Add Christmass advisories

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StellaOps Bot
2025-12-25 20:15:19 +02:00
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Heres a tight, practical blueprint for evolving StellaOpss policy engine into a **fully deterministic verdict engine**—so the *same SBOM + VEX + reachability subgraph ⇒ the exact same, replayable verdict* every time, with auditorgrade trails and signed “delta verdicts.”
# Why this matters (quick)
* **Reproducibility:** auditors can replay any scan and get identical results.
* **Trust & scale:** crossagent consensus via contentaddressed inputs and signed outputs.
* **Operational clarity:** diffs between builds become crisp, machineverifiable artifacts.
# Core principles
* **Determinism-first:** no wallclock time, no random iteration order, no network during evaluation.
* **Contentaddressing:** hash every *input* (SBOM, VEX docs, reachability subgraph, policy set, rule versions, feed snapshots).
* **Declarative state:** a compact **Scan Manifest** lists input hashes + policy bundle hash + engine version.
* **Pure evaluation:** the verdict function is referentially transparent: `Verdict = f(Manifest)`.
# Data artifacts
* **Scan Manifest (`manifest.jsonc`)**
* `sbom_sha256`, `vex_set_sha256[]`, `reach_subgraph_sha256`, `feeds_snapshot_sha256`, `policy_bundle_sha256`, `engine_version`, `policy_semver`, `options_hash`
* **Verdict (`verdict.json`)**
* canonical JSON (stable key order); includes:
* `risk_score`, `status` (pass/warn/fail), `unknowns_count`
* **evidence_refs:** content IDs for cited VEX statements, nodes/edges from reachability, CVE records, featureflags, envguards
* **explanations:** stable, templatedriven strings (+ machine reasons)
* **Delta Verdict (`delta.json`)**
* computed between two manifests/verdicts:
* `added_findings[]`, `removed_findings[]`, `severity_shift[]`, `unknowns_delta`, `policy_effects[]`
* signed (DSSE/COSE/JWS), timestamped, and linkable to both verdicts
# Engine architecture (deterministic path)
1. **Normalize inputs**
* SBOM: sort by `packageUrl`/`name@version`; resolve aliases; freeze semver comparison rules.
* VEX: normalize provider → `vex_id`, `product_ref`, `status` (`affected`, `not_affected`, …), *with* source trust score precomputed from a **trust registry** (strict, versioned).
* Reachability: store subgraph as adjacency lists sorted by node ID; hash after topological stable ordering.
* Feeds: lock to a **snapshot** (timestamp + commit/hash); no live calls.
2. **Policy bundle**
* Declarative rules (e.g., lattice/merge semantics), compiled to a **canonical IR** (e.g., OPARego → sorted DNF).
* Merge precedence is explicit (e.g., `vendor > distro > internal` can be replaced by a latticemerge table).
* Unknowns policy baked in: e.g., `fail_if_unknowns > N in prod`.
3. **Evaluation**
* Build a **finding set**: `(component, vuln, context)` tuples with deterministic IDs.
* Apply **latticebased VEX merge** (proofcarrying): each suppression must carry an evidence pointer (feature flag off, code path unreachable, patchedbackport proof).
* Compute final `status` and `risk_score` using fixedprecision math; round rules are part of the bundle.
4. **Emit**
* Canonicalize verdict JSON; attach **evidence map** (content IDs only).
* Sign verdict; attach as **OCI attestation** to image/digest.
# APIs (minimal but complete)
* `POST /evaluate` → returns `verdict.json` + attestation
* `POST /delta` with `{base_verdict, head_verdict}``delta.json` (signed)
* `GET /replay?manifest_sha=` → reexecutes using cached snapshot bundles, returns the same `verdict_sha`
* `GET /evidence/:cid` → fetches immutable evidence blobs (offlineready)
# Storage & indexing
* **CAS (contentaddressable store):** `/evidence/<sha256>` for SBOM/VEX/graphs/feeds/policies.
* **Verdict registry:** keyed by `(image_digest, manifest_sha, engine_version)`.
* **Delta ledger:** appendonly, signed; supports crossagent consensus (multiple engines can cosign identical deltas).
# UI slices (where it lives)
* **Run details → “Verdict” tab:** status, risk score, unknowns, top evidence links.
* **“Diff” tab:** render **Delta Verdict** (added/removed/changed), with drilldown to proofs.
