Files
glpi-neural-brain/internal/engine/source_inbox.go
jbergner 94dbd4ccab
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RC-4
2026-08-09 18:41:47 +02:00

881 lines
40 KiB
Go

package engine
import (
"context"
"fmt"
"log/slog"
"math"
"regexp"
"strings"
"time"
"github.com/local/glpi-neural-brain/internal/graph"
"github.com/local/glpi-neural-brain/internal/model"
"github.com/local/glpi-neural-brain/internal/research"
"github.com/local/glpi-neural-brain/internal/sourceagent"
)
const SourceInboxClassifierVersion = 3
type sourceInboxClassification struct {
Status string
Priority float64
Semantic float64
Freshness float64
TaskContext float64
EventSignal float64
Security bool
Reason string
MatchedNodeID string
}
type securityInboxAssessment struct {
Materialize bool `json:"materialize"`
SecurityRelevant bool `json:"security_relevant"`
Confidence float64 `json:"confidence"`
EventType string `json:"event_type"`
Severity string `json:"severity"`
Vendor string `json:"vendor"`
Products []string `json:"products"`
CVEs []string `json:"cves"`
AffectedVersions []string `json:"affected_versions"`
FixedVersions []string `json:"fixed_versions"`
Summary string `json:"summary"`
Facts []string `json:"facts"`
RecommendedActions []string `json:"recommended_actions"`
ResearchNeeded bool `json:"research_needed"`
ResearchQueries []string `json:"research_queries"`
Reason string `json:"reason"`
}
func (e *Engine) SetSourceInbox(store *sourceagent.Store) { e.SourceInbox = store }
func (e *Engine) evidenceAcquisitionEnabled() bool {
return (e.SourceInbox != nil && e.Cfg.SourceInboxEnabled) || e.ResearchEnabledForRuntime()
}
func (e *Engine) sourceInboxLoop(ctx context.Context) {
e.reconcileProactiveSecurityMaterialization(ctx)
e.queueExistingProactiveSecurityCandidates(ctx)
run := func() int {
processed := e.processSourceInbox(ctx)
e.queueExistingProactiveSecurityCandidates(ctx)
processed += e.processProactiveSecurityInbox(ctx)
return processed
}
drain := func() {
for {
processed := run()
if !e.SpeedModeEnabled() || processed == 0 || ctx.Err() != nil {
return
}
}
}
// Always classify once immediately. In Speed mode the loop keeps claiming
// batches until the queues are empty instead of sleeping between batches.
drain()
ticker := time.NewTicker(e.Cfg.SourceInboxInterval)
defer ticker.Stop()
for {
select {
case <-ctx.Done():
return
case <-ticker.C:
drain()
case <-e.sourceInboxWake:
drain()
}
}
}
func (e *Engine) WakeSourceInbox() {
if e == nil || e.sourceInboxWake == nil {
return
}
select {
case e.sourceInboxWake <- struct{}{}:
default:
}
}
func (e *Engine) processSourceInbox(ctx context.Context) int {
if e.SourceInbox == nil || !e.Cfg.SourceInboxEnabled {
return 0
}
items, err := e.SourceInbox.ClaimInbox(ctx, e.Cfg.SourceInboxBatchSize)
if err != nil {
slog.Warn("source inbox claim failed", "error", err)
return 0
}
if len(items) == 0 {
return 0
}
texts := make([]string, 0, len(items))
for _, item := range items {
text := item.Document.Title + "\n" + strings.Join(item.Document.Categories, " · ") + "\n" + item.Document.Text
if len([]rune(text)) > 12000 {
text = string([]rune(text)[:12000])
}
texts = append(texts, text)
}
cctx, cancel := context.WithTimeout(e.backgroundOllamaContext(ctx), 4*time.Minute)
vectors, embedErr := e.Ollama.Embed(cctx, texts)
cancel()
if embedErr != nil || len(vectors) != len(items) {
reason := fmt.Sprint(embedErr)
if embedErr == nil {
reason = fmt.Sprintf("embedding response count mismatch: got %d vectors for %d inbox documents", len(vectors), len(items))
}
for _, item := range items {
if releaseErr := e.SourceInbox.ReleaseInbox(ctx, item.ID, reason); releaseErr != nil {
slog.Error("source inbox release after embedding failure failed", "inbox_id", item.ID, "error", releaseErr)
}
}
return 0
}
candidateCount := 0
for i, item := range items {
hits, stats := e.similarKnowledge(vectors[i], 8, e.effectiveLearningFilter(), 0)
hit, found := e.sourceInboxKnowledgeHit(hits)
if !found {
if releaseErr := e.SourceInbox.ReleaseInbox(ctx, item.ID, "knowledge vectors are not ready"); releaseErr != nil {
slog.Error("source inbox release without knowledge hit failed", "inbox_id", item.ID, "error", releaseErr)
}
continue
}
classification := e.classifySourceInboxItem(item, hit.Score, hit.NodeID, time.Now().UTC())
if classification.Status == "candidate" {
candidateCount++
}
meta := make(map[string]any, len(item.Metadata)+12)
for key, value := range item.Metadata {
meta[key] = value
}
meta["processing_mode"] = e.RuntimeSettings().ProcessingMode
