cassandra-spark-connector — Watchdog Audit

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.

apache/cassandra-spark-connector carries serious gaps (27%). Several issues below can materially affect correctness, security, or the cost of changing it — and propagate to everything that depends on it.

It is strongest in Code Health (97%) — the code is clean and low-risk to change. Architecture (96%) is solid too.

The area that most needs attention is Security (1%) — exposure to security and compliance incidents is elevated. Readiness (23%) is the next concern — releases are harder to depend on — versioning, release notes and dependency hygiene are thin, so consumers can't easily tell what changed or trust an upgrade.

Leadership focus, highest impact first: 1 Rotate the exposed credentials finding(s) in Secrets (history) (Secrets (history)); 23 High finding(s) (Static Analysis (SAST)); 1 No tests found finding(s) in Test Distribution (Test Distribution).

For scale: Hobby (~0 production lines); rebuilding it from scratch would take roughly ~0.1 person-years (~1 engineer). Approximate, ±~30%.

It builds on a genuinely strong Code Health foundation (97%); the priorities above are the highest-leverage way to bring the rest up to that level.

Code Health 97% ★ Exemplary Architecture 96% ★ Exemplary Maturity 64% Adequate · gated by M2 Readiness 23% ⚠ Critical · gated by D9, P2, P3 Security 1% ⚠ Critical · gated by D28, D29

How the score is built — each lens's share of the headline Width 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.

Security 1% · 47% weightReadiness 23% · 26% weightMaturity 64% · 14% weightArchitecture 96% · 8% weightCode Health 97% · 4% weight

Raise Security 1 → 70 (the Healthy floor) ⇒ headline 27 → ~49.

Code composition — where the lines go

Tests 100%

New since the last scan (19+)

19 finding(s) are new versus the previous scan (2026-08-03) — surfaced by this scheduled scan itself, no pull request required.

D4 · Duplicated block (608 lines × 2) connector/src/main/java/com/datastax/spark/connector/japi/CassandraJavaUtil.java
D4 · Duplicated block (212 lines × 2) connector/src/main/java/com/datastax/spark/connector/japi/RDDAndDStreamCommonJavaFunctions.java
D4 · Duplicated block (211 lines × 4) connector/src/main/java/com/datastax/spark/connector/japi/RDDAndDStreamCommonJavaFunctions.java
D4 · Duplicated block (54 lines × 15) connector/src/main/java/com/datastax/spark/connector/japi/CassandraJavaUtil.java
D4 · Duplicated block (54 lines × 2) connector/src/main/java/com/datastax/spark/connector/japi/CassandraJavaUtil.java
D4 · Duplicated block (52 lines × 2) connector/src/main/java/com/datastax/spark/connector/japi/CassandraJavaUtil.java
D4 · Duplicated block (48 lines × 2) connector/src/main/java/com/datastax/spark/connector/japi/CassandraJavaUtil.java
D4 · Duplicated block (37 lines × 2) connector/src/main/java/com/datastax/spark/connector/japi/CassandraJavaUtil.java
D4 · Duplicated block (20 lines × 2) connector/src/main/java/com/datastax/spark/connector/japi/CassandraJavaUtil.java
D4 · Duplicated block (19 lines × 2) connector/src/main/java/com/datastax/spark/connector/japi/RDDAndDStreamCommonJavaFunctions.java
D4 · Duplicated block (11 lines × 2) connector/src/main/java/com/datastax/spark/connector/japi/rdd/CassandraTableScanJavaRDD.java
D4 · Duplicated block (5 lines × 3) connector/src/main/java/com/datastax/spark/connector/japi/RDDAndDStreamCommonJavaFunctions.java
D8 · Coverage not measured — test suite did not build
D13 · Leaked secret: private-key test-support/src/main/resources/client.key
D18 · Dimension evaluation failed
D20 · No consequences/trade-offs section describing what will happen to existing Spark-Cassandra embedded test code doc/10_embedded.md
D20 · Context/problem (which version to prefer) and consequences/trade-offs are not stated in the visible text doc/12_building_and_artifacts.md
D20 · No context/problem and no consequences/trade-offs for setting up Cassandra/Spark (e.g. resource cost of running stand-alone Spark) doc/13_1_setup_spark_shell.md
P2 · No structured logging

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.

Top priorities

The highest-leverage moves; the full ranked list is in the Roadmap below.

Resolve the 1 Rotate the exposed credentials finding(s) in Secrets (history).

+17.8 pts · Low effort · Secrets (history)

Resolve the 1 No tests found finding(s) in Test Distribution.

+15.4 pts · Low effort · Test Distribution

Resolve the 1 Leaked secret finding(s) in Secret Scanning — start with client.key.

+11.9 pts · Low effort · Secret Scanning

Diagnosis — what's actually going on

Highest-leverage move · Medium · Leverage

Of everything flagged, the best return on effort is: Resolve the 1 Rotate the exposed credentials finding(s) in Secrets (history). The rest can wait behind it.

Evidence: priority ranking: top of 5 ranked by impact/effort

→ Resolve the 1 Rotate the exposed credentials finding(s) in Secrets (history).

At a glance — Code Health · 97% · Exemplary

The Good

D1 · .NET / C# Cyclomatic Complexity 10.0 D2 · .NET / C# Cognitive Complexity 10.0 D3 · .NET / C# God Classes 10.0 D4 · .NET / C# Code Duplication 7.0 X1 · Repo Async correctness 10.0 X3 · Repo Exception handling 10.0 X4 · Repo Structured logging 10.0

At a glance — Architecture · 96% · Exemplary

The Good

D7 · .NET / C# Architectural Integrity 10.0 D26 · .NET / C# Project Cohesion 10.0 D27 · .NET / C# Navigability 10.0 AX5 · Repo Architecture & structure 10.0

The Bad

D5 · .NET / C# Coupling 6.9

At a glance — Maturity · 64% · Adequate · gated by M2

The Good

D15 · .NET / C# Churn × Complexity Hotspots 10.0 D16 · .NET / C# Bus Factor 10.0 D21 · .NET / C# Naming Consistency 10.0 D25 · .NET / C# ADR Conformance 10.0 D34 · .NET / C# Knowledge Freshness 10.0 M1 · Repo Documentation (README) 7.3 M4 · Repo Documentation accuracy 10.0

The Bad

D20 · .NET / C# ADR Quality 6.9 M3 · Repo Folder & project structure 6.0

The Ugly

M2 · Repo Architecture documentation 3.5

At a glance — Readiness · 23% · Critical · gated by D9, P2, P3

The Good

D12 · .NET / C# Dependency Hygiene 10.0 P1 · Repo CI/CD gates 10.0

The Bad

D13 · .NET / C# Secret Scanning 5.0

The Ugly

P2 · Repo Observability 0.0 P3 · Repo Security & performance tooling 0.0

At a glance — Security · 1% · Critical · gated by D28, D29

The Ugly

D28 · .NET / C# Secrets (history) 0.0 D29 · .NET / C# Static Analysis (SAST) 0.2

Security & Compliance — OWASP Top-10 mapping

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
A03:2021 — Injection	23	High / Critical
A02:2021 — Cryptographic Failures	2	High / Critical

Roadmap

First, resolve the exposed credentials in the secrets history and address the 23 high-priority static analysis findings, particularly in CassandraDataFrameDateBehaviors.scala, main.yml, and CassandraCatalogSpecBase.scala. Next, ensure all projects have associated tests by resolving the missing test coverage gaps. Then, implement structured logging using ILogger or Serilog at key points across the projects. Finally, introduce a static application security testing step, such as CodeQL, to strengthen the security and performance tooling pipeline.