* **“Replay” button:** shows the exact manifest & engine version; oneclick reevaluation (offline possible).
* **Audit export:** zip of `manifest.jsonc`, `verdict.json`, `delta.json` (if any), attestation, and referenced evidence.
# Testing & QA (musthave)
* **Golden tests:** fixtures of manifests → frozen verdict JSONs (byteforbyte).
* **Chaos determinism tests:** vary thread counts, env vars, map iteration seeds; assert identical verdicts.
* **Crossengine roundtrips:** two independent builds of the engine produce the same verdict for the same manifest.
* **Timetravel tests:** replay older feed snapshots to ensure stability.
# Rollout plan
1. **Phase 1:** Introduce Manifest + canonical verdict format alongside existing policy engine (shadow mode).
2. **Phase 2:** Make verdicts the **firstclass artifact** (OCIattached); ship UI “Verdict/Diff”.
3. **Phase 3:** Enforce **deltagates** in CI/CD (risk budgets + exception packs referenceable by content ID).
4. **Phase 4:** Open **consensus mode**—accept externally signed identical delta verdicts to strengthen trust.
# Notes for Stella modules
* **scanner.webservice:** keep lattice algorithms here (per your standing rule). Concelier/Excitors “preserveprune source.”
* **Authority/Attestor:** handle DSSE signing, key management, regional crypto profiles (eIDAS/FIPS/GOST/SM).
* **Feedser/Vexer:** produce immutable **snapshot bundles**; never query live during evaluation.
* **Router/Scheduler:** schedule replay jobs; cache manifests to speed up audits.
* **Db:** Postgres as SoR; Valkey only for ephemeral queues/caches (per your BSDonly profile).
If you want, I can generate:
* a sample **Manifest + Verdict + Delta** trio,
* the **canonical JSON schema**,
* and a **.NET10** reference evaluator (deterministic LINQ pipeline + fixedprecision math) you can drop into `scanner.webservice`.

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Heres a small but highimpact practice to make your hashes/signatures and “same inputs → same verdict” truly stable across services: **pick one canonicalization and enforce it at the resolver boundary.**
---
### Why this matters (in plain words)
Two JSONs that *look* the same can serialize differently (key order, spacing, Unicode forms). If one producer emits slightly different bytes, your REG/verdict hash changes—even though the meaning didnt—breaking dedup, cache hits, attestations, and audits.
---
### The rule
**Adopt one canonicalization spec and apply it everywhere at ingress/egress of your resolver:**
* **Strings:** normalize to **UTF8, Unicode NFC** (Normalization Form C).
* **JSON:** canonicalize with a deterministic scheme (e.g., **RFC 8785 JCS**: sorted keys, no insignificant whitespace, exact number formatting, escape rules).
* **Binary for hashing/signing:** always hash **the canonical bytes**, never adhoc serializer output.
---
### Minimal contract (put this in your CONTRIBUTING/AGREEMENTS.md)
1. Inputs may arrive in any wellformed JSON.
2. Resolver **normalizes strings (NFC)** and **reemits JSON in JCS**.
3. **REG hash** is computed from **JCScanonical UTF8 bytes** only.
4. Any signature/attestation (DSSE/OCI) MUST cover those same bytes.
5. Any module that cant speak JCS must pass raw data to the resolver; only the resolver serializes.
---
### Practical .NET 10 snippet (dropin utility)
```csharp
using System.Text;
using System.Text.Json;
using System.Globalization;
public static class Canon
{
// 1) Unicode → NFC
public static string ToNfc(string s) => s is null ? null : s.Normalize(NormalizationForm.FormC);
// 2) Walk JSON tree, NFC all strings
public static JsonElement NormalizeStrings(JsonElement node, JsonSerializerOptions opts = null!)