meta["exact_comparisons"] = stats.ExactComparisons
meta["coarse_comparisons"] = stats.CoarseComparisons
meta["candidate_pool"] = stats.CandidatePool
meta["classification_version"] = SourceInboxClassifierVersion
meta["classification_reason"] = classification.Reason
meta["semantic_similarity"] = classification.Semantic
meta["priority_score"] = classification.Priority
meta["freshness_score"] = classification.Freshness
meta["task_context_score"] = classification.TaskContext
meta["event_signal_score"] = classification.EventSignal
meta["security_candidate"] = classification.Security
if completeErr := e.SourceInbox.CompleteClassification(ctx, item.ID, classification.Status, classification.Priority, classification.MatchedNodeID, meta); completeErr != nil {
slog.Error("source inbox classification completion failed", "inbox_id", item.ID, "error", completeErr)
if releaseErr := e.SourceInbox.ReleaseInbox(ctx, item.ID, completeErr.Error()); releaseErr != nil {
slog.Error("source inbox classification recovery failed", "inbox_id", item.ID, "error", releaseErr)
}
continue
}
if classification.Security && e.Cfg.SourceInboxSecurityProactiveEnabled && classification.Priority >= e.Cfg.SourceInboxSecurityMinPriority {
if queueErr := e.SourceInbox.QueueProactiveSecurity(ctx, item.ID); queueErr != nil {
slog.Error("source inbox security queue failed", "inbox_id", item.ID, "error", queueErr)
}
}
}
if e.Broker != nil {
e.Broker.Publish(model.Activity{Type: "source.inbox.classified", Source: "brain", Phase: "source-inbox", Message: fmt.Sprintf("Source-Inbox: %d Dokumente geprüft · %d als Wissenskandidaten vorgemerkt", len(items), candidateCount), Strength: .36, Metadata: map[string]any{"documents": len(items), "candidates": candidateCount, "minimum_similarity": e.Cfg.SourceInboxMinSimilarity, "minimum_priority": e.Cfg.SourceInboxMinPriority, "novelty_floor": e.Cfg.SourceInboxNoveltyFloor, "classifier_version": SourceInboxClassifierVersion}})
}
return len(items)
}
func (e *Engine) sourceInboxKnowledgeHit(hits []model.Hit) (model.Hit, bool) {
for _, hit := range hits {
node, ok := e.Graph.GetNode(hit.NodeID)
if !ok || (node.Kind != "knowledge" && node.Kind != "ai-think") {
continue
}
return hit, true
}
return model.Hit{}, false
}
func (e *Engine) classifySourceInboxItem(item sourceagent.InboxDocument, semantic float64, matchedNodeID string, now time.Time) sourceInboxClassification {
freshness := sourceInboxFreshness(item, now)
taskContext := sourceInboxTaskContext(item)
eventSignal := sourceInboxEventSignal(item)
priority := clampInboxScore(0.65*semantic + 0.15*taskContext + 0.10*freshness + 0.10*eventSignal)
status := "archived"
reason := "zu geringe Nähe zur bestehenden Wissensbasis und keine ausreichend starken Aktualitäts-/Quellensignale"
if semantic >= e.Cfg.SourceInboxMinSimilarity {
status = "candidate"
reason = "direkte semantische Nähe zur bestehenden Wissensbasis"
} else if semantic >= e.Cfg.SourceInboxNoveltyFloor && priority >= e.Cfg.SourceInboxMinPriority {
status = "candidate"
reason = "neues, ausreichend KB-nahes Material mit zusätzlichem Quellen-, Aktualitäts- oder Advisory-Signal"
}
security := sourceInboxSecurityProactive(item, taskContext, eventSignal)
return sourceInboxClassification{Status: status, Priority: priority, Semantic: semantic, Freshness: freshness, TaskContext: taskContext, EventSignal: eventSignal, Security: security, Reason: reason, MatchedNodeID: matchedNodeID}
}
func sourceInboxSecurityProactive(item sourceagent.InboxDocument, taskContext, eventSignal float64) bool {
mode := strings.ToLower(strings.TrimSpace(sourceInboxMetadataString(item.Metadata, "security_proactive")))
switch mode {
case "false", "0", "off", "passive", "disabled":
return false
case "true", "1", "on", "proactive", "enabled":
return true
}
return taskContext >= .9 && eventSignal >= .75
}
func sourceInboxMetadataString(meta map[string]any, key string) string {
if meta == nil {
return ""
}
value, ok := meta[key]
if !ok || value == nil {
return ""
}
return fmt.Sprint(value)
}
func sourceInboxFreshness(item sourceagent.InboxDocument, now time.Time) float64 {
t := item.Document.PublishedAt
if t.IsZero() {
t = item.Document.DiscoveredAt
}
if t.IsZero() {
t = item.ReceivedAt
}
if t.IsZero() {
return .25
}
age := now.Sub(t)
if age < 0 {
age = 0
}
switch {
case age <= 24*time.Hour:
return 1
case age <= 7*24*time.Hour:
return .85
case age <= 30*24*time.Hour:
return .55
case age <= 90*24*time.Hour:
return .25
default:
return .10
}
}
