I’m sharing this because I think your architecture‑moat ambitions for Stella Ops map really well onto what’s already emerging in SBOM/VEX + call‑graph / contextual‑analysis tooling — and you could use those ideas to shape Stella Ops’ “policy + proof‑market” features.

![Image](https://media.licdn.com/dms/image/v2/D4E10AQEoFUPDMr5QLA/image-shrink_800/image-shrink_800/0/1722522453006?e=2147483647\&t=9-LR6W8KjhwT3A2wJY_eVH9FEpNV8wGYRbQUzN00uHg\&v=beta)

![Image](https://docs.snyk.io/~gitbook/image?height=630\&sign=dcd0a8fe\&sv=2\&url=https%3A%2F%2F2533899886-files.gitbook.io%2F~%2Ffiles%2Fv0%2Fb%2Fgitbook-x-prod.appspot.com%2Fo%2Fspaces%252F-MdwVZ6HOZriajCf5nXH%252Fsocialpreview%252FoBTkxPamYEBso7JhPIeg%252Fgitbook-home.png%3Falt%3Dmedia%26token%3D0d25dc13-6cf8-40f4-97b3-389ce331f856\&width=1200)

![Image](https://speedmedia2.jfrog.com/08612fe1-9391-4cf3-ac1a-6dd49c36b276/media.jfrog.com/wp-content/uploads/2023/04/13105443/jas-placeholder.png)

## ✅ What SBOM↔VEX + Reachability / Call‑Path Tools Already Offer

* The combination of Snyk’s “reachability analysis” and Vulnerability Exploitability eXchange (VEX) lets you label each reported vulnerability as **REACHABLE / NO PATH FOUND / NOT APPLICABLE**, based on static call‑graph (or AI‑enhanced analysis) of your actual application code rather than just “this library version has a CVE.” ([Snyk User Docs][1])
* If reachable, Snyk even provides a **“call‑path” view** showing how your code leads to the vulnerable element — giving a human-readable trace from your own functions/modules into the vulnerable dependency. ([Snyk User Docs][1])
* The VEX model (as defined e.g. in CycloneDX) is designed to let you embed exploitability/ context‑specific data alongside a standard SBOM. That way, you don’t just convey “what components are present,” but “which known vulnerabilities actually matter in this build or environment.” ([CycloneDX][2])

In short: SBOM → alerts many potential CVEs. SBOM + VEX + Reachability/Call‑path → highlights only those with an actual path from your code — drastically reducing noise and focusing remediation where it matters.

## 🔧 What Artefact‑ or Container‑Level “Contextual Analysis” Adds (Triage + Proof Trail)

* JFrog Xray’s “Contextual Analysis” (when used on container images or binary artifacts) goes beyond “is the library present” — it tries to reason **whether the vulnerable code is even invoked / relevant in this build**. If not, it marks the CVE as “not exploitable / not applicable.” That dramatically reduces false positives: in one study JFrog found ~78% of reported CVEs in popular DockerHub images were not actually exploitable. ([JFrog][3])
* Contextual Analysis includes a **call‑graph view** (direct vs transitive calls), highlights affected files/functions & line numbers, and lets you copy details for remediation or auditing. ([JFrog][4])
* Combined with SBOM/VEX metadata, this enables a **full proof trail**: you can track from “component in SBOM” → “vulnerability discovered” → “reachable from my code or image” → “call‑path evidence” → “justified exploitability status.” That makes your SBOM/VEX data actionable and auditable without manual spreadsheets or email threads. ([Endor Labs][5])

## 🎯 Why This Matters for Stella Ops’ Moats

Given your ambitious Stella Ops design — deterministic scans, reproducible proofs, cryptographically verifiable supply‑chain attestations — this established workflow model is a **very powerful blueprint**:

* You could integrate call‑graph reachability + artifact‑level contextual analysis directly into your “Proof‑of‑Integrity Graph,” giving customers a **clear, machine‑readable + human‑auditable exploitability verdict** per vulnerability.
* The “one‑click evidence” model (call‑path + signed SBOM/VEX + transparency‑log index) maps neatly onto your planned **Proof‑Market Ledger** / “trust‑credit” economy: consumers see not just “vulnerable component included,” but “here’s the exact evidence proving it is or isn’t reachable/exploitable.”
* It also supports **tiered remediation prioritization** (e.g. reachable + high severity + business‑critical vs unreachable / low‑impact), reducing burden on teams just like Snyk and JFrog do for their customers.