{
switch (node.ValueKind)
{
case JsonValueKind.String:
var nfc = ToNfc(node.GetString()!);
return JsonDocument.Parse(JsonSerializer.Serialize(nfc)).RootElement;
case JsonValueKind.Object:
{
using var doc = JsonDocument.Parse("{}");
var dict = new SortedDictionary<string, JsonElement>(StringComparer.Ordinal); // sorted keys (JCS)
foreach (var p in node.EnumerateObject())
{
var key = ToNfc(p.Name);
dict[key] = NormalizeStrings(p.Value, opts);
}
// reemit in sorted order
using var buf = new MemoryStream();
using (var w = new Utf8JsonWriter(buf, new JsonWriterOptions { SkipValidation = false, Indented = false }))
{
w.WriteStartObject();
foreach (var kv in dict)
WriteCanonical(kv.Key, kv.Value, w);
w.WriteEndObject();
}
return JsonDocument.Parse(buf.ToArray()).RootElement;
}
case JsonValueKind.Array:
{
var items = new List<JsonElement>();
foreach (var v in node.EnumerateArray())
items.Add(NormalizeStrings(v, opts));
using var buf = new MemoryStream();
using (var w = new Utf8JsonWriter(buf, new JsonWriterOptions { SkipValidation = false, Indented = false }))
{
w.WriteStartArray();
foreach (var v in items) v.WriteTo(w);
w.WriteEndArray();
}
return JsonDocument.Parse(buf.ToArray()).RootElement;
}
default:
return node; // numbers/bools/null unchanged (JCS rules avoid extra zeros, no NaN/Inf)
}
}
// helper to write a property with an already-built JsonElement
static void WriteCanonical(string name, JsonElement value, Utf8JsonWriter w)
{
w.WritePropertyName(name); // JCS: name is exact UTF8, no extra spaces
value.WriteTo(w); // keep canonicalized subtree
}
// 3) Canonical bytes for hashing/signing
public static byte[] CanonicalizeUtf8(ReadOnlySpan<byte> utf8Json)
{
using var doc = JsonDocument.Parse(utf8Json);
var normalized = NormalizeStrings(doc.RootElement);
using var buf = new MemoryStream();
using (var w = new Utf8JsonWriter(buf, new JsonWriterOptions { Indented = false })) // no whitespace
normalized.WriteTo(w);
return buf.ToArray(); // feed into SHA256/DSSE
}
}
```
**Usage (hash/sign):**
```csharp
var inputBytes = File.ReadAllBytes("input.json");
var canon = Canon.CanonicalizeUtf8(inputBytes);
var sha256 = System.Security.Cryptography.SHA256.HashData(canon);
// sign `canon` bytes; attach hash to verdict/attestation
```
---
### Dropin checklist (pin on your wall)
* [ ] One canonicalization policy: **UTF8 + NFC + JCS**.
* [ ] Resolver owns canonicalization (single chokepoint).
* [ ] **REG hash/signatures always over canonical bytes.**
* [ ] CI gate: reject outputs that arent JCS; fuzz keys/order/whitespace in tests.
* [ ] Log both the precanonical and canonical SHA256 for audits.
* [ ] Backwardcompat path: migrate legacy verdicts by recanonicalizing once, store “old_hash → new_hash” map.
---
If you want, I can wrap this into a tiny **`StellaOps.Canonicalizer`** NuGet (net10.0) and a Git precommit hook + CI check so your agents and services cant drift.

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Heres a practical blueprint for linking what you *build* to what actually *runs*, and turning that into proof-grade security decisions.
# Static → Binary braid (build-time proof of “what functions are inside”)
**Goal:** Prove exactly which functions/offsets shipped in an artifact—without exposing full source.
* **What to store (per artifact):**
* Minimal callstack “entry→sink” traces for relevant code paths (e.g., public handlers → sensitive sinks).
* Symbol map concordance: `{ function, file, address-range, BuildID, debug-id }`.
* Hashes per function-range (e.g., rolling BLAKE3 over `.text` subranges), plus overall `.text`/`.rodata` digests.
* **How to generate:**
* During build, emit:
* ELF/PE/MachO: capture BuildID, section ranges, and DWARF/CodeView ↔ symbol table mapping.
* Function-range hashing: disassemble to find prolog/epilog (fallback to symbol boundaries), hash byte ranges.
* Entry→sink traces: from static CFG or unit/integration tests with instrumentation; serialize as compact spans (start fn, end fn, edge list hash).
* **Proof object (tiny & replayable):**
* `{ build_id, section_hashes, [ {func: name, addr: start..end, func_hash}, … ], [trace_hashes] }`
* Sign with DSSE (intoto envelope). Auditors can replay using the published BuildID + debug symbols to verify function boundaries without your source.
* **Attach & ship:**
* Publish as an OCI referrers artifact alongside the image (e.g., `application/vnd.stellaops.funcproof+json`), referenced from SBOM (CycloneDX `evidence` or SPDX `verificationCode` extension).