func sourceInboxTaskContext(item sourceagent.InboxDocument) float64 {
contextText := strings.ToLower(strings.Join(append(append([]string{}, item.Document.Categories...), item.Document.SourceName, item.Document.SourceBaseURL), " "))
for _, marker := range []string{"security", "sicherheit", "advisory", "alert", "vulnerability", "vulnerabil", "cve", "incident", "patch", "release", "threat", "bedroh", "exploit"} {
if strings.Contains(contextText, marker) {
return 1
}
}
if len(item.Document.Categories) > 0 {
return .65
}
if strings.TrimSpace(item.Document.SourceName) != "" {
return .40
}
return .20
}
func sourceInboxEventSignal(item sourceagent.InboxDocument) float64 {
text := strings.ToLower(item.Document.Title + " " + strings.Join(item.Document.Categories, " ") + " " + item.Document.SourceName)
for _, marker := range []string{"0-day", "0day", "zero-day", "cve-", "kritisch", "critical", "actively exploited", "aktiv ausgenutzt", "backdoor", "authentifizierung umgehen", "authentication bypass", "remote code", "rce", "schadcode", "malware", "kompromitt"} {
if strings.Contains(text, marker) {
return 1
}
}
for _, marker := range []string{"angreifer", "attack", "sicherheitslücke", "sicherheitsleck", "vulnerability", "security update", "sicherheitsupdate", "patch", "update", "exploit", "datenleck", "security", "firewall", "advisory"} {
if strings.Contains(text, marker) {
return .75
}
}
return .20
}
func clampInboxScore(v float64) float64 { return math.Max(0, math.Min(1, v)) }
func (e *Engine) reconcileProactiveSecurityMaterialization(ctx context.Context) {
if e.SourceInbox == nil || e.Graph == nil {
return
}
lifecycles, err := e.SourceInbox.SecurityLifecycles(ctx, time.Unix(0, 0).UTC())
if err != nil {
slog.Error("source security startup reconciliation failed", "error", err)
return
}
requeued := 0
repairedVectors := 0
for _, lifecycle := range lifecycles {
state := strings.ToLower(strings.TrimSpace(lifecycle.ProactiveState))
status := strings.ToLower(strings.TrimSpace(lifecycle.Status))
if state != "done" || (status != "materialized" && status != "used") {
continue
}
node, exists := e.Graph.GetNode(lifecycle.MaterializedNodeID)
if lifecycle.MaterializedNodeID == "" || !exists || node.Origin != "source-agent-security" {
reason := "materialized Source-Inbox record has no persisted source-agent-security graph node after restart"
if requeueErr := e.SourceInbox.RequeueMissingMaterializedSecurity(ctx, lifecycle.InboxID, reason); requeueErr != nil {
slog.Error("source security startup requeue failed", "inbox_id", lifecycle.InboxID, "error", requeueErr)
continue
}
requeued++
continue
}
if vector, ok := e.Graph.Vector(node.ID); !ok || len(vector) == 0 {
stats := e.learnProactiveSecurityNode(ctx, node)
if !stats.Empty() {
repairedVectors++
}
}
}
if (requeued > 0 || repairedVectors > 0) && e.Broker != nil {
e.Broker.Publish(model.Activity{Type: "source.security.reconciled", Source: "brain", Phase: "source-inbox-security", Message: fmt.Sprintf("Security-Startup-Reconciliation: %d fehlende Materialisierungen neu eingeplant · %d fehlende Vektoren repariert", requeued, repairedVectors), Strength: .72, Metadata: map[string]any{"requeued": requeued, "vectors_repaired": repairedVectors}})
}
}
func (e *Engine) queueExistingProactiveSecurityCandidates(ctx context.Context) {
if e.SourceInbox == nil || !e.Cfg.SourceInboxEnabled || !e.Cfg.SourceInboxSecurityProactiveEnabled {
return
}
items, err := e.SourceInbox.ListInbox(ctx, "candidate", 1000)
if err != nil {
return
}
for _, item := range items {
priority := item.Relevance
if v, ok := item.Metadata["priority_score"].(float64); ok {
priority = v
}
taskContext := sourceInboxTaskContext(item)
eventSignal := sourceInboxEventSignal(item)
if item.ProactiveState == "" && priority >= e.Cfg.SourceInboxSecurityMinPriority && sourceInboxSecurityProactive(item, taskContext, eventSignal) {
if queueErr := e.SourceInbox.QueueProactiveSecurity(ctx, item.ID); queueErr != nil {
slog.Error("existing source inbox security queue failed", "inbox_id", item.ID, "error", queueErr)
}
}
}
}
func (e *Engine) processProactiveSecurityInbox(ctx context.Context) int {
if e.SourceInbox == nil || !e.Cfg.SourceInboxEnabled || !e.Cfg.SourceInboxSecurityProactiveEnabled || e.Ollama == nil {
return 0
}
items, err := e.SourceInbox.ClaimProactiveSecurity(ctx, e.Cfg.SourceInboxSecurityBatchSize)
if err != nil {
slog.Warn("source inbox proactive security claim failed", "error", err)
return 0
}
if len(items) == 0 {
return 0
}
materialized := 0
