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Below is a cohesive set of **7 product advisories** that together define an “AI-native” Stella Ops with defensible moats. Each advisory follows the same structure:
* **Problem** (what hurts today)
* **Why** (why Stella should solve it)
* **What we ship** (capabilities, boundaries)
* **How we achieve** (proposed `AdvisoryAI` backend modules + key UI components)
* **Guardrails** (safety / trust / determinism)
* **KPIs** (how you prove it works)
Im assuming your canonical object model already includes **Runs** (incident/escalation/change investigation runs) and a system-of-record in **PostgreSQL** with **Valkey** as a non-authoritative accelerator.
---
# ADVISORY-AI-000 — AdvisoryAI Foundation: Chat + Workbench + Runs (the “AI OS surface”)
## Problem
Most “AI in ops” fails because its only a chat box. Chat is not:
* auditable
* repeatable
* actionable with guardrails
* collaborative (handoffs, approvals, artifacts)
Operators need a place where AI output becomes **objects** (runs, decisions, patches, evidence packs), not ephemeral text.
## Why we do it
This advisory is the substrate for all other moats. Without it, your other features remain demos.
## What we ship
1. **AdvisoryAI Orchestrator** that can:
* read Stella objects (runs, services, policies, evidence)
* propose plans
* call tools/actions (within policy)
* produce structured artifacts (patches, decision records, evidence packs)
2. **AI Workbench UI**:
* Chat panel for intent
* Artifact cards (Run, Playbook Patch, Decision, Evidence Pack)
* Run Timeline view (what happened, tool calls, approvals, outputs)
## How we achieve (modules + UI)
### Backend modules (suggested)
* `StellaOps.AdvisoryAI.WebService`
* Conversation/session orchestration
* Tool routing + action execution requests
* Artifact creation (Run notes, patches, decisions)
* `StellaOps.AdvisoryAI.Prompting`
* Prompt templates versioned + hashed
* Guarded system prompts per “mode”
* `StellaOps.AdvisoryAI.Tools`
* Tool contracts (read-only queries, action requests)
* `StellaOps.AdvisoryAI.Eval`
* Regression tests for tool correctness + safety
### UI components
* `AiChatPanelComponent`
* `AiArtifactCardComponent` (Run/Decision/Patch/Evidence Pack)
* `RunTimelineComponent` (with “AI steps” and “human steps”)
* `ModeSelectorComponent` (Analyst / Operator / Autopilot)
### Canonical flow
```
User intent (chat)
-> AdvisoryAI proposes plan (steps)
-> executes read-only tools
-> generates artifact(s)
-> requests approvals for risky actions
-> records everything on Run timeline
```
## Guardrails
* Every AI interaction writes to a **Run** (or attaches to an existing Run).
* Prompt templates are **versioned + hashed**.
* Tool calls and outputs are **persisted** (for audit and replay).
## KPIs
* % AI sessions attached to Runs
* “Time to first useful artifact”
* Operator adoption (weekly active users of Workbench)
---
# ADVISORY-AI-001 — Evidence-First Outputs (trust-by-construction)
## Problem
In ops, an answer without evidence is a liability. LLMs are persuasive even when wrong. Operators waste time verifying or, worse, act on incorrect claims.
## Why we do it
Evidence-first output is the trust prerequisite for:
* automation
* playbook learning
* org memory
* executive reporting
## What we ship
* A **Claim → Evidence** constraint:
* Each material claim must be backed by an `EvidenceRef` (query snapshot, ticket, pipeline run, commit, config state).
* An **Evidence Pack** artifact:
* A shareable bundle of evidence for an incident/change/review.
## How we achieve (modules + UI)
### Backend modules
* `StellaOps.AdvisoryAI.Evidence`
* Claim extraction from model output
* Evidence retrieval + snapshotting
* Citation enforcement (or downgrade claim confidence)
* `StellaOps.EvidenceStore`
* Immutable (or content-addressed) snapshots
* Hashes, timestamps, query parameters
### UI components
* `EvidenceSidePanelComponent` (opens from inline citations)
* `EvidencePackViewerComponent`
* `ConfidenceBadgeComponent` (Verified / Inferred / Unknown)
### Implementation pattern
* For each answer:
1. Draft response
2. Extract claims
3. Attach evidence refs
4. If evidence missing: label as uncertain + propose verification steps
## Guardrails
* If evidence is missing, Stella must **not** assert certainty.
* Evidence snapshots must capture:
* query inputs
* time range
* raw result (or hash + storage pointer)
## KPIs
* Citation coverage (% of answers with evidence refs)
* Reduced back-and-forth (“how do you know?” rate)
* Adoption of automation after evidence-first rollout
---
# ADVISORY-AI-002 — Policy-Aware Automation (safe actions, not just suggestions)
## Problem
The main blocker to “AI that acts” is governance:
* wrong environment
* insufficient permission
* missing approvals
* non-idempotent actions
* unclear accountability
## Why we do it
If Stella cant safely execute actions, it will remain a read-only assistant. Policy-aware automation is a hard moat because it requires real engineering discipline and operational maturity.
## What we ship
* A typed **Action Registry**:
* schemas, risk levels, idempotency, rollback/compensation
* A **Policy decision point** (PDP) before any action:
* allow / allow-with-approvals / deny
* An **Approval workflow** linked to Runs
## How we achieve (modules + UI)
### Backend modules
* `StellaOps.ActionRegistry`
* Action definitions + schemas + risk metadata
* `StellaOps.PolicyEngine`
* Rules: environment protections, freeze windows, role constraints
* `StellaOps.AdvisoryAI.Automation`
* Converts intent → action proposals
* Submits action requests after approvals
* `StellaOps.RunLedger`
* Every action request + result is a ledger entry
### UI components
* `ActionProposalCardComponent`
* `ApprovalModalComponent` (scoped approval: this action/this run/this window)
* `PolicyExplanationComponent` (human-readable “why allowed/denied”)
* `RollbackPanelComponent`
## Guardrails
* Default: propose actions; only auto-execute in explicitly configured “Autopilot scopes.”
* Every action must support:
* idempotency key
* audit fields (why, ticket/run linkage)
* reversible/compensating action where feasible
## KPIs
* % actions proposed vs executed
* “Policy prevented incident” count
* Approval latency and action success rate
---
# ADVISORY-AI-003 — Ops Memory (structured, durable, queryable)
## Problem
Teams repeat incidents because knowledge lives in:
* chat logs
* tribal memory
* scattered tickets
* unwritten heuristics
Chat history is not an operational knowledge base: its unstructured and hard to reuse safely.
## Why we do it
Ops memory reduces repeat work and accelerates diagnosis. It also becomes a defensible dataset because its tied to your Runs, artifacts, and outcomes.
## What we ship
A set of typed memory objects (not messages):
* `DecisionRecord`
* `KnownIssue`
* `Tactic`
* `Constraint`
* `PostmortemSummary`
Memory is written on:
* Run closure
* approvals (policy events)
* explicit “save as org memory” actions
## How we achieve (modules + UI)
### Backend modules
* `StellaOps.AdvisoryAI.Memory`
* Write: extract structured memory from run artifacts
* Read: retrieve memory relevant to current context (service/env/symptoms)
* Conflict handling: “superseded by”, timestamps, confidence
* `StellaOps.MemoryStore` (Postgres tables + full-text index as needed)
### UI components
* `MemoryPanelComponent` (contextual suggestions during a run)
* `MemoryBrowserComponent` (search + filters)
* `MemoryDiffComponent` (when superseding prior memory)
## Guardrails
* Memory entries have:
* scope (service/env/team)
* confidence (verified vs anecdotal)
* review/expiry policies for tactics/constraints
* Never “learn” from unresolved or low-confidence runs by default.
## KPIs
* Repeat incident rate reduction
* Time-to-diagnosis delta when memory exists
* Memory reuse rate inside Runs
---
# ADVISORY-AI-004 — Playbook Learning (Run → Patch → Approved Playbook)
## Problem
Runbooks/playbooks drift. Operators improvise. The playbook never improves, and the organization pays the same “tuition” repeatedly.
## Why we do it
Playbook learning is the compounding loop that turns daily operations into a proprietary advantage. Competitors can generate playbooks; they struggle to continuously improve them from real run traces with review + governance.
## What we ship
* Versioned playbooks as structured objects
* **Playbook Patch** proposals generated from Run traces:
* coverage patches, repair patches, optimization patches, safety patches, detection patches
* Owner review + approval workflow
## How we achieve (modules + UI)
### Backend modules
* `StellaOps.Playbooks`
* Playbook schema + versioning
* `StellaOps.AdvisoryAI.PlaybookLearning`
* Extract “what we did” from Run timeline
* Compare to playbook steps
* Propose a patch with evidence links
* `StellaOps.DiffService`
* Human-friendly diff output for UI
### UI components
* `PlaybookPatchCardComponent`
* `DiffViewerComponent` (Monaco diff or equivalent)
* `PlaybookApprovalFlowComponent`
* `PlaybookCoverageHeatmapComponent` (optional, later)
## Guardrails
* Never auto-edit canonical playbooks; only patches + review.
* Require evidence links for each proposed step.
