ack ✅

Acknowledgments with rationale and policy updates:

| Task | Status |
|------|--------|
| `--reason "text"` flag | ✅ `cli.rs` — required on `ack`, `bless`, `update` commands |
| Store rationale in assertion metadata | ✅ `policy_ops.rs` — stored in value/description fields |
| `aphoria update` for intentional drift | ✅ `policy_ops.rs` — creates `policy_update` assertion |
| Policy update assertions | ✅ `types/mod.rs` — `predicates::POLICY_UPDATE` |

**Files:** `cli.rs`, `handlers.rs`, `policy_ops.rs`, `types/command.rs`, `types/mod.rs`

```bash
$ aphoria ack db/pool_size --reason "Scaling for Black Friday"
$ aphoria update db/pool_size 100 --reason "New baseline after load test"
```

### 4E: Hosted Mode ✅

Organizations run their own StemeDB server and all team members automatically sync observations:

| Task | Status |
|------|--------|
| `HostedConfig` in config.rs | ✅ `url`, `project_id`, `team_id`, `sync_mode`, `offline_fallback`, `api_key_env` |
| `SyncMode` enum | ✅ `remote-only` (default), `local-and-remote` |
| `OfflineFallback` enum | ✅ `skip` (default), `fail`, `queue` |
| `HostedClient` HTTP client | ✅ `hosted.rs` — retry logic, auth headers, observation push |
| `POST /v1/aphoria/observations` endpoint | ✅ Server receives observations with project/team metadata |
| Scan integration | ✅ Auto-enables sync when `[hosted]` configured |
| `Hosted(String)` error variant | ✅ For connection/auth failures |
| Graceful offline fallback | ✅ Based on `offline_fallback` config |
| Tests | ✅ Config parsing, client creation, assertion conversion |

```toml
# aphoria.toml
[hosted]
url = "https://episteme.acme.corp"    # Enables hosted mode
project_id = "billing-service"         # Optional, defaults to [project.name]
team_id = "platform-team"              # Optional, for multi-team servers
sync_mode = "remote-only"              # "remote-only" | "local-and-remote"
offline_fallback = "skip"              # "skip" | "fail" | "queue"
api_key_env = "APHORIA_API_KEY"        # Env var for auth token
```

**Architecture:**
```
┌──────────────┐  ┌──────────────┐  ┌──────────────┐
│ Developer A  │  │ Developer B  │  │ Developer C  │
│ aphoria scan │  │ aphoria scan │  │ aphoria scan │
└──────┬───────┘  └──────┬───────┘  └──────┬───────┘
       │                 │                 │
       └─────────────────┼─────────────────┘
                         ▼
              ┌─────────────────────┐
              │ Team StemeDB Server │
              │ POST /v1/aphoria/   │
              │      observations   │
              └─────────────────────┘
                         │
                         ▼
              Aggregated team patterns
```

**Files:** `config.rs`, `hosted.rs`, `scan.rs`, `error.rs`, `lib.rs`, `crates/stemedb-api/src/handlers/aphoria.rs`, `crates/stemedb-api/src/dto/aphoria.rs`

---

## Phase 4.5: Ephemeral Scan Mode ✅

> Performance optimization: 40x faster scans by skipping Episteme storage when persistence isn't needed.

### Problem

Every `aphoria scan` was slow because it initialized the full Episteme stack:
- WAL recovery (O(n) on every startup)
- Dual backend initialization (fjall + redb)
- Store and index initialization

But conflict detection is actually 100% in-memory — it never reads from the KV store. The authoritative corpus is built fresh each time, and code claims are extracted fresh each scan.

### Solution

Added `ScanMode` enum with two modes:

| Mode | Use Case | Storage | Performance |
|------|----------|---------|-------------|
| **Ephemeral** (default) | CI, pre-commit, quick checks | None | ~0.25 seconds |
| **Persistent** | Baseline/diff tracking, alias creation | WAL + store | ~1-2 seconds |

### Implementation ✅

| Task | Status |
|------|--------|
| `ScanMode` enum | ✅ `types.rs` — Ephemeral (default), Persistent |
| `EphemeralDetector` struct | ✅ `episteme/mod.rs` — in-memory corpus + ConceptIndex |
| `check_conflicts_pure()` | ✅ Extracted as standalone function for reuse |
| Mode-based dispatch in `run_scan()` | ✅ Uses `EphemeralDetector` for Ephemeral, `LocalEpisteme` for Persistent |
| `--persist` CLI flag | ✅ `main.rs` — opt-in to persistent mode |
| Tests for both modes | ✅ `test_ephemeral_scan_no_storage_created`, `test_persistent_scan_creates_storage`, `test_scan_modes_produce_same_conflicts` |

### Usage

```bash
# Fast ephemeral scan (default) — no storage created
aphoria scan .

# Persistent scan — enables baseline, diff, auto-alias features
aphoria scan . --persist
```

### Performance

| Mode | Time | Storage |
|------|------|---------|
| Ephemeral | ~0.25s | None |
| Persistent | ~1-2s | WAL + store directories |

**Files:** `types.rs`, `episteme/mod.rs`, `lib.rs`, `main.rs`, `tests.rs`

---

## Phase 5: Research Agent Loop ✅

> Research agent fills gaps in authoritative coverage by researching official documentation.

### 5.1 Gap Detection ✅

| Task | Status |
|------|--------|
| `Gap` struct | ✅ `research/gap_detector.rs` — concept_path, topic, predicate, source info |
| `detect_gaps()` | ✅ Compares claims against ConceptIndex, identifies missing coverage |
| Topic normalization | ✅ Extracts last 2 path segments for cross-scheme matching |
| Deduplication | ✅ Deduplicates gaps by topic+predicate key |

### 5.2 Gap Storage ✅

| Task | Status |
|------|--------|
| `GapRecord` | ✅ `research/gap_store.rs` — tracking metadata, project count, research status |
| `GapStore` | ✅ JSON-backed persistent storage with atomic saves |
| Project tracking | ✅ Records which projects reported each gap |
| Research eligibility | ✅ `is_eligible_for_research()` with threshold and cooldown |
| Gap pruning | ✅ `prune_old_gaps()` removes stale entries |

### 5.3 Quality Validation ✅

| Task | Status |
|------|--------|
| `QualityValidator` | ✅ `research/quality.rs` — validates researched claims |
| Source attribution | ✅ Checks for authoritative domains (rfc-editor, owasp, vendor docs) |
| Normative language | ✅ Verifies MUST/SHOULD/SHALL keywords present |
| Vague content detection | ✅ Rejects "it depends", "typically", etc. |
| Consistency scoring | ✅ Detects conflicting claims on same subject |
| `QualityReport` | ✅ Detailed per-claim validation results |
| `filter_passed()` | ✅ Returns only claims meeting quality threshold |

### 5.4 Research Execution ✅

| Task | Status |
|------|--------|
| `Researcher` | ✅ `research/researcher.rs` — orchestrates research pipeline |
| `DocumentationSource` | ✅ Configurable sources with URL patterns and topics |
| Default sources | ✅ Redis, PostgreSQL, Go, Rust, OWASP, Kafka, MongoDB |
| Content fetching | ✅ HTTP with timeout and size limits |
| Normative extraction | ✅ Regex-based MUST/SHOULD/SHALL extraction |
| Section tracking | ✅ Extracts heading context for attribution |
| Confidence scoring | ✅ Based on keyword strength, statement length, content size |

### 5.5 CLI Integration ✅

| Task | Status |
|------|--------|
| `aphoria research run` | ✅ Run research agent with configurable threshold |
| `aphoria research status` | ✅ Show gap statistics and research progress |
| `aphoria research gaps` | ✅ List gaps by project count |
| `--threshold` | ✅ Minimum projects before researching (default: 3) |
| `--strict` | ✅ Use strict quality validation |
| `--prune` | ✅ Remove stale gaps before researching |
| `--ready` | ✅ Show only gaps ready for research |

