Public report — aspnetrun-microservices, published 3 Aug 2026.
Concrete security findings (CVE IDs, secret matches, dependency versions) are hidden in this version;
ask the repo owner for the full report.
35findings with an exact file:lineof 85 — the remainder are repo-wide signals (a dimension-level measurement, not a single line); open any file:line and verify
67/100dimensions across the health lenses9058 LoC · 22 projects — wide & deep
Executive summary
Read through the Production lens — the standard calibration. *Green* means good enough to run in production. The score is absolute and comparable across repos.
sanjyotagureddy/aspnetrun-microservices is in a workable but fragile state (60%). It is not in crisis, but it carries material risk that makes change slower and incidents harder to contain if left unaddressed.
It is strongest in Event-Driven (100%) — its messaging keeps components properly decoupled. Code Health (86%) is solid too.
The area that most needs attention is Security (50%) — exposure to security and compliance incidents is elevated. Performance (64%) is the next concern — it raises ongoing delivery and operational cost.
Leadership focus, highest impact first: Encrypt sensitive data at rest (ASP.NET Core Data Protection /… (Data Protection); authorization at every handler (Access Controls); security response headers (Content-Security-Policy (Web-Security Posture).
For scale: Small (~9,058 production lines); rebuilding it from scratch would take roughly ~0.3 person-years (~1 engineer). Approximate, ±~30%.
It builds on a genuinely strong Event-Driven foundation (100%); the priorities above are the highest-leverage way to bring the rest up to that level.
How the score is built — each lens's share of the headlineWidth is the lens's weight in the worst-heaviest fold (the weakest area pulls hardest); colour is that lens's own band. A lens fixes the score in proportion to its width.
D31 · Medium IaC: CKV_DOCKER_2 src/Services/Product/Products.Api/Dockerfile
D31 · Medium IaC: CKV_DOCKER_2 src/Services/Cart/Cart.Api/Dockerfile
D31 · Medium IaC: CKV_DOCKER_2 src/Services/Order/Order.Api/Dockerfile
D31 · Medium IaC: CKV_DOCKER_2 src/Services/Discount/Discount.Grpc/Dockerfile
D31 · Medium IaC: CKV_DOCKER_2 src/Gateway/Gateway.Yarp/Dockerfile
D31 · Medium IaC: CKV2_GHA_1 .github/workflows/codeql-analysis.yml
A full-fidelity diff against the previous run's complete recorded findings — line-move tolerant: a finding that only shifted line counts as unchanged, only genuinely new titles/files surface here.
This codebase represents roughly ~0.3 person-years of build effort (about ~€42,000 to rebuild). Its weakest lens is Security at 50% — the part of that asset most exposed by the findings below.
How we model this: boilerplate at a scaffolding rate + logic × domain Very high (×2.1) — microservices, DDD/clean architecture, CQRS, event-driven integration, high decision density × a 0.8× quality factor, at €60–95/h; indicative, ±~30%. Indicative only — most sensitive to the hourly rate and the domain tier (both tunable in config).
Top priorities
The highest-leverage moves; the full ranked list is in the Roadmap below.
1
Resolve the 4 High finding(s) in Static Analysis (SAST) — start with codeql-analysis.yml (4).
Encrypt sensitive data at rest (ASP.NET Core Data Protection / column encryption) and manage keys in a vault. Skip if delegated to infra (Postgres TDE, KMS, etc.).
Enforce authorization at every handler — call the guard method (throw-on-violation) from each one, or adopt [Authorize] so protected-by-default is demonstrable.
Value concentrated against a weak lens · Medium · Value at risk
This is a Small asset (~0.3 person-years to rebuild), and its weakest lens is Security at 50%. The operational and business risk on an asset this size concentrates there — that's where remediation buys the most protection.
→ Direct remediation budget at Security first — highest risk-reduction per euro on an asset this size.
Highest-leverage move · Medium · Leverage
Of everything flagged, the best return on effort is: Encrypt sensitive data at rest (ASP.NET Core Data Protection / column encryption) and manage keys in a vault. Skip if delegated to infra (Postgres TDE, KMS, etc.). The rest can wait behind it.
Evidence: priority ranking: top of 5 ranked by impact/effort
→ Encrypt sensitive data at rest (ASP.NET Core Data Protection / column encryption) and manage keys in a vault. Skip if delegated to infra (Postgres TDE, KMS, etc.).
Architecture — module dependency graph
Project dependencies, layered top-to-bottom; arrows show direction. Any dashed red edge points upward or sideways — a layering smell or cycle. A clean layered graph has none.
Architecture — module dependency matrix
55 modules, 88 dependencies — 2 dependency cycles, shown as the red cell(s) above the diagonal. Rows and columns are the same modules, ordered so that a module only depends on ones above it. A cell means the row depends on the column, and its number is how many type pairs create that dependency. Read one thing: is anything above the diagonal? A mark there is a dependency cycle. (A cycle is all this shows — an unusual but cycle-free dependency sits below the diagonal like any other.)
Findings mapped to OWASP categories; the specific CVEs/secrets are in the Security dimension cards below and findings.md (redacted only on the public version of this report).
OWASP category
Findings
Severity
A06:2021 — Vulnerable & Outdated Components
11
High / Critical
A05:2021 — Security Misconfiguration
11
Medium
A03:2021 — Injection
4
High / Critical
Roadmap
Begin by encrypting sensitive data at rest and managing keys in a vault, while enforcing authorization at every handler to ensure protected-by-default practices. Next, harden the web-security posture by adding critical security response headers for defense in depth. Finally, address the four high-priority static analysis findings and the nine medium-severity dependency vulnerabilities to complete the security remediation.
Ranked by impact ÷ effort. "Helps" is the estimated gain on the 0–100 health score.
Do this
Helps
Effort
Dimension
Resolve the 4 High finding(s) in Static Analysis (SAST) — start with codeql-analysis.yml (4).
Encrypt sensitive data at rest (ASP.NET Core Data Protection / column encryption) and manage keys in a vault. Skip if delegated to infra (Postgres TDE, KMS, etc.).
Enforce authorization at every handler — call the guard method (throw-on-violation) from each one, or adopt [Authorize] so protected-by-default is demonstrable.
Add security response headers (Content-Security-Policy, X-Frame-Options, X-Content-Type-Options) — defense in depth, even when a reverse proxy could set them.
Add a benchmarking harness for the hot paths and run it in CI to catch regressions (for .NET, a BenchmarkDotNet project with [MemoryDiagnoser] to track allocations).
Watchdog is a deep, periodic assessment — run each sprint, monthly, or quarterly, taking the time to go wider and deeper than a quick check and surfacing in one coherent report what you'd otherwise piece together from a dozen separate tools. It scores deterministically: the same commit yields the same score, every run. 63 of 67 evaluated dimensions are computed purely by tools and static analysis (confidence 1.0); 4 documentation/naming judgement(s) are LLM-assisted and labelled advisory. Overall confidence is 0.7 — the weighted average across measured dimensions; it falls as more of the score leans on LLM-assisted judgement and rises when it's fully tool-backed.
Every figure here is one of three kinds, and we label which: ✓ Measured — a deterministic fact (LoC, complexity, coverage); ~ Modeled — an estimate from a stated model (cost, effort, value-at-risk), always a range with its assumptions, never a precise fact; ◐ Advisory — an LLM prose judgement. We never present a modelled estimate as if it were measured. Perfect or absent scores carry their provenance too (ADR-0011): ✓ Tool-verified means the property itself was measured across the surface; ○ Nothing flagged means the probes came back clean — a claim bounded by what a repository can show; ⊘ Not evidenced means a working control (a tested restore, an automated rollback) showed no positive evidence — absence of evidence is not evidence of a control, so it's excluded from the score rather than awarded a spurious 10; ◐ Sampled · advisory marks an LLM verdict over a bounded sample — advisory, never a deterministic measurement.
What we checked — 67 dimensions across the health lenses
Each chip is a dimension scored from real signals across architecture, testing, dependencies, security & compliance, documentation, git-history and code quality — in one coherent pass. A surface report typically covers a handful.
How to trust any code-health report — three questions
Can you open the finding? Real findings cite a repo-relative file and line you can open at the cited line — never an absolute scratch path. Here, 35 of 85 do; the remainder are repo-wide signals — a dimension-level measurement, not a single line. (Every path in this report is repo-relative by construction: paths are normalized at the producer and the report is rejected if any rooted path leaks through.)
Is there a tool behind the number? Every score below names the method that produced it — Roslyn, git, a scanner, or (for a handful of documentation/naming dimensions) an LLM labelled sampled · advisory — not a narrative.
Does re-running give the same result? Run it again on the same commit and the score — and this report, byte for byte — is identical. A report whose numbers move between runs is describing the run, not the code.
This report answers yes to all three. That's the bar to hold any assessment to.
Tools & methods
The actual versions used this run (captured at analysis time) — re-run on the same commit for the identical score.
Method
Backs
Version
Evaluator
Roslyn static analysis
Complexity, cohesion, coupling, dead code, API surface, layering
What ran differently this time — a tool absent, degraded, or that fell back to an estimate. Named openly, not folded silently into the scores. A degraded run also records its exact cause in diagnostics.md.
D19 Documentation Quality — LLM provider failed — The model provider returned an unusable result, so this LLM-assisted dimension fell back to a measurement gap (confidence 0) rather than a penalty. Re-run with a reachable provider to score it.
Repo exclusion declarations (.gitattributes linguist-generated/vendored, .editorconfig generated_code): none declared — every source file was scored.