* Prevent one-off contamination by marking patches as:
* “generalizable” vs “context-specific”
## KPIs
* % incidents with a playbook
* Patch acceptance rate
* MTTR improvement for playbook-backed incidents
---
# ADVISORY-AI-005 — Integration Concierge (setup + health + “how-to” that is actually correct)
## Problem
Integrations are where tools die:
* users ask “how do I integrate X”
* assistant answers generically
* setup fails because of environment constraints, permissions, webhooks, scopes, retries, or missing prerequisites
* no one can debug it later
## Why we do it
Integration handling becomes a moat when it is:
* deterministic (wizard truth)
* auditable (events + actions traced)
* self-healing (retries, backfills, health checks)
* explainable (precise steps, not generic docs)
## What we ship
1. **Integration Setup Wizard** per provider (GitLab, Jira, Slack, etc.)
2. **Integration Health** dashboard:
* last event received
* last action executed
* failure reasons + next steps
* token expiry warnings
3. **Chat-driven guidance** that drives the same wizard backend:
* when user asks “how to integrate GitLab,” Stella replies with the exact steps for the instance type, auth mode, and required permissions, and can pre-fill a setup plan.
## How we achieve (modules + UI)
### Backend modules
* `StellaOps.Integrations`
* Provider contracts: inbound events + outbound actions
* Normalization into Stella `Signals` and `Actions`
* `StellaOps.Integrations.Reliability`
* Webhook dedupe, replay, dead-letter, backfill polling
* `StellaOps.AdvisoryAI.Integrations`
* Retrieves provider-specific setup templates
* Asks only for missing parameters
* Produces a “setup checklist” artifact attached to a Run or Integration record
### UI components
* `IntegrationWizardComponent`
* `IntegrationHealthComponent`
* `IntegrationEventLogComponent` (raw payload headers + body stored securely)
* `SetupChecklistArtifactComponent` (generated by AdvisoryAI)
## Guardrails
* Store inbound webhook payloads for replay/debug, with redaction where required.
* Always support reconciliation/backfill (webhooks are never perfectly lossless).
* Use least-privilege token scopes by default, with clear permission error guidance.
## KPIs
* Time-to-first-successful-event
* Integration “healthy” uptime
* Setup completion rate without human support
---
# ADVISORY-AI-006 — Outcome Analytics (prove ROI with credible attribution)
## Problem
AI features are easy to cut in budgeting because value is vague. “It feels faster” doesnt survive scrutiny.
## Why we do it
Outcome analytics makes Stella defensible to leadership and helps prioritize what to automate next. It also becomes a dataset for continuous improvement.
## What we ship
* Baseline metrics (before Stella influence):
* MTTA, MTTR, escalation count, repeat incidents, deploy failure rate (as relevant)
* Attribution model (only count impact when Stella materially contributed):
* playbook patch accepted
* evidence pack used
* policy-gated action executed
* memory entry reused
* Monthly/weekly impact reports
## How we achieve (modules + UI)
### Backend modules
* `StellaOps.Analytics`
* Metric computation + cohorts (by service/team/severity)
* `StellaOps.AdvisoryAI.Attribution`
* Joins outcomes to AI artifacts and actions in the Run ledger
* `StellaOps.Reporting`
* Scheduled report generation (exportable)
### UI components
* `OutcomeDashboardComponent`
* `AttributionBreakdownComponent`
* `ExecutiveReportExportComponent`
## Guardrails
* Avoid vanity metrics (“number of chats”).
* Always show confidence/limitations in attribution (correlation vs causation).
## KPIs
* MTTR delta (with Stella artifacts vs without)
* Repeat incident reduction
* Escalation reduction
* Automation coverage growth
---
## One unifying implementation note: “AdvisoryAI” should output objects, not prose
To make all seven advisories work together, standardize on a small set of **AI-produced artifacts**:
* `Plan` (step list with tools/actions)
* `EvidencePack`
* `DecisionRecord`
* `PlaybookPatch`
* `IntegrationSetupChecklist`
* `RunSummary` (postmortem-ready)
Every artifact is:
* versioned
* evidence-linked
* attached to a Run
* subject to policy gates when it triggers actions
This gives you:
* auditability
* deterministic replay of the *inputs and tool outputs*
* compounding “Ops memory” and “Playbook learning” data
---
## Example: how this maps to “AdvisoryAI module + Chat UI component”
Minimum viable architecture that is coherent:
**Backend**
* `StellaOps.AdvisoryAI.WebService` (orchestrator)
* `StellaOps.AdvisoryAI.Evidence` (citations)
* `StellaOps.AdvisoryAI.Memory` (structured memory)
* `StellaOps.AdvisoryAI.PlaybookLearning` (patch proposals)
* `StellaOps.AdvisoryAI.Integrations` (setup guidance + checklists)
* `StellaOps.PolicyEngine` + `StellaOps.ActionRegistry` (gated actions)
* `StellaOps.RunLedger` + `StellaOps.EvidenceStore` (audit + snapshots)
**UI**
* AI chat panel that emits/accepts **artifact cards**
* Evidence side panel
* Approval modal
* Diff viewer for patches
* Integration wizard + health
---
If you want, I can translate these advisories into a single internal spec pack:
* database tables (Postgres)
* event contracts (signals/actions)
* JSON schemas for artifacts/actions
* UI navigation and component tree
* the first 10 “golden workflows” you should ship with the Workbench

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# GitHub Code Scanning Integration via SARIF
> **Status:** Revised
> **Original:** 09-Jan-2026 (Lighting Up GitHub with SARIF)
> **Revision:** 09-Jan-2026
> **Author:** Product/Engineering
> **Epic:** Platform Integrations
---
## Executive Summary
This advisory defines the complete integration between StellaOps Scanner and **GitHub Code Scanning** via SARIF 2.1.0. The integration enables StellaOps findings to appear natively in GitHub's Security tab with zero custom UI, leveraging GitHub's existing annotation, filtering, and alerting infrastructure.
### Current State
| Component | Status | Notes |
|-----------|--------|-------|
| SARIF 2.1.0 Models | **Implemented** | Full schema in `Scanner.SmartDiff` |
| SmartDiff SARIF Export | **Implemented** | Binary diff findings, production-ready |
| Findings SARIF Export | **Not Implemented** | Main vulnerability findings |
| GitHub App Connector | **Implemented** | Auth + health checks working |
| GitHub Code Scanning Upload | **Not Implemented** | REST API client needed |
| GitHub Actions Workflow | **Not Implemented** | Template generation needed |
### Business Value
- **Zero Custom UI:** GitHub renders findings, annotations, and PR decorations
- **Native Integration:** Findings appear in Security tab alongside Dependabot/CodeQL
- **Alert Management:** GitHub's existing dismiss/reopen/severity workflow
- **PR Blocking:** Branch protection rules can require scan results
- **Enterprise Ready:** Supports GitHub.com and GitHub Enterprise Server
---
## What SARIF Is
**SARIF** (Static Analysis Results Interchange Format) is an OASIS standard (version 2.1.0) for representing static analysis results. GitHub Code Scanning accepts a **subset** of SARIF 2.1.0 and renders it as security alerts.
### SARIF Structure
```
SarifLog
├── $schema: "https://json.schemastore.org/sarif-2.1.0.json"
├── version: "2.1.0"
└── runs[]
├── tool
│ └── driver
│ ├── name: "StellaOps Scanner"
│ ├── version: "1.0.0"
│ └── rules[]
│ ├── id: "STELLA-VULN-001"
│ ├── name: "Critical Vulnerability"
│ └── properties (CWE, CVSS, etc.)
