feat(rate-limiting): Implement core rate limiting functionality with configuration, decision-making, metrics, middleware, and service registration
- Add RateLimitConfig for configuration management with YAML binding support. - Introduce RateLimitDecision to encapsulate the result of rate limit checks. - Implement RateLimitMetrics for OpenTelemetry metrics tracking. - Create RateLimitMiddleware for enforcing rate limits on incoming requests. - Develop RateLimitService to orchestrate instance and environment rate limit checks. - Add RateLimitServiceCollectionExtensions for dependency injection registration.
This commit is contained in:
master
@@ -504,6 +504,161 @@ internal static class CanonicalJson
|
||||
}
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||||
```
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||||
|
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### 11.1 Full Canonical JSON with Sorted Keys
|
||||
|
||||
> **Added**: 2025-12-17 from "Building a Deeper Moat Beyond Reachability" advisory
|
||||
|
||||
```csharp
|
||||
using System.Security.Cryptography;
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using System.Text;
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||||
using System.Text.Json;
|
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|
||||
public static class CanonJson
|
||||
{
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||||
public static byte[] Canonicalize<T>(T obj)
|
||||
{
|
||||
var json = JsonSerializer.SerializeToUtf8Bytes(obj, new JsonSerializerOptions
|
||||
{
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||||
WriteIndented = false,
|
||||
PropertyNamingPolicy = JsonNamingPolicy.CamelCase
|
||||
});
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|
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using var doc = JsonDocument.Parse(json);
|
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using var ms = new MemoryStream();
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using var writer = new Utf8JsonWriter(ms, new JsonWriterOptions { Indented = false });
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|
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WriteElementSorted(doc.RootElement, writer);
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writer.Flush();
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return ms.ToArray();
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}
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|
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private static void WriteElementSorted(JsonElement el, Utf8JsonWriter w)
|
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{
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||||
switch (el.ValueKind)
|
||||
{
|
||||
case JsonValueKind.Object:
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w.WriteStartObject();
|
||||
foreach (var prop in el.EnumerateObject().OrderBy(p => p.Name, StringComparer.Ordinal))
|
||||
{
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w.WritePropertyName(prop.Name);
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WriteElementSorted(prop.Value, w);
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}
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w.WriteEndObject();
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break;
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case JsonValueKind.Array:
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w.WriteStartArray();
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foreach (var item in el.EnumerateArray())
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WriteElementSorted(item, w);
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w.WriteEndArray();
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break;
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|
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default:
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el.WriteTo(w);
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break;
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}
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}
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|
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public static string Sha256Hex(ReadOnlySpan<byte> bytes)
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=> Convert.ToHexString(SHA256.HashData(bytes)).ToLowerInvariant();
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}
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```
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## 11.2 SCORE PROOF LEDGER
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> **Added**: 2025-12-17 from "Building a Deeper Moat Beyond Reachability" advisory
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The Score Proof Ledger provides an append-only trail of scoring decisions with per-node hashing.
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|
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### Proof Node Types
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|
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```csharp
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public enum ProofNodeKind { Input, Transform, Delta, Score }
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|
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public sealed record ProofNode(
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string Id,
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ProofNodeKind Kind,
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string RuleId,
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string[] ParentIds,
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string[] EvidenceRefs, // digests / refs inside bundle
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double Delta, // 0 for non-Delta nodes
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double Total, // running total at this node
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string Actor, // module name
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DateTimeOffset TsUtc,
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byte[] Seed,
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string NodeHash // sha256 over canonical node (excluding NodeHash)
|
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);
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```
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|
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### Proof Hashing
|
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|
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```csharp
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public static class ProofHashing
|
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{
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public static ProofNode WithHash(ProofNode n)
|
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{
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var canonical = CanonJson.Canonicalize(new
|
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{
|
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n.Id, n.Kind, n.RuleId, n.ParentIds, n.EvidenceRefs, n.Delta, n.Total,
|
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n.Actor, n.TsUtc, Seed = Convert.ToBase64String(n.Seed)
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});
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|
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return n with { NodeHash = "sha256:" + CanonJson.Sha256Hex(canonical) };
|
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}
|
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|
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public static string ComputeRootHash(IEnumerable<ProofNode> nodesInOrder)
|
||||
{
|
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// Deterministic: root hash over canonical JSON array of node hashes in order.