Limitations & what we did not check
Watchdog assesses the repository exactly as committed, and only the repository. By design it does not reach outside the source tree: the live cloud account, the running CI/CD pipeline, the host's branch-protection and approval rules, the production configuration, or a restore actually exercised against a backup are all out of scope. That boundary is a feature, not a gap — a repo-relative, deterministic scan re-runs identically on any commit and every finding opens at a real file and line, where a live audit can neither be reproduced nor traced. The visible consequence is that controls which leave no in-repo evidence are reported as "not evidenced" and excluded from the score rather than awarded a number a static scan cannot justify.
Per-dimension blind spots
For each dimension that was measured, what a static, repo-only scan structurally cannot see — the honest edge of the measurement, not a failure of it.
D1 Cyclomatic Complexity: Cyclomatic complexity counts branches statically — it cannot tell an essential decision tree from accidental tangle, nor see complexity that lives in data or configuration (large switch-case token tables, DSL lexers/parsers, data-as-code rule tables) rather than control flow: a tokenizer's many single-character cases read as high complexity though each branch is trivial.
D2 Cognitive Complexity: Cognitive-complexity heuristics approximate how hard code is to follow; genuine domain difficulty and well-named intent that eases reading are not captured.
D3 God Classes: "God class" is sized by members and responsibilities visible in the type — a deliberately broad facade over a coherent subsystem can read the same as an accidental grab-bag. For front-end JS the file-length check is cohesion-aware (a single-responsibility module — one class/IIFE — earns a 3× threshold), but cohesion is approximated from top-level declarations, not true dependency structure.
D4 Code Duplication: Duplication is token-similarity (jscpd) — it finds copy-paste, not semantic duplication expressed differently. Committed machine-written code (scaffolded migrations, designer/codegen output, protobuf/OpenAPI stubs, model snapshots) is EXCLUDED — its repetition is the tool's, not the team's — so the score reflects hand-written duplication only.
D5 Coupling: Coupling is measured between projects/assemblies — runtime coupling through DI, reflection, messaging or shared databases is invisible to a static reference graph.
D6 Cohesion (LCOM4): LCOM4 cohesion is syntactic — it infers connectivity from which methods touch which fields/methods by name, not from real runtime behaviour or intent.
D7 Architectural Integrity: Layering is checked against detected/declared rules — an architecture whose boundaries live in convention or in code review, not in a rule a scanner can read, is not enforced here.
D9 Test Distribution: The test-pyramid shape is inferred from project/folder naming and references, with a single test host bucketed per-file by its path tier and content signals — a suite that names tiers unconventionally and gives no per-file signal can still be mis-bucketed.
D10 Test Quality: Assertion density is structural — it cannot tell a meaningful behavioural assertion from a trivial one, only that an assertion is present.
D12 Dependency Hygiene: Dependency health reads manifests and lockfiles — a vulnerability in a vendored/copied dependency, or risk from how a dependency is actually used, is outside this view.
D13 Secret Scanning: Secret detection is signature- and entropy-based on the current tree — a secret that does not match a known pattern, or one already rotated, will not be flagged (a clean scan is "nothing matched", not "no secrets exist").
D14 License Compliance: License compatibility is checked against declared package metadata and a policy — mislabelled or missing license metadata, and obligations that depend on how you distribute, are not resolved here.
D15 Churn × Complexity Hotspots: Churn hotspots come from git history — a freshly imported or squashed repository has no churn signal, and recent rewrites can mask a historically risky file.
D16 Bus Factor: Bus-factor is a time-decayed model of commit attribution (who has recently, repeatedly worked a file), not comprehension — pairing, review and reading-without-committing spread knowledge it can't see; bot commits and shared accounts still distort it.
D17 Explicit Debt: Acknowledged-debt signals (TODO/FIXME, suppressions, dead code) are textual — undocumented debt that nobody marked, and debt that lives in design rather than annotations, is invisible. Committed machine-written code (scaffolded migrations, designer/codegen output, generated stubs) is excluded — it is never the team's dead code to delete.
D18 Solution Shape: Build integrity reflects whether the solution compiled in this environment — a build that needs a private feed, a specific SDK, or a generated file absent from the repo can read as broken when it is merely unreproducible here.
D20 ADR Quality: ADR quality is an LLM read of the decision records present — it cannot know about decisions made and never recorded, and its verdict is sampled and advisory.
D21 Naming Consistency: Naming quality is an LLM judgement over a bounded sample — it assesses clarity/consistency of the names it sees, not domain-correctness, and is advisory.
D24 Comment Value: Comment value (WHY vs WHAT) is an LLM judgement over a bounded sample — it is advisory and cannot weigh a comment against the precise code change it was written to explain.
D25 ADR Conformance: ADR conformance is the LLM-scored fraction of sampled code that follows recorded decisions — it checks the decisions that were written down and the slices it sampled, not unrecorded rules or the whole tree.
D26 Project Cohesion: Project focus is sized from members/namespaces per project — a project that is broad by deliberate design reads the same as one that has sprawled.
D27 Navigability: Indirection/navigability is structural — it measures hops to follow a call, not whether that indirection buys real flexibility or just ceremony.
D28 Secrets (history): Secret-history scanning sweeps the git log for known patterns — a secret that predates the available history, or never matched a signature, is not found (clean means "nothing matched in the history we can see").
D29 Static Analysis (SAST): SAST findings are pattern-based (semgrep) — it finds classes of bug it has rules for; logic flaws, auth/authorization gaps and issues needing runtime context are out of reach (and clean means "no rule matched").
D30 Dependency Vulnerabilities: CVE matching depends on accurate package/version metadata and the advisory database — a vulnerability with no published advisory, or in code not declared as a dependency, is not seen.
D31 IaC & Container Security: IaC scanning checks Dockerfiles/Terraform/Kubernetes against best-practice rules — it cannot see the live cloud account, runtime configuration, or drift between the committed config and what is actually deployed.
D34 Knowledge Freshness: Freshness is decayed commit RECENCY, not comprehension — code read often but rarely committed reads as orphaned, and stable code that genuinely needs no changes is penalised the same as forgotten code; bot/squash commits distort it like the bus factor.
D35 Change Coupling: Change coupling is co-change in COMMITS — files split across separate commits, or coupled only through a shared config/build step, read as uncoupled, and a sweeping commit (rename/format) is excluded so it doesn't couple everything. It shows that files change together, not WHY: a high coupling can be a healthy cohesive pair as readily as a hidden leak.
AX10 Code composition: Role is inferred from namespace/folder convention, not semantics — a domain concept living in a folder named "Services" reads as application, and the split is lines-of-code, not business value. The business-logic-share score is a SOFT, FLOORED signal: it contributes to the Architecture lens but is floored at the Critical gate, so an infrastructure-heavy design (a gateway, an ETL, a driver) is legitimately low without being nuked to zero.
AX9 CQS / query purity: Handlers are found by interface/name convention — a query handler using neither is not seen. Mutation is a resolved write/publish invocation (SaveChanges/repository/bus), so a write hidden behind a hand-rolled wrapper, reflection, or a string-keyed service locator resolves to a non-persistence type and isn't flagged; it detects that a query writes state, not whether the write is a legitimate read-side cache update. Clean means "no resolved write/publish in a query body", not a proof of CQS purity.
C4 Data Retention: This control is scored from in-repo evidence only — its real-world effectiveness, exercised only at runtime, is outside a static scan.
ED5 Idempotency: Idempotency is judged from the handler body's visible writes and guards — a guard enforced by a database unique constraint, a broker's exactly-once delivery, or a domain method whose no-op-when-applied logic the scan can't follow may read as at-risk; the at-risk candidates are confirmed by a SAMPLED LLM verdict (advisory, not exhaustive) and degrade to heuristic-only when no model is configured. It flags the at-least-once double-apply SHAPE, not a runtime proof of a duplicate effect.
M4 Documentation accuracy: Onboarding quality is an LLM read of the docs/setup present — it cannot run the onboarding or measure how long a real new joiner takes; the verdict is sampled and advisory.
P4 Deployment & Rollback: Approval/branch-protection rules live in repository settings the scan cannot see — only their in-repo evidence (config files, workflows) is checked, so a control enforced purely in the host's settings reads as "not evidenced".
The LLM boundary
LLM-set scores this run (6): D20, D21, D24, D25, ED5, M4 (model: Local LLM). For these, a model reads a bounded sample and sets the numeric score (documentation, ADR quality, naming, comment value, onboarding) — D25 sets the ADR-conformance fraction over sampled code, D22 judges API accuracy over a sample. These are sampled and advisory by design: they vary at the margins between runs and are never a deterministic measurement. Every other score in this report is tool-computed at confidence 1.0.
What it measures: How tangled the control flow is — methods with many branches are hard to test and change.
Method: Cyclomatic complexity per method (1 + decision points), computed exhaustively across production source; test projects separated by convention. Deterministic.
What it measures: How hard the code is for a person to follow, beyond raw branching.
Method: Cognitive complexity per method (Sonar-style nesting-penalized score), computed exhaustively over production code, excluding test projects. Deterministic.
Resolve the 1 RequestLoggingMiddlewareBase.InvokeAsync (cognitive 34) finding(s) in Cognitive Complexity — start with RequestLoggingMiddlewareBase.cs. — One of this dimension's main actionable groups (1 warning-level).
Resolve the 1 DefaultPayloadMaskingEngine.Traverse (cognitive 24) finding(s) in Cognitive Complexity — start with DefaultPayloadMaskingEngine.cs. — One of this dimension's main actionable groups (1 warning-level).