Ranked by impact ÷ effort. "Helps" is the estimated gain on the 0–100 health score.

Do this	Helps	Effort	Dimension
Resolve the 1 Rotate the exposed credentials finding(s) in Secrets (history).	+17.8 pts	Low	Secrets (history)
Resolve the 1 No tests found finding(s) in Test Distribution.	+15.4 pts	Low	Test Distribution
Resolve the 1 Leaked secret finding(s) in Secret Scanning — start with client.key.	+11.9 pts	Low	Secret Scanning
Resolve the 23 High finding(s) in Static Analysis (SAST) — start with CassandraDataFrameDateBehaviors.scala (5), main.yml (3), CassandraCatalogSpecBase.scala (2).	+17.5 pts	Medium	Static Analysis (SAST)
Adopt ILogger (or Serilog) and log at meaningful points across the projects.	+15.4 pts	Medium	Observability
Add a SAST step (e.g. CodeQL) or a security analyzer package.	+15.4 pts	Medium	Security & performance tooling
Grow the ADR log (currently 9) — reach 20 to raise the maturity tier; document significant decisions as they're made.	+4.8 pts	Medium	Architecture documentation
Group production code under src/ (or split deliberately, e.g. backend/ + frontend/) so production and tooling code aren't mixed at the root.	+4.8 pts	Medium	Folder & project structure

File quality

Per-file score 0–10 — a quality signature. Of 23 files carrying findings, judged against the Production bar: 0% slop · 83% mixed · 17% near-clean.

File	Score	Band	Worst signal
connector/src/it/scala/com/datastax/spark/connector/sql/CassandraDataFrameDateBehaviors.scala	4.6	Mixed	Static Analysis (SAST): High: tainted-sql-string
.github/workflows/main.yml	5.1	Mixed	Static Analysis (SAST): High: github-actions-mutable-action-tag
connector/src/it/scala/com/datastax/spark/connector/datasource/CassandraCatalogSpecBase.scala	5.8	Mixed	Static Analysis (SAST): High: tainted-sql-string
connector/src/main/java/com/datastax/spark/connector/japi/CassandraJavaUtil.java	7.0	Mixed	Code Duplication: Duplicated block (608 lines × 2)
connector/src/main/java/com/datastax/spark/connector/japi/RDDAndDStreamCommonJavaFunctions.java	7.2	Mixed	Code Duplication: Duplicated block (212 lines × 2)
test-support/src/main/resources/client.key	7.2	Mixed	Secret Scanning: Leaked secret: private-key
connector/src/it/scala/com/datastax/bdp/spark/search/SearchAnalyticsIntegrationSpec.scala	7.2	Mixed	Static Analysis (SAST): High: tainted-sql-string
connector/src/it/scala/com/datastax/spark/connector/SparkCassandraITFlatSpecBase.scala	7.2	Mixed	Static Analysis (SAST): High: tainted-sql-string
connector/src/it/scala/com/datastax/spark/connector/cql/sai/SaiBaseSpec.scala	7.2	Mixed	Static Analysis (SAST): High: tainted-sql-string
connector/src/it/scala/com/datastax/spark/connector/rdd/DseGraphUnionRDDSpec.scala	7.2	Mixed	Static Analysis (SAST): High: tainted-sql-string
connector/src/it/scala/com/datastax/spark/connector/sql/CassandraDataSourceSpec.scala	7.2	Mixed	Static Analysis (SAST): High: tainted-sql-string
connector/src/main/scala/com/datastax/spark/connector/datasource/JoinHelper.scala	7.2	Mixed	Static Analysis (SAST): High: tainted-sql-string
connector/src/main/scala/com/datastax/spark/connector/datasource/ScanHelper.scala	7.2	Mixed	Static Analysis (SAST): High: tainted-sql-string
connector/src/main/scala/com/datastax/spark/connector/rdd/CassandraCoGroupedRDD.scala	7.2	Mixed	Static Analysis (SAST): High: tainted-sql-string
connector/src/main/scala/com/datastax/spark/connector/rdd/CassandraMergeJoinRDD.scala	7.2	Mixed	Static Analysis (SAST): High: tainted-sql-string
connector/src/main/scala/com/datastax/spark/connector/rdd/partitioner/DataSizeEstimates.scala	7.2	Mixed	Static Analysis (SAST): High: tainted-sql-string
connector/src/main/scala/com/datastax/spark/connector/util/PatitionKeyTools.scala	7.2	Mixed	Static Analysis (SAST): High: tainted-sql-string
connector/src/main/scala/com/datastax/spark/connector/writer/TableWriter.scala	7.2	Mixed	Static Analysis (SAST): High: tainted-sql-string
connector/src/main/scala/org/apache/spark/sql/cassandra/SolrPredicateRules.scala	7.2	Mixed	Static Analysis (SAST): High: tainted-sql-string
connector/src/main/java/com/datastax/spark/connector/japi/rdd/CassandraTableScanJavaRDD.java	8.5	Near-clean	Code Duplication: Duplicated block (11 lines × 2)

Methodology & how to trust this report

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. 27 of 30 evaluated dimensions are computed purely by tools and static analysis (confidence 1.0); 3 documentation/naming judgement(s) are LLM-assisted and labelled advisory. Overall confidence is 0.5 — 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 — 30 dimensions across the health lenses

D1D2D3D4D5D7D9D12D13D15D16D20D21D25D26D27D28D29D34AX5M1M2M3M4P1P2P3X1X3X4

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, 39 of 46 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	5.3.0	✓ deterministic
Native secret scanner	Hardcoded secrets / credentials	1.0.0	✓ deterministic
jscpd	Code duplication	—	✓ deterministic
Coverage (coverlet / dotnet-coverage)	Line & branch coverage	10.0.301	✓ deterministic
NuGet / dotnet	Outdated, vulnerable & deprecated dependencies	10.0.301	✓ deterministic
git / LibGit2Sharp	Churn hotspots, knowledge concentration, history	2.43.0 · 0.31.0	✓ deterministic
gitleaks · semgrep · trivy · checkov	Secrets in history, SAST, CVEs, IaC & container, PII / GDPR	1.86.0 · 0.69.3	✓ deterministic
LLM (sampled · advisory)	Documentation quality, ADR conformance, naming — sampled over a bounded sample; advisory, never a deterministic measurement	Local LLM	◐ LLM · sampled · advisory

Every finding is locatable in findings.md. Run 019fdcfa-996b-7a7d-9615-9f05004e646c.

The exact command behind every deep-scan dimension — tool, version, invocation and retained raw output — is in Appendix B — Reproduction & audit trail.

Run transparency — what happened this run

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.

D18 Solution Shape — evaluation did not complete — Dimension evaluation failed — excluded from the score.
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.
D30 Dependency Vulnerabilities — scanner not present in this environment — The backing tool was not installed where this scan ran, so this dimension was not scored. Install the tool (or run in the hosted environment, where it is always present) for a graded result.
D31 IaC & Container Security — scanner not present in this environment — The backing tool was not installed where this scan ran, so this dimension was not scored. Install the tool (or run in the hosted environment, where it is always present) for a graded result.
D32 Data Compliance (PII/GDPR) — scanner not present in this environment — The backing tool was not installed where this scan ran, so this dimension was not scored. Install the tool (or run in the hosted environment, where it is always present) for a graded result.
D33 JS/npm Dependency Vulnerabilities — scanner not present in this environment — The backing tool was not installed where this scan ran, so this dimension was not scored. Install the tool (or run in the hosted environment, where it is always present) for a graded result.
D36 Supply-chain Provenance & Signing — scanner not present in this environment — The backing tool was not installed where this scan ran, so this dimension was not scored. Install the tool (or run in the hosted environment, where it is always present) for a graded result.
D37 Vulnerability-disclosure Policy — scanner not present in this environment — The backing tool was not installed where this scan ran, so this dimension was not scored. Install the tool (or run in the hosted environment, where it is always present) for a graded result.
D38 OSV Dependency Vulnerabilities — scanner not present in this environment — The backing tool was not installed where this scan ran, so this dimension was not scored. Install the tool (or run in the hosted environment, where it is always present) for a graded result.