* **Why it matters:**
* When a CVE names a *symbol* (not just a package version), you can prove whether that symbol (and exact byte-range) is present in your binary.
# Runtime → Build braid (production proof of “what code ran”)
**Goal:** Observe live stacks (cheaply), canonicalize to symbols, and correlate to SBOM components. If a vulnerable symbol appears *in hot paths*, automatically downgrade VEX posture.
* **Collection (Linux):**
* eBPF sampling for targeted processes/containers; use `bpf_get_stackid` to capture stack traces (user & kernel) into a perf map with low overhead.
* Collapse stacks (“frameA;frameB;… count”) à la flamegraph format; include PID, container image digest, BuildID tuples.
* **Canonicalization:**
* Resolve PCs → (BuildID, function, offset) via `perf-map-agent`/`eu-stack`, or your own resolver using `.note.gnu.build-id` + symbol table (prefer `debuginfod` in lab; ship a slim symbol cache in prod).
* Normalize language runtimes: Java/.NET/Python frames mapped to package+symbol via runtime metadata; native frames via ELF.
* **Correlate to SBOM:**
* For each frame: map `(image-digest, BuildID, function)` → SBOM component (pkg + version) and to your **Static→Binary proof** entry.
* **VEX policy reaction:**
* If a CVEs vulnerable symbol appears in observed stacks **and** matches your static proof:
* Autoemit a **VEX downgrade** (e.g., from `not_affected` to `affected`) with DSSE signatures, including runtime evidence:
* Top stacks where the symbol was hot (counts/percentile),
* BuildID(s) observed,
* Timestamp window and container IDs.
* If symbol is present in build but never observed (and policy allows), maintain or upgrade to `not_affected(conditions: not_reachable_at_runtime)`—with timeboxed confidence.
* **Controls & SLOs:**
* Sampling budget per workload (e.g., 49 Hz for N minutes per hour), P99 overhead <1%.
* Privacy guardrails: hash short-lived arguments; only persist canonical frames + counts.
# How this lands in StellaOps (concrete modules & evidence flow)
* **Sbomer**: add `funcproof` generator at build (ELF range hashing + entrysink traces). Emit CycloneDX `components.evidence` link to funcproof artifact.
* **Attestor**: wrap funcproof in DSSE, push as OCI referrer; record in ProofofIntegrity Graph.
* **Signals/Excititor**: eBPF sampler daemonset; push collapsed frames with `(image-digest, BuildID)` to pipeline.
* **Concelier**: resolver service mapping frames SBOM components + funcproof presence; maintain hotsymbol index.
* **Vexer/Policy Engine**: when hot vulnerable symbol is confirmed, produce signed VEX downgrade; route to **Authority** for policygated actions (quarantine, canary freeze, diff-aware release gate).
* **Timeline/Notify**: humanreadable evidence pack: CVE2025XXXX observed in `libfoo::parse_hdr` (BuildID abc…), 17.3% of CPU in apigw@prod between 12:0014:00 UTC; VEX affected.”
# Data shapes (keep them tiny)
* **FuncProof JSON (per binary):**
```json
{
"buildId": "ab12…",
"sections": {".text": "hash", ".rodata": "hash"},
"functions": [
{"sym": "foo::bar", "start": "0x401120", "end": "0x4013af", "hash": "…"}
],
"traces": ["hash(edge-list-1)", "hash(edge-list-2)"],
"meta": {"compiler": "clang-18", "flags": "-O2 -fno-plt"}
}
```
* **Runtime frame sample (collapsed):**
```
api-gw@sha256:…;buildid=ab12…;foo::bar+0x3a;net/http::Serve;… 97
```
# Rollout plan (short and sweet)
1. **Phase 1 — Build plumbing:** implement function-range hashing + DSSE attestation; publish as OCI referrer; link from SBOM.
2. **Phase 2 — Runtime sampler:** ship eBPF agent with stack collapse + BuildID resolution; store only canonical frames.
3. **Phase 3 — Correlation & VEX:** map frames ↔ SBOM ↔ funcproof; autodowngrade VEX on hot vulnerable symbols; wire policy actions.
4. **Phase 4 — Auditor replay:** `stella verify --image X` downloads funcproof + symbols and replays hashes and traces to prove presence/absence without source.