## 🧑‍💻 What’s Still Missing / What You Should Improve

* Reachability analysis — especially static — is not perfect: “NO PATH FOUND” doesn’t guarantee “never exploitable.” Reflection, dynamic loading, environment‑specific behavior can cause false negatives. ([Snyk User Docs][1])
* VEX annotations often remain **semi‑manual or vendor‑supplied** — but for a fully trust‑worthy "Proof‑Market," you’ll need **automated generation + strong signing + revocation / update mechanisms** (which seems aligned with what you planned).
* For containerized builds, the contextual analysis must tie SBOM entries to actual runtime/packaged artifacts — your deterministic rebuild + binary lineage + transparency‑log approach could help guarantee that.

---

I think combining SBOM + VEX + reachability/call‑path + artifact‑level contextual analysis gives a **real, operational model** that matches what you envision for Stella Ops — but with some limitations that your added layers (cryptographic signing, replayability, trust‑market) can uniquely address.

If you like — I can **sketch a minimal architecture** (modules & data flow) that implements exactly that model in Stella Ops (call‑graph analyzer → VEX annotator → signed bundle → ledger entry).

[1]: https://docs.snyk.io/manage-risk/prioritize-issues-for-fixing/reachability-analysis?utm_source=chatgpt.com "Reachability analysis | Snyk User Docs"
[2]: https://cyclonedx.org/capabilities/vex/?utm_source=chatgpt.com "Vulnerability Exploitability eXchange (VEX)"
[3]: https://jfrog.com/blog/turns-out-78-of-reported-cves-on-top-dockerhub-images-are-not-really-exploitable/?utm_source=chatgpt.com "Turns out 78% of reported common CVEs on top ..."
[4]: https://jfrog.com/help/r/jfrog-security-user-guide/products/advanced-security/features-and-capabilities/contextual-analysis-of-cves?utm_source=chatgpt.com "Contextual Analysis of CVEs"
[5]: https://www.endorlabs.com/learn/how-cyclonedx-vex-makes-your-sbom-useful?utm_source=chatgpt.com "How CycloneDX VEX Makes Your SBOM Useful | Blog"
Stella Ops’ big advantage can be: **turn “security findings” into “verifiable claims with evidence”**—portable across org boundaries, continuously updateable, and audit-friendly—by combining SBOM + VEX + reachability/call-path + signed provenance into one evidence graph.

## Stella Ops advantages (what becomes uniquely hard to copy)

### 1) Actionable vulnerability truth, not CVE spam

SBOMs tell you *what’s present*; VEX tells you *whether a known vuln matters in your specific context* (affected vs not_affected vs fixed vs under_investigation), which is the difference between “alert fatigue” and prioritized remediation. ([cyclonedx.org][1])

**Stella Ops moat:** VEX isn’t just a checkbox—it’s backed by *machine-verifiable evidence* (reachability traces, policy decisions, build lineage).

---

### 2) “Evidence bundles” that any downstream can verify

If every release ships with:

* SBOM (what’s in it)
* VEX (what matters + why)
* Provenance/attestations (how it was built)
* Signatures + transparency log inclusion

…then downstream teams can verify claims *without trusting your internal tooling*.

This mirrors best practices in the supply-chain world: SLSA recommends distributing provenance and using transparency logs as part of verification. ([SLSA][2])
Sigstore also standardizes “bundles” that can include DSSE-wrapped attestations plus transparency log material/timestamps. ([Sigstore][3])

**Stella Ops moat:** “Proof packaging + verification UX” becomes a platform primitive, not an afterthought.

---

### 3) A unified **Proof Graph** (the missing layer in most tooling)

Most tools produce *reports*. Stella Ops can maintain a **typed graph**:

`source commit → build step(s) → artifact digest → SBOM components → CVEs → reachability evidence → VEX statements → signers → log inclusion`

That graph lets you answer hard questions fast:

* “Is CVE-XXXX exploitable in prod image sha256:…?”
* “Show the call-path evidence or runtime proof.”
* “Which policy or signer asserted not_affected, and when?”