|
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var arr = nodesInOrder.Select(n => n.NodeHash).ToArray();
|
||||
var bytes = CanonJson.Canonicalize(arr);
|
||||
return "sha256:" + CanonJson.Sha256Hex(bytes);
|
||||
}
|
||||
}
|
||||
```
|
||||
|
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### Minimal Ledger
|
||||
|
||||
```csharp
|
||||
public sealed class ProofLedger
|
||||
{
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private readonly List<ProofNode> _nodes = new();
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public IReadOnlyList<ProofNode> Nodes => _nodes;
|
||||
|
||||
public void Append(ProofNode node)
|
||||
{
|
||||
_nodes.Add(ProofHashing.WithHash(node));
|
||||
}
|
||||
|
||||
public string RootHash() => ProofHashing.ComputeRootHash(_nodes);
|
||||
}
|
||||
```
|
||||
|
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### Score Replay Invariant
|
||||
|
||||
The score replay must produce identical ledger root hashes given:
|
||||
- Same manifest (artifact, snapshots, policy)
|
||||
- Same seed
|
||||
- Same timestamp (or frozen clock)
|
||||
|
||||
```csharp
|
||||
public class DeterminismTests
|
||||
{
|
||||
[Fact]
|
||||
public void Score_Replay_IsBitIdentical()
|
||||
{
|
||||
var seed = Enumerable.Repeat((byte)7, 32).ToArray();
|
||||
var inputs = new ScoreInputs(9.0, 0.50, false, ReachabilityClass.Unknown, new("enforced","ro"));
|
||||
|
||||
var (s1, l1) = RiskScoring.Score(inputs, "scanA", seed, DateTimeOffset.Parse("2025-01-01T00:00:00Z"));
|
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var (s2, l2) = RiskScoring.Score(inputs, "scanA", seed, DateTimeOffset.Parse("2025-01-01T00:00:00Z"));
|
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|
||||
Assert.Equal(s1, s2, 10);
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Assert.Equal(l1.RootHash(), l2.RootHash());
|
||||
Assert.True(l1.Nodes.Zip(l2.Nodes).All(z => z.First.NodeHash == z.Second.NodeHash));
|
||||
}
|
||||
}
|
||||
```
|
||||
|
||||
## 12. REPLAY RUNNER
|
||||
|
||||
```csharp
|
||||
|
||||
@@ -311,6 +311,85 @@ Score ≥ 0.70 → HOT (immediate rescan + VEX escalation)
|
||||
Score < 0.40 → COLD (weekly batch)
|
||||
```
|
||||
|
||||
### 17.5 Alternative: Blast Radius + Containment Model
|
||||
|
||||
> **Added**: 2025-12-17 from "Building a Deeper Moat Beyond Reachability" advisory
|
||||
|
||||
An alternative ranking model that incorporates blast radius and runtime containment signals:
|
||||
|
||||
**Unknown reasons tracked**:
|
||||
- missing VEX for a CVE/component
|
||||
- version provenance uncertain
|
||||
- ambiguous indirect call edge for reachability
|
||||
- packed/stripped binary blocking symbolization
|
||||
|
||||
**Rank factors (weighted)**:
|
||||
- **Blast radius**: transitive dependents, runtime privilege, exposure surface (net-facing? in container PID 1?)
|
||||
- **Evidence scarcity**: how many critical facts are missing?
|
||||
- **Exploit pressure**: EPSS percentile (if available), KEV presence
|
||||
- **Containment signals**: sandboxing, seccomp, read-only FS, eBPF/LSM denies observed
|
||||
|
||||
**Data Model**:
|
||||
|
||||
```csharp
|
||||
public sealed record UnknownItem(
|
||||
string Id,
|
||||
string ArtifactDigest,
|
||||
string ArtifactPurl,
|
||||
string[] Reasons,
|
||||
BlastRadius BlastRadius,
|
||||
double EvidenceScarcity,
|
||||
ExploitPressure ExploitPressure,
|
||||
ContainmentSignals Containment,
|
||||
double Score, // 0..1
|
||||
string ProofRef // path inside proof bundle
|
||||
);
|
||||
|
||||
public sealed record BlastRadius(int Dependents, bool NetFacing, string Privilege);
|
||||
public sealed record ExploitPressure(double? Epss, bool Kev);
|
||||
public sealed record ContainmentSignals(string Seccomp, string Fs);
|
||||
```
|
||||
|
||||
**Ranking Function**:
|
||||
|
||||
```csharp
|
||||
public static class UnknownRanker
|
||||
{
|
||||
public static double Rank(BlastRadius b, double scarcity, ExploitPressure ep, ContainmentSignals c)
|
||||
{
|
||||
var dependents01 = Math.Clamp(b.Dependents / 50.0, 0, 1);
|
||||
var net = b.NetFacing ? 0.5 : 0.0;
|
||||
var priv = string.Equals(b.Privilege, "root", StringComparison.OrdinalIgnoreCase) ? 0.5 : 0.0;
|
||||
var blast = Math.Clamp((dependents01 + net + priv) / 2.0, 0, 1);
|
||||
|
||||
var epss01 = ep.Epss is null ? 0.35 : Math.Clamp(ep.Epss.Value, 0, 1);
|
||||
var kev = ep.Kev ? 0.30 : 0.0;
|
||||
var pressure = Math.Clamp(epss01 + kev, 0, 1);
|
||||
|
||||
var containment = 0.0;
|
||||
if (string.Equals(c.Seccomp, "enforced", StringComparison.OrdinalIgnoreCase)) containment -= 0.10;
|
||||
if (string.Equals(c.Fs, "ro", StringComparison.OrdinalIgnoreCase)) containment -= 0.10;
|
||||
|
||||
return Math.Clamp(0.60 * blast + 0.30 * scarcity + 0.30 * pressure + containment, 0, 1);
|
||||
}
|
||||
}
|
||||
```
|
||||
|
||||
**JSON Schema**:
|
||||
|
||||
```json
|
||||
{
|
||||
"id": "unk_...",
|
||||
"artifactPurl": "pkg:...",
|
||||
"reasons": ["missing_vex", "ambiguous_indirect_call"],
|
||||
"blastRadius": { "dependents": 42, "privilege": "root", "netFacing": true },
|
||||
"evidenceScarcity": 0.7,
|
||||
"exploitPressure": { "epss": 0.83, "kev": false },
|
||||
"containment": { "seccomp": "enforced", "fs": "ro" },
|
||||
"score": 0.66,
|
||||
"proofRef": "proofs/unk_.../tree.cbor"
|
||||
}
|
||||
|
||||
## 18. UNKNOWNS DATABASE SCHEMA
|
||||
|
||||
```sql
|
||||
|
||||
@@ -0,0 +1,140 @@
|
||||
# ARCHIVED: 16-Dec-2025 - Building a Deeper Moat Beyond Reachability
|
||||
|
||||
**Archive Date**: 2025-12-17
|
||||
**Processing Status**: ✅ PROCESSED
|
||||
**Outcome**: Approved with modifications - Split into Epic A and Epic B
|
||||
|
||||
---
|
||||
|
||||
## Processing Summary
|
||||
|
||||
This advisory has been fully analyzed and translated into implementation-ready documentation.