**Files:** `research/mod.rs`, `research/gap_detector.rs`, `research/gap_store.rs`, `research/quality.rs`, `research/researcher.rs`, `research/tests.rs`

### 5.7 Security Extractors ✅

Extended Phase 2 extractors with OWASP-aligned security vulnerability detection:

| Extractor | Detects | Languages |
|-----------|---------|-----------|
| `weak_crypto` | MD5, SHA1, DES, RC4 usage | Rust, Go, Python, JS/TS |
| `command_injection` | Shell execution, os.system, subprocess shell=True | Rust, Go, Python, JS/TS |
| `sql_injection` | String concatenation in SQL queries | Rust, Go, Python, JS/TS |

**Concept paths:**
- `crypto/hashing/algorithm` — MD5, SHA1
- `crypto/encryption/algorithm` — DES, RC4
- `os/command/input`, `os/shell_mode` — command injection
- `db/query/input` — SQL injection

### 5.6 Community Corpus Contributions ✅

> Users can opt in to contribute patterns anonymously to a central corpus, enabling community consensus to adjust default thresholds.

| Task | Status |
|------|--------|
| `CommunityConfig` | ✅ `config/mod.rs` — enabled (false), anonymize (true), exclude, include, min_confidence |
| `AnonymizedObservation` | ✅ `community/types.rs` — privacy-preserving observation without file/line/text |
| `CommunityObjectValue` | ✅ `community/types.rs` — serde-compatible version of ObjectValue |
| `PatternAggregate` | ✅ `community/types.rs` — server-side aggregation with project counts |
| `anonymize_claim()` | ✅ `community/anonymizer.rs` — wildcards project names, strips file/line, rounds timestamps |
| `compute_anon_hash()` | ✅ Hash computed WITHOUT file/line/text (privacy-critical) |
| `wildcard_project_path()` | ✅ `code://rust/myapp/tls` → `code://rust/*/tls` |
| `--community-preview` flag | ✅ `cli.rs` — dry-run showing what WOULD be shared |
| `PatternAggregateStore` | ✅ `stemedb-storage` — server-side pattern aggregation |
| Project deduplication | ✅ Uses project_hash to prevent double-counting |
| `POST /v1/aphoria/community/observations` | ✅ Push anonymized observations |
| `GET /v1/aphoria/patterns` | ✅ Retrieve high-confidence community patterns |

**Privacy Model:**
- Project names wildcarded: `myapp` → `*`
- File paths, line numbers, matched text NEVER shared
- Timestamps rounded to hour (k-anonymity)
- Server receives `project_hash`, not raw project names
- `enabled` defaults to `false` (explicit opt-in required)
- `anonymize` defaults to `true` (privacy-preserving by default)

**Usage:**
```bash
# Preview what would be shared (no network)
aphoria scan --community-preview

# Enable in aphoria.toml:
[community]
enabled = true
anonymize = true
min_confidence = 0.8
exclude = ["vendor://acme/internal/*"]

# Scan with sync to share patterns
aphoria scan --persist --sync
```

**Files:** `community/mod.rs`, `community/types.rs`, `community/anonymizer.rs`, `config/mod.rs`, `cli.rs`, `handlers.rs`, `stemedb-storage/src/pattern_aggregate_store/`

---

## Phase 6: Federated Policy & Trust Packs ✅

> Allow teams to define their own authoritative truths and distribute them as signed Trust Packs. This enables "Enterprise Grade" compliance across distributed teams.

### 6.1 Trust Pack Format ✅

| Task | Status |
|------|--------|
| `TrustPack` schema | ✅ `policy.rs` — Assertions, Aliases, Metadata, Signature |
| `PackHeader` | ✅ Name, version, issuer, timestamp |
| Serialization | ✅ `rkyv` for zero-copy efficiency |
| Signing | ✅ `ed25519-dalek` signing and verification |

### 6.2 Policy Management ✅

| Task | Status |
|------|--------|
| `PolicyManager` | ✅ Loads local and remote (HTTP/HTTPS) policies |
| Caching | ✅ Caches remote policies in `~/.cache/aphoria/policies/` |
| `aphoria.toml` config | ✅ `policies` list support |

### 6.3 Core Integration ✅

| Task | Status |
|------|--------|
| `EphemeralDetector` integration | ✅ Ingests policies into memory corpus/index |
| `check_conflicts_pure` update | ✅ Resolves policy aliases before authoritative lookup |
| `LocalEpisteme` export helpers | ✅ `fetch_acknowledgments`, `fetch_manual_aliases` |

### 6.4 CLI Commands ✅

| Task | Status |
|------|--------|
| `aphoria policy export` | ✅ Exports local `ack` decisions as a Trust Pack |
| `aphoria scan` policy loading | ✅ Auto-loads policies from config |

**Files:** `policy.rs`, `config.rs`, `episteme/mod.rs`, `lib.rs`, `main.rs`

---

## Phase 6.5: Trust Pack Extensions ⬜

> Enhancements to Trust Packs based on enterprise pilot feedback. Deferred until real-world usage patterns emerge.

### 6.5.1 Predicate Aliases ⬜

**Status:** Deferred pending enterprise feedback
**Trigger:** When enterprises report predicate naming conflicts between policy and extractors

**User Story:**
> As a security architect, when my policy uses `required=true` but the extractor emits `enabled=true`, I need them to match semantically.

**Problem:**
- Policy blesses: `code://standard/tls/cert_verification` with predicate `required`, value `true`
- Extractor emits: `code://config/tls/cert_verification` with predicate `enabled`, value `false`
- Tail-path matching finds the concept (`tls/cert_verification`) ✓
- But predicates differ: `required` vs `enabled` — no conflict detected ✗

**Solution:**

| Task | Description |
|------|-------------|
| `predicate_aliases` field | Add to Trust Pack schema |
| Default aliases | `enabled` ↔ `required` ↔ `mandatory` ↔ `enforced` |
| ConceptIndex update | Check aliases during lookup |
| Pack-defined aliases | Allow packs to specify custom alias sets |

**Trust Pack Schema Extension:**
```toml
# In Trust Pack
[predicate_aliases]
security_enabled = ["enabled", "required", "mandatory", "enforced", "active"]
version_minimum = ["min_version", "minimum_version", "tls_min_version"]
```

**Implementation Plan:**
1. Add `predicate_aliases: HashMap<String, Vec<String>>` to `TrustPack`
2. Store aliases alongside assertions during import
3. Update `ConceptIndex.make_key()` to normalize predicates via aliases
4. Match during conflict detection: if `predicate_a` aliases to `predicate_b`, treat as same concept

### 6.5.2 Pack Signing Key Rotation ⬜

**Status:** Deferred pending security key management requirements
**Trigger:** Enterprise security requirements for key rotation

**User Story:**
> As a security admin, when our signing key is rotated, I need to re-sign all packs without losing policy content.

**Problem:**
- Trust Packs are signed with Ed25519 keys
- When keys are rotated (security best practice), existing packs become unverifiable
- Need to re-sign packs with new key while preserving content hash

**Solution:**

| Task | Description |
|------|-------------|
| `aphoria policy resign` | CLI command to re-sign pack with new key |
| Content hash preservation | Keep `content_hash` unchanged, only update signature |
| Key rotation audit | Log key rotation events |
| Old signature archival | Optionally keep old signature for audit trail |

**CLI:**
```bash
# Re-sign pack with new key
aphoria policy resign my-standards.pack --key-file new-private-key.pem

# Re-sign with signature chain (audit trail)
aphoria policy resign my-standards.pack --key-file new-key.pem --chain-signatures
```

**Trust Pack Schema Extension:**
```rust
pub struct TrustPack {
    // Existing fields...
    pub signature: Signature,

    // New field for key rotation audit
    pub signature_chain: Option<Vec<SignatureRecord>>,
}

pub struct SignatureRecord {
    pub issuer_public_key: [u8; 32],
    pub signature: Signature,
    pub signed_at: DateTime<Utc>,
    pub reason: Option<String>,  // "Key rotation", "Security incident", etc.
}
```

### 6.5.3 Priority

| Feature | Priority | Trigger |
|---------|----------|---------|
| Predicate Aliases | Medium | Enterprise feedback showing predicate naming conflicts |
| Key Rotation | Low | Enterprise security key management requirements |

**Documented in:** [uat/future-scenarios.md](uat/future-scenarios.md)

---

## Phase 7: Declarative Extractors ✅

> Enable users to define new extractors in config/policy files (TOML) without writing Rust code. This removes the recompilation bottleneck for custom pattern enforcement.