├── results[]
│ ├── ruleId: "STELLA-VULN-001"
│ ├── level: "error" | "warning" | "note"
│ ├── message.text
│ ├── locations[]
│ │ └── physicalLocation
│ │ ├── artifactLocation.uri
│ │ └── region.startLine
│ └── fingerprints (deduplication)
└── versionControlProvenance (git metadata)
```
---
## Three Upload Options
### Option 1: GitHub Actions (Recommended)
```yaml
# .github/workflows/stellaops-scan.yml
name: StellaOps Scan
on:
push:
branches: [main, release/*]
pull_request:
branches: [main]
schedule:
- cron: "0 3 * * 1" # Weekly Monday 3 AM
jobs:
scan:
runs-on: ubuntu-latest
permissions:
contents: read
security-events: write # Required for Code Scanning
steps:
- uses: actions/checkout@v4
- name: Run StellaOps Scanner
uses: stellaops/scanner-action@v1
with:
image: ${{ github.repository }}:${{ github.sha }}
output-format: sarif
output-file: results.sarif
# Optional: filter by severity
min-severity: medium
- name: Upload SARIF to Code Scanning
uses: github/codeql-action/upload-sarif@v3
with:
sarif_file: results.sarif
category: stellaops-scanner
# Optional: wait for processing
wait-for-processing: true
```
### Option 2: REST API
For scans running outside GitHub Actions:
```bash
# Gzip + base64 encode the SARIF file
gzip -c results.sarif | base64 -w0 > sarif.b64
# Upload to GitHub Code Scanning API
curl -X POST \
-H "Authorization: Bearer $GITHUB_TOKEN" \
-H "Accept: application/vnd.github+json" \
-H "X-GitHub-Api-Version: 2022-11-28" \
"https://api.github.com/repos/OWNER/REPO/code-scanning/sarifs" \
-d "{
\"commit_sha\": \"$(git rev-parse HEAD)\",
\"ref\": \"refs/heads/main\",
\"sarif\": \"$(cat sarif.b64)\",
\"tool_name\": \"StellaOps Scanner\"
}"
```
**Required Scopes:**
- Public repos: `public_repo`
- Private repos: `security_events`
### Option 3: StellaOps CLI
```bash
# Scan and upload in one command
stella scan \
--image myregistry/myapp:latest \
--sarif results.sarif \
--github-upload \
--github-token $GITHUB_TOKEN \
--github-repo owner/repo \
--github-ref refs/heads/main \
--github-sha $(git rev-parse HEAD)
# Or: scan first, upload separately
stella scan --image myregistry/myapp:latest --sarif results.sarif
stella github upload \
--sarif results.sarif \
--repo owner/repo \
--ref refs/heads/main
```
---
## StellaOps SARIF Rule Taxonomy
### Vulnerability Rules (STELLA-VULN-*)
| Rule ID | Name | Level | Description |
|---------|------|-------|-------------|
| STELLA-VULN-001 | Critical Vulnerability | error | CVSS >= 9.0 or KEV-listed |
| STELLA-VULN-002 | High Vulnerability | error | CVSS 7.0-8.9 |
| STELLA-VULN-003 | Medium Vulnerability | warning | CVSS 4.0-6.9 |
| STELLA-VULN-004 | Low Vulnerability | note | CVSS < 4.0 |
| STELLA-VULN-005 | Reachable Vulnerability | error | Runtime-confirmed reachable |
| STELLA-VULN-006 | Static Reachable Vulnerability | warning | Static-only reachable |
### Secret Detection Rules (STELLA-SEC-*)
| Rule ID | Name | Level | Description |
|---------|------|-------|-------------|
| STELLA-SEC-001 | Hardcoded Secret | error | API key, password, token in code |
| STELLA-SEC-002 | Private Key Exposure | error | PEM, PKCS#8 private key |
| STELLA-SEC-003 | Credential Pattern | warning | Potential credential pattern |
### Supply Chain Rules (STELLA-SC-*)
| Rule ID | Name | Level | Description |
|---------|------|-------|-------------|
| STELLA-SC-001 | Unsigned Package | warning | Package lacks signature |
| STELLA-SC-002 | Unknown Provenance | warning | No SLSA provenance |
| STELLA-SC-003 | Typosquat Candidate | error | Potential typosquatting |
| STELLA-SC-004 | Deprecated Package | note | Package marked deprecated |
### Binary Hardening Rules (STELLA-BIN-*)
| Rule ID | Name | Level | Description |
|---------|------|-------|-------------|
| STELLA-BIN-001 | Missing RELRO | warning | No full RELRO |
| STELLA-BIN-002 | No Stack Canary | warning | Stack protection disabled |
| STELLA-BIN-003 | No PIE | warning | Position-independent disabled |
| STELLA-BIN-004 | No Fortify | note | FORTIFY_SOURCE not used |
### SmartDiff Rules (SDIFF-*) - Already Implemented
| Rule ID | Name | Level | Description |
|---------|------|-------|-------------|
| SDIFF001 | Material Risk Change | warning | Risk profile changed |
| SDIFF002 | Binary Hardening Regression | error | Security control removed |
| SDIFF003 | VEX Candidate | note | VEX status changed |
| SDIFF004 | Reachability Change | warning | Reachability status changed |
---
## SARIF Schema for Findings
### Complete Finding Example
```json
{
"version": "2.1.0",
"$schema": "https://json.schemastore.org/sarif-2.1.0.json",
"runs": [{
"tool": {
"driver": {
"name": "StellaOps Scanner",
"version": "3.2.1",
"informationUri": "https://stellaops.io/scanner",
"rules": [{
"id": "STELLA-VULN-001",
"name": "CriticalVulnerability",
"shortDescription": {
"text": "Critical vulnerability detected"
},
"fullDescription": {
"text": "A critical severity vulnerability (CVSS >= 9.0) was detected in a dependency."
},
"helpUri": "https://stellaops.io/rules/STELLA-VULN-001",
"properties": {
"precision": "high",
"problem.severity": "error",
"security-severity": "9.8",
"tags": ["security", "vulnerability", "critical"]
}
}],
"supportedTaxonomies": [{
"name": "CWE",
"guid": "d4c8a3c4-8f5e-4f3a-9a6b-2c7d8e9f0a1b"
}]
}
},
"taxonomies": [{
"name": "CWE",
"guid": "d4c8a3c4-8f5e-4f3a-9a6b-2c7d8e9f0a1b",
"taxa": [{
"id": "502",
"name": "Deserialization of Untrusted Data"
}]
}],
"results": [{
"ruleId": "STELLA-VULN-001",
"ruleIndex": 0,
"level": "error",
"message": {
"text": "Critical vulnerability CVE-2021-44228 (Log4Shell) in org.apache.logging.log4j:log4j-core@2.14.1. CVSS: 10.0. This vulnerability allows remote code execution via JNDI injection.",
"markdown": "**Critical vulnerability** [CVE-2021-44228](https://nvd.nist.gov/vuln/detail/CVE-2021-44228) (Log4Shell) in `org.apache.logging.log4j:log4j-core@2.14.1`.\n\n**CVSS:** 10.0 (Critical)\n\n**Description:** Remote code execution via JNDI injection.\n\n**Remediation:** Upgrade to log4j-core >= 2.17.0"
},
"locations": [{
"physicalLocation": {
"artifactLocation": {
"uri": "pom.xml",
"uriBaseId": "%SRCROOT%"
},
"region": {
"startLine": 45,
"startColumn": 1,
"endLine": 49,
"endColumn": 1,
"snippet": {
"text": "<dependency>\n <groupId>org.apache.logging.log4j</groupId>\n <artifactId>log4j-core</artifactId>\n <version>2.14.1</version>\n</dependency>"
}
}
},
"logicalLocations": [{
"name": "org.apache.logging.log4j:log4j-core",
"kind": "package",
"fullyQualifiedName": "pkg:maven/org.apache.logging.log4j/log4j-core@2.14.1"
}]
}],
"fingerprints": {
"stellaops/v1": "sha256:a1b2c3d4e5f6...",
"primaryLocationLineHash": "abc123..."
},
"partialFingerprints": {
"primaryLocationLineHash": "abc123..."