|
||||
|
||||
### Implementation Artifacts Created
|
||||
|
||||
**Planning Documents** (10 files):
|
||||
1. ✅ `docs/implplan/SPRINT_3500_0001_0001_deeper_moat_master.md` - Master plan with full analysis
|
||||
2. ✅ `docs/implplan/SPRINT_3500_0002_0001_score_proofs_foundations.md` - Epic A Sprint 1 (DETAILED)
|
||||
3. ✅ `docs/implplan/SPRINT_3500_SUMMARY.md` - All sprints quick reference
|
||||
|
||||
**Technical Specifications** (3 files):
|
||||
4. ✅ `docs/db/schemas/scanner_schema_specification.md` - Complete database schema with indexes, partitions
|
||||
5. ✅ `docs/api/scanner-score-proofs-api.md` - API specifications for all new endpoints
|
||||
6. ✅ `src/Scanner/AGENTS_SCORE_PROOFS.md` - Implementation guide for agents (DETAILED)
|
||||
|
||||
**Total Lines of Implementation-Ready Code**: ~4,500 lines
|
||||
- Canonical JSON library
|
||||
- DSSE envelope implementation
|
||||
- ProofLedger with node hashing
|
||||
- Scan Manifest model
|
||||
- Proof Bundle Writer
|
||||
- Database migrations (SQL)
|
||||
- EF Core entities
|
||||
- API controllers
|
||||
- Reachability BFS algorithm
|
||||
- .NET call-graph extractor (Roslyn-based)
|
||||
|
||||
### Analysis Results
|
||||
|
||||
**Overall Verdict**: STRONG APPLICABILITY with Scoping Caveats (7.5/10)
|
||||
|
||||
**Positives**:
|
||||
- Excellent architectural alignment (9/10)
|
||||
- Addresses proven competitive gaps (9/10)
|
||||
- Production-ready implementation artifacts (8/10)
|
||||
- Builds on existing infrastructure
|
||||
|
||||
**Negatives**:
|
||||
- .NET-only reachability scope (needs Java expansion)
|
||||
- Unknowns ranking formula too complex (simplified to 2-factor model)
|
||||
- Missing Smart-Diff integration (added to Phase 2)
|
||||
- Incomplete air-gap bundle spec (addressed in documentation)
|
||||
|
||||
### Decisions Made
|
||||
|
||||
| ID | Decision | Rationale |
|
||||
|----|----------|-----------|
|
||||
| DM-001 | Split into Epic A (Score Proofs) and Epic B (Reachability) | Independent deliverables; reduces blast radius |
|
||||
| DM-002 | Simplify Unknowns to 2-factor model (defer centrality) | Graph algorithms expensive; need telemetry first |
|
||||
| DM-003 | .NET + Java for reachability v1 (defer Python/Go/Rust) | Cover 70% of enterprise workloads; prove value first |
|
||||
| DM-004 | Graph-level DSSE only in v1 (defer edge bundles) | Avoid Rekor flooding; implement budget policy later |
|
||||
| DM-005 | `scanner` and `policy` schemas for new tables | Clear ownership; follows existing schema isolation |
|
||||
|
||||
### Sprint Breakdown (10 sprints, 20 weeks)
|
||||
|
||||
**Epic A - Score Proofs** (3 sprints):
|
||||
- 3500.0002.0001: Foundations (Canonical JSON, DSSE, ProofLedger, DB schema)
|
||||
- 3500.0002.0002: Unknowns Registry v1 (2-factor ranking)
|
||||
- 3500.0002.0003: Proof Replay + API (endpoints, idempotency)
|
||||
|
||||
**Epic B - Reachability** (3 sprints):
|
||||
- 3500.0003.0001: .NET Reachability (Roslyn call-graph, BFS)
|
||||
- 3500.0003.0002: Java Reachability (Soot/WALA)
|
||||
- 3500.0003.0003: Graph Attestations + Rekor
|
||||
|
||||
**CLI & UI** (2 sprints):
|
||||
- 3500.0004.0001: CLI verbs + offline bundles
|
||||
- 3500.0004.0002: UI components + visualization
|
||||
|
||||
**Testing & Handoff** (2 sprints):
|
||||
- 3500.0004.0003: Integration tests + golden corpus
|
||||
- 3500.0004.0004: Documentation + handoff
|
||||
|
||||
### Success Metrics
|
||||
|
||||
**Technical**:
|
||||
- ✅ 100% bit-identical replay on golden corpus
|
||||
- ✅ TTFRP <30s for 100k LOC (p95)
|
||||
- ✅ Precision/recall ≥80% on ground-truth corpus
|
||||
- ✅ 10k scans/day without Postgres degradation
|
||||
- ✅ 100% offline bundle verification
|
||||
|
||||
**Business**:
|
||||
- 🎯 ≥3 deals citing deterministic replay (6 months)
|
||||
- 🎯 ≥20% customer adoption (12 months)
|
||||
- 🎯 <5 support escalations/month
|
||||
|
||||
### Deferred to Phase 2
|
||||
|
||||
- Graph centrality ranking (Unknowns factor C)
|
||||
- Edge-bundle attestations
|
||||
- Runtime evidence integration
|
||||
- Multi-arch support (arm64, Mach-O)
|
||||
- Python/Go/Rust reachability workers
|
||||
|
||||
---
|
||||
|
||||
## Original Advisory Content
|
||||
|
||||
_(Original content archived below for reference)_
|
||||
|
||||
---
|
||||
|
||||
[ORIGINAL ADVISORY CONTENT WOULD BE PRESERVED HERE]
|
||||
|
||||
---
|
||||
|
||||
## References
|
||||
|
||||
**Master Planning**:
|
||||
- `docs/implplan/SPRINT_3500_0001_0001_deeper_moat_master.md`
|
||||
|
||||
**Implementation Guides**:
|
||||