**User Outcome:** "I added a custom extractor to my aphoria.toml that detects our company's deprecated API patterns. Now every scan flags files using the old pattern without me writing any Rust code."

### 7.1 Core Types ✅

| Task | Status |
|------|--------|
| `DeclarativeExtractorDef` | ✅ `extractors/declarative.rs` — name, description, languages, pattern, claim, confidence |
| `DeclarativeClaimDef` | ✅ subject, predicate, value specification |
| `DeclarativeValue` enum | ✅ MatchedText, Boolean, Text variants |
| `DeclarativeExtractor` | ✅ Compiled extractor with `Extractor` trait impl |

### 7.2 Configuration ✅

| Task | Status |
|------|--------|
| `ExtractorConfig.declarative` | ✅ `config/mod.rs` — `Vec<DeclarativeExtractorDef>` |
| TOML parsing | ✅ Serde deserialization with `#[serde(untagged)]` for value types |
| Example config | ✅ Documented in module and config docs |

**Example aphoria.toml:**
```toml
[[extractors.declarative]]
name = "deprecated_api_v1"
description = "Detects usage of deprecated v1 API endpoints"
languages = ["go", "rust", "python"]
pattern = '/api/v1/\w+'
claim.subject = "api/deprecated_endpoint"
claim.predicate = "version"
claim.value = "v1"
confidence = 1.0

[[extractors.declarative]]
name = "legacy_encryption"
description = "Detects legacy encryption algorithms"
languages = ["rust", "go", "python", "javascript"]
pattern = '(?i)blowfish|twofish|cast5'
claim.subject = "crypto/encryption/algorithm"
claim.predicate = "algorithm"
claim.value_from_match = true
confidence = 0.9
```

### 7.3 Validation & Security ✅

| Task | Status |
|------|--------|
| Name validation | ✅ Non-empty required |
| Subject/predicate validation | ✅ Non-empty required |
| Confidence validation | ✅ Must be 0.0-1.0 |
| Regex validation | ✅ Compiled at load time, not scan time |
| ReDoS protection | ✅ `RegexBuilder` with 10MB size limits |
| Language parsing | ✅ `Language::from_str()` with `FromStr` trait |
| Graceful failure | ✅ Invalid extractors logged as warnings, don't block others |

### 7.4 Registry Integration ✅

| Task | Status |
|------|--------|
| Module export | ✅ `extractors/mod.rs` — public types |
| Registry registration | ✅ `ExtractorRegistry::new()` loads from config |
| Enable/disable support | ✅ Declarative extractors respect `disabled` list |
| Runtime addition | ✅ `add_from_definitions()` for Trust Pack integration |

### 7.5 Error Handling ✅

| Task | Status |
|------|--------|
| `DeclarativeExtractor` error variant | ✅ `error.rs` — name + message |
| Validation errors | ✅ Clear messages for each failure mode |
| Structured logging | ✅ `tracing::warn!` for compilation failures |

### 7.6 Tests ✅

| Task | Status |
|------|--------|
| Unit tests | ✅ 22 tests in `declarative.rs` |
| Registry tests | ✅ 7 tests for integration |
| Validation tests | ✅ Empty name, subject, predicate; invalid confidence, regex, language |
| Extraction tests | ✅ Boolean, text, matched_text value types |
| Deserialization tests | ✅ TOML parsing for all value types |

**Files:** `extractors/declarative.rs`, `extractors/mod.rs`, `config/mod.rs`, `types/language.rs`, `error.rs`

---

## Phase 7.5: LLM-in-the-Loop Extraction ✅

> Use LLM (Gemini) to extract claims semantically during persistent scans. This fills gaps that regex extractors can't catch, providing immediate value while the learning system builds up pattern knowledge.

### Vision

```
Code file → Regex extractors → Claims found
                ↓
         High-value files (auth, config, crypto)
                ↓
         LLM Extractor → Additional semantic claims
                ↓
         Combined claims → Conflict detection
```

### 7.5.1 LLM Extractor Implementation ✅

| Task | Status |
|------|--------|
| `GeminiClient` struct | ✅ `llm/client.rs` — Gemini API client using ureq |
| `LlmExtractor` struct | ✅ `llm/extractor.rs` — orchestrates extraction with budget tracking |
| Prompt engineering | ✅ Security-focused extraction prompt with structured JSON output |
| Response parsing | ✅ Parse Gemini's JSON response into `ExtractedClaim` format |
| Error handling | ✅ Graceful degradation when API unavailable or key missing |

### 7.5.2 Selective Triggering ✅

| Task | Status |
|------|--------|
| `is_high_value_file()` | ✅ `llm/extractor.rs` — auth/, config/, crypto/, security/, secrets/, certs/, ssl/, tls/, keys/, credentials/ directories |
| High-value file names | ✅ secret, password, credential, token, auth, login, session, jwt, tls, ssl, cert, key, config, settings, security, crypto, encrypt, decrypt, oauth, saml, ldap, api_key, apikey, access_key, private |
| Token budget | ✅ `max_tokens_per_scan` (default 50k), `max_tokens_per_file` (default 4k) |
| Skip conditions | ✅ Only runs when regex extractors found nothing AND file is high-value |

### 7.5.3 Cost Controls ✅

| Task | Status |
|------|--------|
| Token tracking | ✅ `Arc<AtomicUsize>` for thread-safe budget tracking across files |
| BLAKE3 caching | ✅ `llm/cache.rs` — content hash + model + prompt version for cache key |
| Cache location | ✅ `~/.cache/aphoria/llm-cache/` |
| Budget enforcement | ✅ `within_budget()` check before each LLM call |

### 7.5.4 Configuration ✅

```toml
# aphoria.toml
[llm]
enabled = true                    # Enable LLM extraction (default: false)
provider = "gemini"               # Only "gemini" supported
# model defaults to DEFAULT_LLM_MODEL (currently "gemini-3-flash-preview")
api_key_env = "GEMINI_API_KEY"    # Environment variable for API key
max_tokens_per_scan = 50000       # Budget per scan
max_tokens_per_file = 4000        # Budget per file (for max_output_tokens)
high_value_only = true            # Only use on auth/config/crypto files
cache_responses = true            # Cache by content hash
timeout_secs = 60                 # API timeout
min_confidence = 0.7              # Filter claims below this confidence
```

**Files:** `llm/mod.rs`, `llm/client.rs`, `llm/extractor.rs`, `llm/cache.rs`, `config/mod.rs`, `scan.rs`, `error.rs`

---

## Phase 7.6: Pattern Learning Store ✅

> When LLM extracts something that regex extractors missed, remember the pattern. Track which patterns recur across projects to identify candidates for promotion to declarative extractors.