# Why this is a moat
* **Symbollevel truth**, not just package versions.
* **Runtimeaware VEX** that flips based on evidence, not assumptions.
* **Tiny proof objects** make audits fast and airgapfriendly.
* **Deterministic replay**: “same inputs → same verdict,” signed.
If you want, I can draft:
* the DSSE schemas,
* the eBPF sampler config for Alpine/Debian/RHEL/SLES/Astra,
* and the exact CycloneDX/SPDX extensions to carry `funcproof` links.

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Heres a simple, practical way to make **release gates** that autodecide if a build is “routine” or “risky” by comparing the *semantic delta* across SBOMs, VEX data, and dependency graphs—so product managers can approve (or defer) with evidence, not guesswork.
### What this means (quick background)
* **SBOM**: a bill of materials for your build (what components you ship).
* **VEX**: vendor statements about whether known CVEs actually affect a product/version.
* **Dependency graph**: how components link together at build/runtime.
* **Semantic delta**: not just “files changed,” but “riskrelevant meaning changed” (e.g., new reachable vuln path, new privileged capability, downgraded VEX confidence).
---
### The gates core signal (one line)
**Risk Verdict = f(ΔSBOM, ΔReachability, ΔVEX, ΔConfig/Capabilities, ΔExploitability)** → Routine | Review | Block
---
### Minimal data you need per release
* **SBOM (CycloneDX/SPDX)** for previous vs current release.
* **Reachability subgraph**: which vulnerable symbols/paths are actually callable (source, package, binary, or eBPF/runtime).
* **VEX claims** merged from vendors/distros/internal (with trust scores).
* **Policy knobs**: env tier (prod vs dev), allowed unknowns, max risk budget, critical assets list.
* **Exploit context**: EPSS/CISA KEV or your internal exploit sighting, if available.
---
### How to compute the semantic delta (fast path)
1. **Component delta**: new/removed/updated packages → tag each change with severity (critical/securityrelevant vs cosmetic).
2. **Vulnerability delta**:
* New CVEs introduced?
* Old CVEs now mitigated (patch/backport) or declared **notaffected** via VEX?
* Any VEX status regressions (e.g., “notaffected” → “underinvestigation”)?
3. **Reachability delta**:
* Any *new* callpaths to vulnerable functions?
* Any risk removed (path eliminated via config/featureflag/off by default)?
4. **Config/capabilities delta**:
* New container perms (NET_ADMIN, SYS_ADMIN), new open ports, new outbound calls.
* New data flows to sensitive stores.
5. **Exploitability delta**:
* EPSS/KEV jumps; active exploitation signals.
---
### A tiny, useful scoring rubric (defaults you can ship)
* Start at 0. Add:
* +6 if any **reachable** critical vuln (no valid VEX “notaffected”).
* +4 if any **reachable** high vuln.
* +3 if new sensitive capability added (e.g., NET_ADMIN) or new public port opened.
* +2 if VEX status regressed (NA→U/I or Affected).
* +1 per unknown package origin or unsigned artifact (cap at +5).
* Subtract:
* 3 per *proven* mitigation (valid VEX NA with trusted source + reachability proof).
* 2 if vulnerable path is demonstrably gated off in target env (feature flag off + policy evidence).
* Verdict:
* **03** → Routine (autoapprove)
* **47** → Review (PM/Eng signoff)
* **≥8** → Block (require remediation/exception)
*(Tune thresholds per env: e.g., prod stricter than staging.)*
---
### What PMs see (clean UI)
* **Badge**: Routine / Review / Block.
* **Why** (35 bullets):
* “Added `libpng` 1.6.43 (new), CVEXXXX reachable via `DecodePng()`
* “Vendor VEX for `libssl` says notaffected (function not built)”
* “Container gained `CAP_NET_RAW`
* **Evidence buttons**:
* “Show reachability slice” (mini graph)
* “Show VEX sources + trust”
* “Show SBOM diff”
* **Call to action**:
* “Autoremediate to 1.6.44” / “Mark exception” / “Open fix PR”
---
### Exception workflow (auditable)
* Exception must include: scope, expiry, compensating controls, owner, and linked evidence (reachability/VEX).
* Gate reevaluates each release; expired exceptions autofail the gate.