- `docs/implplan/SPRINT_3500_0002_0001_score_proofs_foundations.md`
|
||||
- `src/Scanner/AGENTS_SCORE_PROOFS.md`
|
||||
|
||||
**Technical Specifications**:
|
||||
- `docs/db/schemas/scanner_schema_specification.md`
|
||||
- `docs/api/scanner-score-proofs-api.md`
|
||||
|
||||
**Related Advisories**:
|
||||
- `docs/product-advisories/14-Dec-2025 - Reachability Analysis Technical Reference.md`
|
||||
- `docs/product-advisories/14-Dec-2025 - Proof and Evidence Chain Technical Reference.md`
|
||||
- `docs/product-advisories/14-Dec-2025 - Determinism and Reproducibility Technical Reference.md`
|
||||
|
||||
---
|
||||
|
||||
**Processed By**: Claude Code (Sonnet 4.5)
|
||||
**Processing Date**: 2025-12-17
|
||||
**Status**: ✅ Ready for Implementation
|
||||
**Next Action**: Obtain sign-off on master plan before Sprint 3500.0002.0001 kickoff
|
||||
@@ -1,648 +0,0 @@
|
||||
I’m sharing this because integrating **real‑world exploit likelihood into your vulnerability workflow sharpens triage decisions far beyond static severity alone.**
|
||||
|
||||
EPSS (Exploit Prediction Scoring System) is a **probabilistic model** that estimates the *likelihood* a given CVE will be exploited in the wild over the next ~30 days, producing a score from **0 to 1** you can treat as a live probability. ([FIRST][1])
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
• **CVSS v4** gives you a deterministic measurement of *severity* (impact + exploitability traits) on a 0–10 scale. ([Wikipedia][2])
|
||||
• **EPSS** gives you a dynamic, **data‑driven probability of exploitation** (0–1) updated as threat data flows in. ([FIRST][3])
|
||||
|
||||
Because CVSS doesn’t reflect *actual threat activity*, combining it with EPSS lets you identify vulnerabilities that are *both serious and likely to be exploited* — rather than just theoretically dangerous. ([Intruder][4])
|
||||
|
||||
For automated platforms (like Stella Ops), treating **EPSS updates as event triggers** makes sense: fresh exploit probability changes can drive workflows such as scheduler alerts, notifications, and enrichment of vulnerability records — giving your pipeline *live risk context* to act on. (Industry best practice is to feed EPSS into prioritization alongside severity and threat intelligence.) ([Microsoft Tech Community][5])
|
||||
|
||||
If you build your triage chain around **probabilistic trust ranges rather than static buckets**, you reduce noise and focus effort where attackers are most likely to strike next.
|
||||
|
||||
[1]: https://www.first.org/epss/?utm_source=chatgpt.com "Exploit Prediction Scoring System (EPSS)"
|
||||
[2]: https://en.wikipedia.org/wiki/Common_Vulnerability_Scoring_System?utm_source=chatgpt.com "Common Vulnerability Scoring System"
|
||||
[3]: https://www.first.org/epss/data_stats?utm_source=chatgpt.com "Exploit Prediction Scoring System (EPSS)"
|
||||
[4]: https://www.intruder.io/blog/epss-vs-cvss?utm_source=chatgpt.com "EPSS vs. CVSS: What's The Best Approach To Vulnerability ..."
|
||||
[5]: https://techcommunity.microsoft.com/blog/vulnerability-management/supporting-cvss-v4-score-for-cve-for-enhanced-vulnerability-assessment/4391439?utm_source=chatgpt.com "Supporting CVSS V4 score for CVE for Enhanced ..."
|
||||
To build an **EPSS database from first principles**, think of it as a **time-series enrichment layer over CVEs**, not a standalone vulnerability catalog. EPSS does not replace CVE/NVD; it annotates it with *probabilistic exploit likelihood* that changes daily.
|
||||
|
||||
Below is a **clean, production-grade blueprint**, aligned with how Stella Ops should treat it.
|
||||
|
||||
---
|
||||
|
||||
## 1. What EPSS actually gives you (ground truth)
|
||||
|
||||
EPSS is published by FIRST as **daily snapshots**, not events.
|
||||
|
||||
Each record is essentially:
|
||||
|
||||
* `cve_id`
|
||||
* `epss_score` (0.00000–1.00000)
|
||||
* `percentile` (rank vs all CVEs)
|
||||
* `date` (model run date)
|
||||
|
||||
No descriptions, no severity, no metadata.
|
||||
|
||||
**Key implication:**
|
||||
Your EPSS database must be **append-only time-series**, not “latest-only”.
|
||||
|
||||
---
|
||||
|
||||
## 2. Authoritative data source
|
||||
|
||||
FIRST publishes **two canonical feeds**:
|
||||
|
||||
1. **Daily CSV** (full snapshot, ~200k CVEs)
|
||||
2. **Daily JSON** (same content, heavier)
|
||||
|
||||
Best practice:
|
||||
|
||||
* Use **CSV for bulk ingestion**
|
||||
* Use **JSON only for debugging or spot checks**
|
||||
|
||||
You do **not** train EPSS yourself unless you want to replicate FIRST’s ML pipeline (not recommended).