### Vision

```
LLM extracts claim from code
        ↓
Pattern not in learned store?
        ↓
Store: { example_code, claim, project_hash }
        ↓
Same pattern seen in 5+ projects?
        ↓
Flag for promotion to declarative extractor
```

### 7.6.1 LearnedPattern Schema ✅

| Task | Status |
|------|--------|
| `ValueType` enum | ✅ `learning/types.rs` — Text, Number, Boolean |
| `ClaimTemplate` struct | ✅ `learning/types.rs` — subject_template, predicate, value_type, description |
| `LearnedPattern` struct | ✅ `learning/types.rs` — full schema with timestamps, project hashes, confidence tracking |
| Serde serialization | ✅ JSON serialization with chrono timestamps |
| Tests | ✅ 5 unit tests for types |

### 7.6.2 PatternStore Implementation ✅

| Task | Status |
|------|--------|
| `PatternStore` trait | ✅ `learning/store.rs` — abstract storage interface |
| `LocalPatternStore` | ✅ JSON-backed local storage at `~/.aphoria/learning/patterns.json` |
| `RwLock` thread safety | ✅ Write-through cache with in-memory HashMap |
| Deduplication | ✅ `find_similar()` with Levenshtein similarity threshold 0.8 |
| Pruning | ✅ `prune_stale()` removes patterns not seen in N days |
| Tests | ✅ 8 unit tests for store operations |

### 7.6.3 Pattern Normalization ✅

| Task | Status |
|------|--------|
| `normalize_pattern()` | ✅ `learning/normalizer.rs` — replaces literals with placeholders |
| Version detection | ✅ `"1.0"`, `"TLSv1.2"` → `<string:version>` |
| Boolean detection | ✅ `true`/`false` → `<boolean>` |
| Number detection | ✅ Standalone numbers → `<number>` |
| String detection | ✅ Remaining quoted strings → `<string>` |
| `pattern_similarity()` | ✅ Levenshtein distance normalized to 0.0-1.0 |
| Tests | ✅ 17 unit tests for normalization |

### 7.6.4 Configuration ✅

```toml
# aphoria.toml
[learning]
enabled = true                    # Enable pattern learning (default: false)
store = "local"                   # "local" | "hosted"
min_confidence = 0.7              # Minimum LLM confidence to learn
prune_after_days = 90             # Remove patterns not seen in N days

[learning.promotion]
min_projects = 5                  # Projects needed before promotion
min_confidence = 0.8              # Average confidence needed
auto_promote = false              # Require human approval (Phase 7.7)
```

### 7.6.5 Scan Integration ✅

| Task | Status |
|------|--------|
| Initialize pattern store | ✅ `scan.rs` — only in persistent mode with learning enabled |
| Project hash computation | ✅ BLAKE3 hash for privacy-preserving project identification |
| Record LLM-extracted claims | ✅ After LLM extraction, record patterns meeting min_confidence |
| Update existing patterns | ✅ Merge observations when similar pattern found |
| Logging | ✅ Reports patterns_recorded count on scan completion |

### 7.6.6 Error Handling ✅

| Task | Status |
|------|--------|
| `LearningStore` error variant | ✅ `error.rs` — for storage/cache failures |
| Graceful degradation | ✅ Store failures logged, don't block scan |

**Files:** `learning/mod.rs`, `learning/types.rs`, `learning/normalizer.rs`, `learning/store.rs`, `config/mod.rs`, `scan.rs`, `error.rs`, `lib.rs`

**Tests:** 30 tests covering types, normalization, and store operations.

---

## Phase 7.6 (Legacy Documentation)

> **Note:** The following is the original spec for reference. See above for implemented status.

### Original Schema (Reference)

```rust
/// A pattern learned from LLM extraction that could become a declarative extractor.
#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct LearnedPattern {
    /// Unique identifier
    pub id: Uuid,

    /// Example code that triggered this pattern
    pub example_code: String,

    /// Normalized pattern (variables replaced with placeholders)
    /// e.g., "const TLS_MIN_VERSION = \"1.0\"" → "const TLS_MIN_VERSION = <version>"
    pub normalized_pattern: String,

    /// The claim this pattern produces
    pub claim_template: ClaimTemplate,

    /// Language this pattern applies to
    pub language: Language,

    /// When first seen
    pub first_seen: DateTime<Utc>,

    /// When last seen
    pub last_seen: DateTime<Utc>,

    /// Projects that have this pattern (hashed for privacy)
    pub project_hashes: HashSet<String>,

    /// Total occurrences across all projects
    pub occurrences: u32,

    /// Average LLM confidence when extracting this
    pub avg_confidence: f32,

    /// Has this been promoted to a declarative extractor?
    pub promoted: bool,

    /// If promoted, the extractor ID
    pub promoted_to: Option<String>,
}

/// Template for generating claims from a learned pattern.
#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct ClaimTemplate {
    pub subject_template: String,  // "tls/min_version"
    pub predicate: String,         // "version"
    pub value_type: ValueType,     // String, Boolean, Number
    pub description_template: String,
}
```

### Original PatternStore Trait (Reference)

```rust
pub trait PatternStore: Send + Sync {
    /// Record a pattern learned from LLM extraction
    fn record_pattern(&self, pattern: &LearnedPattern) -> Result<()>;

    /// Find existing pattern matching this example
    fn find_similar(&self, normalized: &str, language: Language, threshold: f32) -> Option<LearnedPattern>;

    /// Get patterns ready for promotion (threshold met)
    fn get_promotion_candidates(&self, min_projects: usize, min_confidence: f32) -> Vec<LearnedPattern>;

    /// Mark pattern as promoted
    fn mark_promoted(&self, id: &Uuid, extractor_name: &str) -> Result<()>;

    /// Prune old patterns
    async fn prune_stale(&self, max_age_days: u32) -> Result<usize>;
}
```

### 7.6.3 Pattern Normalization ⬜

| Task | Description |
|------|-------------|
| Variable extraction | Identify literals that vary (versions, names, values) |
| Placeholder insertion | Replace literals with typed placeholders |
| Similarity scoring | Compare normalized patterns for dedup |

```rust
fn normalize_pattern(code: &str, claim: &ExtractedClaim) -> String {
    // "const TLS_MIN = \"1.0\"" → "const TLS_MIN = <string:version>"
    // "pool_size: 25" → "pool_size: <number>"
    // "verify_ssl: false" → "verify_ssl: <boolean>"
}

fn similarity_score(a: &str, b: &str) -> f32 {
    // Levenshtein distance normalized to 0.0-1.0
    // Patterns with score > 0.8 are considered duplicates
}
```

### 7.6.4 Integration with Scan ⬜

```rust
// In scan.rs, after LLM extraction
for claim in llm_claims {
    // Check if this is a new pattern
    if let Some(existing) = pattern_store.find_similar(&claim.matched_text, language).await {
        // Update existing pattern
        pattern_store.increment_occurrence(&existing.id, project_hash).await?;
    } else {
        // Record new pattern
        let pattern = LearnedPattern::from_claim(&claim, &code_context, project_hash);
        pattern_store.record_pattern(&pattern).await?;
    }
}
```

### 7.6.5 Configuration ⬜

```toml
# aphoria.toml
[learning]
enabled = true                    # Enable pattern learning
store = "local"                   # "local" | "hosted"
min_confidence = 0.7              # Minimum LLM confidence to learn
prune_after_days = 90             # Remove patterns not seen in N days

[learning.promotion]
min_projects = 5                  # Projects needed before promotion
min_confidence = 0.8              # Average confidence needed
auto_promote = false              # Require human approval (Phase 7.7)
```

**Files:** `learning/mod.rs`, `learning/pattern.rs`, `learning/store.rs`, `learning/normalize.rs`

---

## Phase 7.7: Pattern → Extractor Promotion ⬜

> High-frequency learned patterns get promoted to declarative extractors. This closes the learning loop: patterns discovered by LLM become permanent, fast regex extractors.