Resolve the 1 MessagingConfigurationValidationHostedService.Validate (cognitive 21) finding(s) in Cognitive Complexity — start with MessagingConfigurationValidationHostedService.cs. — One of this dimension's main actionable groups (1 warning-level).
Detailed fixes: d2_recommendation.md · top locations in Appendix A, every location in findings.md.
Do you agree with this assessment?
D3 · God Classes10.0 / 10Exemplary✓ Tool-verified
What it measures: Over-large classes that try to do too much ("god classes").
Method: God-class detection by line and method-count thresholds per logical type (partial classes unified), filtered for generated code and registration/contract false positives. Deterministic.
What it measures: Copy-pasted code that should be shared instead.
Method: Code duplication via token-stream sliding windows with type-aware normalization (locals masked, type names preserved), density-scored per KLoC of production code. Deterministic.
+ 2 more group(s) — more in Appendix A; the complete list is findings.md.
✓ On the Gold path — maintain.
Detailed fixes: d4_recommendation.md · top locations in Appendix A, every location in findings.md.
Do you agree with this assessment?
D5 · Coupling9.6 / 10Exemplary✓ Tool-verified
What it measures: Whether volatile projects sit underneath others that depend on them (so their churn ripples upward), and whether project dependencies form cycles. A widely-depended-on but stable shared/kernel project is healthy, not penalised.
Method: Dependency cycles via elementary-DFS over real .csproj references, plus Martin instability (afferent/efferent) per project. Exhaustive over the reference graph, deterministic.
Coverage: Exhaustive · type-level: afferent/efferent coupling + cycles computed over every production type — the population is all types, not a name convention.
What it measures: Whether a class's methods are focused on a single responsibility.
Method: LCOM4 cohesion per production class with at least two methods: connected components of methods sharing state or calls, computed syntactically. Deterministic, not a proxy.
Coverage: Exhaustive · type-level: LCOM4 cohesion computed over every production class — the population is all types, not a name convention.
What it measures: Whether the code respects its intended layering / architecture rules.
Method: Enforcement rung (Prevented/Verified/Documented) per checkable ADR via Roslyn, plus dependency cycles via the engine shared with D5/AX3. Deterministic, exact.
Of 3 mechanizable ADRs, 3 are prevented by analyzers, 0 by tests, 0 exist only in prose. Coverage: 100 %. Cycles found: 0.
✓ On the Gold path — maintain.
Detailed fixes: d7_recommendation.md.
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D9 · Test Distribution10.0 / 10Exemplary✓ Tool-verified
What it measures: Whether the test suite has a healthy mix of unit / integration / end-to-end tests.
Method: Test projects classified (Unit/Integration/BDD/E2E) from compiled metadata; test methods counted exhaustively across projects with placement-agnostic disk fallback. Deterministic.
167 test methods: 153 unit, 14 integration, 0 BDD, 0 e2e.
✓ On the Gold path — maintain.
Detailed fixes: d9_recommendation.md.
Do you agree with this assessment?
D10 · Test Quality10.0 / 10Exemplary✓ Tool-verified
What it measures: Whether the tests truly assert behaviour rather than just running the code.
Method: Per-test assertions, skips, and mock references analyzed via Roslyn; structured skip-reason tags (BUG:/ENV:) separate documented deferrals from debt. Deterministic.
What it measures: Whether dependencies are current, secure, and not bloated.
Method: Manifest scan via dotnet list package across all projects; worst-signal-per-package deduction (saturating for vulnerabilities, capped-linear for deprecation/outdated) per KLoC. Exhaustive, deterministic.
Resolve the 1 Vulnerable finding(s) in Dependency Hygiene. — One of this dimension's main actionable groups (1 issue-level).
Enforce Dependency Hygiene in CI to reach Verified (currently Documented). — Hardens enforcement from Documented toward Verified — provenance only; does not change the score.
Detailed fixes: d12_recommendation.md · top locations in Appendix A, every location in findings.md.
What it measures: Whether any secrets (keys, tokens, passwords) have leaked into the code.
Method: In-process native secret scanner (entropy plus signature patterns) across all tracked files; no external tool. A clean result is a measured 10, not no-data zero. Deterministic.
What it measures: Whether the licenses of third-party packages are compatible with your policy.
Method: Third-party package licenses resolved from declared package metadata and checked against the configured policy (allow/deny/copyleft). Deterministic; clean = no incompatible license found at metadata depth.
What it measures: Files that change often and are also complex — the riskiest hotspots.
Method: Per production file churn times cyclomatic complexity over a rolling window, computed from git and Roslyn/JS/Razor analysis. Exhaustive, deterministic per commit date.
Detailed fixes: d15_recommendation.md · top locations in Appendix A, every location in findings.md.
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D16 · Bus Factor9.0 / 10Strong✓ Tool-verified
What it measures: Whether knowledge is concentrated in too few people (the "bus factor").
Method: Living knowledge per author via time-decayed commit attribution (6-month half-life, focus weighting) across largest source files. Deterministic, avoids blame's mechanical-refactor false positives.
16 source file(s) have their living knowledge concentrated in one author (≥90% of recent, decayed contribution). The largest is src/Shared/Common.SharedKernel.Logging/Middleware/RequestLoggingMiddlewareBase.cs.
Small-team knowledge concentration
What to do
Resolve the 1 Small-team knowledge concentration finding(s) in Bus Factor. — One of this dimension's main actionable groups (1 recommendation-level).
Detailed fixes: d16_recommendation.md · top locations in Appendix A, every location in findings.md.
What it measures: Acknowledged debt left in the code — TODOs, dead code, suppressed warnings.
Method: Roslyn syntactic debt markers (suppressions/TODO/FIXME/HACK/empty-catch/commented-code/Obsolete) plus SymbolFinder dead-code analysis; weighted-debt-per-KLoC density deducted 2.0x per unit. Deterministic, exhaustive.
0 deducted debt markers + 2 dead symbols across 9058 LoC (0.0/KLoC) → score 9.9.
Dead code: ToReadOnlyDictionary · ×2src/Shared/Common.SharedKernel.Logging/Abstractions/LogEnrichmentContext.cs:54
✓ On the Gold path — maintain.
Detailed fixes: d17_recommendation.md · top locations in Appendix A, every location in findings.md.
Do you agree with this assessment?
D18 · Solution Shape8.7 / 10Strong✓ Tool-verified
What it measures: Whether the solution is laid out in a sensible, conventional structure.
Method: Solution structure: project count, decomposition, shell-project detection, build success (confirmed failures cap the score); traced to actual .sln files and binaries. Deterministic.
22 projects, 326 source files, 13498 hand-written lines of code (9058 production / 4440 test), 52 inter-project edges.
Thin analysable surface across projects
What to do
Resolve the 1 Thin analysable surface across projects finding(s) in Solution Shape. — One of this dimension's main actionable groups (1 recommendation-level).
Detailed fixes: d18_recommendation.md · top locations in Appendix A, every location in findings.md.
Do you agree with this assessment?
D20 · ADR Quality / 10Strong◐ Sampled · advisory
What it measures: Whether architecture decisions are recorded well (context, decision, consequences).
Method: Per-ADR judgment by language model at low temperature with two-pass stability; confidence is share of ADRs evaluated; enforcement-field presence detected deterministically. Advisory.
Evaluated 4 ADR(s) individually; mean quality 8.5/10 (consistently complete and clear). 0 flagged with a specific gap.
What to do
Improve ADR Quality — currently 8.5/10. — Evaluated 4 ADR(s) individually; mean quality 8.5/10 (consistently complete and clear). 0 flagged with a specific gap.
What it measures: Whether names — types, methods, variables — are clear and consistent.
Method: Judged by language model at low temperature (0.0-0.1) on a deterministic random symbol sample (fixed size, not exhaustive), with disclosed confidence band. Advisory, sampled.
0 naming inconsistencies across 200 sampled symbols.
✓ On the Gold path — maintain.
Detailed fixes: d21_recommendation.md.
Do you agree with this assessment?
D24 · Comment Value / 10Strong◐ Sampled · advisory
What it measures: Whether comments are worth it — explaining WHY (valuable) rather than WHAT (redundant).
Method: Judged by language model at low temperature (0.0-0.1) on deterministically sampled inline comments with surrounding code; findings verified back to sampled comments by substring match. Advisory, sampled.
What it measures: Whether the code actually follows the decisions recorded in the project's ADRs.
Method: Judged by language model at low temperature against ADRs plus a deterministic structural code summary; findings linked to repo-rooted ADR paths for traceability. Advisory.
What it measures: How far you must trace to follow a call — low indirection and co-located slices read easier.
Method: Call indirection (interface hops, cross-namespace calls, slice-locality scaled) over a sampled set of method invocations, size-aware baseline. Sampled; confidence discounted by symbol-resolution gaps.
Coverage: Slice locality from the first namespace segments, SAMPLED (≤400 methods) — not exhaustive.
74 % of calls cross a namespace and 5 % go through an interface, but 100 % of collaborators are co-located — so a call's collaborators sit together and tracing stays easy. Baseline: small — navigation cost is tolerated.
What it measures: Whether any secrets were ever committed — scanned across the full git history, not just now.
Method: Git-history secret scan via gitleaks detect over full history in an isolated checkout; each match flagged High. Exhaustive; degrades cleanly when tool absent.
What it measures: Real static-analysis (SAST) findings — likely security bugs in the code, any language.
Method: Polyglot static analysis via semgrep across the repo using the pinned, image-baked p/security-audit + p/owasp-top-ten rulesets (no scan-time registry fetch); severity rules (ERROR/WARNING/INFO) map to a full-band severity-weighted score. Exhaustive, deterministic; degrades on parse failure.