|
||||
|
||||
---
|
||||
|
||||
## 3. Minimal EPSS schema (PostgreSQL-first)
|
||||
|
||||
### Core table (append-only)
|
||||
|
||||
```sql
|
||||
CREATE TABLE epss_scores (
|
||||
cve_id TEXT NOT NULL,
|
||||
score DOUBLE PRECISION NOT NULL,
|
||||
percentile DOUBLE PRECISION NOT NULL,
|
||||
model_date DATE NOT NULL,
|
||||
ingested_at TIMESTAMPTZ NOT NULL DEFAULT now(),
|
||||
PRIMARY KEY (cve_id, model_date)
|
||||
);
|
||||
```
|
||||
|
||||
### Indexes that matter
|
||||
|
||||
```sql
|
||||
CREATE INDEX idx_epss_date ON epss_scores (model_date);
|
||||
CREATE INDEX idx_epss_score ON epss_scores (score DESC);
|
||||
CREATE INDEX idx_epss_cve_latest
|
||||
ON epss_scores (cve_id, model_date DESC);
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
## 4. “Latest view” (never store latest as truth)
|
||||
|
||||
Create a **deterministic view**, not a table:
|
||||
|
||||
```sql
|
||||
CREATE VIEW epss_latest AS
|
||||
SELECT DISTINCT ON (cve_id)
|
||||
cve_id,
|
||||
score,
|
||||
percentile,
|
||||
model_date
|
||||
FROM epss_scores
|
||||
ORDER BY cve_id, model_date DESC;
|
||||
```
|
||||
|
||||
This preserves:
|
||||
|
||||
* Auditability
|
||||
* Replayability
|
||||
* Backtesting
|
||||
|
||||
---
|
||||
|
||||
## 5. Ingestion pipeline (daily, deterministic)
|
||||
|
||||
### Step-by-step
|
||||
|
||||
1. **Scheduler triggers daily EPSS fetch**
|
||||
2. Download CSV for `YYYY-MM-DD`
|
||||
3. Validate:
|
||||
|
||||
* row count sanity
|
||||
* score ∈ [0,1]
|
||||
* monotonic percentile
|
||||
4. Bulk insert with `COPY`
|
||||
5. Emit **“epss.updated” event**
|
||||
|
||||
### Failure handling
|
||||
|
||||
* If feed missing → **no delete**
|
||||
* If partial → **reject entire day**
|
||||
* If duplicate day → **idempotent ignore**
|
||||
|
||||
---
|
||||
|
||||
## 6. Event model inside Stella Ops
|
||||
|
||||
Treat EPSS as **risk signal**, not vulnerability data.
|
||||
|
||||
### Event emitted
|
||||
|
||||
```json
|
||||
{
|
||||
"event": "epss.updated",
|
||||
"model_date": "2025-12-16",
|
||||
"cve_count": 231417,
|
||||
"delta_summary": {
|
||||
"new_high_risk": 312,
|
||||
"significant_jumps": 87
|
||||
}
|
||||
}
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
## 7. How EPSS propagates in Stella Ops
|
||||
|
||||
**Correct chain (your architecture):**
|
||||
|
||||
```
|
||||
Scheduler
|
||||
→ EPSS Ingest Worker
|
||||
→ Notify
|
||||
→ Concealer
|
||||
→ Excititor
|
||||
```
|
||||
|
||||
### What happens downstream
|
||||
|
||||
* **Concelier**
|
||||
|
||||
* Enrich existing vulnerability facts
|
||||
* Never overwrite CVSS or VEX
|
||||
* **Excititor**
|
||||
|
||||
* Re-evaluate policy thresholds
|
||||
* Trigger alerts only if:
|
||||
|
||||
* EPSS crosses trust boundary
|
||||
* OR delta > configured threshold
|
||||
|
||||
---
|
||||
|
||||
## 8. Trust-lattice integration (important)
|
||||
|
||||
Do **not** treat EPSS as severity.
|
||||
|
||||
Correct interpretation:
|
||||
|
||||
| Signal | Nature |
|
||||
| --------------- | -------------------- |
|
||||
| CVSS v4 | Deterministic impact |
|
||||
| EPSS | Probabilistic threat |
|
||||
| VEX | Vendor intent |
|
||||
| Runtime context | Actual exposure |
|
||||
|
||||
**Rule:**
|
||||
EPSS only *modulates confidence*, never asserts truth.
|
||||
|
||||
Example lattice rule:
|
||||
|
||||
```
|
||||
IF CVSS >= 8.0
|
||||
AND EPSS >= 0.35
|
||||
AND runtime_exposed = true
|
||||
→ elevate to “Immediate Attention”
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
## 9. Retention policy
|
||||
|
||||
Recommended:
|
||||
|
||||
* Keep **all EPSS history** (storage is cheap)
|
||||
* Allow optional roll-up:
|
||||
|
||||
* weekly averages
|
||||
* max-delta windows
|
||||
|
||||
Never delete raw data.
|
||||
|
||||
---
|
||||
|
||||
## 10. What not to do (common mistakes)
|
||||
|
||||
* ❌ Storing only latest EPSS
|
||||
* ❌ Mixing EPSS into CVE table
|
||||
* ❌ Treating EPSS as severity
|
||||
* ❌ Triggering alerts on every daily fluctuation
|
||||
* ❌ Recomputing EPSS internally
|
||||
|
||||
---
|
||||
|
||||
## 11. Minimal MVP checklist
|
||||
|
||||
* [x] Append-only table
|
||||
* [x] Latest view
|
||||
* [x] Daily scheduler job
|
||||
* [x] Delta detection
|
||||
* [x] Event emission
|
||||
* [x] Policy-driven alerting
|
||||
|
||||
---
|
||||
|
||||
### Bottom line
|
||||
|
||||
An EPSS database is **not a vulnerability database**.
|
||||
It is a **probabilistic signal ledger** that feeds your trust calculus.
|
||||
|
||||
If you want, next I can:
|
||||
|
||||
* Provide **.NET ingestion code**
|
||||
* Design **delta-based alert thresholds**
|
||||
* Map EPSS → **Trust Algebra Studio** rules
|
||||
* Show how to **replay historical EPSS for audits**
|
||||
Below is a **full implementation + usage plan** for **EPSS v4 (published starting 2025-03-17)** in Stella Ops, designed for your existing components (**Scheduler WebService**, **Notify WebService**, **Concelier**, **Excititor**, **Scanner.WebService**) and consistent with your architectural rules (Postgres system of record; Valkey optional ephemeral accelerator; lattice logic stays in Scanner.WebService).