for _, item := range items {
if ctx.Err() != nil {
bg := context.Background()
runID, started, startErr := e.SourceInbox.StartProactiveSecurityRun(bg, item.ID)
if startErr == nil {
if releaseErr := e.SourceInbox.ReleaseProactiveSecurity(bg, item.ID, ctx.Err().Error()); releaseErr != nil {
slog.Error("source security cancellation release failed", "inbox_id", item.ID, "error", releaseErr)
}
if e.Broker != nil {
meta := withRunMutations(map[string]any{"run_id": runID, "inbox_id": item.ID, "title": item.Document.Title, "error": ctx.Err().Error(), "duration_ms": time.Since(started).Milliseconds(), "result": "cancelled"}, graph.MutationStats{})
e.Broker.Publish(model.Activity{Type: "source.security.failed", Source: "brain", Phase: "source-inbox-security", Message: "Proaktive Security-Auswertung wurde vor dem Start abgebrochen", Strength: .22, Metadata: meta})
}
} else {
if releaseErr := e.SourceInbox.ReleaseProactiveSecurity(bg, item.ID, ctx.Err().Error()); releaseErr != nil {
slog.Error("source security cancellation recovery failed", "inbox_id", item.ID, "start_error", startErr, "release_error", releaseErr)
}
}
continue
}
runID, started, startErr := e.SourceInbox.StartProactiveSecurityRun(ctx, item.ID)
if startErr != nil {
if releaseErr := e.SourceInbox.ReleaseProactiveSecurity(ctx, item.ID, startErr.Error()); releaseErr != nil {
slog.Error("source security start recovery failed", "inbox_id", item.ID, "start_error", startErr, "release_error", releaseErr)
}
continue
}
if item.Metadata == nil {
item.Metadata = map[string]any{}
}
item.Metadata["proactive_run_id"] = runID
item.Metadata["proactive_started_at"] = started
if e.Broker != nil {
e.Broker.Publish(model.Activity{Type: "source.security.started", Source: "brain", Phase: "source-inbox-security", Message: "Priorisierte Security-Meldung wird gegen die vorhandene KB geprüft", Strength: .58, Metadata: map[string]any{"run_id": runID, "inbox_id": item.ID, "title": item.Document.Title, "agent_id": item.AgentID, "task_id": item.TaskID, "priority": item.Relevance, "matched_node_id": item.MatchedNodeID}})
}
ok, mutations, processErr := e.processProactiveSecurityItem(ctx, item, started)
if processErr != nil {
if releaseErr := e.SourceInbox.ReleaseProactiveSecurity(ctx, item.ID, processErr.Error()); releaseErr != nil {
slog.Error("source security retry release failed", "inbox_id", item.ID, "process_error", processErr, "release_error", releaseErr)
}
if e.Broker != nil {
meta := withRunMutations(map[string]any{"run_id": runID, "inbox_id": item.ID, "title": item.Document.Title, "error": processErr.Error(), "duration_ms": time.Since(started).Milliseconds()}, mutations)
e.Broker.Publish(model.Activity{Type: "source.security.failed", Source: "brain", Phase: "source-inbox-security", Message: "Proaktive Security-Auswertung wurde vertagt", Strength: .28, Metadata: meta})
}
continue
}
if ok {
materialized++
}
}
if materialized > 0 {
e.RequestEnrich("source-security")
}
return len(items)
}
func (e *Engine) processProactiveSecurityItem(ctx context.Context, item sourceagent.InboxDocument, started time.Time) (bool, graph.MutationStats, error) {
var mutations graph.MutationStats
primary, directFetch := e.securityInboxPrimaryEvidence(ctx, item)
matched, _ := e.Graph.GetNode(item.MatchedNodeID)
assessment, err := e.assessSecurityInbox(ctx, item, matched, primary, nil)
if err != nil {
return false, mutations, err
}
supplemental := []model.ResearchResult{}
if assessment.ResearchNeeded && e.ResearchEnabledForRuntime() && e.Research != nil {
supplemental = e.securityInboxSupplementalResearch(ctx, item, assessment)
if len(supplemental) > 0 {
assessment, err = e.assessSecurityInbox(ctx, item, matched, primary, supplemental)
if err != nil {
return false, mutations, err
}
}
}
assessment.Confidence = clamp01(assessment.Confidence)
applicability, applicabilityReason := securityInboxDirectApplicability(assessment, matched)
if !assessment.Materialize || !assessment.SecurityRelevant || assessment.Confidence < e.Cfg.SourceInboxSecurityMinConfidence || strings.TrimSpace(assessment.Summary) == "" || len(assessment.Facts) == 0 {
meta := securityAssessmentMetadata(assessment)
meta["direct_fetch_attempted"] = directFetch
meta["supplemental_sources"] = researchURLs(supplemental)
meta["proactive_run_id"] = sourceInboxMetadataString(item.Metadata, "proactive_run_id")
meta = withRunMutations(meta, mutations)
if rejectErr := e.SourceInbox.RejectProactiveSecurity(ctx, item.ID, nonempty(assessment.Reason, "kein ausreichend belastbarer Security-Faktensatz"), meta); rejectErr != nil {