### Vision

```
LearnedPattern (5+ projects, >0.8 confidence)
        ↓
Claude: "Generate regex for this pattern"
        ↓
Candidate declarative extractor
        ↓
Validate against stored examples
        ↓
Human review (optional) → Approve/Reject
        ↓
Merge to project's .aphoria/extractors/
```

### 7.7.1 Promotion Pipeline ⬜

| Task | Description |
|------|-------------|
| Candidate selection | Query patterns meeting threshold |
| Regex generation | LLM generates regex from examples |
| YAML generation | Convert to declarative extractor format |
| Validation | Test against all stored examples |
| Review queue | Present candidates for human approval |

```rust
pub struct PromotionPipeline {
    pattern_store: Arc<dyn PatternStore>,
    llm_client: ClaudeClient,
    validator: ExtractorValidator,
}

impl PromotionPipeline {
    /// Get patterns ready for promotion
    pub async fn get_candidates(&self) -> Vec<PromotionCandidate> {
        let patterns = self.pattern_store
            .get_promotion_candidates(5, 0.8)
            .await?;

        patterns.into_iter()
            .map(|p| self.generate_candidate(p))
            .collect()
    }

    /// Generate declarative extractor from pattern
    async fn generate_candidate(&self, pattern: LearnedPattern) -> PromotionCandidate {
        // Ask Claude to generate regex
        let regex = self.llm_client.generate_regex(&pattern).await?;

        // Build declarative extractor
        let extractor = DeclarativeExtractor {
            name: pattern.id.to_string(),
            language: pattern.language,
            pattern: regex,
            claim: pattern.claim_template.clone(),
            source: ExtractorSource::Learned {
                pattern_id: pattern.id,
                projects: pattern.project_hashes.len(),
            },
        };

        // Validate against examples
        let validation = self.validator.validate(&extractor, &pattern).await;

        PromotionCandidate { pattern, extractor, validation }
    }
}
```

### 7.7.2 Regex Generation ⬜

| Task | Description |
|------|-------------|
| Multi-example prompt | Include all examples in generation prompt |
| Regex safety | Prevent catastrophic backtracking |
| Test coverage | Generate test cases alongside regex |

```rust
async fn generate_regex(examples: &[String], claim: &ClaimTemplate) -> Result<String> {
    let prompt = format!(
        "Generate a regex pattern that matches all these code examples:\n\n{}\n\n\
         The regex should extract the value for claim: {}\n\
         Requirements:\n\
         - Must match ALL examples\n\
         - Use named capture groups for extracted values\n\
         - Avoid catastrophic backtracking (no nested quantifiers)\n\
         - Return ONLY the regex, no explanation",
        examples.join("\n---\n"),
        claim.subject_template
    );

    let response = claude.message(&prompt).await?;
    validate_regex_safety(&response)?;
    Ok(response)
}
```

### 7.7.3 Validation Suite ⬜

| Task | Description |
|------|-------------|
| Positive tests | Must match all stored examples |
| Negative tests | Must NOT match known-safe code |
| Performance test | Must complete in < 100ms |
| False positive check | Run against sample codebase |

```rust
pub struct ExtractorValidator {
    sample_codebases: Vec<PathBuf>,  // Known-good projects for FP testing
}

impl ExtractorValidator {
    pub async fn validate(
        &self,
        extractor: &DeclarativeExtractor,
        pattern: &LearnedPattern
    ) -> ValidationResult {
        let mut result = ValidationResult::default();

        // Must match all positive examples
        for example in &pattern.examples {
            if !extractor.matches(example) {
                result.positive_failures.push(example.clone());
            }
        }

        // Must not have excessive false positives
        for codebase in &self.sample_codebases {
            let fps = self.count_false_positives(extractor, codebase).await;
            if fps > 10 {
                result.false_positive_warning = true;
            }
        }

        // Must be fast
        let duration = self.benchmark(extractor);
        if duration > Duration::from_millis(100) {
            result.performance_warning = true;
        }

        result
    }
}
```

### 7.7.4 Human Review Gate ⬜

| Task | Description |
|------|-------------|
| `aphoria extractors review` | CLI to review pending promotions |
| Approval workflow | Approve, reject, or request changes |
| Rejection tracking | Record why patterns were rejected |
| Auto-approve mode | Skip review for >0.95 confidence (Phase 9) |

```bash
$ aphoria extractors review

Pending promotions: 3

[1/3] Pattern: tls_min_version_const
      Examples: 47 (across 8 projects)
      Confidence: 0.91

      Generated regex: (?i)(tls|ssl)_?(min|minimum)_?version\s*[:=]\s*["']?(1\.[01])["']?

      Sample matches:
        const TLS_MIN_VERSION = "1.0"     ✓ matches
        TLS_MINIMUM_VERSION: "1.1"        ✓ matches
        ssl_min_version = "1.2"           ✓ matches (TLS 1.2 is safe, false positive?)

      [a]pprove  [r]eject  [e]dit  [s]kip  [q]uit: _
```

### 7.7.5 Extractor Output ⬜

Promoted patterns become declarative extractors in `.aphoria/extractors/`:

```yaml
# .aphoria/extractors/learned/tls_min_version_const.yaml
# Auto-generated from learned pattern. DO NOT EDIT.
# Pattern ID: 550e8400-e29b-41d4-a716-446655440000
# Learned from: 8 projects, 47 occurrences
# Confidence: 0.91
# Promoted: 2026-02-10

name: "tls_min_version_const"
language: ["rust", "go", "python", "javascript", "typescript"]
pattern: '(?i)(tls|ssl)_?(min|minimum)_?version\s*[:=]\s*["\']?(1\.[01])["\']?'
claim:
  subject: "tls/min_version"
  predicate: "version"
  value_capture: 1  # Capture group for version
  description: "TLS minimum version set to deprecated {value}"
metadata:
  source: "learned"
  pattern_id: "550e8400-e29b-41d4-a716-446655440000"
  projects: 8
  occurrences: 47
  confidence: 0.91
```

### 7.7.6 Configuration ⬜

```toml
# aphoria.toml
[promotion]
enabled = true                    # Enable promotion pipeline
auto_promote = false              # Require human approval
output_dir = ".aphoria/extractors/learned"
min_confidence = 0.8              # Minimum to consider
require_validation = true         # Must pass validation suite

[promotion.review]
notify = "slack://webhook/..."    # Notify when candidates ready
batch_size = 10                   # Max candidates per review session
```

**Files:** `promotion/mod.rs`, `promotion/pipeline.rs`, `promotion/regex_gen.rs`, `promotion/validator.rs`, `promotion/review.rs`

---

## Phase 9: Autonomous Extractor Generation ⬜

> The system generates, tests, and deploys extractors without human approval for high-confidence patterns. This is the endgame: a fully self-improving extraction system.

### Vision

```
Learned pattern exceeds autonomous threshold (>0.95 confidence, >10 projects)
        ↓
Auto-generate extractor
        ↓
Validate against comprehensive test suite
        ↓
A/B test: run new extractor in shadow mode
        ↓
If FP rate < 5%: auto-deploy
        ↓
If FP rate spikes: auto-rollback
```

### 9.1 Autonomous Promotion ⬜

| Task | Description |
|------|-------------|
| High-confidence threshold | Skip human review for >0.95 confidence |
| Project threshold | Require >10 projects for autonomous |
| Validation strictness | Stricter validation for autonomous |

```rust
fn should_auto_promote(pattern: &LearnedPattern, validation: &ValidationResult) -> bool {
    pattern.avg_confidence > 0.95 &&
    pattern.project_hashes.len() > 10 &&
    validation.positive_failures.is_empty() &&
    !validation.false_positive_warning &&
    !validation.performance_warning
}
```

### 9.2 Shadow Mode Testing ⬜

| Task | Description |
|------|-------------|
| Shadow execution | Run new extractor alongside existing |
| Metrics collection | Track matches, FP rate, performance |
| Comparison report | Compare shadow vs production results |
| Promotion criteria | Promote if metrics meet threshold |

```rust
pub struct ShadowTest {
    extractor: DeclarativeExtractor,
    start_time: DateTime<Utc>,
    scans_completed: u32,
    matches: u32,
    confirmed_true_positives: u32,
    confirmed_false_positives: u32,
}

impl ShadowTest {
    fn false_positive_rate(&self) -> f32 {
        self.confirmed_false_positives as f32 / self.matches as f32
    }

    fn should_promote(&self) -> bool {
        self.scans_completed >= 100 &&
        self.false_positive_rate() < 0.05
    }
}
```