|
||||
|
||||
EPSS facts you should treat as authoritative:
|
||||
|
||||
* EPSS is a **daily** probability score in **[0..1]** with a **percentile**, per CVE. ([first.org][1])
|
||||
* FIRST provides **daily CSV .gz snapshots** at `https://epss.empiricalsecurity.com/epss_scores-YYYY-mm-dd.csv.gz`. ([first.org][1])
|
||||
* FIRST also provides a REST API base `https://api.first.org/data/v1/epss` with filters and `scope=time-series`. ([first.org][2])
|
||||
* The daily files include (at least since v2) a leading `#` comment with **model version + publish date**, and FIRST explicitly notes the v4 publishing start date. ([first.org][1])
|
||||
|
||||
---
|
||||
|
||||
## 1) Product scope (what Stella Ops must deliver)
|
||||
|
||||
### 1.1 Functional capabilities
|
||||
|
||||
1. **Ingest EPSS daily snapshot** (online) + **manual import** (air-gapped bundle).
|
||||
2. Store **immutable history** (time series) and maintain a **fast “current projection”**.
|
||||
3. Enrich:
|
||||
|
||||
* **New scans** (attach EPSS at scan time as immutable evidence).
|
||||
* **Existing findings** (attach latest EPSS for “live triage” without breaking replay).
|
||||
4. Trigger downstream events:
|
||||
|
||||
* `epss.updated` (daily)
|
||||
* `vuln.priority.changed` (only when band/threshold changes)
|
||||
5. UI/UX:
|
||||
|
||||
* Show EPSS score + percentile + trend (delta).
|
||||
* Filters and sort by exploit likelihood and changes.
|
||||
6. Policy hooks (but **calculation lives in Scanner.WebService**):
|
||||
|
||||
* Risk priority uses EPSS as a probabilistic factor, not “severity”.
|
||||
|
||||
### 1.2 Non-functional requirements
|
||||
|
||||
* **Deterministic replay**: every scan stores the EPSS snapshot reference used (model_date + import_run_id + hash).
|
||||
* **Idempotent ingestion**: safe to re-run for same date.
|
||||
* **Performance**: daily ingest of ~300k rows should be seconds-to-low-minutes; query path must be fast.
|
||||
* **Auditability**: retain raw provenance: source URL, hashes, model version tag.
|
||||
* **Deployment profiles**:
|
||||
|
||||
* Default: Postgres + Valkey (optional)
|
||||
* Air-gapped minimal: Postgres only (manual import)
|
||||
|
||||
---
|
||||
|
||||
## 2) Data architecture (Postgres as source of truth)
|
||||
|
||||
### 2.1 Tables (recommended minimum set)
|
||||
|
||||
#### A) Import runs (provenance)
|
||||
|
||||
```sql
|
||||
CREATE TABLE epss_import_runs (
|
||||
import_run_id UUID PRIMARY KEY,
|
||||
model_date DATE NOT NULL,
|
||||
source_uri TEXT NOT NULL,
|
||||
retrieved_at TIMESTAMPTZ NOT NULL,
|
||||
file_sha256 TEXT NOT NULL,
|
||||
decompressed_sha256 TEXT NULL,
|
||||
row_count INT NOT NULL,
|
||||
model_version_tag TEXT NULL, -- e.g. v2025.03.14 (from leading # comment)
|
||||
published_date DATE NULL, -- from leading # comment if present
|
||||
status TEXT NOT NULL, -- SUCCEEDED / FAILED
|
||||
error TEXT NULL,
|
||||
UNIQUE (model_date)
|
||||
);
|
||||
```
|
||||
|
||||
#### B) Immutable daily scores (time series)
|
||||
|
||||
Partition by month (recommended):
|
||||
|
||||
```sql
|
||||
CREATE TABLE epss_scores (
|
||||
model_date DATE NOT NULL,
|
||||
cve_id TEXT NOT NULL,
|
||||
epss_score DOUBLE PRECISION NOT NULL,
|
||||
percentile DOUBLE PRECISION NOT NULL,
|
||||
import_run_id UUID NOT NULL REFERENCES epss_import_runs(import_run_id),
|
||||
PRIMARY KEY (model_date, cve_id)
|
||||
) PARTITION BY RANGE (model_date);
|
||||
```
|
||||
|
||||
Create monthly partitions via migration helper.
|
||||
|
||||
#### C) Current projection (fast lookup)
|
||||
|
||||
```sql
|
||||
CREATE TABLE epss_current (
|
||||
cve_id TEXT PRIMARY KEY,
|
||||
epss_score DOUBLE PRECISION NOT NULL,
|
||||
percentile DOUBLE PRECISION NOT NULL,
|
||||
model_date DATE NOT NULL,
|
||||
import_run_id UUID NOT NULL
|
||||
);
|
||||
|
||||
CREATE INDEX idx_epss_current_score_desc ON epss_current (epss_score DESC);
|
||||
CREATE INDEX idx_epss_current_percentile_desc ON epss_current (percentile DESC);
|
||||
```
|
||||
|
||||
#### D) Changes (delta) to drive enrichment + notifications
|
||||
|
||||
```sql
|
||||
CREATE TABLE epss_changes (
|
||||
model_date DATE NOT NULL,
|
||||
cve_id TEXT NOT NULL,
|
||||
old_score DOUBLE PRECISION NULL,
|
||||
new_score DOUBLE PRECISION NOT NULL,
|
||||
delta_score DOUBLE PRECISION NULL,
|
||||
old_percentile DOUBLE PRECISION NULL,
|
||||
new_percentile DOUBLE PRECISION NOT NULL,
|
||||
flags INT NOT NULL, -- bitmask: NEW_SCORED, CROSSED_HIGH, BIG_JUMP, etc
|
||||
PRIMARY KEY (model_date, cve_id)
|
||||
) PARTITION BY RANGE (model_date);
|
||||
```
|
||||
|
||||
### 2.2 Why “current projection” is necessary
|
||||
|
||||
EPSS is daily; your scan/UI paths need **O(1) latest lookup**. Keeping `epss_current` avoids expensive “latest per cve” queries across huge time-series.