return false, mutations, rejectErr
}
if e.Broker != nil {
terminalMeta := mergeResearchMetadata(meta, map[string]any{"run_id": sourceInboxMetadataString(item.Metadata, "proactive_run_id"), "inbox_id": item.ID, "title": item.Document.Title, "duration_ms": time.Since(started).Milliseconds(), "direct_fetch_attempted": directFetch, "supplemental_sources": len(supplemental)})
e.Broker.Publish(model.Activity{Type: "source.security.rejected", Source: "brain", Phase: "source-inbox-security", Message: "Security-Candidate bleibt passiv in der Inbox; Gemma sah noch keinen belastbaren Graph-Faktensatz", Strength: .34, Metadata: terminalMeta})
}
return false, mutations, nil
}
allEvidence := append([]model.ResearchResult{primary}, supplemental...)
evidencePaths := e.persistResearchMaterial(allEvidence)
nodeID := graph.ID("external", primary.URL)
now := time.Now().UTC()
meta := securityAssessmentMetadata(assessment)
meta["security_applicability"] = applicability
meta["security_applicability_reason"] = applicabilityReason
meta["validation_state"] = "security_verified"
meta["proactive_security"] = true
meta["source_inbox_id"] = item.ID
meta["source_agent_id"] = item.AgentID
meta["source_task_id"] = item.TaskID
meta["source"] = graph.SourceFromURL(primary.URL)
meta["priority_score"] = item.Relevance
meta["matched_node_id"] = item.MatchedNodeID
meta["published_at"] = item.Document.PublishedAt
meta["evidence_paths"] = evidencePaths
meta["supplemental_sources"] = researchURLs(supplemental)
meta["direct_fetch_attempted"] = directFetch
meta["verified_by_model"] = e.Cfg.ArticleSynthesisModel
meta["content_sha256"] = item.Document.ContentSHA256
summary := strings.TrimSpace(assessment.Summary)
if len(assessment.Facts) > 0 {
summary += "\n\nFakten:\n- " + strings.Join(unique(assessment.Facts), "\n- ")
}
if len(assessment.RecommendedActions) > 0 {
summary += "\n\nEmpfohlene Maßnahmen:\n- " + strings.Join(unique(assessment.RecommendedActions), "\n- ")
}
categories := unique(append(append([]string{}, item.Document.Categories...), "Security Update", "Source Agent"))
node := model.Node{ID: nodeID, Kind: "external", Label: nonempty(item.Document.Title, primary.Title), Summary: clamp(summary, 6000), Status: "research", Origin: "source-agent-security", ExternalID: primary.URL, URI: primary.URL, Categories: categories, Keywords: unique(append(append([]string{}, assessment.Products...), assessment.CVEs...)), Weight: 1.15 + item.Relevance*.35 + assessment.Confidence*.25, Metadata: meta, UpdatedAt: now}
mutations.Add(e.Graph.UpsertNodeWithStats(node))
if item.MatchedNodeID != "" {
if _, ok := e.Graph.GetNode(item.MatchedNodeID); ok {
edgeType := "security_context_for"
edgeConfidence := math.Min(assessment.Confidence, math.Max(.35, item.Relevance*.80))
edgeWeight := math.Max(.35, item.Relevance*.55)
if applicability == "direct" {
edgeType = "security_update_for"
edgeConfidence = assessment.Confidence
edgeWeight = math.Max(.65, item.Relevance)
}
edge := model.Edge{Source: nodeID, Target: item.MatchedNodeID, Type: edgeType, Origin: "source-agent-security", Status: "staging", Confidence: edgeConfidence, Weight: edgeWeight, Explanation: applicabilityReason, Metadata: map[string]any{"event_type": assessment.EventType, "severity": assessment.Severity, "cves": unique(assessment.CVEs), "products": unique(assessment.Products), "source_inbox_id": item.ID, "applicability": applicability}}
mutations.Add(e.Graph.UpsertEdgeWithStats(edge))
}
}
mutations.Add(e.learnProactiveSecurityNode(ctx, node))
meta["proactive_run_id"] = sourceInboxMetadataString(item.Metadata, "proactive_run_id")
meta = withRunMutations(meta, mutations)
if err := e.SourceInbox.CompleteProactiveSecurity(ctx, item.ID, nodeID, meta); err != nil {
return false, mutations, err
}
if e.Broker != nil {
terminalMeta := withRunMutations(map[string]any{"run_id": sourceInboxMetadataString(item.Metadata, "proactive_run_id"), "inbox_id": item.ID, "node_id": nodeID, "title": node.Label, "confidence": assessment.Confidence, "severity": assessment.Severity, "event_type": assessment.EventType, "cves": unique(assessment.CVEs), "products": unique(assessment.Products), "matched_node_id": item.MatchedNodeID, "supplemental_sources": len(supplemental), "direct_fetch_attempted": directFetch, "research_needed": assessment.ResearchNeeded, "security_applicability": applicability, "duration_ms": time.Since(started).Milliseconds()}, mutations)