Coverage: semgrep pattern rules over all files — exhaustive for the rule set, blind to classes of bug without a rule (clean = no rule matched).
High: github-actions-mutable-action-tag · ×4.github/workflows/codeql-analysis.yml:41detected by semgrep finding
What to do
Resolve the 4 High finding(s) in Static Analysis (SAST) — start with codeql-analysis.yml (4). — One of this dimension's main actionable groups (4 issue-level).
Detailed fixes: d29_recommendation.md · top locations in Appendix A, every location in findings.md.
What it measures: Whether any dependencies have known published vulnerabilities (CVEs), direct or transitive.
Method: NuGet CVE scan via dotnet list package --vulnerable including transitive; severity tally (Critical/High/Medium/Low) to 0-10 tight normalizer. Exhaustive, deterministic; degrades when absent.
What it measures: Whether anyone still has living knowledge of each file, or it has been orphaned — last understood long ago by someone now gone quiet. The sibling of the bus factor: D16 asks who owns it, D34 asks whether anyone still knows it.
Method: File orphaning as total living-knowledge decay below one focused-commit's worth within a year, computed per-file from the D16 decay model. Exhaustive, deterministic over fixed history.
What it measures: Whether files that change together actually belong together — pairs that repeatedly co-change in git history despite having no explicit code dependency, surfacing the hidden/logical coupling (and boundaries in the wrong place) a static scan can't see.
Method: Pairwise co-occurrence over the per-commit file sets in git history (production source only — tests and generated dropped): Degree-of-Coupling = shared ÷ min individual revisions, reported above noise floors (each file ≥10 revisions, ≥5 shared commits, ≥50% strength); sweeping commits excluded. Deterministic over fixed history.
Coverage: Population: PRODUCTION source files only — test and generated files are dropped before pairing, so a class co-changing with its own test (trivially ~100%) can't drown the real production↔production coupling. Pairs ranked by Degree-of-Coupling; coupling through a build step, config, or non-source file isn't seen.
No strong hidden change-coupling between production files.
✓ On the Gold path — maintain.
Detailed fixes: d35_recommendation.md.
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D39 · IL Efficiency10.0 / 10Exemplary✓ Tool-verified
Method: IL instruction count per method, read from the BUILT first-party assemblies via Mono.Cecil (the target is compiled on a deep run); scored on the fraction of methods whose emitted IL body exceeds the size threshold. Sees compiler-generated bloat source can't; not-applicable when the target fails to build. Deterministic.
Other · Architecture — Whether any singleton service captures a scoped/transient dependency — a silent lifetime/threading bug.
Method: Roslyn scan: DI registrations parsed from AddSingleton/Scoped/Transient; each singleton checked for captured shorter-lifetime dependencies. Exhaustive, deterministic.
Other · Architecture — How the codebase splits by code ROLE — domain, application, infrastructure, test, generated. The significance map behind the knowledge/coupling weighting, and a DDD signal in its own right: a thin domain core under fat infrastructure is the anemic-domain smell, quantified.
Method: Roslyn line-count by code ROLE: every source file classified Domain/Application/Infrastructure/Test/Generated by namespace + path convention (the shared CodeRoleClassifier), then significant lines summed per role. Deterministic; the advisory score is the business-logic (domain+application) share of production code.
Coverage: Population: ALL source files, each bucketed into ONE of five roles (Domain/Application/Infrastructure/Test/Generated) by namespace + path convention — a file whose layer isn't named in the convention falls to Application (the neutral default), and the split is line-count, not semantic depth or business value.
What to do
The domain core is a small share of production code — check that business logic isn't leaking into the application/infrastructure layers (a thin domain is the anemic-domain smell).
Other · Architecture — Whether singleton services avoid mutable shared instance state that concurrent callers would race on.
Method: Roslyn scan: singleton field mutations unguarded by lock or Interlocked, per type; syntax-based guard detection. Deterministic, traceable per field.
`MessagingInstrumentation` is a singleton (one shared instance) but mutates instance state outside any lock (_consumerLag; e.g. `_consumerLag` at line 42). — MessagingInstrumentation.cs:6
What to do
Keep singletons stateless or back their state with thread-safe types (Concurrent*/Immutable*); otherwise concurrent callers race.
Other · Architecture — Whether the project-reference graph is acyclic (cycles block independent build/deploy and signal eroding boundaries).
Method: Project reference cycles via elementary-DFS over real .csproj references, using the engine shared with D5/D7; cyclic versus acyclic. Exhaustive, deterministic.
Other · Architecture — Whether dependencies point inward (Domain ← Application ← Infrastructure/Web) — the clean-architecture dependency rule, checked across the project graph.
Method: Layer violations by name-segment inference (Domain/Core to Application to Infrastructure/Web) over the project-reference graph. Exhaustive over all projects, deterministic.
Other · Architecture — Whether the codebase has a recognisable, scale-appropriate structure (a named architectural style, or modular enough for its size) rather than being an ad-hoc ball of mud.
Method: Roslyn plus csproj analysis: architecture style detection (DDD, clean, vertical-slice, CQRS) and structure fitness for repo size. Deterministic.
Other · Architecture — Whether feature slices stay independent (no direct cross-slice references) — the discipline that makes vertical-slice architecture pay off.
Method: Roslyn scan (vertical-slice gated): feature slices resolved from namespaces (.Features.*, .Slices.*) or project names; cross-slice type references detected. Deterministic, traceable.
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AX8 · Test isolation10.0 / 10Exemplary✓ Tool-verified
Other · Architecture — Whether production projects stay free of references to test projects — tests may depend on production, never the reverse.
Method: Csproj graph: each production project checked for references to test projects (identified by test-framework presence, not name). Zero violations is clean. Deterministic.
Other · Architecture — Whether read (query) handlers stay side-effect-free — a query that writes persistent state or raises events breaks CQS and makes reads unsafe to retry, cache, or route to a read replica.
Method: Roslyn scan: CQRS handlers classified query-vs-command by interface (IQueryHandler/ICommandHandler/IRequestHandler<TQuery,TResult>) and name convention (*Query/Get*/Find* vs *Command); each query handler's body checked for persistent-state writes (SaveChanges/repository Add-Update) or event publishes by resolved invocation. Deterministic, type-level, exhaustive over the detected handlers.
Coverage: Population: CQRS handlers identified by IQueryHandler/ICommandHandler/IRequestHandler interface + *Query/Get*/Find*/*Command NAME convention; query purity then checked exhaustively within that set — a query handler using neither convention is invisible, and mutation is a resolved persistence/publish CALL, not full dataflow.
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C1 · Data Protection3.0 / 10Weak✓ Tool-verified
Other · Security — Whether sensitive data is encrypted at rest and in transit and keys are vaulted.
Method: Roslyn plus filesystem scan: encryption presence (EF ColumnEncryption, key-vault references, HTTPS enforcement) and key-derivation KDF detection. Deterministic.
No data-protection or encryption usage (ASP.NET Data Protection, AES, column encryption, PBKDF2) was found — sensitive data at rest may be unprotected. If TDE/KMS/vault is delegated to infrastructure, ignore.
What to do
Encrypt sensitive data at rest (ASP.NET Core Data Protection / column encryption) and manage keys in a vault. Skip if delegated to infra (Postgres TDE, KMS, etc.).
Do you agree with this assessment?
C2 · Access Controls3.0 / 10Weak✓ Tool-verified
Other · Security — Whether access is authorized by default — a framework authorization attribute/decorator or policy, or imperative guard methods (throw-on-violation) called from handlers.
Method: Roslyn scan: [Authorize] usage and authorization policies, plus imperative throw-on-violation guard methods detected via syntax. Deterministic.
Authorization machinery exists but no [Authorize] usage and no imperative guard calls were found at handlers.
What to do
Enforce authorization at every handler — call the guard method (throw-on-violation) from each one, or adopt [Authorize] so protected-by-default is demonstrable.
Do you agree with this assessment?
C4 · Data Retention7.5 / 10Strong✓ Tool-verified
Other · Security — Whether data has a defined lifetime — retention periods, TTLs, cleanup jobs (storage limitation).
Method: Roslyn scan: retention/TTL configuration presence in schema; CascadeDelete detected but not scored as retention control. Deterministic, gated by PII presence.
A retention mechanism is present, but the data-lifecycle is not yet complete — missing: a scheduled purge / cleanup job (PurgeOlderThan / CleanupJob).
What to do
Complete the data-lifecycle story: an expiry limit (a declared maximum age for the stored data — a retention-age setting, or a store-level TTL where your storage offers one), a scheduled purge/cleanup job that enforces it, and a documented retention period covering the personal data.
Other · Event-Driven — Whether event handlers stay asynchronous (no blocking remote HTTP/gRPC calls awaited inside a handler).
Method: Roslyn semantic scan (event-driven gated): event-handler bodies scanned for HTTP/gRPC invocations by resolved symbol type, not substring. Deterministic, semantic-resolved.
Other · Event-Driven — Whether commands have a single handler (one owner of the decision) and fan-out is modelled with events.
Method: Roslyn scan (event-driven gated): command-shaped messages identified by convention; handler count per command checked for the exactly-one rule. Deterministic, hard fact.
Other · Event-Driven — Whether state changes and message publishes are atomic (a transactional outbox) rather than a crash-unsafe dual write.
Method: Roslyn semantic scan (event-driven gated): event-handler methods scanned for DB-save plus bus-publish without a transactional outbox reference. Deterministic, semantic-resolved.
Other · Readiness — Whether retry-prone mutations (command handlers + message/event consumers) are idempotent so an at-least-once redelivery or client retry doesn't double-apply the effect — heuristic at-risk detection confirmed by language model, advisory.