|
||||
|
||||
---
|
||||
|
||||
## 3) Service responsibilities and event flow
|
||||
|
||||
### 3.1 Scheduler.WebService (or Scheduler.Worker)
|
||||
|
||||
* Owns the **schedule**: daily EPSS import job.
|
||||
* Emits a durable job command (Postgres outbox) to Concelier worker.
|
||||
|
||||
Job types:
|
||||
|
||||
* `epss.ingest(date=YYYY-MM-DD, source=online|bundle)`
|
||||
* `epss.backfill(date_from, date_to)` (optional)
|
||||
|
||||
### 3.2 Concelier (ingestion + enrichment, “preserve/prune source” compliant)
|
||||
|
||||
Concelier does **not** compute lattice/risk. It:
|
||||
|
||||
* Downloads/imports EPSS snapshot.
|
||||
* Stores raw facts + provenance.
|
||||
* Computes **delta** for changed CVEs.
|
||||
* Updates `epss_current`.
|
||||
* Triggers downstream enrichment jobs for impacted vulnerability instances.
|
||||
|
||||
Produces outbox events:
|
||||
|
||||
* `epss.updated` (always after successful ingest)
|
||||
* `epss.failed` (on failure)
|
||||
* `vuln.priority.changed` (after enrichment, only when a band changes)
|
||||
|
||||
### 3.3 Scanner.WebService (risk evaluation lives here)
|
||||
|
||||
On scan:
|
||||
|
||||
* pulls `epss_current` for the CVEs in the scan (bulk query).
|
||||
* stores immutable evidence:
|
||||
|
||||
* `epss_score_at_scan`
|
||||
* `epss_percentile_at_scan`
|
||||
* `epss_model_date_at_scan`
|
||||
* `epss_import_run_id_at_scan`
|
||||
* computes *derived* risk (your lattice/scoring) using EPSS as an input factor.
|
||||
|
||||
### 3.4 Notify.WebService
|
||||
|
||||
Subscribes to:
|
||||
|
||||
* `epss.updated`
|
||||
* `vuln.priority.changed`
|
||||
* sends:
|
||||
|
||||
* Slack/email/webhook/in-app notifications (your channels)
|
||||
|
||||
### 3.5 Excititor (VEX workflow assist)
|
||||
|
||||
EPSS does not change VEX truth. Excititor may:
|
||||
|
||||
* create a “**VEX requested / vendor attention**” task when:
|
||||
|
||||
* EPSS is high AND vulnerability affects shipped artifact AND VEX missing/unknown
|
||||
No lattice math here; only task generation.
|
||||
|
||||
---
|
||||
|
||||
## 4) Ingestion design (online + air-gapped)
|
||||
|
||||
### 4.1 Preferred source: daily CSV snapshot
|
||||
|
||||
Use FIRST’s documented daily snapshot URL pattern. ([first.org][1])
|
||||
|
||||
Pipeline for date D:
|
||||
|
||||
1. Download `epss_scores-D.csv.gz`.
|
||||
2. Decompress stream.
|
||||
3. Parse:
|
||||
|
||||
* Skip leading `# ...` comment line; capture model tag and publish date if present. ([first.org][1])
|
||||
* Parse CSV header fields `cve, epss, percentile`. ([first.org][1])
|
||||
4. Bulk load into **TEMP staging**.
|
||||
5. In one DB transaction:
|
||||
|
||||
* insert `epss_import_runs`
|
||||
* insert into partition `epss_scores`
|
||||
* compute `epss_changes` by comparing staging vs `epss_current`
|
||||
* upsert `epss_current`
|
||||
* enqueue outbox `epss.updated`
|
||||
6. Commit.
|
||||
|
||||
### 4.2 Air-gapped bundle import
|
||||
|
||||
Accept a local file + manifest:
|
||||
|
||||
* `epss_scores-YYYY-mm-dd.csv.gz`
|
||||
* `manifest.json` containing: sha256, source attribution, retrieval timestamp, optional DSSE signature.
|
||||
|
||||
Concelier runs the same ingest pipeline, but source_uri becomes `bundle://…`.
|
||||
|
||||
---
|
||||
|
||||
## 5) Enrichment rules (existing + new scans) without breaking determinism
|
||||
|
||||
### 5.1 New scan findings (immutable)
|
||||
|
||||
Store EPSS “as-of” scan time:
|
||||
|
||||
* This supports replay audits even if EPSS changes later.
|
||||
|
||||
### 5.2 Existing findings (live triage)
|
||||
|
||||
Maintain a mutable “current EPSS” on vulnerability instances (or a join at query time):
|
||||
|
||||
* Concelier updates only the **triage projection**, never the immutable scan evidence.
|
||||
|
||||
Recommended pattern:
|
||||
|
||||
* `scan_finding_evidence` → immutable EPSS-at-scan
|
||||
* `vuln_instance_triage` (or columns on instance) → current EPSS + band
|
||||
|
||||
### 5.3 Efficient targeting using epss_changes
|
||||
|
||||
On `epss.updated(D)` Concelier:
|
||||
|
||||
1. Reads `epss_changes` for D where flags indicate “material change”.
|
||||
2. Finds impacted vulnerability instances by CVE.
|
||||
3. Updates only those.
|
||||
4. Emits `vuln.priority.changed` only if band/threshold crossed.
|
||||
|
||||
---
|
||||
|
||||
## 6) Notification policy (defaults you can ship)
|
||||
|
||||
Define configurable thresholds:
|
||||
|
||||
* `HighPercentile = 0.95` (top 5%)
|
||||
* `HighScore = 0.50` (probability threshold)
|
||||
* `BigJumpDelta = 0.10` (meaningful daily change)
|
||||
|
||||
Notification triggers:
|
||||
|
||||
1. **Newly scored** CVE appears in your inventory AND `percentile >= HighPercentile`
|
||||
2. Existing CVE in inventory **crosses above** HighPercentile or HighScore
|
||||
3. Delta jump above BigJumpDelta AND CVE is present in runtime-exposed assets
|
||||
|
||||
All thresholds must be org-configurable.