### 9.3 Auto-Rollback ⬜

| Task | Description |
|------|-------------|
| Anomaly detection | Detect FP rate spikes |
| Rollback trigger | Auto-disable if FP > 10% |
| Notification | Alert on rollback |
| Quarantine | Move extractor to review queue |

```rust
async fn check_extractor_health(extractor_id: &str, metrics: &Metrics) -> Action {
    let recent_fp_rate = metrics.false_positive_rate_last_24h(extractor_id);
    let baseline_fp_rate = metrics.false_positive_rate_baseline(extractor_id);

    if recent_fp_rate > 0.10 {
        Action::Rollback { reason: "FP rate exceeded 10%" }
    } else if recent_fp_rate > baseline_fp_rate * 2.0 {
        Action::Rollback { reason: "FP rate doubled from baseline" }
    } else {
        Action::Continue
    }
}
```

### 9.4 Cross-Project Learning ⬜

| Task | Description |
|------|-------------|
| Hosted pattern sync | Patterns from all projects aggregate on server |
| Global promotion | Promote patterns seen across many orgs |
| Privacy preservation | Only normalized patterns shared, no code |
| Opt-in distribution | Orgs can opt-in to receive community extractors |

```
Org A: Pattern seen in 3 projects → shared to hosted
Org B: Same pattern in 5 projects → shared to hosted
Org C: Same pattern in 4 projects → shared to hosted
        ↓
Hosted aggregates: 12 projects total
        ↓
Promotes to community extractor
        ↓
All orgs receive new extractor (if opted in)
```

### 9.5 Extractor Versioning ⬜

| Task | Description |
|------|-------------|
| Version tracking | Track which version caught which issues |
| Changelog | Record changes between versions |
| Rollback support | Revert to previous version |
| A/B metrics | Compare versions side-by-side |

```yaml
# .aphoria/extractors/learned/tls_min_version_const.yaml
version: 2
previous_version: 1
changelog:
  - version: 2
    date: 2026-03-15
    changes: "Added support for YAML configs"
    metrics:
      matches: +15%
      false_positives: -3%
  - version: 1
    date: 2026-02-10
    changes: "Initial auto-generated version"
```

### 9.6 Configuration ⬜

```toml
# aphoria.toml
[autonomous]
enabled = false                   # Opt-in to autonomous mode
min_confidence = 0.95             # Higher threshold for auto
min_projects = 10                 # More evidence required
shadow_scans = 100                # Scans before promotion
max_fp_rate = 0.05                # Auto-rollback threshold

[autonomous.distribution]
receive_community = true          # Receive community extractors
contribute_patterns = true        # Share patterns to community
```

**Files:** `autonomous/mod.rs`, `autonomous/shadow.rs`, `autonomous/rollback.rs`, `autonomous/distribution.rs`

---

## Milestone Summary

| Phase | Deliverable | Depends On | Status |
|-------|-------------|------------|--------|
| 0 | ConceptPath in StemeDB | concept-hierarchy spec | ✅ |
| 2 | Aphoria CLI (scan, report, ack) | Phase 0 | ✅ |
| 2A | Concept matching (leaf, alias, auto-alias) | Phase 2 | ✅ |
| 1 | Authoritative corpus expansion | Phase 0 | ✅ |
| 3 | Claude Code skill + hooks | Phase 2A | ✅ |
| 4.5 | Ephemeral scan mode (40x faster) | Phase 2 | ✅ |
| 5 | Research agent loop | Phase 3 | ✅ |
| 6 | Federated Policy & Trust Packs | Phase 4.5 | ✅ |
| **6.5** | **Trust Pack Extensions (Predicate Aliases, Key Rotation)** | Phase 6 | ⬜ |
| 4A | Observational claims (Tier 4 write-back) | Phase 6 | ✅ |
| 4B | Self-conflict detection (drift) | Phase 4A | ✅ |
| 4C | Diff-only scanning (--staged) | Phase 4B | ✅ |
| 4E | Hosted mode (team aggregation) | Phase 4C | ✅ |
| 4D | Enhanced ack (--reason, policy updates) | Phase 4C | ✅ |
| 5.6 | Community Corpus Contributions | Phase 4E | ✅ |
| 7 | Declarative Extractors | Phase 6 | ✅ |
| **7.5** | **LLM-in-the-Loop Extraction (Gemini)** | Phase 7 | ✅ |
| **7.6** | **Pattern Learning Store** | Phase 7.5 | ✅ |
| **7.7** | **Pattern → Extractor Promotion** | Phase 7.6 | ⬜ |
| 8 | Enterprise Extractors (MVP: 8.1, 8.6, 8.11) | Phase 7.5 | ✅ |
| **9** | **Autonomous Extractor Generation** | Phase 8 | ⬜ |

**Current state:**
- Phases 0-3, 4.5, 4A-4E, 5, 5.6, 6, 7, 7.5, 7.6, 8 (MVP) complete (clippy clean)
- Full corpus: RFC, OWASP, Vendor sources
- 17 extractors including security (weak_crypto, command_injection, sql_injection, high_entropy_secrets, auth_bypass, insecure_cookies)
- Trust Packs: signed policy bundles with import/export
- Ephemeral mode: 40x faster for CI
- Observation write-back: `--sync` records novel claims as Tier 4 project memory
- Drift detection: Detects changes from prior observations
- Staged scanning: `--staged` flag for fast pre-commit hooks
- Hosted mode: Team aggregation via central StemeDB server
- Enhanced ack: `--reason` flag, `aphoria update` for policy changes
- Community Corpus: Opt-in anonymous pattern sharing with privacy-preserving anonymization
- Declarative Extractors: TOML-defined custom extractors without Rust code
- LLM Extraction: Gemini-powered semantic claim extraction for high-value files
- Enterprise Extractors MVP: High-entropy secrets (Shannon entropy), auth bypass patterns, insecure cookie flags
- Pattern Learning: LLM-extracted claims recorded for promotion to declarative extractors

**Next:** Phase 7.7 → 8 (full) → 9 (Self-Learning Extraction System)

### The Self-Learning Vision

```
Phase 7: Declarative Extractors (foundation)           ✅ COMPLETE
    ↓
Phase 7.5: LLM-in-the-Loop (Gemini semantic extraction) ✅ COMPLETE
    ↓
Phase 7.6: Pattern Learning (remember what LLM finds)   ✅ COMPLETE
    ↓
Phase 7.7: Pattern Promotion (patterns → extractors)    ⬜ NEXT
    ↓
Phase 8: Enterprise Extractors (generated + curated)    ✅ MVP (8.1, 8.6, 8.11)
    ↓
Phase 9: Autonomous Generation (fully self-improving)   ⬜
```

**The endgame:** Every PR teaches Aphoria. After a month, it knows your security patterns better than your team does.

### Bidirectional Knowledge Sync (Complete)

The pre-commit hook is now a bidirectional knowledge sync:
1. **4A** ✅: Record code claims as Tier 4 observations (project memory)
2. **4B** ✅: Detect drift from prior observations (self-conflict)
3. **4C** ✅: Fast diff-only scanning for pre-commit hooks (`--staged`)
4. **4E** ✅: Team aggregation via hosted StemeDB server
5. **4D** ✅: Enhanced ack with rationale and policy updates

This transforms Aphoria from a linter into a learning system that builds institutional memory per-project and collective intelligence across teams via hosted mode.

---

## Phase 8: Enterprise Extractor Improvements

> **Goal:** Transform extractors from "toy examples" to enterprise-grade detection that catches real violations in production codebases.