Method: Roslyn heuristic (any mutation, ungated): command handlers and message/event consumers that mutate persistent state without a visible idempotency guard (exists/dedup check, upsert, idempotency-key/inbox, conditional/versioned write, fixed-value set) flagged as at-risk; each at-risk candidate then confirmed or cleared by a language model as genuinely non-idempotent versus naturally-idempotent. Advisory without a model (heuristic-only, degraded), per-candidate judged with one.
Coverage: Population: retry-prone mutations — command handlers (CQRS write side) + message/event consumers (IConsumer/I*EventHandler) — that mutate persistent state; runs on any repo with mutations, not only event-driven ones. The at-risk subset (no obvious guard) is a HEURISTIC candidate set, each then LLM-JUDGED non-idempotent vs safe; a handler outside those conventions, or a guard the LLM can't confirm, is bounded by the sample. Degrades to heuristic-only when no model is configured.
Other · Code Health — Unreviewed-generation residue: shipped members still throwing NotImplementedException, and placeholder string literals left in non-test, non-generated code. Scored as a quality signature, never as a claim about authorship.
Method: Roslyn syntax scan: NotImplementedException throws and placeholder string literals in non-test, non-generated shipped code. Deterministic, code-shape signature.
Other · Code Health — Unfinished work detected by code SHAPE, not keywords: members that only throw a "not implemented" exception, methods that take inputs and return a constant, async methods that never await, dead `if (false)` / `#if false` branches, and skeleton types most of whose members are holes. A real, objective slice of technical debt.
Maturity · Maturity — Whether the repo and its projects have a README, and whether it's substantive and current.
Method: Filesystem scan: README presence, word count, and headings for depth; git history for staleness. Exhaustive across root and project dirs, deterministic.
What to do
Add a README to the 20 of 22 project(s) that lack one — worth up to 1.8 pts.
Maturity · Maturity — Whether the repo is organised deliberately — src/test separation and consistent project naming.
Method: Filesystem scan: src/test folder separation and namespace-prefix consistency (majority RootNamespace agreement). Exhaustive across projects, deterministic.
Only 8/22 projects share a common root namespace — the code's module identity is inconsistent.
What to do
Adopt a consistent root-namespace convention (a shared prefix, e.g. Acme.*); short project-file/directory names are fine as long as the RootNamespace is uniform.
Maturity · Maturity — Whether the README actually describes the code that exists (LLM-judged, advisory).
Method: Judged by language model at low temperature: README accuracy versus actual projects, within a disclosed tolerance. Advisory, not a measured number.
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P1 · CI/CD gates8.5 / 10Strong✓ Tool-verified
Readiness · Readiness — Whether an automated pipeline builds and tests every change.
Method: Filesystem scan: CI workflow files (.github/workflows, .gitlab-ci.yml, etc.) for build and test stages. Exhaustive, deterministic.
A CI pipeline exists and the word "test" appears, but no explicit test-runner invocation (your stack's test command, or a test job) was matched — so either the gate runs tests through a step this pass could not recognise, or "test" is incidental here (a path, "latest", a reporter). Check the coverage dimensions first: if this repo has no test suite yet, that is the finding and this row follows from it. If a suite does exist, make the runner step explicit so the gate is unambiguous.
What to do
Run the test suite in CI via an explicit runner step for your stack, and gate merges on it.
Do you agree with this assessment?
P2 · Observability8.6 / 10Strong✓ Tool-verified
Readiness · Readiness — Whether the code is diagnosable in production — structured logging, tracing/metrics, health checks.
Only 6/11 service-like projects use logging (pure contract/DTO projects are excluded — they have nothing to log). Of those 11, 7 ship a process this repository operates; the rest are libraries their consumer hosts, where the logging decision belongs to the host.
What to do
Extend structured logging across the projects you operate, and give the library ones a diagnostics seam instead — an `EventSource`/`ActivitySource` the host can subscribe to, or an optional logger on your options object — rather than taking a logging dependency on your consumers' behalf.
Readiness · Readiness — Whether SAST, secret/dependency scanning and performance benchmarking are wired in (presence, not runtime).
Method: Filesystem scan: SAST configuration, dependency-update automation, secret scanning, and a benchmark harness or benchmark step — in this repository's own ecosystem. Exhaustive, deterministic.
What to do
Enable Dependabot/Renovate or a dependency-review gate.
Add gitleaks/trufflehog in CI to block PRs that introduce committed secrets.
Readiness · Readiness — Whether releases are automated and safely reversible (probes, rolling updates, approval gates) — from manifests/pipeline files, not the live environment.
Method: Filesystem scan: deployment manifests/IaC (K8s YAML, Helm, Terraform) for rolling updates, probes, approval gates, migration hooks. Exhaustive, deterministic.
Deployment automation exists but no readiness/liveness probes, rolling-update strategy, lifecycle hooks or migration job were evidenced — a bad release is harder to detect and reverse.
What to do
Add readiness/liveness probes and a rolling-update (or blue/green) strategy so a bad release is caught and rolled back automatically.
Readiness · Performance — Whether the library protects its performance with benchmarks — a benchmark suite, allocation/memory measurement, and (ideally) a CI gate. Presence is credited as a bonus, never a deduction.
Method: Repo + source scan: BenchmarkDotNet referenced (csproj/source), [Benchmark]/[MemoryDiagnoser] attribute counts, and a benchmark step in CI — scored as a bonus ladder (absence is neutral, never a deduction). Deterministic, presence detection.
No benchmark suite was found. Where code is performance-sensitive, a benchmark guards against silent regressions — but it's a bonus here, not a deduction.
What to do
Add a benchmarking harness for the hot paths and run it in CI to catch regressions (for .NET, a BenchmarkDotNet project with [MemoryDiagnoser] to track allocations).
Readiness · Performance — Whether the code is written to minimise allocations so it doesn't pressure its host's memory manager — buffer/slice views over copies, object pooling, stack or value-type allocation, and buffer writers. Reward-only: credited where present, never penalised where a simpler style is fine.
Raise allocation-aware density on the hot paths — currently 34 use(s) across 9,815 production line(s) (~3.5/1k). More Span/Memory, pooling (ArrayPool/ObjectPool), stackalloc and ValueTask on the allocation-heavy paths climbs this toward 10.
Readiness · Performance — Whether asynchronous code keeps its host responsive — a library awaits with ConfigureAwait(false) (so it never captures and stalls the host's context) and avoids sync-over-async blocking (.Wait()/.GetAwaiter().GetResult()) that wastes threads and risks deadlock.
Method: Production-source scan: sync-over-async blocking (.Wait()/.GetAwaiter().GetResult()) counted everywhere, and — for a library with ≥5 awaits — the share of awaits using ConfigureAwait(false). Deterministic, syntax/text detection.
7 blocking call(s) on async work (.Wait()/.GetAwaiter().GetResult()) — these waste a thread and can deadlock in a consumer with a synchronization context.
What to do
Make the call chain async end-to-end and await it — never block on a Task with .Wait()/.GetAwaiter().GetResult() in library code.
Other · Security — Transport security, security headers, secure cookies, input validation, middleware order and crypto hygiene (presence, not runtime).
No Content-Security-Policy / X-Frame-Options / X-Content-Type-Options configuration found — defense in depth, even when a reverse proxy could set them. (−2.0 on this card.)
What to do
Add security response headers (Content-Security-Policy, X-Frame-Options, X-Content-Type-Options) — defense in depth, even when a reverse proxy could set them.
Other · Code Health — Whether the code avoids sync-over-async (deadlock-prone blocking on tasks) and async void.
Method: Roslyn syntax scan: async methods scanned for .Wait()/.GetAwaiter().GetResult() and async-void outside event handlers. Deterministic, hard fact per invocation.
Blocking on a Task with `.Wait()`/`.GetAwaiter().GetResult()` can deadlock (and wastes a thread). Prefer awaiting it: make the caller `async` and `await` instead. Where a synchronous entry point must stay — a public sync API you cannot break, or a process entry point that must not return until the work finishes — the block belongs in ONE documented bridge and never inside code that is already async; and where it already is that bridge, give the wait a TIMEOUT so a hung task fails the call instead of hanging the process. (×7) — ILogger.cs:14, ILogger.cs:17, ILogger.cs:20, …
Other · Code Health — Whether async methods accept a CancellationToken so work can be cancelled (adoption curve).
Method: Roslyn scan: every async method (excluding framework-fixed overrides/Blazor handlers) checked for CancellationToken parameter presence. Deterministic, adoption percentage.
Only 77/83 async methods accept a CancellationToken, so in-flight work can't be stopped early when the caller gives up — whatever ends it in your host (shutdown signal, timeout, abandoned request, user cancel). Thread a token through the call chain and honour it at each await and loop; where a method genuinely cannot be interrupted, omitting it is a deliberate choice — judge against your hosting model.
No CancellationToken parameter — the body observes an ambient token instead (a field or a context object), so the work does stop on cancellation, but a caller cannot cancel this call independently of the owner that created that token. (×3) — RequestLoggingMiddlewareBase.cs:17, RequestLoggingMiddlewareBase.cs:338, RequestLoggingMiddlewareBase.cs:382
No CancellationToken parameter — this work can't be stopped early once started. (×3) — RequestLoggingMiddlewareBase.cs:420, KafkaDestinationProvisioner.cs:171, AppCallContextMiddlewareBase.cs:16
What to do
Thread a CancellationToken through async methods so work stops promptly on cancellation.
Other · Code Health — Whether exceptions are handled rather than silently swallowed or rethrown with lost stack traces.