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 (EF migration scaffolds, *.Designer.cs, model snapshots) is EXCLUDED — its repetition is the tool's, not the team's — so the score reflects hand-written duplication only; the generated footprint is reported separately under Solution Shape.
D5 Coupling: Coupling is measured between projects/assemblies — runtime coupling through DI, reflection, messaging or shared databases is invisible to a static reference graph.
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.
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").
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.
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.
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").
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.
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.

The LLM boundary

LLM-set scores this run (4): D20, D21, D25, 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.

Dimensions

D1 · Cyclomatic Complexity10.0 / 10Exemplary✓ Tool-verified

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.

Maturity: Documented → Verified → Prevented · effective 10.0 / 10 · rule-coverage 100% · ceiling Prevented

0 method(s) exceeded the cyclomatic complexity threshold of 15.

✓ On the Gold path — maintain.

Detailed fixes: d1_recommendation.md.

Do you agree with this assessment?

D2 · Cognitive Complexity10.0 / 10Exemplary✓ Tool-verified

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.

Maturity: Documented → Verified → Prevented · effective 10.0 / 10 · rule-coverage 100% · ceiling Prevented

0 method(s) exceeded the cognitive complexity threshold of 15.

✓ On the Gold path — maintain.

Detailed fixes: d2_recommendation.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.

Maturity: Documented → Verified → Prevented · effective 10.0 / 10 · rule-coverage 100% · ceiling Prevented

0 god class(es) detected.

✓ On the Gold path — maintain.

Detailed fixes: d3_recommendation.md.

Do you agree with this assessment?

D4 · Code Duplication7.0 / 10Strong✓ Tool-verified

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.

Maturity: Documented → Verified → Prevented · effective 7.0 / 10 · rule-coverage 100% · ceiling Verified

12 duplicated block group(s) detected.

Duplicated block (608 lines × 2)connector/src/main/java/com/datastax/spark/connector/japi/CassandraJavaUtil.java:996

Duplicated block (212 lines × 2)connector/src/main/java/com/datastax/spark/connector/japi/RDDAndDStreamCommonJavaFunctions.java:197

Duplicated block (211 lines × 4)connector/src/main/java/com/datastax/spark/connector/japi/RDDAndDStreamCommonJavaFunctions.java:197

Duplicated block (54 lines × 15)connector/src/main/java/com/datastax/spark/connector/japi/CassandraJavaUtil.java:1918

Duplicated block (54 lines × 2)connector/src/main/java/com/datastax/spark/connector/japi/CassandraJavaUtil.java:1098

+ 7 more group(s) — more in Appendix A; the complete list is findings.md.

What to do

Resolve the 1 Duplicated block (608 lines × 2) finding(s) in Code Duplication — start with CassandraJavaUtil.java. — One of this dimension's main actionable groups (1 warning-level).
Resolve the 1 Duplicated block (212 lines × 2) finding(s) in Code Duplication — start with RDDAndDStreamCommonJavaFunctions.java. — One of this dimension's main actionable groups (1 warning-level).
Resolve the 1 Duplicated block (211 lines × 4) finding(s) in Code Duplication — start with RDDAndDStreamCommonJavaFunctions.java. — One of this dimension's main actionable groups (1 warning-level).
Enforce Code Duplication in CI to reach Verified (currently Documented). — Hardens enforcement from Documented toward Verified — provenance only; does not change the score.

Detailed fixes: d4_recommendation.md · top locations in Appendix A, every location in findings.md.

Do you agree with this assessment?

D5 · Coupling6.9 / 10Adequate✓ 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.

Maturity: Documented → Verified → Prevented · effective 6.9 / 10 · rule-coverage 100% · ceiling Prevented

0 projects, 0 dependency cycle(s), 0 unstable depended-on project(s).

What to do

Enforce Coupling in CI to reach Verified (currently Documented). — Hardens enforcement from Documented toward Prevented — provenance only; does not change the score.

Detailed fixes: d5_recommendation.md.

Do you agree with this assessment?

D7 · Architectural Integrity10.0 / 10Exemplary✓ Tool-verified

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.

Maturity: Documented → Verified → Prevented · effective 10.0 / 10 · rule-coverage 100% · ceiling Prevented

Of 1 mechanizable ADRs, 1 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.

Do you agree with this assessment?

D9 · Test Distribution0.0 / 10Critical✓ 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.

Maturity: Documented → Verified → Prevented · effective 0.0 / 10 · rule-coverage 100% · ceiling Documented

No test projects found.

No tests found

What to do

Resolve the 1 No tests found finding(s) in Test Distribution. — One of this dimension's main actionable groups (1 recommendation-level).

Detailed fixes: d9_recommendation.md · top locations in Appendix A, every location in findings.md.

Do you agree with this assessment?

D12 · Dependency Hygiene10.0 / 10Exemplary✓ Tool-verified

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.

Maturity: Documented → Verified → Prevented · effective 10.0 / 10 · rule-coverage 100% · ceiling Verified

0 outdated, 0 vulnerable, 0 deprecated packages.

✓ On the Gold path — maintain.

Detailed fixes: d12_recommendation.md.

Do you agree with this assessment?

D13 · Secret Scanning5.0 / 10Adequate✓ Tool-verified

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.

Maturity: Documented → Verified → Prevented · effective 5.0 / 10 · rule-coverage 100% · ceiling Prevented

1 secret(s) detected.

Leaked secret: private-keytest-support/src/main/resources/client.key:1

What to do

Resolve the 1 Leaked secret finding(s) in Secret Scanning — start with client.key. — One of this dimension's main actionable groups (1 issue-level).
Enforce Secret Scanning in CI to reach Verified (currently Documented). — Hardens enforcement from Documented toward Prevented — provenance only; does not change the score.

Detailed fixes: d13_recommendation.md · top locations in Appendix A, every location in findings.md.

Do you agree with this assessment?

D15 · Churn × Complexity Hotspots10.0 / 10Exemplary✓ Tool-verified

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.

Maturity: Documented → Verified → Prevented · effective 10.0 / 10 · rule-coverage 100% · ceiling Documented

No churn × complexity hotspots in the window.

✓ On the Gold path — maintain.

Detailed fixes: d15_recommendation.md.

Do you agree with this assessment?

D16 · Bus Factor10.0 / 10Exemplary✓ 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.

Maturity: Documented → Verified → Prevented · effective 10.0 / 10 · rule-coverage 100% · ceiling Documented

No source file's living knowledge is concentrated in a single author.

✓ On the Gold path — maintain.

Detailed fixes: d16_recommendation.md.

Do you agree with this assessment?

D20 · ADR Quality / 10Adequate◐ 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.

Maturity: Documented → Verified → Prevented · effective Adequate / 10 · rule-coverage 100% · ceiling Documented

Evaluated 9 ADR(s) individually; mean quality 6.9/10 (mixed — many ADRs miss context or consequences). 3 flagged with a specific gap.