SPDX 3.x explicitly aims to support vulnerability metadata (including VEX fields) in a way that can evolve as security knowledge changes. ([spdx.dev][4])

**Moat:** graph-scale lineage + queryability + verification, not just scanning.

---

### 4) Reachability becomes **a signed, reviewable artifact**

Reachability analysis commonly produces statuses like “REACHABLE / NO PATH FOUND / NOT APPLICABLE.” ([docs.snyk.io][5])
Stella Ops can store:

* the reachability result,
* the methodology (static, runtime, hybrid),
* confidence/coverage,
* and the call-path (optionally redacted),
  then sign it and tie it to a specific artifact digest.

**Moat:** you’re not asking teams to *trust* a reachability claim—you’re giving them something they can verify and audit.

---

### 5) Continuous updates without chaos (versioned statements, not tribal knowledge)

VEX statements change over time (“under_investigation” → “not_affected” or “affected”). OpenVEX requires that “not_affected” includes a justification or an impact statement—so consumers can understand *why* it’s not affected. ([GitHub][6])
Stella Ops can make those transitions explicit and signed, with append-only history.

**Moat:** an operational truth system for vulnerability status, not a spreadsheet.

---

### 6) “Proof Market” (if you want the deep moat)

Once evidence is a first-class signed object, you can support multiple signers:

* vendor (you),
* third-party auditors,
* internal security team,
* trusted scanner services.

A “proof market” is essentially: **policy chooses whose attestations count** for which claims. (You can start simple—just “org signers”—and expand.)

**Moat:** trust-routing + signer reputation + network effects.

---

## Developer guidelines (for teams adopting Stella Ops)

### A. Build + identity: make artifacts verifiable

1. **Anchor everything to an immutable subject**
   Use the *artifact digest* (e.g., OCI image digest) as the primary key for SBOM, VEX, provenance, reachability results.

2. **Aim for reproducible-ish builds**
   Pin dependencies (lockfiles), pin toolchains, and record build inputs/params in provenance. The goal is: “same inputs → same digest,” or at least “digest ↔ exact inputs.” (Even partial determinism pays off.)

3. **Use standard component identifiers**
   Prefer PURLs for dependencies and keep them consistent across SBOM + VEX. (This avoids “can’t match vulnerability to component” pain.)

---

### B. SBOM: generate it like you mean it

4. **Generate SBOMs at the right layer(s)**

* Source-level SBOM (dependency graph)
* Artifact/container SBOM (what actually shipped)

If they disagree, treat that as a signal—your build pipeline is mutating inputs.

5. **Don’t weld vulnerability state into SBOM unless you must**
   It’s often cleaner operationally to publish SBOM + separate VEX (since vuln knowledge changes faster). SPDX 3.x explicitly supports richer, evolving security/vulnerability info. ([spdx.dev][4])

---

### C. VEX: make statuses evidence-backed and automatable

6. **Use the standard status set**
   Common VEX implementations use:

* `affected`
* `not_affected`
* `fixed`
* `under_investigation` ([Docker Documentation][7])

7. **Require justification for `not_affected`**
   OpenVEX requires a status justification or an impact statement for `not_affected`. ([GitHub][6])
   Practical rule: no “not_affected” without one of:

* “vulnerable code not in execute path” (+ evidence)
* “component not present”
* “inline mitigations exist”
  …plus a link to the supporting artifact(s).

8. **Version and timestamp VEX statements**
   Treat VEX like a living contract. Consumers need to know what changed and when.

---

### D. Reachability / contextual analysis: avoid false certainty

9. **Treat reachability as “evidence with confidence,” not absolute truth**
   Static reachability is great but imperfect (reflection, plugins, runtime dispatch). Operationally:

* `REACHABLE` → prioritize
* `NO PATH FOUND` → deprioritize, don’t ignore
* `NOT APPLICABLE` → fall back to other signals ([docs.snyk.io][5])

10. **Attach the “why”: call-path or runtime proof**
    If you claim “reachable,” include the call path (or a redacted proof).
    If you claim “not_affected,” include the justification and a reachability artifact.