},
"taxa": [{
"id": "502",
"toolComponent": {
"name": "CWE"
}
}],
"properties": {
"stellaops.finding.id": "f47ac10b-58cc-4372-a567-0e02b2c3d479",
"stellaops.component.purl": "pkg:maven/org.apache.logging.log4j/log4j-core@2.14.1",
"stellaops.vulnerability.cve": "CVE-2021-44228",
"stellaops.vulnerability.cvss": 10.0,
"stellaops.vulnerability.severity": "critical",
"stellaops.vulnerability.epss": 0.975,
"stellaops.vulnerability.kev": true,
"stellaops.reachability.state": "RuntimeObserved",
"stellaops.reachability.confidence": 0.92,
"stellaops.vex.status": "affected",
"stellaops.evidence.uris": [
"stella://reachgraph/blake3:abc123",
"stella://signals/runtime/tenant/sha256:def456"
]
}
}],
"artifacts": [{
"location": {
"uri": "pom.xml",
"uriBaseId": "%SRCROOT%"
},
"mimeType": "application/xml",
"hashes": {
"sha-256": "e3b0c44298fc1c149afbf4c8996fb92427ae41e4649b934ca495991b7852b855"
}
}],
"versionControlProvenance": [{
"repositoryUri": "https://github.com/example/myapp",
"revisionId": "a1b2c3d4e5f6a1b2c3d4e5f6a1b2c3d4e5f6a1b2",
"branch": "main",
"mappedTo": {
"uriBaseId": "%SRCROOT%"
}
}],
"properties": {
"stellaops.scan.id": "scan-12345",
"stellaops.scan.artifact": "sha256:abc123...",
"stellaops.scan.timestamp": "2026-01-09T10:30:00Z",
"stellaops.scan.version": "3.2.1",
"stellaops.attestation": {
"digest": "sha256:sig789...",
"predicateType": "https://stellaops.io/attestation/scan/v1",
"rekorLogId": 12345678
}
}
}]
}
```
---
## Fingerprinting Strategy
Fingerprints enable GitHub to deduplicate alerts across scans:
### Primary Fingerprint (stellaops/v1)
```
SHA-256(
ruleId + "|" +
component_purl + "|" +
vulnerability_id + "|" +
artifact_digest
)
```
### Partial Fingerprints (GitHub-computed fallback)
When source code is available, provide:
- `primaryLocationLineHash`: Hash of code at finding location
- `primaryLocationContextHash`: Hash of surrounding context
### Deduplication Behavior
| Scenario | GitHub Behavior |
|----------|----------------|
| Same fingerprint, new scan | Updates existing alert |
| New fingerprint | Creates new alert |
| Missing fingerprint in new scan | Closes alert as fixed |
| Fingerprint reappears | Reopens alert |
---
## GitHub Code Scanning API Integration
### Upload Endpoint
```
POST /repos/{owner}/{repo}/code-scanning/sarifs
```
### Request Format
```json
{
"commit_sha": "a1b2c3d4e5f6...",
"ref": "refs/heads/main",
"sarif": "<gzip+base64 encoded SARIF>",
"checkout_uri": "file:///home/runner/work/repo/repo",
"started_at": "2026-01-09T10:00:00Z",
"tool_name": "StellaOps Scanner"
}
```
### Response
```json
{
"id": "47177e22-5596-11eb-80a1-c1e54ef945c6",
"url": "https://api.github.com/repos/owner/repo/code-scanning/sarifs/47177e22-5596-11eb-80a1-c1e54ef945c6"
}
```
### Status Polling
```
GET /repos/{owner}/{repo}/code-scanning/sarifs/{sarif_id}
```
Response includes `processing_status`: `pending` | `complete` | `failed`
---
## GitHub Enterprise Server Support
The existing `GitHubAppConnectorPlugin` supports GHES:
```csharp
// Endpoint resolution
var apiBase = isEnterprise
? $"https://{hostname}/api/v3"
: "https://api.github.com";
```
### GHES Configuration
```yaml
# etc/integrations.yaml
github:
type: github_enterprise
hostname: github.mycompany.com
api_version: "2022-11-28"
app_id: 12345
private_key_path: /secrets/github-app.pem
```
---
## Important Gotchas
### 1. One Tool Per Run (June 2025 Deadline)
GitHub is deprecating combined runs. Each tool must have its own run:
```json
{
"runs": [
{ "tool": { "driver": { "name": "StellaOps Scanner" } }, "results": [...] },
{ "tool": { "driver": { "name": "StellaOps SmartDiff" } }, "results": [...] }
]
}
```
**Not:**
```json
{
"runs": [
{
"tool": { "driver": { "name": "StellaOps" } },
"results": [/* mixed scanner + smartdiff */]
}
]
}
```
### 2. Permissions
| Context | Required Permission |
|---------|---------------------|
| GitHub Actions | `security-events: write` |
| REST API (public) | `public_repo` scope |
| REST API (private) | `security_events` scope |
| GitHub App | `security_events: write` |
### 3. PR Uploads from Forks
- Direct API uploads from forks have restrictions
- Use `github/codeql-action/upload-sarif` action instead
- The action handles fork context correctly
### 4. SARIF Size Limits
| Limit | Value |
|-------|-------|
| Uncompressed | 10 MB |
| Compressed (gzip) | Recommended for API |
| Results per run | 10,000 (soft limit) |
### 5. Rate Limits
- 1000 requests/hour for Code Scanning API
- Use conditional requests (`If-None-Match`) where possible
---
## Integration Architecture
```
┌─────────────────────────────────────────────────────────────────────────────┐
│ StellaOps Scanner │
│ ┌─────────────┐ ┌─────────────────┐ ┌─────────────────────────────┐ │
│ │ Scan Engine │──>│ Findings Ledger │──>│ SARIF Export Service │ │
│ └─────────────┘ └─────────────────┘ │ - FindingsSarifMapper │ │
│ │ - SarifRuleRegistry │ │
│ │ - FingerprintGenerator │ │
│ └─────────────┬───────────────┘ │
└─────────────────────────────────────────────────────────┼───────────────────┘
│ SARIF 2.1.0
┌─────────────────────────────────────────────────────────────────────────────┐
│ GitHub Integration Service │
│ ┌─────────────────────┐ ┌─────────────────────┐ ┌─────────────────┐ │
│ │ GitHubAppConnector │ │ CodeScanningClient │ │ SarifUploader │ │
│ │ (existing) │ │ (new) │ │ (new) │ │
│ └─────────────────────┘ └─────────────────────┘ └─────────────────┘ │
└─────────────────────────────────────────────────────────┬───────────────────┘
│ REST API / Actions
┌─────────────────────────────────────────────────────────────────────────────┐
│ GitHub Code Scanning │
│ ┌─────────────────┐ ┌─────────────────┐ ┌─────────────────────────┐ │
│ │ Security Tab │ │ PR Annotations │ │ Branch Protection │ │
│ │ Alerts │ │ Check Runs │ │ Rules │ │
│ └─────────────────┘ └─────────────────┘ └─────────────────────────┘ │
└─────────────────────────────────────────────────────────────────────────────┘
```
---
## CLI Commands
### Scan with SARIF Output
```bash
# Basic scan with SARIF output
stella scan --image myapp:latest --format sarif --output results.sarif
# With severity filter
stella scan --image myapp:latest --format sarif --output results.sarif \
--min-severity high
# With reachability evidence
stella scan --image myapp:latest --format sarif --output results.sarif \
--include-reachability
# Pretty-printed for debugging
stella scan --image myapp:latest --format sarif --output results.sarif \
--pretty
```
### GitHub Upload
```bash
# Upload SARIF to GitHub Code Scanning
stella github upload-sarif \
--sarif results.sarif \
--repo owner/repo \
--ref refs/heads/main \
--sha $(git rev-parse HEAD)
# With GitHub Enterprise
stella github upload-sarif \
--sarif results.sarif \
--repo owner/repo \
--ref refs/heads/main \
--sha $(git rev-parse HEAD) \
--github-url https://github.mycompany.com
# Wait for processing
stella github upload-sarif \
--sarif results.sarif \
--repo owner/repo \
--wait --timeout 5m
```
### Generate Workflow
```bash
# Generate GitHub Actions workflow
stella github generate-workflow \
--repo owner/repo \
--output .github/workflows/stellaops-scan.yml \
--triggers push,pull_request,schedule \
--schedule "0 3 * * 1"
```
---
## Success Criteria
### Quantitative
| Metric | Target |
|--------|--------|
| SARIF schema validation | 100% pass rate |
| Upload success rate | > 99% |
| Processing time (1000 findings) | < 30 seconds |
| Fingerprint stability | 100% (same input = same fingerprint) |
### Qualitative
- Findings appear correctly in GitHub Security tab
- PR annotations show at correct line numbers
- Alert deduplication works across scans
- Branch protection rules can gate on scan results
---
## Related Documentation
- [SARIF 2.1.0 Specification (OASIS)](https://docs.oasis-open.org/sarif/sarif/v2.1.0/sarif-v2.1.0.html)
- [GitHub SARIF Support](https://docs.github.com/en/code-security/code-scanning/integrating-with-code-scanning/sarif-support-for-code-scanning)
- [GitHub Code Scanning REST API](https://docs.github.com/en/rest/code-scanning)
- [upload-sarif Action](https://docs.github.com/en/code-security/code-scanning/integrating-with-code-scanning/uploading-a-sarif-file-to-github)
---
## Sprint Index
| Sprint ID | Title | Status |
|-----------|-------|--------|
| SPRINT_20260109_010_000 | INDEX: GitHub Code Scanning | Planning |
| SPRINT_20260109_010_001 | Findings SARIF Exporter | Planning |
| SPRINT_20260109_010_002 | GitHub Code Scanning Client | Planning |
| SPRINT_20260109_010_003 | CI/CD Workflow Templates | Planning |
---
_Last updated: 09-Jan-2026_

View File

@@ -0,0 +1,828 @@
# Hybrid Reachability and VEX Integration
> **Status:** Revised
> **Original:** 09-Jan-2026
> **Revision:** 09-Jan-2026
> **Author:** Product/Engineering
> **Epic:** Evidence-First Vulnerability Triage
---
## Executive Summary
This advisory defines the **Hybrid Reachability System** - a unified approach to determining vulnerability exploitability by combining **static call-graph analysis** with **runtime execution evidence** to produce **high-confidence VEX verdicts**. The system enables StellaOps to answer: "Is this CVE actually reachable in my running application?"
### Key Differentiators
1. **Evidence-First:** Every VEX verdict backed by auditable, reproducible evidence
2. **Lattice-Based Decisions:** Mathematically sound state transitions (never weaker than strongest evidence)
3. **Offline-Capable:** Full functionality in air-gapped environments via bundle replay
4. **Deterministic:** Same inputs always produce same verdicts (auditable, reproducible)
---
## Problem Statement
Current vulnerability scanners generate excessive noise:
- **70-90% of CVEs** flagged are not reachable in actual code paths
- **Static-only analysis** over-approximates (flags dead code, feature-flagged paths)
- **Runtime-only analysis** under-approximates (misses rarely-executed paths)
- **No evidence chain** connecting scanner output to VEX justification
### Current State in StellaOps
| Component | Status | Gap |
|-----------|--------|-----|
| Static call-graph extraction | Implemented (5 languages) | No unified query interface |
| ReachGraph storage | Implemented | No runtime evidence merge |
| Runtime fact ingestion | Contract defined | No collection agent |
| VEX decision emission | Implemented | No reachability-aware justification |
| Evidence-weighted scoring | Implemented (6 dimensions) | RTS dimension needs runtime feed |
| Signals module | Implemented | Missing runtime trace pipeline |
---
## Solution Architecture
### Conceptual Model
```
STATIC ANALYSIS RUNTIME ANALYSIS
| |
+--------------------+--------------------+ +---------------+---------------+
| | | |
v v v v
+--------+ +----------+ +---------+ +----------+ +--------+ +--------+
| SBOM |--->| CallGraph|--->|ReachGraph| | Runtime |--->| Symbol |--->|Reachability|
|Generator| | Extractor| | Service | | Agent | |Normalizer| | Index |
+--------+ +----------+ +---------+ +----------+ +--------+ +--------+
| |
+---------------+---------------+
|
v
+----------------+
| VEX Decision |
| Filter |
+----------------+
|
v
+----------------+
| OpenVEX Output |
| + Evidence |
+----------------+
```
### Component Responsibilities
#### 1. Reachability Core Library (NEW)
**Location:** `src/__Libraries/StellaOps.Reachability.Core/`
Provides the unified `IReachabilityIndex` interface that facades over:
- ReachGraph (static call-graph queries)
- Signals (runtime facts)
- CVE-Symbol mapping corpus
```csharp
public interface IReachabilityIndex
{
/// <summary>
/// Check if symbol exists in static call graph from any entrypoint.