---
### How to wire it into CI/CD (quick recipe)
1. Generate SBOM + reachability slice for `prev` and `curr`.
2. Merge VEX from vendor/distro/internal with trust scoring.
3. Run **Delta Evaluator** → score + verdict + evidence bundle (JSON + attestation).
4. Gate policy checks score vs environment thresholds.
5. Publish an **OCIattached attestation** (DSSE/intoto) so auditors can replay: *same inputs → same verdict*.
---
### Starter policy you can copy
* **Prod**: block on any reachable Critical; review on any reachable High; unknowns ≤ 2; no new privileged caps without exception.
* **Preprod**: review on reachable High/Critical; unknowns ≤ 5.
* **Dev**: allow but flag; collect evidence.
---
### Why this helps immediately
* PMs get **evidencebacked** green/yellow/red, not CVE walls.
* Engineers get **actionable deltas** (what changed that matters).
* Auditors get **replayable proofs** (deterministic verdicts + inputs).
If you want, I can turn this into a readytodrop spec for StellaOps (modules, JSON schemas, attestation format, and a tiny React panel mock) so your team can implement the gate this sprint.

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Heres a practical, lowfriction way to modernize how you sign and verify build “verdicts” in CI/CD using Sigstore—no longlived keys, offlinefriendly, and easy to audit.
---
### 1) Use **keyless** signing in CI
* In your pipeline, obtain an OIDC token (from your CI runner) and let **Fulcio** issue a shortlived X.509 codesigning cert (~10 minutes). You sign with the ephemeral key; cert + signature are logged to Rekor. ([Sigstore Blog][1])
**Why:** no key escrow in CI, nothing persistent to steal, and every signature is timebound + transparencylogged.
---
### 2) Keep one **hardwarebacked org key** only for special cases
* Reserve a physical HSM/YubiKey (or KMS) key for:
a) resigning monthly bundles (see §4), and
b) offline/airgapped verification workflows where a trust anchor is needed.
Cosign supports disconnected/offline verification patterns and mirroring the proof data. ([Sigstore][2])
---
### 3) Make “verdicts” firstclass OCI attestations
* Emit DSSE/attestations (SBOM deltas, reachability graphs, policy results) as OCIattached artifacts and sign them with keyless in CI. (Cosign is designed to sign/verify arbitrary OCI artifacts alongside images.) ([Artifact Hub][3])
---
### 4) Publish a **rotation & refresh policy**
* Every month, collect older attestations and **resign into a longlived “bundle”** (plus timestamps) using the org key. This keeps proofs verifiable over years—even if the 10minute certs expire—because the bundle contains the cert chain, Rekor inclusion proof, and timestamps suitable for **offline** verification. ([Trustification][4])
**Suggested SLOs**
* CI keyless cert TTL: 10 minutes (Fulcio default). ([Sigstore][5])
* Bundle cadence: monthly (or per release); retain N=24 months.
---
### 5) Offline / airgapped verification
* Mirror the image + attestation + Rekor proof (or bundle) into the disconnected registry. Verify with `cosign verify` using the mirrored materials—no internet needed. (Multiple guides show fully disconnected OpenShift/airgapped flows.) ([Red Hat Developer][6])
---
### 6) Address common concerns (“myths”)
* “Shortlived certs will break verification later.” → They dont: you verify against the Rekor proof/bundle, not live cert validity. ([Trustification][4])
* “Keyless means less security.” → The opposite: no static secrets in CI; certs expire in ~10 minutes; identity bound via OIDC and logged. ([Chainguard][7])
---
### Minimal rollout checklist
* [ ] Enable OIDC on your CI runners; test `cosign sign --identity-token ...`
* [ ] Enforce identity/issuer in policy: `--certificate-identity` + `--certificate-oidc-issuer` at verify time. ([Sigstore][2])
* [ ] Set up a monthly job to build **Sigstore bundles** from past attestations and resign with the org key. ([Trustification][4])
* [ ] For offline sites: mirror images + attestations + bundles; verify with `cosign verify` entirely offline. ([Red Hat Developer][6])
Want me to draft the exact cosign commands and a GitLab/GitHub Actions snippet for your StellaOps pipelines (keyless sign, verify gates, monthly bundling, and an offline verification playbook)?