e.Broker.Publish(model.Activity{Type: "source.security.materialized", Source: "brain", Phase: "source-inbox-security", NodeIDs: []string{nodeID}, Message: "Priorisierte Security-Meldung wurde als verifizierter externer Graph-Node materialisiert", Strength: .82, Metadata: terminalMeta})
}
return true, mutations, nil
}
func securityInboxDirectApplicability(assessment securityInboxAssessment, matched model.Node) (string, string) {
if matched.ID == "" {
return "standalone", "Security-Meldung wird als eigenständige Evidenz materialisiert; es existiert kein direktes KB-Ziel."
}
target := strings.ToLower(strings.Join(append([]string{matched.Label}, matched.Keywords...), " "))
targetTokens := securityApplicabilityTokens(target)
for _, cve := range assessment.CVEs {
cve = strings.ToLower(strings.TrimSpace(cve))
if cve != "" && strings.Contains(target, cve) {
return "direct", "Direkte Applicability: dieselbe CVE ist im KB-Ziel explizit referenziert."
}
}
for _, product := range assessment.Products {
normalized := strings.TrimSpace(strings.ToLower(product))
if normalized == "" {
continue
}
if len([]rune(normalized)) >= 4 && strings.Contains(target, normalized) {
return "direct", fmt.Sprintf("Direkte Applicability: Produkt %q ist im Titel/Keyword-Kontext des KB-Ziels enthalten.", product)
}
productTokens := securityApplicabilityTokens(normalized)
if len(productTokens) == 1 {
for token := range productTokens {
if len(token) >= 5 && targetTokens[token] {
return "direct", fmt.Sprintf("Direkte Applicability: Produktbegriff %q stimmt mit dem KB-Ziel überein.", product)
}
}
}
if len(productTokens) >= 2 && tokenJaccard(productTokens, targetTokens) >= .75 {
return "direct", fmt.Sprintf("Direkte Applicability: Produktbegriffe %q stimmen weitgehend mit dem KB-Ziel überein.", product)
}
}
return "contextual", "Nur kontextuelle Security-Nähe: Produkt/CVE stimmt nicht direkt mit Titel oder Keywords des KB-Ziels überein; daher keine security_update_for-Relation."
}
func securityApplicabilityTokens(value string) map[string]bool {
value = strings.ToLower(value)
parts := regexp.MustCompile(`[^a-z0-9äöüß._+-]+`).Split(value, -1)
stop := map[string]bool{"security": true, "sicherheit": true, "update": true, "advisory": true, "multiple": true, "mehrere": true, "the": true, "und": true, "for": true, "für": true, "unter": true}
out := map[string]bool{}
for _, part := range parts {
part = strings.TrimSpace(part)
if len(part) < 3 || stop[part] {
continue
}
out[part] = true
}
return out
}
func tokenJaccard(a, b map[string]bool) float64 {
if len(a) == 0 || len(b) == 0 {
return 0
}
intersection := 0
union := map[string]bool{}
for value := range a {
union[value] = true
if b[value] {
intersection++
}
}
for value := range b {
union[value] = true
}
return float64(intersection) / float64(len(union))
}
func (e *Engine) securityInboxPrimaryEvidence(ctx context.Context, item sourceagent.InboxDocument) (model.ResearchResult, bool) {
d := item.Document
result := model.ResearchResult{Title: d.Title, URL: nonempty(d.CanonicalURL, d.URL), Snippet: clamp(d.Text, 1200), Content: d.Text, ContentType: d.ContentType, Language: d.Language, Fetched: true, Relevant: true, Relevance: item.Relevance, SourceQuality: "curated_agent", SourceQualityScore: .82, AssessmentReason: "Vom konfigurierten Source-Agent als priorisierte Security-Meldung geliefert."}
canonicalURL := result.URL
textShort := len([]rune(strings.TrimSpace(d.Text))) < e.Cfg.SourceInboxSecurityFetchMinChars
fetchError := strings.TrimSpace(sourceInboxMetadataString(item.Metadata, "fetch_error_kind")) != ""
if !textShort && !fetchError {
return result, false
}
client := e.Research
if client == nil {
client = research.New("")
}
var page research.FetchedPage
err := e.withSharedResearchWork(ctx, "web.fetch", func() error {
var fetchErr error
page, _, fetchErr = client.FetchPage(ctx, result.URL, research.FetchOptions{MaxBytes: e.Cfg.ArticleResearchPageMaxBytes, MaxChars: maxInt(e.Cfg.ArticleResearchPageMaxChars, e.Cfg.SourceInboxSecurityFetchMinChars*2), Timeout: e.Cfg.ArticleResearchFetchTimeout, AllowPrivate: e.Cfg.ArticleResearchAllowPrivate})
return fetchErr
})
if err == nil && len([]rune(strings.TrimSpace(page.Content))) > len([]rune(strings.TrimSpace(result.Content))) {
result.Content = page.Content
result.Snippet = clamp(page.Content, 1200)
result.ContentType = page.ContentType
// Keep the Agent's canonical URL stable so later Claim-Grounding can mark
// the same inbox record as used even when the publisher redirects.