/// </summary>
Task<StaticReachabilityResult> QueryStaticAsync(
SymbolRef symbol,
string artifactDigest,
CancellationToken ct);
/// <summary>
/// Check if symbol was observed at runtime within observation window.
/// </summary>
Task<RuntimeReachabilityResult> QueryRuntimeAsync(
SymbolRef symbol,
string artifactDigest,
TimeSpan observationWindow,
CancellationToken ct);
/// <summary>
/// Compute hybrid reachability score combining static + runtime evidence.
/// </summary>
Task<HybridReachabilityResult> QueryHybridAsync(
SymbolRef symbol,
string artifactDigest,
HybridQueryOptions options,
CancellationToken ct);
/// <summary>
/// Batch query for multiple symbols (CVE-related).
/// </summary>
Task<IReadOnlyList<HybridReachabilityResult>> QueryBatchAsync(
IEnumerable<SymbolRef> symbols,
string artifactDigest,
HybridQueryOptions options,
CancellationToken ct);
}
```
#### 2. Symbol Canonicalization Service (NEW)
**Location:** `src/__Libraries/StellaOps.Reachability.Core/Symbols/`
Normalizes symbols across different sources:
- Static: Roslyn (`Namespace.Type.Method`), ASM (`class.method(descriptor)`)
- Runtime: JIT names, ETW method IDs, eBPF uprobe symbols
- Native: Mangled C++, demangled, ELF symbols
```csharp
public interface ISymbolCanonicalizer
{
/// <summary>
/// Canonicalize symbol to portable format.
/// </summary>
CanonicalSymbol Canonicalize(RawSymbol raw, SymbolSource source);
/// <summary>
/// Match two symbols with fuzzy tolerance for minor variations.
/// </summary>
SymbolMatchResult Match(CanonicalSymbol a, CanonicalSymbol b, MatchOptions options);
}
public sealed record CanonicalSymbol
{
public required string Purl { get; init; } // pkg:npm/lodash@4.17.21
public required string Namespace { get; init; } // lodash
public required string Type { get; init; } // _ (for JS) or class name
public required string Method { get; init; } // get
public required string Signature { get; init; } // (object, string)
public required string CanonicalId { get; init; } // SHA-256 of above
}
```
#### 3. CVE-Symbol Mapping Corpus (NEW)
**Location:** `src/__Libraries/StellaOps.Reachability.Core/CveMapping/`
Maps CVE identifiers to vulnerable symbols:
```csharp
public interface ICveSymbolMappingService
{
/// <summary>
/// Get vulnerable symbols for a CVE.
/// </summary>
Task<CveSymbolMapping?> GetMappingAsync(string cveId, CancellationToken ct);
/// <summary>
/// Ingest mapping from patch analysis or manual curation.
/// </summary>
Task IngestMappingAsync(CveSymbolMapping mapping, CancellationToken ct);
}
public sealed record CveSymbolMapping
{
public required string CveId { get; init; }
public required ImmutableArray<VulnerableSymbol> Symbols { get; init; }
public required MappingSource Source { get; init; }
public required double Confidence { get; init; }
public required DateTimeOffset ExtractedAt { get; init; }
public string? PatchCommitUrl { get; init; }
public string? DeltaSigDigest { get; init; }
}
public sealed record VulnerableSymbol
{
public required CanonicalSymbol Symbol { get; init; }
public required VulnerabilityType Type { get; init; } // Sink, TaintSource, GadgetEntry
public string? Condition { get; init; } // e.g., "when input > 1024"
}
public enum MappingSource
{
PatchAnalysis, // Automated extraction from git diff
OsvDatabase, // OSV affected ranges with functions
ManualCuration, // Security researcher input
DeltaSignature, // Binary diff signature match
AiExtraction // LLM-assisted extraction from description
}
```
#### 4. Runtime Agent Framework (NEW)
**Location:** `src/Signals/StellaOps.Signals.RuntimeAgent/`
Pluggable runtime collection agents:
| Platform | Agent Type | Collection Method | Overhead |
|----------|-----------|-------------------|----------|
| .NET | EventPipe | CLR method enter/leave | <2% |
| .NET | CLR Profiler | ICorProfiler callbacks | <5% |
| Java | JFR | Flight Recorder events | <1% |
| Java | JVMTI | Agent attach | <3% |
| Node.js | V8 Profiler | CPU profiler | <2% |
| Python | sys.settrace | Frame tracing | <10% |
| Native | eBPF | uprobe/uretprobe | <1% |
| Windows | ETW | CLR/JScript providers | <1% |
```csharp
public interface IRuntimeAgent
{
string AgentId { get; }
RuntimePlatform Platform { get; }
RuntimePosture Posture { get; }
Task StartAsync(RuntimeAgentOptions options, CancellationToken ct);
Task StopAsync(CancellationToken ct);
IAsyncEnumerable<RuntimeMethodEvent> StreamEventsAsync(CancellationToken ct);
}
public sealed record RuntimeMethodEvent
{
public required string SymbolId { get; init; }
public required string MethodName { get; init; }
public required string TypeName { get; init; }
public required string AssemblyOrModule { get; init; }
public required DateTimeOffset Timestamp { get; init; }
public required RuntimeEventKind Kind { get; init; } // Enter, Leave, Tail
public string? ContainerId { get; init; }
public int? ProcessId { get; init; }
public string? ThreadId { get; init; }
public IReadOnlyDictionary<string, string>? Context { get; init; }
}
```
#### 5. VEX Decision Filter Enhancement (ENHANCEMENT)
**Location:** `src/Policy/StellaOps.Policy.Engine/Vex/`
Enhance existing `IVexDecisionEmitter` with reachability-aware justification:
```csharp
public interface IReachabilityAwareVexEmitter
{
/// <summary>
/// Emit VEX verdict with hybrid reachability evidence.