No consequences/trade-offs section describing what will happen to existing Spark-Cassandra embedded test codedoc/10_embedded.md

Context/problem (which version to prefer) and consequences/trade-offs are not stated in the visible textdoc/12_building_and_artifacts.md

No context/problem and no consequences/trade-offs for setting up Cassandra/Spark (e.g. resource cost of running stand-alone Spark)doc/13_1_setup_spark_shell.md

What to do

Resolve the 1 No consequences/trade-offs section describing what will happen to… finding(s) in ADR Quality — start with 10_embedded.md. — One of this dimension's main actionable groups (1 warning-level).
Resolve the 1 Context/problem (which version to prefer) and consequences/trade-offs… finding(s) in ADR Quality — start with 12_building_and_artifacts.md. — One of this dimension's main actionable groups (1 warning-level).
Resolve the 1 No context/problem and no consequences/trade-offs for setting up… finding(s) in ADR Quality — start with 13_1_setup_spark_shell.md. — One of this dimension's main actionable groups (1 warning-level).

Detailed fixes: d20_recommendation.md · top locations in Appendix A, every location in findings.md.

Do you agree with this assessment?

D21 · Naming Consistency / 10Exemplary◐ Sampled · advisory

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.

Maturity: Documented → Verified → Prevented · effective Exemplary / 10 · rule-coverage 100% · ceiling Verified

0 naming inconsistencies across 0 sampled symbols.

✓ On the Gold path — maintain.

Detailed fixes: d21_recommendation.md.

Do you agree with this assessment?

D25 · ADR Conformance / 10Exemplary◐ Sampled · advisory

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.

Maturity: Documented → Verified → Prevented · effective Exemplary / 10 · rule-coverage 100% · ceiling Verified

2 conform / 0 violate across 9 ADRs.

✓ On the Gold path — maintain.

Detailed fixes: d25_recommendation.md.

Do you agree with this assessment?

D26 · Project Cohesion10.0 / 10Exemplary✓ Tool-verified

What it measures: Whether each project is a focused, coherent unit rather than an oversized grab-bag.

Method: Project size overshoot penalties (LoC / public-type count / namespace count, 2-of-3 flag) weighted by log magnitude. Exhaustive across projects, deterministic, LLM-independent.

Maturity: Documented → Verified → Prevented · effective 10.0 / 10 · rule-coverage 100% · ceiling Documented

No projects to assess.

✓ On the Gold path — maintain.

Detailed fixes: d26_recommendation.md.

Do you agree with this assessment?

D27 · Navigability10.0 / 10Exemplary✓ Tool-verified

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.

Maturity: Documented → Verified → Prevented · effective 10.0 / 10 · rule-coverage 100% · ceiling Documented

Too little code to assess navigability.

✓ On the Gold path — maintain.

Detailed fixes: d27_recommendation.md.

Do you agree with this assessment?

D28 · Secrets (history)0.0 / 10Critical✓ Tool-verified

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.

Maturity: Documented → Verified → Prevented · effective 0.0 / 10 · rule-coverage 100% · ceiling Documented

87 finding(s): 0 critical, 87 high, 0 medium, 0 low. Remediation for historically-committed secrets is credential rotation — they remain in history regardless of later deletion.

Rotate the exposed credentials — git history can't be un-committed

What to do

Resolve the 1 Rotate the exposed credentials finding(s) in Secrets (history). — One of this dimension's main actionable groups (1 recommendation-level).

Detailed fixes: d28_recommendation.md · top locations in Appendix A, every location in findings.md.

Do you agree with this assessment?

D29 · Static Analysis (SAST)0.2 / 10Critical✓ Tool-verified

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).

Maturity: Documented → Verified → Prevented · effective 0.2 / 10 · rule-coverage 100% · ceiling Documented

23 finding(s): 0 critical, 23 high, 0 medium, 0 low.

High: github-actions-mutable-action-tag · ×23.github/workflows/main.yml:20detected by semgrep finding

What to do

Resolve the 23 High finding(s) in Static Analysis (SAST) — start with CassandraDataFrameDateBehaviors.scala (5), main.yml (3), CassandraCatalogSpecBase.scala (2). — One of this dimension's main actionable groups (23 issue-level).

Detailed fixes: d29_recommendation.md · top locations in Appendix A, every location in findings.md.

Do you agree with this assessment?

D34 · Knowledge Freshness10.0 / 10Exemplary✓ Tool-verified

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.

Maturity: Documented → Verified → Prevented · effective 10.0 / 10 · rule-coverage 100% · ceiling Documented

Every significant source file has living knowledge — recently and meaningfully worked.

✓ On the Gold path — maintain.

Detailed fixes: d34_recommendation.md.

Do you agree with this assessment?

Frontend & cross-cutting dimensions

R = React/JS · M = Maturity · P = Readiness.

AX5 · Architecture & structure10.0 / 10Exemplary✓ Tool-verified

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.

Do you agree with this assessment?

M1 · Documentation (README)7.3 / 10Strong✓ Tool-verified

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 an 'Architecture' / 'How it works' section to the root README — the high-level shape.

Do you agree with this assessment?

M2 · Architecture documentation3.5 / 10Weak✓ Tool-verified

Maturity · Maturity — Whether key decisions (ADRs) and the high-level shape (C4/diagrams) are written down.

Method: Filesystem scan: ADR folder/naming conventions or content, plus Mermaid/PlantUML/C4/architecture.md discovery. Exhaustive, deterministic.

No C4/PlantUML/Mermaid diagram or architecture.md — the high-level shape isn't documented.

What to do

Grow the ADR log (currently 9) — reach 20 to raise the maturity tier; document significant decisions as they're made.
Add a C4 context/container diagram (Structurizr, PlantUML or Mermaid) or an architecture.md overview.

Do you agree with this assessment?

M3 · Folder & project structure6.0 / 10Adequate✓ Tool-verified

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.

Projects aren't grouped under a src/ folder — production and tooling code are mixed at the root.
Test projects aren't grouped under a tests/ folder — the test surface isn't separable from production code at a glance.

What to do

Group production code under src/ (or split deliberately, e.g. backend/ + frontend/) so production and tooling code aren't mixed at the root.
Group test projects under tests/ (or test/, spec/) so the test surface is discoverable and CI can scope it.

Do you agree with this assessment?

M4 · Documentation accuracy10.0 / 10Exemplary◐ Sampled · advisory

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.

Do you agree with this assessment?

P1 · CI/CD gates10.0 / 10Exemplary○ Nothing flagged

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.

Do you agree with this assessment?

P2 · Observability0.0 / 10Critical✓ Tool-verified

Readiness · Readiness — Whether the code is diagnosable in production — structured logging, tracing/metrics, health checks.

Method: Filesystem/Roslyn scan: structured-logging frameworks (Serilog, NLog), OpenTelemetry, and health-check endpoint patterns. Exhaustive, deterministic.

No ILogger/Serilog usage found — production issues will be hard to diagnose.

What to do

Adopt ILogger (or Serilog) and log at meaningful points across the projects.
Consider OpenTelemetry tracing/metrics and a health-check endpoint for operability.

Do you agree with this assessment?

P3 · Security & performance tooling0.0 / 10Critical✓ Tool-verified

Readiness · Readiness — Whether SAST, secret/dependency scanning and performance benchmarking are wired in (presence, not runtime).

Method: Filesystem/Roslyn scan: CodeQL, Dependabot, secret-scanning, and BenchmarkDotNet presence in pipelines and projects. Exhaustive, deterministic.

No static application security testing (CodeQL / security analyzers / codehealth) detected.

What to do

Add a SAST step (e.g. CodeQL) or a security analyzer package.
Enable Dependabot/Renovate or a dependency-review gate.
Add gitleaks/trufflehog in CI to block PRs that introduce committed secrets.