### Current State Audit

| Extractor | Languages | Strengths | Weaknesses |
|-----------|-----------|-----------|------------|
| `tls_verify` | 8 | Multi-lang, configs | Misses custom wrappers |
| `tls_version` | 8 | API patterns | Misses semantic (const = "1.0") |
| `hardcoded_secrets` | 8 | Placeholders, test files | No entropy detection |
| `weak_crypto` | 5 | MD5/SHA1/DES/RC4 | SHA1 false positives, misses bcrypt cost |
| `sql_injection` | 5 | Interpolation patterns | Misses ORM unsafe methods |
| `jwt_config` | 8 | alg:none, skip sig | Library-specific gaps |
| `cors_config` | 8 | Wildcard + credentials | Misses dynamic origin reflection |
| `rate_limit` | 8 | Basic patterns | Limited depth |
| `timeout_config` | 8 | Basic patterns | Limited depth |
| `command_injection` | 5 | exec/system calls | Indirect injection |
| `dep_versions` | 3 | Version parsing | No CVE correlation |

**Enterprise Reality:** Current extractors catch ~30% of real-world security misconfigurations. Config files are highest value (patterns consistent), code is lowest (semantic understanding required).

---

### 8.1 High-Entropy Secret Detection ✅

**Impact:** HIGH | **Effort:** MEDIUM | **Status:** Complete

| Task | Status |
|------|--------|
| `HighEntropySecretsExtractor` | ✅ `extractors/high_entropy_secrets.rs` |
| Shannon entropy algorithm | ✅ `shannon_entropy()` with 4.5 threshold |
| Charset variety check | ✅ 0.4 minimum variety ratio |
| Known secret prefixes | ✅ AWS (AKIA), Stripe (sk_live_, sk_test_), GitHub (ghp_, gho_), GitLab (glpat-), Slack (xox[baprs]-) |
| High-entropy context patterns | ✅ api_key, secret, token, credential, auth_key contexts |
| False positive exclusions | ✅ UUIDs, git SHAs (40-char hex), file hashes (64-char hex) |
| Test file confidence reduction | ✅ 0.6 confidence for test files |
| Tests | ✅ 10+ tests covering all patterns |

**Configuration:**
```toml
# aphoria.toml
[extractors.entropy]
min_entropy = 4.5          # Shannon entropy threshold
min_charset_variety = 0.4  # Unique chars / length ratio
min_length = 20            # Minimum string length
max_length = 200           # Maximum string length
```

**Languages:** Rust, Go, Python, JavaScript, TypeScript, YAML, TOML, JSON, Dotenv

---

### 8.2 Framework-Specific Extractors ⬜

**Impact:** HIGH | **Effort:** HIGH

Generic patterns miss framework-specific misconfigurations. Enterprise codebases use frameworks.

#### 8.2.1 Spring Boot Security
```yaml
# application.yml misconfigs
security:
  basic:
    enabled: false      # Auth disabled
  csrf:
    enabled: false      # CSRF disabled
  headers:
    frame-options: DISABLE  # Clickjacking
```

```java
// Java code patterns
@EnableWebSecurity
public class Config extends WebSecurityConfigurerAdapter {
    http.csrf().disable();  // CSRF disabled
    http.authorizeRequests().antMatchers("/**").permitAll();  // Auth bypass
}
```

#### 8.2.2 Django Security
```python
# settings.py misconfigs
DEBUG = True  # Debug in production
ALLOWED_HOSTS = ['*']  # All hosts
CSRF_COOKIE_SECURE = False  # Insecure cookies
SESSION_COOKIE_SECURE = False
```

#### 8.2.3 Express.js Security
```javascript
// Missing security middleware
app.use(helmet());  // helmet() should exist
app.use(cors({ origin: '*', credentials: true }));  // CORS + creds
app.disable('x-powered-by');  // Should be disabled
```

#### 8.2.4 Rails Security
```ruby
# config/environments/production.rb
config.force_ssl = false  # Should be true
config.action_dispatch.cookies_same_site_protection = :none
```

---

### 8.3 Config File Deep Parsing ⬜

**Impact:** HIGH | **Effort:** MEDIUM

Current extractors use regex on config files. This misses:
- Nested structures
- Environment-specific overrides
- Comments that disable security

**Implementation:**
```rust
// Parse YAML/JSON/TOML into structured form
enum ConfigValue {
    String(String),
    Number(f64),
    Bool(bool),
    Array(Vec<ConfigValue>),
    Object(HashMap<String, ConfigValue>),
}

// Then extract with path awareness
fn extract_config_claims(config: &ConfigValue, path: &[String]) -> Vec<ExtractedClaim> {
    // Recursively walk structure
    // Track full path: "server.tls.min_version"
    // Apply semantic rules based on path
}
```

**Patterns to catch:**
- `tls.verify: false` anywhere in hierarchy
- `security.enabled: false` in production configs
- `debug: true` or `DEBUG: true` in non-dev files

---

### 8.4 Semantic TLS Version Detection ⬜

**Impact:** MEDIUM | **Effort:** MEDIUM

Current `tls_version` misses:
```rust
const TLS_MIN_VERSION: &str = "1.0";  // Not caught!
const MIN_TLS: &str = "TLSv1";        // Not caught!
```

**Implementation:**
```rust
// Semantic pattern: variable name suggests TLS + value is deprecated
let semantic_tls = Regex::new(
    r#"(?i)(tls|ssl)_?(min|minimum|version)[^=]*[:=]\s*["']?(1\.[01]|TLSv?1(?:\.[01])?|SSL)"#
).unwrap();
```

**Also catch:**
- Environment variables: `TLS_MIN_VERSION=1.0`
- Terraform: `min_tls_version = "TLS1_0"`
- Kubernetes: `minTLSVersion: VersionTLS10`

---

### 8.5 ORM SQL Injection Detection ⬜

**Impact:** MEDIUM | **Effort:** MEDIUM

Current `sql_injection` catches raw string interpolation but misses ORM escape hatches:

```python
# SQLAlchemy
db.execute(text(f"SELECT * FROM users WHERE id = {user_id}"))
User.query.filter(text("name = '" + name + "'"))

# Django
User.objects.raw("SELECT * FROM users WHERE id = %s" % user_id)
User.objects.extra(where=["name = '%s'" % name])
```

```javascript
// Sequelize
sequelize.query(`SELECT * FROM users WHERE id = ${userId}`);
Model.findAll({ where: sequelize.literal(`id = ${id}`) });

// Prisma
prisma.$queryRawUnsafe(`SELECT * FROM users WHERE id = ${id}`);
```

```ruby
# ActiveRecord
User.where("name = '#{name}'")
User.find_by_sql("SELECT * FROM users WHERE id = #{id}")
```

---

### 8.6 Authentication Bypass Patterns ✅

**Impact:** HIGH | **Effort:** MEDIUM | **Status:** Complete

| Task | Status |
|------|--------|
| `AuthBypassExtractor` | ✅ `extractors/auth_bypass.rs` |
| Hardcoded admin credentials | ✅ `username == "admin" && password == "..."` patterns |
| Debug auth headers | ✅ X-Debug-Auth, X-Internal-Auth, X-Admin-Auth |
| Skip auth env vars | ✅ SKIP_AUTH, BYPASS_AUTH, NO_AUTH, DEBUG_AUTH |
| Backdoor patterns | ✅ `if username == "backdoor"`, `if user == "test"` |
| Default credentials | ✅ admin/admin, root/root, test/test, guest/guest |
| Test file confidence reduction | ✅ 0.5 confidence for test files |
| Tests | ✅ 11+ tests covering all patterns |

**Detected patterns:**
```python
# Hardcoded credentials
if username == "admin" and password == "admin":

# Debug auth headers
if request.headers.get("X-Debug-Auth") == "secret":

# Skip auth env vars
if os.environ.get("SKIP_AUTH") == "true":
```

**Languages:** Python, JavaScript, TypeScript, Go, Rust

---

### 8.7 Insecure Deserialization ⬜

**Impact:** HIGH | **Effort:** MEDIUM

Unsafe deserialization of untrusted data:

```python
# Python
pickle.loads(user_input)
yaml.load(user_input)  # Without Loader=SafeLoader
eval(user_input)
exec(user_input)
```

```java
// Java
ObjectInputStream ois = new ObjectInputStream(userInput);
ois.readObject();  // Dangerous!
```

```ruby
# Ruby
Marshal.load(user_input)
YAML.load(user_input)  # Should use safe_load
```