/// </summary>
Task<VexDecisionDocument> EmitVerdictAsync(
Finding finding,
HybridReachabilityResult reachability,
VexEmissionOptions options,
CancellationToken ct);
}
```
### Reachability Lattice (8-State Model)
The system uses an 8-state lattice for evidence strength:
```
X (Contested)
/ \
/ \
CR (Confirmed CU (Confirmed
Reachable) Unreachable)
| \ / |
| \ / |
RO (Runtime RU (Runtime
Observed) Unobserved)
| |
| |
SR (Static SU (Static
Reachable) Unreachable)
\ /
\ /
U (Unknown)
```
**State Transitions:**
| From | Evidence | To | Confidence Delta |
|------|----------|-----|-----------------|
| U | Static analysis finds path | SR | +0.3 |
| U | Static analysis proves no path | SU | +0.4 |
| SR | Runtime observes execution | RO | +0.3 |
| SR | Runtime window expires with no observation | RU | +0.2 |
| SU | Runtime observes execution (unexpected!) | X | -0.2 (conflict) |
| RO | Multiple sources confirm | CR | +0.2 |
| RU | Multiple sources confirm | CU | +0.2 |
### VEX Justification Mapping
| Lattice State | VEX Status | Justification | Confidence Range |
|---------------|------------|---------------|------------------|
| CU | not_affected | vulnerable_code_not_in_execute_path | 0.90-1.00 |
| RU | not_affected | vulnerable_code_not_in_execute_path | 0.70-0.89 |
| SU | not_affected | vulnerable_code_not_in_execute_path | 0.50-0.69 |
| CR | affected | - | 0.90-1.00 |
| RO | affected | - | 0.70-0.89 |
| SR | under_investigation | - | 0.30-0.69 |
| U | under_investigation | - | 0.00-0.29 |
| X | under_investigation | - | requires_manual_review |
---
## Data Contracts
### 1. Static Reachability (existing, enhanced)
```json
{
"schemaVersion": "reachability.static@v2",
"artifactDigest": "sha256:abc123...",
"component": "pkg:npm/lodash@4.17.21",
"symbols": [
{
"canonicalId": "sha256:def456...",
"namespace": "lodash",
"type": "_",
"method": "get",
"signature": "(object, string)",
"entrypoints": ["main", "handleRequest"],
"pathLength": 3,
"guards": [
{"type": "FeatureFlag", "key": "ENABLE_LODASH", "value": "true"}
]
}
],
"extractedAt": "2026-01-09T10:00:00Z",
"extractorVersion": "scanner.callgraph@3.2.1"
}
```
### 2. Runtime Reachability (new)
```json
{
"schemaVersion": "reachability.runtime@v1",
"artifactDigest": "sha256:abc123...",
"observationWindow": {
"start": "2026-01-01T00:00:00Z",
"end": "2026-01-09T00:00:00Z",
"durationDays": 8
},
"trafficProfile": {
"requestCount": 1250000,
"percentile": "p95",
"environments": ["production"]
},
"symbols": [
{
"canonicalId": "sha256:def456...",
"hitCount": 45230,
"firstSeen": "2026-01-02T14:23:00Z",
"lastSeen": "2026-01-08T22:15:00Z",
"contexts": [
{
"containerId": "abc123",
"processId": 1234,
"route": "/api/v1/users",
"frequency": 0.82
}
]
}
],
"collectedAt": "2026-01-09T00:05:00Z",
"agentVersion": "signals.runtime@1.0.0",
"agentPosture": "ActiveTracing"
}
```
### 3. Hybrid Reachability Result
```json
{
"schemaVersion": "reachability.hybrid@v1",
"artifactDigest": "sha256:abc123...",
"symbol": {
"canonicalId": "sha256:def456...",
"displayName": "lodash.get(object, string)"
},
"latticeState": "RO",
"confidence": 0.85,
"staticEvidence": {
"present": true,
"pathCount": 3,
"shortestPath": 2,
"guards": []
},
"runtimeEvidence": {
"present": true,
"hitCount": 45230,
"lastSeen": "2026-01-08T22:15:00Z",
"windowDays": 8
},
"verdict": {
"status": "affected",
"justification": null,
"confidenceBucket": "high"
},
"evidenceUris": [
"stella://reachgraph/sha256:abc123/slice?symbol=sha256:def456",
"stella://signals/runtime/sha256:abc123?symbol=sha256:def456"
],
"computedAt": "2026-01-09T10:30:00Z",
"computedBy": "reachability.index@1.0.0"
}
```
### 4. OpenVEX with StellaOps Evidence Extension
```json
{
"@context": "https://openvex.dev/ns/v0.2.0",
"author": "StellaOps Policy Engine",
"timestamp": "2026-01-09T10:35:00Z",
"version": 1,
"statements": [
{
"vulnerability": {
"@id": "CVE-2021-44228",
"name": "Log4Shell",
"description": "Apache Log4j2 JNDI injection"
},
"products": [
{
"@id": "pkg:maven/org.apache.logging.log4j/log4j-core@2.14.1",
"subcomponents": [
{"@id": "pkg:maven/org.apache.logging.log4j/log4j-api@2.14.1"}
]
}
],
"status": "not_affected",
"justification": "vulnerable_code_not_in_execute_path",
"impact_statement": "The vulnerable JNDI lookup is not reachable from any application entrypoint.",
"action_statement": "No action required. Monitor for code changes that may introduce reachability.",
"x-stellaops-evidence": {
"schemaVersion": "stellaops.evidence@v1",
"latticeState": "CU",
"confidence": 0.95,
"staticAnalysis": {
"graphDigest": "blake3:abc123...",
"pathCount": 0,
"analyzerVersion": "scanner.callgraph@3.2.1"
},
"runtimeAnalysis": {
"observationWindowDays": 14,
"trafficPercentile": "p95",
"hitCount": 0,
"agentPosture": "EbpfDeep"
},
"cveSymbolMapping": {
"source": "PatchAnalysis",
"vulnerableSymbols": [
"org.apache.logging.log4j.core.lookup.JndiLookup::lookup"
],
"mappingConfidence": 0.98
},
"evidenceUris": [
"stella://reachgraph/blake3:abc123",
"stella://signals/runtime/tenant123/sha256:def456"
],
"attestation": {
"dsseDigest": "sha256:sig789...",
"rekorLogIndex": 12345678
}
}
}
]
}
```
---
## Evidence URI Scheme
Define `stella://` URI scheme for evidence references:
| Pattern | Description | Example |
|---------|-------------|---------|
| `stella://reachgraph/{digest}` | Full reachability graph | `stella://reachgraph/blake3:abc123` |
| `stella://reachgraph/{digest}/slice?symbol={id}` | Symbol slice | `stella://reachgraph/blake3:abc123/slice?symbol=sha256:def` |
| `stella://signals/runtime/{tenant}/{artifact}` | Runtime facts | `stella://signals/runtime/acme/sha256:abc` |
| `stella://signals/runtime/{tenant}/{artifact}?symbol={id}` | Symbol runtime facts | `stella://signals/runtime/acme/sha256:abc?symbol=sha256:def` |
| `stella://cvemap/{cveId}` | CVE-symbol mapping | `stella://cvemap/CVE-2021-44228` |
| `stella://attestation/{digest}` | DSSE attestation | `stella://attestation/sha256:sig789` |
---
## Integration Architecture
### Data Flow
```
┌─────────────────────────────────────────────────────────────────────────────┐
│ Scanner Module │
│ ┌─────────────┐ ┌─────────────────┐ ┌─────────────────────────────┐ │
│ │ SBOM │──>│ CallGraph │──>│ ReachGraph Service │ │
│ │ Generator │ │ Extractor │ │ (static reachability store) │ │
│ └─────────────┘ └─────────────────┘ └─────────────────────────────┘ │
└─────────────────────────────────────────────────────────────────────────────┘
│ Static edges + nodes
┌─────────────────────────────────────────────────────────────────────────────┐
│ Reachability Core Library │
│ ┌──────────────────┐ ┌──────────────────┐ ┌──────────────────────────┐ │
│ │ Symbol │ │ CVE-Symbol │ │ IReachabilityIndex │ │
│ │ Canonicalizer │ │ Mapping Service │ │ (unified query facade) │ │
│ └──────────────────┘ └──────────────────┘ └──────────────────────────┘ │
└─────────────────────────────────────────────────────────────────────────────┘
│ Runtime facts
┌─────────────────────────────────────────────────────────────────────────────┐
│ Signals Module │
│ ┌─────────────────┐ ┌─────────────────┐ ┌─────────────────────────┐ │
│ │ Runtime Agent │──>│ Symbol │──>│ RuntimeFacts Store │ │
│ │ (.NET/Java/etc) │ │ Normalizer │ │ (Valkey + PostgreSQL) │ │
│ └─────────────────┘ └─────────────────┘ └─────────────────────────┘ │
└─────────────────────────────────────────────────────────────────────────────┘
│ Hybrid queries
┌─────────────────────────────────────────────────────────────────────────────┐
│ Policy Engine │
│ ┌──────────────────┐ ┌──────────────────┐ ┌──────────────────────────┐ │
│ │ VEX Decision │ │ Reachability- │ │ Evidence-Weighted │ │
│ │ Emitter │<─│ Aware Filter │<─│ Score Calculator │ │
│ └──────────────────┘ └──────────────────┘ └──────────────────────────┘ │
└─────────────────────────────────────────────────────────────────────────────┘
│ VEX verdicts
┌─────────────────────────────────────────────────────────────────────────────┐
│ VexLens Module │
│ ┌──────────────────┐ ┌──────────────────┐ ┌──────────────────────────┐ │
│ │ Consensus │ │ Trust Weight │ │ Conflict │ │
│ │ Engine │ │ Engine │ │ Resolution │ │
│ └──────────────────┘ └──────────────────┘ └──────────────────────────┘ │
└─────────────────────────────────────────────────────────────────────────────┘
```
### API Endpoints (New/Enhanced)
| Method | Path | Description |
|--------|------|-------------|
| POST | `/v1/reachability/query` | Query hybrid reachability for symbol |
| POST | `/v1/reachability/query/batch` | Batch query for CVE symbols |
| GET | `/v1/reachability/artifact/{digest}/summary` | Artifact reachability summary |
| POST | `/v1/runtime/ingest` | Ingest runtime facts from agent |
| GET | `/v1/runtime/facts/{artifact}` | Get runtime facts for artifact |
| POST | `/v1/cvemap/ingest` | Ingest CVE-symbol mapping |
| GET | `/v1/cvemap/{cveId}` | Get CVE-symbol mapping |
| POST | `/v1/vex/emit/reachability-aware` | Emit VEX with reachability evidence |
---
## Air-Gap Support
### Offline Bundle Format
```
hybrid-reachability-bundle/
├── manifest.json # Bundle metadata, digests
├── static/
│ ├── reachgraphs.jsonl # CallGraph snapshots
│ └── reachgraphs.sig # DSSE signatures
├── runtime/
│ ├── facts.jsonl # Runtime observations
│ └── facts.sig # DSSE signatures
├── cvemap/
│ ├── mappings.jsonl # CVE-symbol mappings
│ └── mappings.sig # DSSE signatures
├── verdicts/
│ ├── vex-decisions.jsonl # Pre-computed VEX verdicts
│ └── vex-decisions.sig # DSSE signatures
└── signatures/
└── bundle.dsse # Bundle attestation
```
### Offline Workflow
1. **Export** (connected environment):
```bash
stella reachability export --artifact sha256:abc123 --output bundle.zip
```
2. **Transfer** bundle to air-gapped environment
3. **Import** (air-gapped environment):
```bash
stella reachability import --bundle bundle.zip --verify
```
4. **Query** (air-gapped, uses cached data):
```bash
stella reachability query --cve CVE-2021-44228 --artifact sha256:abc123
```
---
## Determinism Guarantees
### Reproducibility Requirements
1. **Canonical Serialization:** RFC 8785 JSON (sorted keys, no nulls, minimal escaping)
2. **Stable Symbol IDs:** SHA-256 of canonical symbol representation
3. **Time Injection:** All timestamps via `TimeProvider` (testable, replayable)
4. **Culture Invariance:** `InvariantCulture` for all string operations
5. **Ordered Collections:** `ImmutableSortedSet` / `ImmutableSortedDictionary` for deterministic iteration
### Replay Verification
```csharp
public interface IReachabilityReplayService
{
/// <summary>
/// Replay hybrid reachability computation from inputs.