Do you agree with this assessment?

X1 · Async correctness10.0 / 10Exemplary○ Nothing flagged

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.

Do you agree with this assessment?

X3 · Exception handling10.0 / 10Exemplary○ Nothing flagged

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.

Do you agree with this assessment?

X4 · Structured logging10.0 / 10Exemplary○ Nothing flagged

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.

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.

Lens	Score	Rating	Impact
Code Health	97%	Exemplary	Strongest area.
Architecture	96%	Exemplary	Solid.
Maturity	64%	Adequate — gated by M2	Capped at Fair by a Critical contributor — resolve it before relying on this lens.
Readiness	23%	Critical — gated by D9, P2, P3	Capped at Fair by a Critical contributor — resolve it before relying on this lens.
Security	1%	Critical — gated by D28, D29	Capped at Fair by a Critical contributor — resolve it before relying on this lens.

Not included — 60 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.
AX1 Captive dependencies — no DI registrations detected
AX10 Code composition — no source files detected — code composition not applicable
AX2 Stateful singletons — no singleton implementations detected
AX3 Project dependency cycles — no csproj graph available
AX4 Dependency direction — no csproj graph available
AX6 Interface segregation — no public interfaces
AX7 Slice cohesion — not applicable — not a vertical-slice architecture
AX8 Test isolation — no test/production split to check
AX9 CQS / query purity — no CQRS query handlers detected — query purity is not applicable to this codebase
C1 Data Protection — No personal data detected in the analyzed source — no PII-typed entity/column names (Email, FirstName, DateOfBirth, …), no ASP.NET Identity / user-account model, and no stored user credentials. GDPR data-protection controls are therefore N/A here. If this is intentional, record the no-PII posture in an ADR; if the app does process personal data, name those fields conventionally so this dimension activates.
C2 Access Controls — No access-control surface detected in the analyzed source — no web/app surface to authorize (no HTTP API or web-UI project) and no authorization code at all (no [Authorize]/policies, no imperative guard methods). Access control is therefore N/A here — this is a library/CLI, which is authorized by its CALLER, not by itself. If this codebase grows request handlers, the dimension reactivates and a default-deny posture is expected then.
C3 Audit Trail — No personal data detected in the analyzed source — no PII-typed entity/column names (Email, FirstName, DateOfBirth, …), no ASP.NET Identity / user-account model, and no stored user credentials. GDPR data-protection controls are therefore N/A here. If this is intentional, record the no-PII posture in an ADR; if the app does process personal data, name those fields conventionally so this dimension activates.
C4 Data Retention — No personal data detected in the analyzed source — no PII-typed entity/column names (Email, FirstName, DateOfBirth, …), no ASP.NET Identity / user-account model, and no stored user credentials. GDPR data-protection controls are therefore N/A here. If this is intentional, record the no-PII posture in an ADR; if the app does process personal data, name those fields conventionally so this dimension activates.
C5 Data-Subject Rights — No personal data detected in the analyzed source — no PII-typed entity/column names (Email, FirstName, DateOfBirth, …), no ASP.NET Identity / user-account model, and no stored user credentials. GDPR data-protection controls are therefore N/A here. If this is intentional, record the no-PII posture in an ADR; if the app does process personal data, name those fields conventionally so this dimension activates.
D10 Test Quality — ~1308 lines of test code exist on disk but weren't loaded from the analyzed solution (excluded from the .sln, or co-located/using a test attribute not loaded here), so test quality couldn't be assessed. Include the tests in the analyzed solution to enable this check.
D11 Test Reliability — Test reliability not included
D14 License Compliance — license scan produced no result — the tool ran but its JSON output could not be parsed; the offline NuGet fallback resolved nothing
D17 Explicit Debt — the C# workspace loaded 0 projects, so explicit-debt density could not be measured
D18 Solution Shape — Dimension evaluation failed
D19 Documentation Quality — LLM evaluation failed
D22 Internal API Consistency — No exposed public API
D23 Boundary Type-Coupling — Zero projects and zero LoC mean the codebase is trivial and has no structure to justify boundaries.
D24 Comment Value — No inline comments to assess — comment value is not applicable here.
D30 Dependency Vulnerabilities — No .NET solution found; no NuGet dependencies to scan for vulnerabilities.
D31 IaC & Container Security — No Infrastructure-as-Code or container manifests found (Dockerfile, Terraform, Kubernetes/Helm, CloudFormation); nothing to scan.
D32 Data Compliance (PII/GDPR) — No PII/GDPR ruleset is bundled (the public p/gdpr semgrep pack was retired) — data compliance is not assessed in this scan.
D33 JS/npm Dependency Vulnerabilities — No JS/npm manifest or lockfile found outside bin/obj (package.json, package-lock.json, yarn.lock, pnpm-lock.yaml, bun.lockb); no JS dependencies to scan.
D35 Change Coupling — no production change history to mine for change-coupling
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 NuGet package, a container image, a GitHub release).
D37 Vulnerability-disclosure Policy — No vulnerability-disclosure policy file found (SECURITY.md, .github/SECURITY.md, docs/SECURITY.md, .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 JS/npm lockfile found outside bin/obj (package-lock.json, yarn.lock, pnpm-lock.yaml, bun.lockb); nothing for OSV to scan.
D39 IL Efficiency — The target did not build, so no IL was available to measure.
D6 Cohesion (LCOM4) — No production classes were analyzable, so cohesion (LCOM4) was not measured (the solution likely failed to load or has no production code).
D8 Code Coverage — Coverage not measured — test suite did not build
DM1 Domain Modelling — not run — only 1/3 markers (2 value object(s))
ED1 Event-Driven — not run — 0/3 markers found
ED5 Idempotency — no mutating command handlers or message consumers detected — idempotency check not applicable
ES1 Event Sourcing — not run — 0/3 markers found
GD1 Unfinished & placeholder code — no source files
IC1 Incompleteness & stubs — no C# methods found
P12 CI test-gate honesty — no data
P4 Deployment & Rollback — not evidenced — no deploy/rollback/approval signal in the repo; absence of evidence is not evidence of a manual release
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
P7 Outbound HTTP resilience — not applicable — this isn't a service/API/worker
P8 Schema migrations — no EF Core usage detected
P9 Domain vs controller coverage — no coverage report found on disk — run tests with `--collect:"XPlat Code Coverage"` (or in CI) to enable this cross-layer check
PF1 Benchmark discipline — Performance is assessed only for perf-relevant repos — a packaged library, one that ships benchmarks, or one already using allocation-aware APIs. This repo isn't one, so the Performance lens is not applicable and is excluded from the score.
PF2 Allocation hygiene — Performance is assessed only for perf-relevant repos — a packaged library, one that ships benchmarks, or one already using allocation-aware APIs. This repo isn't one, so the Performance lens is not applicable and is excluded from the score.
PF3 Async & latency hygiene — Performance is assessed only for perf-relevant repos — a packaged library, one that ships benchmarks, or one already using allocation-aware APIs. This repo isn't one, so the Performance lens is not applicable and is excluded from the score.
S1 Web-Security Posture — No web surface detected in the analyzed source — no HTTP API or web-UI project (no controllers/minimal-API endpoints, no Razor/Blazor views) and no web middleware (HTTPS redirection, HSTS, security headers, cookies). Transport security, security headers, secure cookies, CSRF/input-validation and middleware-order controls are therefore N/A here — this is a library/CLI/worker, not a web app. Crypto hygiene was still checked and found nothing to flag. If this codebase becomes web-facing, the dimension reactivates automatically.
X2 Cancellation propagation — no async methods found
X5 Nullable reference types — no NRT-eligible projects

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.