result.URL = canonicalURL
result.Title = nonempty(page.Title, result.Title)
}
return result, true
}
func (e *Engine) assessSecurityInbox(ctx context.Context, item sourceagent.InboxDocument, matched model.Node, primary model.ResearchResult, supplemental []model.ResearchResult) (securityInboxAssessment, error) {
var b strings.Builder
fmt.Fprintf(&b, "SOURCE-INBOX-ID: %s\nAGENT: %s\nTASK: %s\nPRIORITÄT: %.3f\n\n", item.ID, item.AgentID, item.TaskID, item.Relevance)
if matched.ID != "" {
fmt.Fprintf(&b, "PASSENDSTER KB-KONTEXT:\nID: %s\nTitel: %s\nKategorien: %s\nInhalt: %s\n\n", matched.ID, matched.Label, strings.Join(matched.Categories, ", "), clamp(matched.Summary, 3000))
}
fmt.Fprintf(&b, "P1 PRIMÄRQUELLE:\nTitel: %s\nURL: %s\nVeröffentlicht: %s\nInhalt:\n%s\n", primary.Title, primary.URL, item.Document.PublishedAt.UTC().Format(time.RFC3339), clamp(primary.Content, 12000))
for i, result := range supplemental {
fmt.Fprintf(&b, "\nS%d ERGÄNZUNGSQUELLE:\nTitel: %s\nURL: %s\nInhalt:\n%s\n", i+1, result.Title, result.URL, clamp(result.Content, 7000))
}
var out securityInboxAssessment
modelName := strings.TrimSpace(e.Cfg.ArticleSynthesisModel)
if modelName == "" {
modelName = e.Cfg.ChatModel
}
cctx, cancel := context.WithTimeout(e.backgroundOllamaContext(ctx), 6*time.Minute)
err := e.Ollama.ChatJSONModel(cctx, modelName, securityInboxSystemPrompt(), b.String(), securityInboxSchema(), &out)
cancel()
out = normalizeSecurityAssessment(out, item.Document.Title)
return out, err
}
var cvePattern = regexp.MustCompile(`(?i)^CVE-[0-9]{4}-[0-9]{4,}$`)
func normalizeSecurityAssessment(out securityInboxAssessment, sourceTitle string) securityInboxAssessment {
out.Products = unique(out.Products)
validCVEs := make([]string, 0, len(out.CVEs))
for _, cve := range unique(out.CVEs) {
cve = strings.ToUpper(strings.TrimSpace(cve))
if cvePattern.MatchString(cve) {
validCVEs = append(validCVEs, cve)
}
}
out.CVEs = validCVEs
out.AffectedVersions = unique(out.AffectedVersions)
out.FixedVersions = unique(out.FixedVersions)
out.Facts = unique(out.Facts)
out.RecommendedActions = unique(out.RecommendedActions)
out.ResearchQueries = unique(out.ResearchQueries)
out.Severity = normalizeSecuritySeverity(out.Severity, sourceTitle)
out.EventType = normalizeSecurityEventType(out.EventType)
return out
}
func normalizeSecuritySeverity(value, sourceTitle string) string {
v := strings.ToLower(strings.TrimSpace(value))
switch v {
case "critical", "kritisch", "sehr hoch", "very high":
return "critical"
case "high", "hoch":
return "high"
case "medium", "mittel", "moderate", "moderat":
return "medium"
case "low", "niedrig":
return "low"
case "informational", "information", "info":
return "informational"
}
title := strings.ToLower(sourceTitle)
for _, candidate := range []struct {
markers []string
value string
}{
{[]string{"[kritisch]", "[critical]"}, "critical"},
{[]string{"[hoch]", "[high]"}, "high"},
{[]string{"[mittel]", "[medium]"}, "medium"},
{[]string{"[niedrig]", "[low]"}, "low"},
} {
for _, marker := range candidate.markers {
if strings.Contains(title, marker) {
return candidate.value
}
}
}
return "unknown"
}
func normalizeSecurityEventType(value string) string {
v := strings.ToLower(strings.TrimSpace(value))
v = strings.NewReplacer("-", "_", " ", "_", "/", "_").Replace(v)
for strings.Contains(v, "__") {
v = strings.ReplaceAll(v, "__", "_")
}
switch v {
case "vulnerability", "security_vulnerability", "schwachstelle", "vulnerabilities", "multiple_vulnerabilities":
return "vulnerability"
case "security_advisory", "advisory":
return "security_advisory"
case "security_update", "update":
return "security_update"
case "denial_of_service", "dos":