Method: Roslyn syntax scan: every catch clause counted; empty catches and bare rethrows flagged. Population is all catch clauses, not estimated. Deterministic, hard fact.
Other · Code Health — Whether log calls use message templates (queryable) rather than interpolated strings.
Method: Roslyn syntax scan: every log call-site counted; interpolated-string first-argument violations flagged. Population is all log calls, not estimated. Deterministic.
Other · Code Health — Whether nullable reference types are enabled and not undermined by heavy `!` suppression.
Method: Roslyn compiler-options scan: NullableContextOptions per project; null-forgiving (!) suppression density per 1k syntax nodes. Deterministic, adoption plus suppression penalty.
~0.2 `!` suppressions per 1k syntax nodes — 9 suppression(s) across the 45961 syntax node(s) in code where nullable warnings are ENABLED, which is the only code a `!` can suppress anything in (a `!` under `#nullable disable` is inert and is not counted, and its file's nodes are not in the denominator). Each one tells the compiler to trust you about null, suppressing the very safety NRTs provide.
What to do
Enable <Nullable>enable</Nullable> across all projects and resolve warnings rather than suppressing with `!`.
Do you agree with this assessment?
Reference — by lens
The score is the rank-weighted fold of these lenses (worst-heaviest), each including its meta-dimensions; a lens with a Critical contributor is capped at Fair (its band reads "gated by …") and is never the strongest area however high its average.
Not included — 33 check(s) not relevant to this codebase
These checks had nothing to measure here (no tests, no git history, the codebase is small, or the architecture style doesn't apply), so they're omitted above rather than scored low.
AC1 Text alternatives — No web markup found — accessibility is not applicable to this repository.
AC2 Forms & labels — No web markup found — accessibility is not applicable to this repository.
AC3 Page structure — No web markup found — accessibility is not applicable to this repository.
AC4 Keyboard semantics — No web markup found — accessibility is not applicable to this repository.
AC5 ARIA correctness — No web markup found — accessibility is not applicable to this repository.
AC6 Visual & motion safety — No web markup found — accessibility is not applicable to this repository.
AC7 A11y enforcement — No web markup found — accessibility is not applicable to this repository.
AXB2 Runtime readiness — Advisory — this card reports evidence and never carries a score, so there is nothing missing here.
C3 Audit Trail — Repo shows no audit-logging mechanism (IAuditable, an immutable audit log, an EF SaveChanges interceptor) for sensitive changes — absence of evidence is not evidence of a working control. Record an audit trail in code (or document where it lives) so this dimension can be scored.
C5 Data-Subject Rights — Repo shows no corroborated data-subject-rights mechanism (erasure / export-portability / consent) tied to a subject id or GDPR vocabulary — absence of evidence is not evidence of a working control. Implement erasure, data export/portability and consent tracking over the subject's records.
D11 Test Reliability — Test reliability not measured — no test run produced results
D19 Documentation Quality — LLM evaluation failed
D22 Internal API Consistency — No exposed public API
D23 Boundary Type-Coupling — Bounded contexts not declared
D32 Data Compliance (PII/GDPR) — No PII/GDPR-handling patterns detected (p/gdpr ruleset) — no data-compliance surface to assess.
D33 JS/npm Dependency Vulnerabilities — No JS/npm manifest or lockfile found outside build output (package.json, package-lock.json, yarn.lock, pnpm-lock.yaml, bun.lockb); no JS dependencies to scan.
D36 Supply-chain Provenance & Signing — The CI pipeline builds and tests but publishes no released artifact — no package publish, container push, GitHub release or deployment step. Supply-chain provenance, signing and SBOM attest RELEASED artifacts, so there is nothing to attest here. Add them to the release pipeline when this repo starts shipping artifacts (a published package, a container image, a deployed service or a tagged release).
D37 Vulnerability-disclosure Policy — No vulnerability-disclosure policy file found (SECURITY.md/.markdown/.rst/.txt at root or under .github/.forgejo/.gitea/docs, .well-known/security.txt). A coordinated-disclosure policy may live off-repo, so this is not evidenced rather than failed.
D38 OSV Dependency Vulnerabilities — No supported non-.NET dependency lockfile found outside build output (npm package-lock/yarn/pnpm/bun, Go go.mod, Rust Cargo.lock, Maven pom.xml, Gradle lockfiles, Python requirements.txt/poetry.lock/Pipfile.lock/pdm.lock, PHP composer.lock, Ruby Gemfile.lock, Elixir mix.lock, Dart pubspec.lock, Swift Package.resolved); nothing for OSV to scan. A NuGet-only repo stays NotApplicable — .NET CVEs are D30's domain.
D40 Network Egress Confinement — No Kubernetes/orchestration workloads found in the repository manifests; network egress policy is a cluster-native control that may live at the platform/firewall layer, so there is nothing to assess here.
D41 Kernel & Syscall Confinement — No Kubernetes/orchestration workloads found in the repository manifests; seccomp/AppArmor/SELinux confinement is a workload-level control, so there is nothing to assess here.
D42 Runtime Threat Enforcement — No Kubernetes/orchestration workloads found in the repository manifests; runtime threat-detection and admission-control policy are cluster-level controls, so there is nothing to assess here.
D8 Code Coverage — Coverage not measured
DM1 Domain Modelling — applicable but not scored (2 of 3 signals for this style — below the bar we score at): 5 domain event(s); a Domain/Aggregates/ValueObjects layer
ES1 Event Sourcing — not scored — this repository shows none of the 3 signals this check looks for
P12 CI test-gate honesty — Reported, not scored — this card publishes what the CI gate does with the test inventory rather than grading it. The findings above are its output.
P5 DR & Backup — not evidenced — repo shows no backup/RTO/RPO controls; absence of evidence is not evidence of a working control
P6 Release Hygiene — not evidenced — no changelog, version stamp or semver release tag in the repo
P8 Schema migrations — no EF Core usage detected
P9 Domain vs controller coverage — no coverage report found on disk — produce a coverage report in a standard format (Cobertura — `dotnet test --collect:"XPlat Code Coverage"` with a `coverlet.collector` PackageReference) into the repo working tree before the scan — a CI step is the usual place, since the artefact is commonly gitignored, or wire coverage collection into CI, to enable this cross-layer check
SC1 Supply-chain hygiene — Advisory — this card reports evidence and never carries a score, so there is nothing missing here.
X6 Hand-rolled structured-format parsing — Reported, not scored — this card publishes what it found rather than grading it. Its content is the findings and the key metric above.
X7 Silent fallback defaults — Reported, not scored — this card publishes what it found rather than grading it. Its content is the findings and the key metric above.
Appendix A — Findings (grouped)
The findings behind the scores, grouped by severity, then by dimension and kind. The high-severity issues are enumerated in full below; items per group are capped at 25 with any overflow stated explicitly per group, never silently truncated. The complete machine-readable list of every finding (all severities) is the companion findings.md in this report's bundle.
High: github-actions-mutable-action-tag .github/workflows/codeql-analysis.yml:41— GitHub Actions step uses a mutable tag or branch reference. Tags and branch names can be silently repointed by the action owner, enabling supply-chain attacks — as seen in the trivy-action and kics-github-action compromises. Pin the reference to a full 40-character commit SHA instead, e.g. `uses: actions/checkout@<40-character SHA>`. This step references `actions/checkout@v3`; resolve the SHA it points at today with `gh api repos/actions/checkout/commits/v3 --jq .sha`.
High: github-actions-mutable-action-tag .github/workflows/codeql-analysis.yml:45— GitHub Actions step uses a mutable tag or branch reference. Tags and branch names can be silently repointed by the action owner, enabling supply-chain attacks — as seen in the trivy-action and kics-github-action compromises. Pin the reference to a full 40-character commit SHA instead, e.g. `uses: github/codeql-action/init@<40-character SHA>`. This step references `github/codeql-action/init@v2`; resolve the SHA it points at today with `gh api repos/github/codeql-action/commits/v2 --jq .sha`. `github/codeql-action/init` is hosted INSIDE the `github/codeql-action` repository (a subdirectory action or a reusable workflow), so the SHA to pin is that repository's commit — keep the full `github/codeql-action/init` path in `uses:` and query only `github/codeql-action`.
High: github-actions-mutable-action-tag .github/workflows/codeql-analysis.yml:59— GitHub Actions step uses a mutable tag or branch reference. Tags and branch names can be silently repointed by the action owner, enabling supply-chain attacks — as seen in the trivy-action and kics-github-action compromises. Pin the reference to a full 40-character commit SHA instead, e.g. `uses: github/codeql-action/autobuild@<40-character SHA>`. This step references `github/codeql-action/autobuild@v2`; resolve the SHA it points at today with `gh api repos/github/codeql-action/commits/v2 --jq .sha`. `github/codeql-action/autobuild` is hosted INSIDE the `github/codeql-action` repository (a subdirectory action or a reusable workflow), so the SHA to pin is that repository's commit — keep the full `github/codeql-action/autobuild` path in `uses:` and query only `github/codeql-action`.
High: github-actions-mutable-action-tag .github/workflows/codeql-analysis.yml:72— GitHub Actions step uses a mutable tag or branch reference. Tags and branch names can be silently repointed by the action owner, enabling supply-chain attacks — as seen in the trivy-action and kics-github-action compromises. Pin the reference to a full 40-character commit SHA instead, e.g. `uses: github/codeql-action/analyze@<40-character SHA>`. This step references `github/codeql-action/analyze@v2`; resolve the SHA it points at today with `gh api repos/github/codeql-action/commits/v2 --jq .sha`. `github/codeql-action/analyze` is hosted INSIDE the `github/codeql-action` repository (a subdirectory action or a reusable workflow), so the SHA to pin is that repository's commit — keep the full `github/codeql-action/analyze` path in `uses:` and query only `github/codeql-action`.