Issue — 25 finding(s)

D29 · Static Analysis (SAST) · High · ×23

High: github-actions-mutable-action-tag .github/workflows/main.yml:20 — 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@8ade135a41bc03ea155e62e844d188df1ea18608`.
High: github-actions-mutable-action-tag .github/workflows/main.yml:28 — 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@8ade135a41bc03ea155e62e844d188df1ea18608`.
High: github-actions-mutable-action-tag .github/workflows/main.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: actions/checkout@8ade135a41bc03ea155e62e844d188df1ea18608`.
High: tainted-sql-string connector/src/it/scala/com/datastax/bdp/spark/search/SearchAnalyticsIntegrationSpec.scala:455 — User data flows into this manually-constructed SQL string. User data can be safely inserted into SQL strings using prepared statements or an object-relational mapper (ORM). Manually-constructed SQL strings is a possible indicator of SQL injection, which could let an attacker steal or manipulate data from the database. Instead, use prepared statements (`connection.PreparedStatement`) or a safe library.
High: tainted-sql-string connector/src/it/scala/com/datastax/spark/connector/SparkCassandraITFlatSpecBase.scala:249 — User data flows into this manually-constructed SQL string. User data can be safely inserted into SQL strings using prepared statements or an object-relational mapper (ORM). Manually-constructed SQL strings is a possible indicator of SQL injection, which could let an attacker steal or manipulate data from the database. Instead, use prepared statements (`connection.PreparedStatement`) or a safe library.
High: tainted-sql-string connector/src/it/scala/com/datastax/spark/connector/cql/sai/SaiBaseSpec.scala:50 — User data flows into this manually-constructed SQL string. User data can be safely inserted into SQL strings using prepared statements or an object-relational mapper (ORM). Manually-constructed SQL strings is a possible indicator of SQL injection, which could let an attacker steal or manipulate data from the database. Instead, use prepared statements (`connection.PreparedStatement`) or a safe library.
High: tainted-sql-string connector/src/it/scala/com/datastax/spark/connector/datasource/CassandraCatalogSpecBase.scala:49 — User data flows into this manually-constructed SQL string. User data can be safely inserted into SQL strings using prepared statements or an object-relational mapper (ORM). Manually-constructed SQL strings is a possible indicator of SQL injection, which could let an attacker steal or manipulate data from the database. Instead, use prepared statements (`connection.PreparedStatement`) or a safe library.
High: tainted-sql-string connector/src/it/scala/com/datastax/spark/connector/datasource/CassandraCatalogSpecBase.scala:64 — User data flows into this manually-constructed SQL string. User data can be safely inserted into SQL strings using prepared statements or an object-relational mapper (ORM). Manually-constructed SQL strings is a possible indicator of SQL injection, which could let an attacker steal or manipulate data from the database. Instead, use prepared statements (`connection.PreparedStatement`) or a safe library.
High: tainted-sql-string connector/src/it/scala/com/datastax/spark/connector/rdd/DseGraphUnionRDDSpec.scala:61 — User data flows into this manually-constructed SQL string. User data can be safely inserted into SQL strings using prepared statements or an object-relational mapper (ORM). Manually-constructed SQL strings is a possible indicator of SQL injection, which could let an attacker steal or manipulate data from the database. Instead, use prepared statements (`connection.PreparedStatement`) or a safe library.
High: tainted-sql-string connector/src/it/scala/com/datastax/spark/connector/sql/CassandraDataFrameDateBehaviors.scala:46 — User data flows into this manually-constructed SQL string. User data can be safely inserted into SQL strings using prepared statements or an object-relational mapper (ORM). Manually-constructed SQL strings is a possible indicator of SQL injection, which could let an attacker steal or manipulate data from the database. Instead, use prepared statements (`connection.PreparedStatement`) or a safe library.
High: tainted-sql-string connector/src/it/scala/com/datastax/spark/connector/sql/CassandraDataFrameDateBehaviors.scala:47 — User data flows into this manually-constructed SQL string. User data can be safely inserted into SQL strings using prepared statements or an object-relational mapper (ORM). Manually-constructed SQL strings is a possible indicator of SQL injection, which could let an attacker steal or manipulate data from the database. Instead, use prepared statements (`connection.PreparedStatement`) or a safe library.
High: tainted-sql-string connector/src/it/scala/com/datastax/spark/connector/sql/CassandraDataFrameDateBehaviors.scala:48 — User data flows into this manually-constructed SQL string. User data can be safely inserted into SQL strings using prepared statements or an object-relational mapper (ORM). Manually-constructed SQL strings is a possible indicator of SQL injection, which could let an attacker steal or manipulate data from the database. Instead, use prepared statements (`connection.PreparedStatement`) or a safe library.
High: tainted-sql-string connector/src/it/scala/com/datastax/spark/connector/sql/CassandraDataFrameDateBehaviors.scala:89 — User data flows into this manually-constructed SQL string. User data can be safely inserted into SQL strings using prepared statements or an object-relational mapper (ORM). Manually-constructed SQL strings is a possible indicator of SQL injection, which could let an attacker steal or manipulate data from the database. Instead, use prepared statements (`connection.PreparedStatement`) or a safe library.
High: tainted-sql-string connector/src/it/scala/com/datastax/spark/connector/sql/CassandraDataFrameDateBehaviors.scala:92 — User data flows into this manually-constructed SQL string. User data can be safely inserted into SQL strings using prepared statements or an object-relational mapper (ORM). Manually-constructed SQL strings is a possible indicator of SQL injection, which could let an attacker steal or manipulate data from the database. Instead, use prepared statements (`connection.PreparedStatement`) or a safe library.
High: tainted-sql-string connector/src/it/scala/com/datastax/spark/connector/sql/CassandraDataSourceSpec.scala:111 — User data flows into this manually-constructed SQL string. User data can be safely inserted into SQL strings using prepared statements or an object-relational mapper (ORM). Manually-constructed SQL strings is a possible indicator of SQL injection, which could let an attacker steal or manipulate data from the database. Instead, use prepared statements (`connection.PreparedStatement`) or a safe library.
High: tainted-sql-string connector/src/main/scala/com/datastax/spark/connector/datasource/JoinHelper.scala:86 — User data flows into this manually-constructed SQL string. User data can be safely inserted into SQL strings using prepared statements or an object-relational mapper (ORM). Manually-constructed SQL strings is a possible indicator of SQL injection, which could let an attacker steal or manipulate data from the database. Instead, use prepared statements (`connection.PreparedStatement`) or a safe library.
High: tainted-sql-string connector/src/main/scala/com/datastax/spark/connector/datasource/ScanHelper.scala:125 — User data flows into this manually-constructed SQL string. User data can be safely inserted into SQL strings using prepared statements or an object-relational mapper (ORM). Manually-constructed SQL strings is a possible indicator of SQL injection, which could let an attacker steal or manipulate data from the database. Instead, use prepared statements (`connection.PreparedStatement`) or a safe library.
High: tainted-sql-string connector/src/main/scala/com/datastax/spark/connector/rdd/CassandraCoGroupedRDD.scala:128 — User data flows into this manually-constructed SQL string. User data can be safely inserted into SQL strings using prepared statements or an object-relational mapper (ORM). Manually-constructed SQL strings is a possible indicator of SQL injection, which could let an attacker steal or manipulate data from the database. Instead, use prepared statements (`connection.PreparedStatement`) or a safe library.
High: tainted-sql-string connector/src/main/scala/com/datastax/spark/connector/rdd/CassandraMergeJoinRDD.scala:116 — User data flows into this manually-constructed SQL string. User data can be safely inserted into SQL strings using prepared statements or an object-relational mapper (ORM). Manually-constructed SQL strings is a possible indicator of SQL injection, which could let an attacker steal or manipulate data from the database. Instead, use prepared statements (`connection.PreparedStatement`) or a safe library.
High: tainted-sql-string connector/src/main/scala/com/datastax/spark/connector/rdd/partitioner/DataSizeEstimates.scala:125 — User data flows into this manually-constructed SQL string. User data can be safely inserted into SQL strings using prepared statements or an object-relational mapper (ORM). Manually-constructed SQL strings is a possible indicator of SQL injection, which could let an attacker steal or manipulate data from the database. Instead, use prepared statements (`connection.PreparedStatement`) or a safe library.
High: tainted-sql-string connector/src/main/scala/com/datastax/spark/connector/util/PatitionKeyTools.scala:40 — User data flows into this manually-constructed SQL string. User data can be safely inserted into SQL strings using prepared statements or an object-relational mapper (ORM). Manually-constructed SQL strings is a possible indicator of SQL injection, which could let an attacker steal or manipulate data from the database. Instead, use prepared statements (`connection.PreparedStatement`) or a safe library.
High: tainted-sql-string connector/src/main/scala/com/datastax/spark/connector/writer/TableWriter.scala:94 — User data flows into this manually-constructed SQL string. User data can be safely inserted into SQL strings using prepared statements or an object-relational mapper (ORM). Manually-constructed SQL strings is a possible indicator of SQL injection, which could let an attacker steal or manipulate data from the database. Instead, use prepared statements (`connection.PreparedStatement`) or a safe library.
High: tainted-sql-string connector/src/main/scala/org/apache/spark/sql/cassandra/SolrPredicateRules.scala:393 — User data flows into this manually-constructed SQL string. User data can be safely inserted into SQL strings using prepared statements or an object-relational mapper (ORM). Manually-constructed SQL strings is a possible indicator of SQL injection, which could let an attacker steal or manipulate data from the database. Instead, use prepared statements (`connection.PreparedStatement`) or a safe library.