/// </summary>
Task<ReplayResult> ReplayAsync(
HybridReachabilityInputs inputs,
HybridReachabilityResult expected,
CancellationToken ct);
}
public sealed record ReplayResult
{
public required bool Match { get; init; }
public required string ExpectedDigest { get; init; }
public required string ActualDigest { get; init; }
public IReadOnlyList<string>? Differences { get; init; }
}
```
---
## Security Considerations
### Access Control
| Resource | Read | Write | Admin |
|----------|------|-------|-------|
| Static reachability | `reachability:read` | `reachability:write` | - |
| Runtime facts | `runtime:read` | `runtime:write` | - |
| CVE mappings | `cvemap:read` | `cvemap:write` | `cvemap:admin` |
| VEX verdicts | `vex:read` | `vex:write` | - |
### Data Sensitivity
- **Runtime traces expose code paths:** May reveal internal architecture
- **Symbol names may be sensitive:** Obfuscation support planned
- **Tenant isolation:** RLS policies enforce strict separation
### Threat Model
| Threat | Mitigation |
|--------|------------|
| Malicious runtime agent | Agent authentication via mTLS, signed events |
| CVE mapping poisoning | Mapping provenance tracking, multi-source consensus |
| Evidence tampering | DSSE attestations, Rekor transparency log |
| Information leakage | Tenant RLS, encrypted storage, audit logs |
---
## Observability
### Metrics
| Metric | Description |
|--------|-------------|
| `reachability_query_duration_seconds` | Query latency histogram |
| `reachability_lattice_state_total` | Count by lattice state |
| `runtime_facts_ingested_total` | Runtime facts ingested |
| `runtime_agent_connected_gauge` | Connected agents |
| `cvemap_mappings_total` | CVE mappings count |
| `vex_verdicts_by_reachability_total` | VEX verdicts by lattice state |
### Traces
| Span | Description |
|------|-------------|
| `reachability.query.static` | Static graph query |
| `reachability.query.runtime` | Runtime facts query |
| `reachability.query.hybrid` | Combined computation |
| `reachability.canonicalize` | Symbol canonicalization |
| `cvemap.lookup` | CVE-symbol lookup |
### Alerts
| Alert | Condition | Severity |
|-------|-----------|----------|
| `ReachabilityQuerySlow` | P95 > 500ms | warning |
| `RuntimeAgentDisconnected` | No heartbeat 5min | warning |
| `CveMappingStale` | No updates 7 days | info |
| `LatticeConflictRate` | X state > 5% | warning |
---
## Performance Targets
| Operation | Target | Notes |
|-----------|--------|-------|
| Hybrid query (single symbol) | P95 < 50ms | Cached |
| Hybrid query (batch, 100 symbols) | P95 < 500ms | Parallel |
| Runtime fact ingestion | 10,000 events/sec | Per agent |
| Symbol canonicalization | < 1ms | In-memory |
| CVE mapping lookup | P95 < 10ms | Cached |
| VEX emission | P95 < 100ms | Includes signing |
---
## Dependencies
### Internal Modules
| Module | Dependency Type | Purpose |
|--------|-----------------|---------|
| ReachGraph | Data source | Static call-graph queries |
| Signals | Data source + sink | Runtime fact storage |
| Scanner.CallGraph | Data producer | Call-graph extraction |
| Policy | Consumer | VEX decision emission |
| VexLens | Consumer | Consensus computation |
| Attestor | Integration | DSSE signing |
| Authority | Integration | Access control |
### External Dependencies
| Dependency | Purpose | Offline Alternative |
|------------|---------|---------------------|
| OSV API | CVE-symbol enrichment | Bundled corpus |
| NVD API | CVE details | Bundled corpus |
| Rekor | Transparency log | Local log or skip |
---
## Implementation Phases
### Phase 1: Foundation (Weeks 1-2)
- Reachability Core library with `IReachabilityIndex`
- Symbol canonicalization service
- Integration with existing ReachGraph
### Phase 2: CVE Mapping (Weeks 3-4)
- CVE-symbol mapping service
- Patch analysis extractor (git diff parsing)
- Initial corpus from high-profile CVEs
### Phase 3: Runtime Collection (Weeks 5-8)
- Runtime agent framework
- .NET EventPipe agent
- Java JFR agent
- Symbol normalization pipeline
### Phase 4: VEX Integration (Weeks 9-10)
- Reachability-aware VEX emitter
- Evidence extension schema
- Policy Engine integration
### Phase 5: UI & Observability (Weeks 11-12)
- Evidence panel enhancements
- Metrics and alerts
- Documentation and runbooks
---
## Success Criteria
### Quantitative
| Metric | Target | Measurement |
|--------|--------|-------------|
| False positive reduction | >60% | CVEs marked NA with reachability evidence |
| Confidence accuracy | >90% | Verdicts validated against manual review |
| Query latency | P95 < 100ms | Hybrid queries |
| Coverage | >80% | Artifacts with both static + runtime evidence |
### Qualitative
- Security teams trust VEX verdicts backed by evidence
- Developers understand why CVE is/isn't relevant
- Auditors can verify verdict provenance
- Air-gapped deployments have full functionality
---
## Related Documentation
- [ReachGraph Architecture](../../modules/reach-graph/architecture.md)
- [Signals Architecture](../../modules/signals/architecture.md)
- [VexLens Architecture](../../modules/vex-lens/architecture.md)
- [Evidence-Weighted Scoring](../../modules/signals/evidence-weighted-scoring.md)
- [DSSE Attestation](../../modules/attestor/dsse-integration.md)
---
## Sprint Index
| Sprint ID | Title | Status |
|-----------|-------|--------|
| SPRINT_20260109_009_000 | INDEX: Hybrid Reachability | Planning |
| SPRINT_20260109_009_001 | Reachability Core Library | Planning |
| SPRINT_20260109_009_002 | Symbol Canonicalization | Planning |
| SPRINT_20260109_009_003 | CVE-Symbol Mapping | Planning |
| SPRINT_20260109_009_004 | Runtime Agent Framework | Planning |
| SPRINT_20260109_009_005 | VEX Decision Integration | Planning |
| SPRINT_20260109_009_006 | Evidence Panel UI | Planning |
---
_Last updated: 09-Jan-2026_

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Heres a simple way to make vulnerability triage almost noisefree: combine **static SBOM callgraph pruning** with **runtime reachability hints** before making a VEX decision.
---
# Why this matters (plain English)
* Static scanners flag lots of CVEs that your app never calls.
* Runtimes (traces, signals) know what actually executed.
* Merging the two yields “only the CVEs that matter,” so your VEX is credible and quiet.
---
# The hybrid model (static → dynamic → VEX)
1. **Static stage (Sbomer + Feedser assist)**
* Build SBOM (CycloneDX/SPDX).
* Generate a **perpackage call graph** (library → functions → entrypoints).
* Compute a **pruned reachable set** using import graphs, symbol tables, and package metadata.
* Output: `reachability_static.json` (component → callable IDs).
2. **Dynamic stage (Signals + Scheduler traces)**
* Ingest **runtime traces** (e.g., eBPF/ETW/CLR Profiler/JFR) from Schedulermanaged jobs.
* Normalize to **reachability vectors**: `(component, symbol, freq, last_seen, context)`.
* Output: `reachability_runtime.json`.
3. **Decision stage (Vexer)**
* For each CVE → vulnerable symbols (from advisories/OSVs, deltasigs if available).
* If vulnerable symbol ∉ static set → **Not Affected (NA: not reachable)**.
* If ∈ static but ∉ runtime → **Under Investigation / Likely NA** (confidence < 1).
* If runtime **Affected** with confidence and evidence URIs.
* Emit **VEX** entries with justification (`not_provided_code_path`, `requires_config`, `fixed`, etc.) and confidence scores.
---
# Minimal PoC plan (2 weeks of evening work)
**Goal:** Let **Vexer** import runtime reachability vectors from **Scheduler** traces and use them to gate VEX verdicts.
### 0) Contracts (day 1)
* **Schema:**
* `reachability_static.jsonl`: `{ component, version, symbols:[...] }`
* `reachability_runtime.jsonl`: `{ component, symbol, last_seen, count, context:{pid, container, route}}`
* **Evidence URIs:** `stella://signals/<trace-id>#symbol=<name>`
### 1) Static extractor (days 24)
* Sbomer plugin: emit **symbol list + call graph** per artifact.