Hotspot: src/Shared/Common.SharedKernel.Logging/Middleware/RequestLoggingMiddlewareBase.cs src/Shared/Common.SharedKernel.Logging/Middleware/RequestLoggingMiddlewareBase.cs— src/Shared/Common.SharedKernel.Logging/Middleware/RequestLoggingMiddlewareBase.cs changed 3 times in last 90 days, max complexity 22. Frequent change and high complexity in one file compound: schedule the next change to it to include carving out the part being edited, behind tests written first.
Hotspot: src/Shared/Common.SharedKernel.Messaging/DependencyInjection/MessagingConfigurationValidationHostedService.cs src/Shared/Common.SharedKernel.Messaging/DependencyInjection/MessagingConfigurationValidationHostedService.cs— src/Shared/Common.SharedKernel.Messaging/DependencyInjection/MessagingConfigurationValidationHostedService.cs changed 4 times in last 90 days, max complexity 15. Frequent change and high complexity in one file compound: schedule the next change to it to include carving out the part being edited, behind tests written first.
Dead code: ToReadOnlyDictionary src/Shared/Common.SharedKernel.Logging/Abstractions/LogEnrichmentContext.cs:54— Method ToReadOnlyDictionary — no references found in solution.
Dead code: NullMessageConsumer src/Shared/Common.SharedKernel.Messaging/Providers/NullMessageConsumer.cs:3— NamedType NullMessageConsumer — no references found in solution.
Duplicated block (13 lines × 2) src/Services/Inventory/Inventory.Api/Infrastructure/Persistence/InventoryTransactionExecutor.cs:32— src/Services/Inventory/Inventory.Api/Infrastructure/Persistence/InventoryTransactionExecutor.cs:32-44 | src/Services/Product/Products.Api/Infrastructure/Persistence/ProductTransactionExecutor.cs:32-44 — the copies span different directories, so extracting a shared function means choosing where it lives: put it somewhere both call sites can already reach — a location they all depend on today, or a new shared one if there is none — and call it from each site; until then, every change has to be made twice. Read the line range as the matched WINDOW rather than a finished unit: at `src/Services/Inventory/Inventory.Api/Infrastructure/Persistence/InventoryTransactionExecutor.cs:32` it does not close everything it opens, so those exact lines cannot be lifted as they stand — widen the region to the smallest complete statement or declaration that contains it, and extract that. Note that the copies do not run to the end of the range shown: their LAST lines are different code, not the same code under different names — the matched region ends inside that line. Extract the lines above it, and read the last line of each site separately.
Duplicated block (13 lines × 2) src/Services/Inventory/Inventory.Api/Observability/InventoryRequestLoggingMiddleware.cs:25— src/Services/Inventory/Inventory.Api/Observability/InventoryRequestLoggingMiddleware.cs:25-37 | src/Services/Product/Products.Api/Observability/ProductsRequestLoggingMiddleware.cs:25-37 — the copies span different directories, so extracting a shared function means choosing where it lives: put it somewhere both call sites can already reach — a location they all depend on today, or a new shared one if there is none — and call it from each site; until then, every change has to be made twice.
Off the main sequence: aspnetrun-microservices.ServiceDefaults — aspnetrun-microservices.ServiceDefaults: abstractness 0.00, instability 0.00, distance 1.00 — zone of pain — concrete and depended on by 6 project(s), so it's rigid to change.
Off the main sequence: Common.SharedKernel — Common.SharedKernel: abstractness 0.26, instability 0.00, distance 0.74 — the shape a shared-kernel / building-block library has BY DESIGN — concrete and widely depended-on is what makes it useful, and this dimension does not penalise it (the distance is reported for completeness, not as a defect). Worth a look only if it has grown past one coherent kernel into an everything-bucket.
RequestLoggingMiddlewareBase.InvokeAsync (cyclomatic 22) src/Shared/Common.SharedKernel.Logging/Middleware/RequestLoggingMiddlewareBase.cs:17— RequestLoggingMiddlewareBase.InvokeAsync has cyclomatic complexity 22 (threshold 15). To reduce it, separate the cases: extract each independent branch into its own named function, and where the body has guards that only reject input, fold those into early returns at the top.
MessageContractCompatibility.IsCompatible (cyclomatic 17) src/Shared/Common.SharedKernel.Messaging/Compatibility/MessageContractCompatibility.cs:5— MessageContractCompatibility.IsCompatible has cyclomatic complexity 17 (threshold 15). To reduce it, separate the branches: extract each independent case into its own named function, or replace a long branch ladder over a single value with a data-driven lookup or dispatch table.
D11 · Test Reliability· Test reliability not measured · ×1
Test reliability not measured — no test run produced results — Test reliability NOT MEASURED: the test run produced no results for any test tier, so no test ever ran and flakiness could not be exercised. The cause could not be attributed, so it is excluded from the score rather than read as an absence of tests.
LLM evaluation failed — JSON parse error: Expected end of string, but instead reached end of data. Path: $.findings[0].suggestion | LineNumber: 0 | BytePositionInLine: 1170.
RequestLoggingMiddlewareBase.InvokeAsync (cognitive 34) src/Shared/Common.SharedKernel.Logging/Middleware/RequestLoggingMiddlewareBase.cs:17— RequestLoggingMiddlewareBase.InvokeAsync has cognitive complexity 34 (threshold 15). To reduce it, split the body into named stages: move each independent step or branch into its own named function so the body reads as a short sequence of named calls rather than one long body.
DefaultPayloadMaskingEngine.Traverse (cognitive 24) src/Shared/Common.SharedKernel.Logging/Pipeline/DefaultPayloadMaskingEngine.cs:81— DefaultPayloadMaskingEngine.Traverse has cognitive complexity 24 (threshold 15). To reduce it, split the body into named stages: move each independent step or branch into its own named function so the body reads as a short sequence of named calls rather than one long body.
MessagingConfigurationValidationHostedService.Validate (cognitive 21) src/Shared/Common.SharedKernel.Messaging/DependencyInjection/MessagingConfigurationValidationHostedService.cs:98— MessagingConfigurationValidationHostedService.Validate has cognitive complexity 21 (threshold 15). Of this number, 20 points are the body's own statements and 1 belongs to one function literal inside it that branches. To reduce it, split the body into named stages: move each independent step or branch into its own named function so the body reads as a short sequence of named calls rather than one long body.
OutboxPublisherBase.ExecuteAsync (cognitive 19) src/Shared/Common.SharedKernel.Messaging/Outbox/OutboxPublisherBase.cs:23— OutboxPublisherBase.ExecuteAsync has cognitive complexity 19 (threshold 15). To reduce it, flatten the nesting: invert conditions into early returns or guard clauses so the happy path stays at one level, and lift the deepest nested block into its own named function.
LoggingConfiguration.Validate (cognitive 16) src/Shared/Common.SharedKernel.Logging/DependencyInjection/LoggingBuilder.cs:240— LoggingConfiguration.Validate has cognitive complexity 16 (threshold 15). To reduce it, split the body into named stages: move each independent step or branch into its own named function so the body reads as a short sequence of named calls rather than one long body.
Duplicated block (40 lines × 2) src/Services/Inventory/Inventory.Api/Infrastructure/GlobalExceptionHandler.cs:16— src/Services/Inventory/Inventory.Api/Infrastructure/GlobalExceptionHandler.cs:16-55 | src/Services/Product/Products.Api/Infrastructure/GlobalExceptionHandler.cs:17-56 — the copies span different directories, so extracting a shared function means choosing where it lives: put it somewhere both call sites can already reach — a location they all depend on today, or a new shared one if there is none — and call it from each site; until then, every change has to be made twice. Read the line range as the matched WINDOW rather than a finished unit: at `src/Services/Inventory/Inventory.Api/Infrastructure/GlobalExceptionHandler.cs:16` it begins part-way through the construct above it, so those exact lines cannot be lifted as they stand — widen the region to the smallest complete statement or declaration that contains it, and extract that.
Duplicated block (37 lines × 2) src/Gateway/Gateway.Yarp/Program.cs:15— src/Gateway/Gateway.Yarp/Program.cs:15-51 | src/Services/Cart/Cart.Api/Program.cs:15-51 — the copies span different directories, so extracting a shared function means choosing where it lives: put it somewhere both call sites can already reach — a location they all depend on today, or a new shared one if there is none — and call it from each site; until then, every change has to be made twice. Read the line range as the matched WINDOW rather than a finished unit: at `src/Gateway/Gateway.Yarp/Program.cs:15` it begins part-way through the construct above it, so those exact lines cannot be lifted as they stand — widen the region to the smallest complete statement or declaration that contains it, and extract that.
Duplicated block (17 lines × 2) src/Shared/Common.SharedKernel.Logging/Pipeline/DefaultPayloadMaskingEngine.cs:347— src/Shared/Common.SharedKernel.Logging/Pipeline/DefaultPayloadMaskingEngine.cs:347-363 | src/Shared/Common.SharedKernel.Logging/Redaction/DefaultLogRedactor.cs:148-164 — the copies span different directories, so extracting a shared function means choosing where it lives: put it somewhere both call sites can already reach — a location they all depend on today, or a new shared one if there is none — and call it from each site; until then, every change has to be made twice.