D13 · Secret Scanning · Leaked secret · ×1

Leaked secret: private-key test-support/src/main/resources/client.key:1 — private-key detected.

D18 · Solution Shape · Dimension evaluation failed · ×1

Dimension evaluation failed — no .NET solution found at target path

Warning — 17 finding(s)

D19 · Documentation Quality · LLM evaluation failed · ×1

LLM evaluation failed — JSON parse error: Expected end of string, but instead reached end of data. Path: $.findings[0].suggestion | LineNumber: 0 | BytePositionInLine: 1265.

D20 · ADR Quality · No consequences/trade-offs section describing what will happen to existing Spark-Cassandra embedded test code · ×1

No consequences/trade-offs section describing what will happen to existing Spark-Cassandra embedded test code doc/10_embedded.md — Add a Consequences section noting that any remaining embedded tests must be migrated to the new CCM-based framework and how to do so

D20 · ADR Quality · Context/problem (which version to prefer) and consequences/trade-offs are not stated in the visible text · ×1

Context/problem (which version to prefer) and consequences/trade-offs are not stated in the visible text doc/12_building_and_artifacts.md — Add a Context section explaining why Scala 2.11 artifacts matter and a Consequences section noting trade-offs of preferring main over assembly

D20 · ADR Quality · No context/problem and no consequences/trade-offs for setting up Cassandra/Spark (e.g. resource cost of running stand-alone Spark) · ×1

No context/problem and no consequences/trade-offs for setting up Cassandra/Spark (e.g. resource cost of running stand-alone Spark) doc/13_1_setup_spark_shell.md — Add a Context section explaining why Cassandra/Spark setup is needed and a Consequences section noting operational overhead of standalone mode

D4 · Code Duplication · Duplicated block (608 lines × 2) · ×1

Duplicated block (608 lines × 2) connector/src/main/java/com/datastax/spark/connector/japi/CassandraJavaUtil.java:996 — connector/src/main/java/com/datastax/spark/connector/japi/CassandraJavaUtil.java:996-1045 | connector/src/main/java/com/datastax/spark/connector/japi/CassandraJavaUtil.java:1779-2386

D4 · Code Duplication · Duplicated block (212 lines × 2) · ×1

Duplicated block (212 lines × 2) connector/src/main/java/com/datastax/spark/connector/japi/RDDAndDStreamCommonJavaFunctions.java:197 — connector/src/main/java/com/datastax/spark/connector/japi/RDDAndDStreamCommonJavaFunctions.java:197-184 | connector/src/main/java/com/datastax/spark/connector/japi/RDDAndDStreamCommonJavaFunctions.java:254-465

D4 · Code Duplication · Duplicated block (211 lines × 4) · ×1

Duplicated block (211 lines × 4) connector/src/main/java/com/datastax/spark/connector/japi/RDDAndDStreamCommonJavaFunctions.java:197 — connector/src/main/java/com/datastax/spark/connector/japi/RDDAndDStreamCommonJavaFunctions.java:197-183 | connector/src/main/java/com/datastax/spark/connector/japi/RDDAndDStreamCommonJavaFunctions.java:216-233 | connector/src/main/java/com/datastax/spark/connector/japi/RDDAndDStreamCommonJavaFunctions.java:235-195 | connector/src/main/java/com/datastax/spark/connector/japi/RDDAndDStreamCommonJavaFunctions.java:254-464

D4 · Code Duplication · Duplicated block (54 lines × 15) · ×1

Duplicated block (54 lines × 15) connector/src/main/java/com/datastax/spark/connector/japi/CassandraJavaUtil.java:1918 — connector/src/main/java/com/datastax/spark/connector/japi/CassandraJavaUtil.java:1918-1945 | connector/src/main/java/com/datastax/spark/connector/japi/CassandraJavaUtil.java:1946-248 | connector/src/main/java/com/datastax/spark/connector/japi/CassandraJavaUtil.java:1976-2007 | connector/src/main/java/com/datastax/spark/connector/japi/CassandraJavaUtil.java:2008-2041 | connector/src/main/java/com/datastax/spark/connector/japi/CassandraJavaUtil.java:2042-2077 | connector/src/main/java/com/datastax/spark/connector/japi/CassandraJavaUtil.java:2078-2115 | connector/src/main/java/com/datastax/spark/connector/japi/CassandraJavaUtil.java:2116-2155 | connector/src/main/java/com/datastax/spark/connector/japi/CassandraJavaUtil.java:2156-2197 | connector/src/main/java/com/datastax/spark/connector/japi/CassandraJavaUtil.java:2198-2241 | connector/src/main/java/com/datastax/spark/connector/japi/CassandraJavaUtil.java:2242-2287 | connector/src/main/java/com/datastax/spark/connector/japi/CassandraJavaUtil.java:2288-2335 | connector/src/main/java/com/datastax/spark/connector/japi/CassandraJavaUtil.java:2336-1777 | connector/src/main/java/com/datastax/spark/connector/japi/CassandraJavaUtil.java:2386-2437 | connector/src/main/java/com/datastax/spark/connector/japi/CassandraJavaUtil.java:2438-2491 | connector/src/main/java/com/datastax/spark/connector/japi/CassandraJavaUtil.java:2492-1791

D4 · Code Duplication · Duplicated block (54 lines × 2) · ×1

Duplicated block (54 lines × 2) connector/src/main/java/com/datastax/spark/connector/japi/CassandraJavaUtil.java:1098 — connector/src/main/java/com/datastax/spark/connector/japi/CassandraJavaUtil.java:1098-1151 | connector/src/main/java/com/datastax/spark/connector/japi/CassandraJavaUtil.java:2439-2492