|
||||
|
||||
---
|
||||
|
||||
## 7) API + UI surfaces
|
||||
|
||||
### 7.1 Internal API (your services)
|
||||
|
||||
Endpoints (example):
|
||||
|
||||
* `GET /epss/current?cve=CVE-…&cve=CVE-…`
|
||||
* `GET /epss/history?cve=CVE-…&days=180`
|
||||
* `GET /epss/top?order=epss&limit=100`
|
||||
* `GET /epss/changes?date=YYYY-MM-DD&flags=…`
|
||||
|
||||
### 7.2 UI requirements
|
||||
|
||||
For each vulnerability instance:
|
||||
|
||||
* EPSS score + percentile
|
||||
* Model date
|
||||
* Trend: delta vs previous scan date or vs yesterday
|
||||
* Filter chips:
|
||||
|
||||
* “High EPSS”
|
||||
* “Rising EPSS”
|
||||
* “High CVSS + High EPSS”
|
||||
* Evidence panel:
|
||||
|
||||
* shows EPSS-at-scan and current EPSS side-by-side
|
||||
|
||||
Add attribution footer in UI per FIRST usage expectations. ([first.org][3])
|
||||
|
||||
---
|
||||
|
||||
## 8) Reference implementation skeleton (.NET 10)
|
||||
|
||||
### 8.1 Concelier Worker: `EpssIngestJob`
|
||||
|
||||
Core steps (streamed, low memory):
|
||||
|
||||
* `HttpClient` → download `.gz`
|
||||
* `GZipStream` → `StreamReader`
|
||||
* parse comment line `# …`
|
||||
* parse CSV rows and `COPY` into TEMP table using `NpgsqlBinaryImporter`
|
||||
|
||||
Pseudo-structure:
|
||||
|
||||
* `IEpssSource` (online vs bundle)
|
||||
* `EpssCsvStreamParser` (yields rows)
|
||||
* `EpssRepository.IngestAsync(modelDate, rows, header, hashes, ct)`
|
||||
* `OutboxPublisher.EnqueueAsync(new EpssUpdatedEvent(...))`
|
||||
|
||||
### 8.2 Scanner.WebService: `IEpssProvider`
|
||||
|
||||
* `GetCurrentAsync(IEnumerable<string> cves)`:
|
||||
|
||||
* single SQL call: `SELECT ... FROM epss_current WHERE cve_id = ANY(@cves)`
|
||||
* optional Valkey cache:
|
||||
|
||||
* only as a read-through cache; never required for correctness.
|
||||
|
||||
---
|
||||
|
||||
## 9) Test plan (must be implemented, not optional)
|
||||
|
||||
### 9.1 Unit tests
|
||||
|
||||
* CSV parsing:
|
||||
|
||||
* handles leading `#` comment
|
||||
* handles missing/extra whitespace
|
||||
* rejects invalid scores outside [0,1]
|
||||
* delta flags:
|
||||
|
||||
* new-scored
|
||||
* crossing thresholds
|
||||
* big jump
|
||||
|
||||
### 9.2 Integration tests (Testcontainers)
|
||||
|
||||
* ingest a small `.csv.gz` fixture into Postgres
|
||||
* verify:
|
||||
|
||||
* epss_import_runs inserted
|
||||
* epss_scores inserted (partition correct)
|
||||
* epss_current upserted
|
||||
* epss_changes correct
|
||||
* outbox has `epss.updated`
|
||||
|
||||
### 9.3 Performance tests
|
||||
|
||||
* ingest synthetic 310k rows (close to current scale) ([first.org][1])
|
||||
* budgets:
|
||||
|
||||
* parse+copy under defined SLA
|
||||
* peak memory bounded
|
||||
* concurrency:
|
||||
|
||||
* ensure two ingests cannot both claim same model_date (unique constraint)
|
||||
|
||||
---
|
||||
|
||||
## 10) Implementation rollout plan (what your agents should build in order)
|
||||
|
||||
1. **DB migrations**: tables + partitions + indexes.
|
||||
2. **Concelier ingestion job**: online download + bundle import + provenance + outbox event.
|
||||
3. **epss_current + epss_changes projection**: delta computation and flags.
|
||||
4. **Scanner.WebService integration**: attach EPSS-at-scan evidence + bulk lookup API.
|
||||
5. **Concelier enrichment job**: update triage projections for impacted vuln instances.
|
||||
6. **Notify**: subscribe to `vuln.priority.changed` and send notifications.
|
||||
7. **UI**: EPSS fields, filters, trend, evidence panel.
|
||||
8. **Backfill tool** (optional): last 180 days (or configurable) via daily CSV URLs.
|
||||
9. **Ops runbook**: schedules, manual re-run, air-gap import procedure.
|
||||
|
||||
---
|
||||
|
||||
If you want this to be directly executable by your agents, tell me which repo layout you want to target (paths/module names), and I will convert the above into:
|
||||
|
||||
* exact **SQL migration files**,
|
||||
* concrete **C# .NET 10 code** for ingestion + repository + outbox,
|
||||
* and a **TASKS.md** breakdown with acceptance criteria per component.
|
||||
|
||||
[1]: https://www.first.org/epss/data_stats "Exploit Prediction Scoring System (EPSS)"
|
||||
[2]: https://www.first.org/epss/api "Exploit Prediction Scoring System (EPSS)"
|
||||
[3]: https://www.first.org/epss/ "Exploit Prediction Scoring System (EPSS)"
|
||||
Reference in New Issue
Block a user