Duplicated block (15 lines × 2) src/Shared/Common.SharedKernel.Logging/Options/LoggingPolicyOptions.cs:44— src/Shared/Common.SharedKernel.Logging/Options/LoggingPolicyOptions.cs:44-58 | src/Shared/Common.SharedKernel.Logging/Options/PayloadProtectionOptions.cs:64-78 — the copies sit in sibling files of one directory: extract the block into a single shared function in that directory and call it from each site, so a change lands once.
Duplicated block (12 lines × 2) src/Services/Inventory/Inventory.Api/Program.cs:13— src/Services/Inventory/Inventory.Api/Program.cs:13-24 | src/Services/Product/Products.Api/Program.cs:17-28 — the copies span different directories, so extracting a shared function means choosing where it lives: put it somewhere both call sites can already reach — a location they all depend on today, or a new shared one if there is none — and call it from each site; until then, every change has to be made twice.
Duplicated block (5 lines × 2) src/Services/Product/Products.Api/Features/Products/Create/CreateProductCommandValidator.cs:7— src/Services/Product/Products.Api/Features/Products/Create/CreateProductCommandValidator.cs:7-11 | src/Services/Product/Products.Api/Features/Products/Update/UpdateProductCommandValidator.cs:8-12 — the copies span different directories, so extracting a shared function means choosing where it lives: put it somewhere both call sites can already reach — a location they all depend on today, or a new shared one if there is none — and call it from each site; until then, every change has to be made twice.
Coverage not measured — The test suite couldn't be built/run in-image and no coverage report is committed, so line coverage was not measured — and it is EXCLUDED from the score rather than scored on a LoC-ratio proxy. No coverage collector was found in your CI either, so there is no existing report to hand us: add a coverage collector to your test run and commit (or publish) its Cobertura/OpenCover/lcov output anywhere in the repo, or make the suite runnable in-image, and real coverage will be measured.
Low IaC: DS-0026 src/Gateway/Gateway.Yarp/Dockerfile— No HEALTHCHECK defined Without one the runtime only knows whether the process is alive, not whether it is serving, so a wedged container is restarted by nobody. The step: add a `HEALTHCHECK` to the image that probes the service the way a client would — this image already declares `EXPOSE 8080`, so a request to `localhost:8080` on the service's own health or root route, exiting non-zero when it does not answer, is the probe — and give it an `--interval`, a `--timeout` and a `--start-period` long enough to cover startup. If the image ships no HTTP client, probe with whatever the runtime already has, or declare the check in the orchestrator instead and say so here.
Low IaC: DS-0026 src/Services/Cart/Cart.Api/Dockerfile— No HEALTHCHECK defined Without one the runtime only knows whether the process is alive, not whether it is serving, so a wedged container is restarted by nobody. The step: add a `HEALTHCHECK` to the image that probes the service the way a client would — this image already declares `EXPOSE 8080`, so a request to `localhost:8080` on the service's own health or root route, exiting non-zero when it does not answer, is the probe — and give it an `--interval`, a `--timeout` and a `--start-period` long enough to cover startup. If the image ships no HTTP client, probe with whatever the runtime already has, or declare the check in the orchestrator instead and say so here.
Low IaC: DS-0026 src/Services/Discount/Discount.Grpc/Dockerfile— No HEALTHCHECK defined Without one the runtime only knows whether the process is alive, not whether it is serving, so a wedged container is restarted by nobody. The step: add a `HEALTHCHECK` to the image that probes the service the way a client would — this image already declares `EXPOSE 8080`, so a request to `localhost:8080` on the service's own health or root route, exiting non-zero when it does not answer, is the probe — and give it an `--interval`, a `--timeout` and a `--start-period` long enough to cover startup. If the image ships no HTTP client, probe with whatever the runtime already has, or declare the check in the orchestrator instead and say so here.
Low IaC: DS-0026 src/Services/Order/Order.Api/Dockerfile— No HEALTHCHECK defined Without one the runtime only knows whether the process is alive, not whether it is serving, so a wedged container is restarted by nobody. The step: add a `HEALTHCHECK` to the image that probes the service the way a client would — this image already declares `EXPOSE 8080`, so a request to `localhost:8080` on the service's own health or root route, exiting non-zero when it does not answer, is the probe — and give it an `--interval`, a `--timeout` and a `--start-period` long enough to cover startup. If the image ships no HTTP client, probe with whatever the runtime already has, or declare the check in the orchestrator instead and say so here.
Low IaC: DS-0026 src/Services/Product/Products.Api/Dockerfile— No HEALTHCHECK defined Without one the runtime only knows whether the process is alive, not whether it is serving, so a wedged container is restarted by nobody. The step: add a `HEALTHCHECK` to the image that probes the service the way a client would — this image already declares `EXPOSE 8080`, so a request to `localhost:8080` on the service's own health or root route, exiting non-zero when it does not answer, is the probe — and give it an `--interval`, a `--timeout` and a `--start-period` long enough to cover startup. If the image ships no HTTP client, probe with whatever the runtime already has, or declare the check in the orchestrator instead and say so here.
D16 · Bus Factor· Small-team knowledge concentration · ×1
Small-team knowledge concentration — 16 file(s) are concentrated to one author — the ambient state with 2 active author(s), not 16 separate risks. The signal becomes meaningful as ownership spreads; no per-file action implied now.
Thin analysable surface across projects — 7 project(s) carry only a thin slice of real code (e.g. `Cart.Api.Tests` with 17 significant line(s)). The mean analysable-surface weight is 84 %, lowering Solution Shape by about 1.28 point(s). Consolidate thin projects or grow them into substantial, well-scoped assemblies.
D23 · Boundary Type-Coupling· Bounded contexts not declared · ×1
Bounded contexts not declared — At 9058 LoC spread over 22 projects the codebase is large and multi-module, so explicit bounded contexts are needed. Name this codebase's bounded contexts (≥2 module groups, e.g. per subsystem) so cross-boundary type coupling can be assessed. Declare them in `.codehealth/config.yaml` at the repository root (create it if absent), mapping each context name to the module-path or namespace prefixes that belong to it — e.g. `architecture:` → `contexts:` → `Billing: ["src/billing", "Acme.Billing"]`, `Catalog: ["src/catalog", "Acme.Catalog"]`.
IL efficiency: 1 authored method(s) exceed the IL budget src/Shared/Common.SharedKernel.Logging/DependencyInjection/LoggingBuilder.cs:142— 1 of 691 first-party methods compile to oversized IL bodies (> 250 instructions); worst: Common.SharedKernel.Logging.LoggingBuilder.Register @ src/Shared/Common.SharedKernel.Logging/DependencyInjection/LoggingBuilder.cs:142, 264 IL instructions; large bodies don't JIT-inline, which pulled this dimension to 10.0/10; splitting the hottest bodies recovers the most.
D22 · Internal API Consistency· No exposed public API · ×1
No exposed public API — No intentionally-exposed types (IsPackable or .Contracts) to evaluate.
Appendix B — Reproduction & audit trail
Every external tool invocation behind a deep-scan dimension — the tool, its captured version, the exact command, how many findings it yielded, and a link to the retained raw output. To reproduce any finding: check out the same commit and run the command shown (repo-relative — never an absolute scratch path). The complete raw scanner output is retained verbatim under artifacts/raw/ (indexed in artifacts/raw/index.json); per-invocation exit codes and wall-clock durations are in sidecar.json — kept out of this table so the rendered report stays byte-identical across runs of the same commit.
trivy: not applicable — No JS/npm manifest or lockfile found outside build output (package.json, package-lock.json, yarn.lock, pnpm-lock.yaml, bun.lockb); no JS dependencies to scan.
provenance: not applicable — The CI pipeline builds and tests but publishes no released artifact — no package publish, container push, GitHub release or deployment step. Supply-chain provenance, signing and SBOM attest RELEASED artifacts, so there is nothing to attest here. Add them to the release pipeline when this repo starts shipping artifacts (a published package, a container image, a deployed service or a tagged release).
disclosure: not applicable — No vulnerability-disclosure policy file found (SECURITY.md/.markdown/.rst/.txt at root or under .github/.forgejo/.gitea/docs, .well-known/security.txt). A coordinated-disclosure policy may live off-repo, so this is not evidenced rather than failed.
runtime-hardening: not applicable — No Kubernetes/orchestration workloads found in the repository manifests; network egress policy is a cluster-native control that may live at the platform/firewall layer, so there is nothing to assess here.
runtime-hardening: not applicable — No Kubernetes/orchestration workloads found in the repository manifests; seccomp/AppArmor/SELinux confinement is a workload-level control, so there is nothing to assess here.
runtime-hardening: not applicable — No Kubernetes/orchestration workloads found in the repository manifests; runtime threat-detection and admission-control policy are cluster-level controls, so there is nothing to assess here.
0
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Run 019fc8c2-f790-72d1-be21-321bc7002ffb · every finding is also locatable in findings.md, and the complete scoring record (with exit codes + durations) in sidecar.json.
Appendix C — Personal-data map
Every field, property and record parameter whose name is conventional personal data — 3 field(s) across 3 categories, each with an exact repo-relative file:line. This is the data inventory a compliance review starts from — right-to-erasure, retention, minimisation. Detected by name with a deliberately specific classifier (the same one the GDPR dimensions use, so CardDefinition or FileName don't trip); informational — it feeds no score.
Issues: 7 · Warnings: 39 · Recommendations: 9 · Info: 30 — Appendix A · all findings · full markdown report.
Generated by Watchdog — deterministic code-health analysis. 03-08-2026 @ 17:54 UTC.
Downloadable artifacts
Machine-readable and reproducible from this commit + frozen rubric — drop them straight into a contract appendix, a CRA dossier, or a downstream SCA / VEX tool.