D4 · Code Duplication · Duplicated block (52 lines × 2) · ×1

Duplicated block (52 lines × 2) connector/src/main/java/com/datastax/spark/connector/japi/CassandraJavaUtil.java:1046 — connector/src/main/java/com/datastax/spark/connector/japi/CassandraJavaUtil.java:1046-1097 | connector/src/main/java/com/datastax/spark/connector/japi/CassandraJavaUtil.java:2387-2438

D4 · Code Duplication · Duplicated block (48 lines × 2) · ×1

Duplicated block (48 lines × 2) connector/src/main/java/com/datastax/spark/connector/japi/CassandraJavaUtil.java:948 — connector/src/main/java/com/datastax/spark/connector/japi/CassandraJavaUtil.java:948-995 | connector/src/main/java/com/datastax/spark/connector/japi/CassandraJavaUtil.java:2289-2336

D4 · Code Duplication · Duplicated block (37 lines × 2) · ×1

Duplicated block (37 lines × 2) connector/src/main/java/com/datastax/spark/connector/japi/CassandraJavaUtil.java:1152 — connector/src/main/java/com/datastax/spark/connector/japi/CassandraJavaUtil.java:1152-1188 | connector/src/main/java/com/datastax/spark/connector/japi/CassandraJavaUtil.java:1672-1688

D4 · Code Duplication · Duplicated block (20 lines × 2) · ×1

Duplicated block (20 lines × 2) connector/src/main/java/com/datastax/spark/connector/japi/CassandraJavaUtil.java:395 — connector/src/main/java/com/datastax/spark/connector/japi/CassandraJavaUtil.java:395-414 | connector/src/main/java/com/datastax/spark/connector/japi/CassandraJavaUtil.java:423-395

D4 · Code Duplication · Duplicated block (19 lines × 2) · ×1

Duplicated block (19 lines × 2) connector/src/main/java/com/datastax/spark/connector/japi/RDDAndDStreamCommonJavaFunctions.java:216 — connector/src/main/java/com/datastax/spark/connector/japi/RDDAndDStreamCommonJavaFunctions.java:216-234 | connector/src/main/java/com/datastax/spark/connector/japi/RDDAndDStreamCommonJavaFunctions.java:235-196

D4 · Code Duplication · Duplicated block (11 lines × 2) · ×1

Duplicated block (11 lines × 2) connector/src/main/java/com/datastax/spark/connector/japi/rdd/CassandraTableScanJavaRDD.java:50 — connector/src/main/java/com/datastax/spark/connector/japi/rdd/CassandraTableScanJavaRDD.java:50-60 | connector/src/main/java/com/datastax/spark/connector/japi/rdd/CassandraTableScanJavaRDD.java:65-70

D4 · Code Duplication · Duplicated block (5 lines × 3) · ×1

Duplicated block (5 lines × 3) connector/src/main/java/com/datastax/spark/connector/japi/RDDAndDStreamCommonJavaFunctions.java:197 — connector/src/main/java/com/datastax/spark/connector/japi/RDDAndDStreamCommonJavaFunctions.java:197-201 | connector/src/main/java/com/datastax/spark/connector/japi/RDDAndDStreamCommonJavaFunctions.java:216-220 | connector/src/main/java/com/datastax/spark/connector/japi/RDDAndDStreamCommonJavaFunctions.java:235-239

D8 · Code Coverage · Coverage not measured · ×1

Coverage not measured — test suite did not build — Coverage NOT MEASURED: the repo's own test suite did not build (a C#/MSBuild compiler error in the test code), so no coverage could be collected. It is excluded from the score rather than counted as a near-zero defect. Fix the test build, or commit the Cobertura/OpenCover/lcov report your CI already produces, and real coverage will be measured.

Recommendation — 3 finding(s)

D11 · Test Reliability · Test reliability not included · ×1

Test reliability not included — No test projects found, so reliability couldn't be assessed.

D28 · Secrets (history) · Rotate the exposed credentials · ×1

Rotate the exposed credentials — git history can't be un-committed — Some of these secrets are in git HISTORY: deleting the file does not remove them (the commit persists on every clone, fork and backup). The remediation is to ROTATE each historically-exposed credential and treat it as compromised — not to delete the file. Rewriting history is disruptive and unreliable across existing forks. (Working-tree-only secrets — no commit — can instead be removed from the file and moved to a secret store.)

D9 · Test Distribution · No tests found · ×1

No tests found — No test projects found in the repository.

Info — 1 finding(s)

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.

Dimension	Tool	Version	Command	Findings	Raw output
D28 · Secrets (history)	gitleaks	—	gitleaks detect --no-banner --report-format json --report-path /dev/stdout --exit-code 0 --source .	87	artifacts/raw/gitleaks-history.json
D29 · Static Analysis (SAST)	semgrep	—	semgrep --config /opt/semgrep-rules/security-audit.yml --config /opt/semgrep-rules/owasp-top-ten.yml --json --quiet --timeout 0 --metrics off .	23	artifacts/raw/semgrep.json
D30 · Dependency Vulnerabilities	dotnet (no .NET solution)	—	dotnet (no .NET solution): not present in this environment	0	—
D31 · IaC & Container Security	trivy	—	trivy: not applicable — No Infrastructure-as-Code or container manifests found (Dockerfile, Terraform, Kubernetes/Helm, CloudFormation); nothing to scan.	0	—
D32 · Data Compliance (PII/GDPR)	semgrep	—	semgrep: not applicable — No PII/GDPR ruleset is bundled (the public p/gdpr semgrep pack was retired) — data compliance is not assessed in this scan.	0	—
D33 · JS/npm Dependency Vulnerabilities	trivy	—	trivy: not applicable — No JS/npm manifest or lockfile found outside bin/obj (package.json, package-lock.json, yarn.lock, pnpm-lock.yaml, bun.lockb); no JS dependencies to scan.	0	—
D36 · Supply-chain Provenance & Signing	provenance	—	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 NuGet package, a container image, a GitHub release).	0	—
D37 · Vulnerability-disclosure Policy	disclosure	—	disclosure: not applicable — No vulnerability-disclosure policy file found (SECURITY.md, .github/SECURITY.md, docs/SECURITY.md, .well-known/security.txt). A coordinated-disclosure policy may live off-repo, so this is not evidenced rather than failed.	0	—
D38 · OSV Dependency Vulnerabilities	osv-scanner	—	osv-scanner: not applicable — No JS/npm lockfile found outside bin/obj (package-lock.json, yarn.lock, pnpm-lock.yaml, bun.lockb); nothing for OSV to scan.	0	—

Run 019fdcfa-996b-7a7d-9615-9f05004e646c · every finding is also locatable in findings.md, and the complete scoring record (with exit codes + durations) in sidecar.json.

Apache/cassandra-Spark-Connector

Executive summary

Top priorities

Diagnosis — what's actually going on

At a glance — Code Health · 97% · Exemplary

At a glance — Architecture · 96% · Exemplary

At a glance — Maturity · 64% · Adequate · gated by M2

At a glance — Readiness · 23% · Critical · gated by D9, P2, P3

At a glance — Security · 1% · Critical · gated by D28, D29

Security & Compliance — OWASP Top-10 mapping

Roadmap

File quality

Methodology & how to trust this report

Tools & methods

Run transparency — what happened this run

Limitations & what we did not check

Per-dimension blind spots

The LLM boundary

Dimensions

Frontend & cross-cutting dimensions

Reference — by lens

Appendix A — Findings (grouped)

Appendix B — Reproduction & audit trail

Downloadable artifacts