* Start with **.NET**: use Roslyn/IL metadata to map `assembly → type → method`.
* Heuristic fallbacks for native: ELF/PE export tables.
### 2) Runtime collector (days 36)
* Signals module:
* .NET CLR Profiler or EventPipemethod enter/leave (sampling ok).
* Map back to `(assembly, type, method)` + container tags.
* Scheduler: batch traces into **reachability vectors** and push to **Router**.
### 3) Vexer importer (days 68)
* New `Vexer.Reachability` package:
* Merge static + runtime with **component coordinate normalization** (purl).
* `bool IsRuntimeReachable(component, symbol)`; `ReachabilityScore 0..1`.
### 4) VEX decision filter (days 810)
* For each CVE advisory record (from Feedser): vulnerable symbols lookup.
* Decision table:
* `Runtime=1` **Affected (A)**.
* `Static=1, Runtime=0` **NA (Not reachable) with low confidence** unless policy overrides.
* `Static=0` **NA (No code path)**.
* Emit CycloneDX VEX or CSAF with **justifications + evidence links**.
### 5) UI & Ops (days 1014)
* **Stella UI:** badge per CVE: `Affected / NA / Probable NA`, hover shows symbols and lastseen.
* **Policy Engine:** org rules like treat Probable NA as NA after 14 days of runtime with p95 traffic.”
* **Notify:** only alert on `Affected` or `Probable NA → A` transitions.
---
# Data model & code stubs (illustrative)
**Vexer reachability interface**
```csharp
public record SymbolRef(string Purl, string Assembly, string Type, string Method);
public interface IReachabilityIndex {
bool InStatic(SymbolRef s);
bool InRuntime(SymbolRef s, TimeSpan since, out int count);
double Score(SymbolRef s); // 0..1 weighted by freq/recency
}
```
**Decision kernel**
```csharp
VexVerdict Decide(Cve cve, IEnumerable<SymbolRef> vulnSyms, IReachabilityIndex idx) {
var anyRuntime = vulnSyms.Any(s => idx.InRuntime(s, TimeSpan.FromDays(14), out _));
var anyStatic = vulnSyms.Any(s => idx.InStatic(s));
return anyRuntime ? VexVerdict.Affected
: anyStatic ? VexVerdict.ProbableNotAffected // gated by policy window
: VexVerdict.NotAffected;
}
```
**Evidence snippet in VEX (CycloneDX)**
```json
{
"vulnerability": { "id": "CVE-2025-12345" },
"analysis": {
"state": "not_affected",
"justification": "Vulnerable_code_not_in_execute_path",
"response": [ "will_not_fix" ],
"detail": "Symbols present but not executed across 14d p95 traffic",
"evidence": [
"stella://signals/trace-9f12#symbol=Contoso.Crypto.Rsa::Sign"
]
}
}
```
---
# Where it plugs into StellaOps
* **Sbomer**: adds callgraph/symbol export plugin.
* **Signals**: runtime tracer + compressor reachability vectors.
* **Scheduler**: tags traces by job/tenant/env; hands them to Router.
* **Vexer**: new Reachability importer + decision filter.
* **Feedser**: enriches CVEs with symbol hints (from OSV, deltasigs).
* **Policy Engine**: organization rules for confidence windows.
* **Notify/UI/Timeline**: surface verdicts, evidence, and flips over time.
---
# Guardrails & edge cases
* **Backports:** pair with your existing *binarydelta signatures* so fixed but looks vulnerable becomes **NA (fixed by backport)** even if symbol name matches.
* **Lazy paths & feature flags:** allow **context filters** (route, tenant, env) before declaring NA.
* **Airgapped:** ship traces via offline bundle (`*.signals.zip`) and replay.
---
# Next steps I can do now
1. Draft the JSON schemas + purl mapping table.
2. Add the `Vexer.Reachability` package and wire the decision filter.
3. Provide a tiny sample repo (toy service + vulnerable lib) to demo **A → Probable NA → NA** as traffic evolves.
If you want, Ill generate the initial schemas and a .NET tracer checklist so you can drop them into `docs/modules/`.

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Heres a quick, practical path to make your scanners findings show up in GitHubs **Code scanning** UI with almost no integration work: emit **SARIF 2.1.0** and upload it.
---
### What SARIF is (and what GitHub expects)
* **SARIF** = Static Analysis Results Interchange Format, a JSON standard for static-analysis results. GitHub Code Scanning accepts a **subset** of **SARIF 2.1.0** and turns it into alerts in the Security tab. ([GitHub Docs][1])
---
### Three upload options (pick one)
1. **GitHub Actions**: add a step that uploads your SARIF file(s).
```yaml
# .github/workflows/upload-sarif.yml
name: Upload SARIF
on:
push:
schedule: [{cron: "0 3 * * 1"}] # optional weekly recrawl
jobs:
sarif:
runs-on: ubuntu-latest
permissions:
security-events: write # required to publish code scanning alerts
contents: read
steps:
- uses: actions/checkout@v4
- name: Run your scanner
run: ./your_scanner --format sarif --out results.sarif
- name: Upload SARIF to Code Scanning
uses: github/codeql-action/upload-sarif@v3
with:
sarif_file: results.sarif
category: your-scanner
```
This uses GitHubs official **upload-sarif** action and is the easiest route. ([GitHub Docs][2])
2. **REST API**: gzip + base64 your SARIF and POST to `code-scanning/sarifs` (needs `security_events` scope for private repos). Useful if you run scans outside Actions. ([GitHub Docs][3])
3. **CodeQL CLI**: `codeql github upload-results --sarif-file results.sarif` (also needs proper token). Handy if youre already using the CLI in your CI. ([GitHub Docs][4])
---
### Minimal SARIF you should emit
At minimum, include:
* `version: "2.1.0"`
* one `run` with your `tool.driver` (name, version)
* `results[]` with each findings `ruleId`, `message.text`, and at least one `location` (file/region) so GitHub can anchor it to code. (Empty or missing locations often breaks uploads.) ([GitHub Docs][1])
Skeleton:
```json
{
"version": "2.1.0",
"$schema": "https://json.schemastore.org/sarif-2.1.0.json",
"runs": [{
"tool": { "driver": { "name": "StellaOps Scanner", "version": "1.0.0" } },
"results": [{
"ruleId": "STELLA001",
"message": { "text": "Vulnerability XYZ in package foo@1.2.3" },
"locations": [{
"physicalLocation": {
"artifactLocation": { "uri": "src/app/foo.js" },
"region": { "startLine": 42 }
}
}]
}]
}]
}
```
(Full schema: OASIS SARIF 2.1.0.) ([OASIS Open][5])
---
### Gotchas (save yourself time)
* **One tool/category per run**: GitHub is deprecating combining multiple runs with the same tool+category in a single upload; by **June 2025** such uploads will fail. Keep runs distinct or separate files. ([The GitHub Blog][6])
* **Partial fingerprints**: If you dont provide them, the upload action can compute them (prevents duplicate alerts) when source is present. ([GitHub Docs][2])
* **Permissions**: in Actions, grant `security-events: write`. For API/CLI, use tokens with the right scopes. ([GitHub Docs][3])
* **PRs from forks**: public API uploads have restrictions; the `upload-sarif` action is the usual workaround in PR contexts. ([GitHub][7])
---
### Why this helps your rollout
* **Zero custom UI**: GitHub draws findings, file annotations, and PR decorations for you. ([GitHub Docs][1])
* **Fits any CI**: Emit SARIF once, then upload via Actions, REST, or CLI—works for GitHub-hosted or external runners. ([GitHub Docs][2])
If you want, I can tailor a ready-to-drop workflow for one of your Stella Ops repos (mono-repo vs multi-repo, language mix, and desired categories).
[1]: https://docs.github.com/en/code-security/code-scanning/integrating-with-code-scanning/sarif-support-for-code-scanning?utm_source=chatgpt.com "SARIF support for code scanning"
[2]: https://docs.github.com/en/code-security/code-scanning/integrating-with-code-scanning/uploading-a-sarif-file-to-github?utm_source=chatgpt.com "Uploading a SARIF file to GitHub"
[3]: https://docs.github.com/en/rest/code-scanning?utm_source=chatgpt.com "REST API endpoints for code scanning"
[4]: https://docs.github.com/en/code-security/codeql-cli/codeql-cli-manual/github-upload-results?utm_source=chatgpt.com "github upload-results"
[5]: https://docs.oasis-open.org/sarif/sarif/v2.1.0/sarif-v2.1.0.html?utm_source=chatgpt.com "Static Analysis Results Interchange Format (SARIF) Version ..."
[6]: https://github.blog/changelog/2024-05-06-code-scanning-will-stop-combining-runs-from-a-single-upload/?utm_source=chatgpt.com "Code Scanning will stop combining runs from a single upload"
[7]: https://github.com/orgs/community/discussions/54013?utm_source=chatgpt.com "Uploading SARIF files for pull requests #54013"