[1]: https://blog.sigstore.dev/trusted-time/?utm_source=chatgpt.com "Trusted Time in Sigstore"
[2]: https://docs.sigstore.dev/cosign/verifying/verify/?utm_source=chatgpt.com "Verifying Signatures - Cosign"
[3]: https://artifacthub.io/packages/container/cosign/cosign/latest?utm_source=chatgpt.com "cosign latest · sigstore/cosign"
[4]: https://trustification.io/blog/?utm_source=chatgpt.com "Blog"
[5]: https://docs.sigstore.dev/certificate_authority/overview/?utm_source=chatgpt.com "Fulcio"
[6]: https://developers.redhat.com/articles/2025/08/27/how-verify-container-signatures-disconnected-openshift?utm_source=chatgpt.com "How to verify container signatures in disconnected OpenShift"
[7]: https://www.chainguard.dev/unchained/life-of-a-sigstore-signature?utm_source=chatgpt.com "Life of a Sigstore signature"

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Im sharing this with you because your StellaOps vision for vulnerability triage and supplychain context beats what many current tools actually deliver — and the differences highlight exactly where to push hard to outexecute the incumbents.
![Image](https://res.cloudinary.com/snyk/image/upload/f_auto%2Cw_1240%2Cq_auto/v1630430045/wordpress-sync/blog-graph-vulnerable-code-reachability-4.jpg)
![Image](https://cdn-dllid.nitrocdn.com/lfaFdmeTaONuMeYAvisIiEiZRrNJpVpd/assets/images/optimized/rev-ebe8dd3/anchore.com/wp-content/uploads/2025/11/4-1.png)
![Image](https://www.paloaltonetworks.com/content/dam/pan/en_US/images/prisma/usecases/container-security/container-compliance.png?imwidth=480)
![Image](https://mma.prnewswire.com/media/1498459/Prisma_Cloud_Attack_Dashboard.jpg)
**Where competitors actually land today**
**Snyk — reachability + continuous context**
* Snyk now implements *reachability analysis* that builds a call graph to determine if vulnerable code *is actually reachable by your application*. This is factored into their risk and priority scores to help teams triage what matters most, beyond just severity numbers. ([Snyk Docs][1])
* Their model uses static program analysis combined with AI and expert curation for prioritization. ([Snyk Docs][1])
* For ongoing monitoring, Snyk *tracks issues over time* as projects are monitored and rescanned (e.g., via CLI or integrations), updating status as new CVEs are disclosed — without needing to repull unchanged images. ([Snyk Docs][1])
**Anchore — vulnerability annotations & VEX export**
* Anchore Enterprise has shipped *vulnerability annotation workflows* where users or automation can label each finding with context (“not applicable”, “mitigated”, “under investigation”, etc.) via UI or API. ([Anchore Documentation][2])
* These annotations are exportable as *OpenVEX and CycloneDX VEX* formats so downstream consumers can consume authoritative exploitability state instead of raw scanner noise. ([Anchore][3])
* This means Anchore customers can generate SBOM + VEX outputs that carry your curated reasoning, reducing redundant triage across the supply chain.
**Prisma Cloud — runtime defense**
* Prisma Clouds *runtime defense* for containers continually profiles behavior and enforces *process, file, and network rules* for running workloads — using learning models to baseline expected behavior and block/alert on anomalies. ([Prisma Cloud][4])
* This gives security teams *runtime context* during operational incidents, not just predeployment scan results — which can improve triage but is conceptually orthogonal to static SBOM/VEX artifacts.
**What StellaOps should outexecute**
Instead of disparate insights, StellaOps can unify and elevate:
1. **One triage canvas with rich evidence**
* Combine static *reachability/evidence graphs* with call stacks and evidence traces — so users see *why* a finding matters, not just “reachable vs. not”.
* If you build this as a subgraph panel, teams can trace from SBOM → code paths → runtime indicators.
2. **VEX decisioning as firstclass**
* Treat VEX not as an export format but as *core policy objects*: policies that can *explain*, *override*, and *drive decisions*.
* This includes programmable policy rules driving whether something is actionable or suppressed in a given context — surfacing context alongside triage.
3. **Attestable exception objects**
* Model exceptions as *attestable contracts* with *expiries and audit trails* — not adhoc labels. These become firstclass artifacts that can be cryptographically attested, shared, and verified across orgs.
4. **Offline replay packs for airgapped parity**
* Build *offline replay packs* so the *same UI, interactions, and decisions* work identically in fully airgapped environments.
* This is critical for compliance/defense customers who cannot connect to external feeds but still need consistent triage and reasoning workflows.