---

### E. Signing + distribution: ship proofs the way you ship artifacts

11. **Bundle evidence and sign it**
    A practical Stella Ops “release bundle” looks like:

* `sbom.(cdx|spdx).json`
* `vex.(openvex|cdx|spdx|csaf).json`
* `provenance.intoto.json`
* `reachability.json|sarif`
* `bundle.sigstore.json` (or equivalent)

Sigstore’s bundle format supports DSSE envelopes over attestations and can include transparency log entry material/timestamps. ([Sigstore][3])

12. **Publish to an append-only transparency log**
    Transparency logs are valuable because they’re auditable and append-only; monitors can check consistency/inclusion. ([Sigstore][8])

---

### F. Policy: gate on what matters, not what’s loud

13. **Write policies in terms of (severity × exploitability × confidence)**
    Example policy pattern:

* Block deploy if: `affected AND reachable AND critical`
* Warn if: `affected AND no_path_found`
* Allow with waiver if: `under_investigation` but time-boxed and signed

14. **Make exceptions first-class and expiring**
    Exceptions should be signed statements tied to artifact digests, with TTL and rationale.

---

## Developer guidelines (for engineers building Stella Ops itself)

1. **Everything is a signed claim about a subject**
   Model each output as: `subject digest + predicate + evidence + signer + time`.

2. **Support multiple VEX formats, but normalize internally**
   There are multiple VEX implementations (e.g., CycloneDX, SPDX, OpenVEX, CSAF); normalize into a canonical internal model so policy doesn’t care about input format. ([Open Source Security Foundation][9])

3. **Expose uncertainty**
   Store:

* analysis method (static/runtime/hybrid),
* coverage (entrypoints, languages supported),
* confidence score,
* and known limitations.
  This prevents “NO PATH FOUND” being treated as “impossible.”

4. **Make verification fast and offline-friendly**
   Cache transparency log checkpoints, ship inclusion proofs in bundles, and support air-gapped verification flows where possible.

5. **Design for redaction**
   Call-path evidence can leak internals. Provide:

* full evidence (internal),
* redacted evidence (external),
* plus hash-based linking so the two correspond.

6. **Build plugin rails**
   Reachability analyzers, SBOM generators, scanners, and policy engines will vary by ecosystem. A stable plugin interface is key for adoption.

---

If you want a crisp deliverable to hand to engineering, you can lift the above into a 1–2 page “Stella Ops Integration Guide” with: **pipeline steps, required artifacts, recommended policy defaults, and a VEX decision checklist**.

[1]: https://cyclonedx.org/capabilities/vex/?utm_source=chatgpt.com "Vulnerability Exploitability eXchange (VEX)"
[2]: https://slsa.dev/spec/v1.0/distributing-provenance?utm_source=chatgpt.com "Distributing provenance"
[3]: https://docs.sigstore.dev/about/bundle/?utm_source=chatgpt.com "Sigstore Bundle Format"
[4]: https://spdx.dev/capturing-software-vulnerability-data-in-spdx-3-0/?utm_source=chatgpt.com "Capturing Software Vulnerability Data in SPDX 3.0"
[5]: https://docs.snyk.io/manage-risk/prioritize-issues-for-fixing/reachability-analysis?utm_source=chatgpt.com "Reachability analysis | Snyk User Docs"
[6]: https://github.com/openvex/spec/blob/main/OPENVEX-SPEC.md?utm_source=chatgpt.com "spec/OPENVEX-SPEC.md at main"
[7]: https://docs.docker.com/scout/how-tos/create-exceptions-vex/?utm_source=chatgpt.com "Create an exception using the VEX"
[8]: https://docs.sigstore.dev/logging/overview/?utm_source=chatgpt.com "Rekor"
[9]: https://openssf.org/blog/2023/09/07/vdr-vex-openvex-and-csaf/?utm_source=chatgpt.com "VDR, VEX, OpenVEX and CSAF"