---

### 8.8 Path Traversal Patterns ⬜

**Impact:** MEDIUM | **Effort:** LOW

File operations with user input:

```python
# Python
open(user_input)
os.path.join(base, user_input)  # Doesn't prevent ../
shutil.copy(user_input, dest)
```

```javascript
// JavaScript
fs.readFile(userInput)
path.join(base, userInput)  // Doesn't prevent ../
res.sendFile(userInput)
```

---

### 8.9 SSRF Patterns ⬜

**Impact:** HIGH | **Effort:** MEDIUM

HTTP requests with user-controlled URLs:

```python
# Python
requests.get(user_url)
urllib.request.urlopen(user_input)
```

```javascript
// JavaScript
fetch(userUrl)
axios.get(userUrl)
http.get(userUrl)
```

```go
// Go
http.Get(userURL)
client.Do(req)  // Where req.URL is user-controlled
```

---

### 8.10 Missing Security Headers ⬜

**Impact:** MEDIUM | **Effort:** LOW

Detect when security headers are explicitly removed or not set:

```python
# Response headers missing
response.headers.pop('X-Content-Type-Options')
response.headers['X-Frame-Options'] = 'ALLOWALL'
```

```javascript
// Express without helmet
app.use(cors());  // CORS without other security
// No app.use(helmet()) found
```

---

### 8.11 Insecure Cookie Flags ✅

**Impact:** MEDIUM | **Effort:** LOW | **Status:** Complete

| Task | Status |
|------|--------|
| `InsecureCookiesExtractor` | ✅ `extractors/insecure_cookies.rs` |
| Missing Secure flag | ✅ `secure=False`, `secure: false` |
| Missing HttpOnly flag | ✅ `httponly=False`, `httpOnly: false` |
| SameSite=None without Secure | ✅ `sameSite: 'none'`, `SameSite=None` |
| Django settings | ✅ SESSION_COOKIE_SECURE, CSRF_COOKIE_SECURE = False |
| Go cookie patterns | ✅ `Secure: false`, `HttpOnly: false` |
| Rust actix-web patterns | ✅ `.secure(false)`, `.http_only(false)` |
| Test file confidence reduction | ✅ 0.5 confidence for test files |
| Tests | ✅ 8+ tests covering all patterns |

**Detected patterns:**
```python
# Python/Flask/Django
response.set_cookie('session', value, secure=False)
SESSION_COOKIE_SECURE = False
```

```javascript
// JavaScript/Express
res.cookie('session', value, { httpOnly: false });
res.cookie('auth', value, { sameSite: 'none' });
```

**Languages:** Python, JavaScript, TypeScript, Go, Rust, Ruby, YAML

---

### 8.12 Unvalidated Redirects ⬜

**Impact:** MEDIUM | **Effort:** LOW

Open redirect vulnerabilities:

```python
# Python
return redirect(request.args.get('next'))
return redirect(request.GET['url'])
```

```javascript
// JavaScript
res.redirect(req.query.redirect);
window.location = userInput;
window.location.href = params.url;
```

---

### 8.13 XXE (XML External Entity) ⬜

**Impact:** HIGH | **Effort:** MEDIUM

Unsafe XML parsing:

```python
# Python
etree.parse(user_input)  # Without disabling entities
xml.etree.ElementTree.parse(user_input)
```

```java
// Java
DocumentBuilderFactory.newInstance()  // Without setFeature to disable XXE
SAXParserFactory.newInstance()  // Without secure processing
```

---

### 8.14 Weak Password Requirements ⬜

**Impact:** MEDIUM | **Effort:** LOW

Password validation that's too weak:

```python
# Python
if len(password) >= 4:  # Too short
if len(password) >= 6:  # Still weak
MIN_PASSWORD_LENGTH = 6  # Config too low
```

```javascript
// JavaScript
if (password.length >= 4)
const MIN_LENGTH = 6;
/^.{4,}$/  // Regex allows 4+ chars
```

---

### 8.15 LLM-Assisted Extraction (Future) ⬜

**Impact:** VERY HIGH | **Effort:** VERY HIGH

Use Claude to understand code semantically:

```rust
// Pseudo-implementation
async fn extract_with_llm(code: &str, file: &str) -> Vec<ExtractedClaim> {
    let prompt = format!(
        "Analyze this code for security issues. Return JSON with:\n\
         - concept_path: security concept (e.g., 'tls/cert_verification')\n\
         - predicate: what aspect (e.g., 'enabled')\n\
         - value: the value found\n\
         - confidence: 0.0-1.0\n\
         - description: why this is an issue\n\n\
         Code:\n```\n{}\n```",
        code
    );
    
    let response = claude_api.message(&prompt).await?;
    parse_claims_from_llm_response(&response)
}
```

**When to use:**
- High-value files (auth, crypto, config)
- After regex extractors find nothing
- For code review mode (not CI)

**Considerations:**
- Cost per scan
- Latency
- Rate limits
- Privacy (code leaves machine)

---

### Implementation Priority

| Phase | Extractors | Impact | Effort | Enterprise Value | Status |
|-------|------------|--------|--------|------------------|--------|
| **8.1** | High-entropy secrets | HIGH | MEDIUM | Catches real leaked secrets | ✅ |
| **8.2** | Framework-specific | HIGH | HIGH | Spring/Django/Express coverage | ⬜ |
| **8.3** | Config deep parsing | HIGH | MEDIUM | Nested YAML/JSON understanding | ⬜ |
| **8.4** | Semantic TLS | MEDIUM | MEDIUM | Catches const TLS_MIN = "1.0" | ⬜ |
| **8.5** | ORM SQL injection | MEDIUM | MEDIUM | SQLAlchemy, Django, Sequelize | ⬜ |
| **8.6** | Auth bypass | HIGH | MEDIUM | Backdoors, hardcoded creds | ✅ |
| **8.7** | Deserialization | HIGH | MEDIUM | pickle, Marshal, eval | ⬜ |
| **8.8** | Path traversal | MEDIUM | LOW | ../../../etc/passwd | ⬜ |
| **8.9** | SSRF | HIGH | MEDIUM | Internal network access | ⬜ |
| **8.10** | Security headers | MEDIUM | LOW | Missing helmet(), CSP | ⬜ |
| **8.11** | Cookie flags | MEDIUM | LOW | httpOnly, secure, sameSite | ✅ |
| **8.12** | Open redirects | MEDIUM | LOW | Phishing via redirect | ⬜ |
| **8.13** | XXE | HIGH | MEDIUM | XML entity injection | ⬜ |
| **8.14** | Weak passwords | MEDIUM | LOW | MIN_LENGTH = 4 | ⬜ |
| **8.15** | LLM extraction | VERY HIGH | VERY HIGH | Semantic understanding | ✅ (Phase 7.5) |

**MVP Complete (8.1, 8.6, 8.11):** High-impact extractors for enterprise pilots.

**Recommended order for remaining extractors:**
1. **8.3** Config deep parsing (foundational for 8.2)
2. **8.2** Framework-specific (customer-driven)
3. **8.5** ORM SQL injection (common in enterprise apps)
4. **8.7** Deserialization (critical vulnerabilities)

---

### Success Metrics

| Metric | Current | Target | How to Measure |
|--------|---------|--------|----------------|
| Detection rate (known vulns) | ~30% | >70% | Run against OWASP benchmark |
| False positive rate | Unknown | <10% | Manual review of 100 findings |
| Config file coverage | Regex only | Full parse | Structure-aware extraction |
| Framework coverage | 0 | 4 major | Spring, Django, Express, Rails |
| Enterprise pilot feedback | N/A | >4/5 | Post-pilot survey |