In short, competitors give you pieces — reachability scores, VEX exports, or behavioral runtime signals — but StellaOps can unify these into *a single, evidencerich, policydriven triage experience that works both online and offline*. You already have the architecture to do it; now its about integrating these signals into a coherent decision surface that beats siloed tools.
[1]: https://docs.snyk.io/manage-risk/prioritize-issues-for-fixing/reachability-analysis?utm_source=chatgpt.com "Reachability analysis | Snyk User Docs"
[2]: https://docs.anchore.com/current/docs/vulnerability_management/vuln_annotations/?utm_source=chatgpt.com "Vulnerability Annotations and VEX"
[3]: https://anchore.com/blog/anchore-enterprise-5-23-cyclonedx-vex-and-vdr-support/?utm_source=chatgpt.com "Anchore Enterprise 5.23: CycloneDX VEX and VDR Support"
[4]: https://docs.prismacloud.io/en/compute-edition/30/admin-guide/runtime-defense/runtime-defense-containers?utm_source=chatgpt.com "Runtime defense for containers - Prisma Cloud Documentation"
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Note from the the product manager. Note there is AdvisoryAI module on the Stella Ops suite

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Heres a simple, highleverage UX pattern you can borrow from top observability tools: **treat every policy decision or reachability change as a visual diff.**
---
### Why this helps
* Turns opaque “why is this verdict different?” moments into **quick, explainable triage**.
* Reduces backandforth between Security, Dev, and Audit—**everyone sees the same before/after evidence**.
### Core UI concept
* **Sidebyside panes**: **Before** (previous scan/policy) vs **After** (current).
* **Graph focus**: show the dependency/reachability subgraph; **highlight added/removed/changed nodes/edges**.
* **Evidence strip** (right rail): humanreadable facts used by the engine (e.g., *feature flag OFF*, *code path unreachable*, *kernel eBPF trace absent*).
* **Diff verdict header**: “Risk ↓ from *Medium → Low* (policy v1.8 → v1.9)”.
* **Filter chips**: Scope by component, package, CVE, policy rule, environment.
### Minimal data model (so UI is easy)
* `GraphSnapshot`: nodes, edges, metadata (component, version, tags).
* `PolicySnapshot`: version, rules hash, inputs (flags, env, VEX sources).
* `Delta`: `added/removed/changed` for nodes, edges, and rule outcomes.
* `EvidenceItems[]`: typed facts (trace hits, SBOM lines, VEX claims, config values) with source + timestamp.
* `SignedDeltaVerdict`: final status + signatures (who/what produced it).
### Microinteractions that matter
* Hover a changed node ⇒ **inline badge** explaining *why it changed* (e.g., “now gated by `--no-xml` runtime flag”).
* Click a rule change in the right rail ⇒ **spotlight** the exact subgraph it affected.
* Toggle **“explain like Im new”** ⇒ expands jargon into plain language.
* Oneclick **“copy audit bundle”** ⇒ exports the delta + evidence as an attachment.
### Where this belongs in your product
* **Primary**: in the **Triage** view for any new finding/regression.
* **Secondary**: in **Policy history** (compare vX vs vY) and **Release gates** (compare build A vs build B).
* **Inline surfaces**: small “diff pills” next to every verdict in tables; click opens the big sidebyside.
### Quick build checklist (dev & PM)
* Compute a stable **graph hash** per scan; store **snapshots**.
* Add a **delta builder** that outputs `added/removed/changed` at node/edge + rule outcome levels.
* Normalize **evidence items** (source, digest, excerpt) so the UI can render consistent cards.
* Ship a **Signed Delta Verdict** (OCIattached) so audits can replay the view from the artifact alone.
* Include **hotkeys**: `1` focus changes only, `2` show full graph, `E` expand evidence, `A` export audit.
### Empty state & failure modes
* If evidence is incomplete: show a **yellow “Unknowns present” ribbon** with a count and a button to collect missing traces.
* If graphs are huge: default to **“changed neighborhood only”** with a minimap to pan.
### Success metric (simple)
* **Mean time to explain (MTTE)**: time from “why did this change?” to user clicking *“Understood”*. Track trend ↓.
If you want, I can sketch a quick wireframe (header, graph panes, evidence rail, and the export action) or generate a JSON schema for the `Delta` and `EvidenceItem` objects you can hand to your frontend.