return "denial_of_service"
case "cross_site_scripting", "xss":
return "xss"
case "privilege_escalation", "privilegieneskalation":
return "privilege_escalation"
case "remote_code_execution", "code_execution", "rce", "codeausführung", "codeausfuehrung":
return "code_execution"
case "authentication_bypass", "auth_bypass":
return "authentication_bypass"
case "information_disclosure", "information_leak":
return "information_disclosure"
}
if v == "" || v == "unknown" {
return "vulnerability"
}
return v
}
func securityInboxSystemPrompt() string {
return `Du bist der Security-Intelligence-Extractor des Neural Brain. Prüfe eine vom Betreiber kuratierte Security-/Advisory-Quelle gegen den angegebenen KB-Kontext.
WICHTIG:
- Der Source-Agent ist ein bestätigter Discovery-Kanal, aber du darfst AUSSCHLIESSLICH Fakten aus P1 und den S-Quellen übernehmen.
- Nutze kein parametrisches Modellwissen für CVEs, Versionen, Schweregrade, Produkte oder Maßnahmen.
- materialize=true nur wenn die Quellen eine konkrete neue oder aktualisierte Security-Information enthalten, die zum KB-Kontext passt oder diesen sinnvoll erweitert.
- facts müssen konkrete, quellenbelegte Aussagen sein. Keine allgemeinen Security-Floskeln.
- severity nur setzen, wenn sie aus den Quellen hervorgeht; sonst "unknown".
- CVE-IDs, betroffene/fixe Versionen und Maßnahmen nur übernehmen, wenn explizit belegt.
- research_needed=true, wenn die Meldung erkennbar relevant ist, aber für einen belastbaren Faktensatz wichtige Angaben fehlen. Formuliere dann höchstens zwei präzise Suchanfragen.
- Wenn die Meldung nur allgemeine Meinung/Marketing ohne konkretes Security-Ereignis ist, materialize=false.
Ziel ist ein kleiner, belastbarer Security-Faktensatz für einen externen Graph-Node; noch kein KB-Artikel.`
}
func securityInboxSchema() map[string]any {
return map[string]any{
"type": "object",
"properties": map[string]any{
"materialize": map[string]any{"type": "boolean"}, "security_relevant": map[string]any{"type": "boolean"}, "confidence": map[string]any{"type": "number"},
"event_type": map[string]any{"type": "string"}, "severity": map[string]any{"type": "string"}, "vendor": map[string]any{"type": "string"},
"products": map[string]any{"type": "array", "items": map[string]any{"type": "string"}}, "cves": map[string]any{"type": "array", "items": map[string]any{"type": "string"}},
"affected_versions": map[string]any{"type": "array", "items": map[string]any{"type": "string"}}, "fixed_versions": map[string]any{"type": "array", "items": map[string]any{"type": "string"}},
"summary": map[string]any{"type": "string"}, "facts": map[string]any{"type": "array", "items": map[string]any{"type": "string"}}, "recommended_actions": map[string]any{"type": "array", "items": map[string]any{"type": "string"}},
"research_needed": map[string]any{"type": "boolean"}, "research_queries": map[string]any{"type": "array", "items": map[string]any{"type": "string"}}, "reason": map[string]any{"type": "string"},
},
"required": []string{"materialize", "security_relevant", "confidence", "event_type", "severity", "vendor", "products", "cves", "affected_versions", "fixed_versions", "summary", "facts", "recommended_actions", "research_needed", "research_queries", "reason"},
}
}
func (e *Engine) securityInboxSupplementalResearch(ctx context.Context, item sourceagent.InboxDocument, assessment securityInboxAssessment) []model.ResearchResult {
if e.Research == nil || !e.ResearchEnabledForRuntime() {
return nil
}
queries := append([]string{}, assessment.ResearchQueries...)
if len(queries) == 0 {
queries = []string{strings.TrimSpace(item.Document.Title + " " + assessment.Vendor + " security advisory")}
}
if len(queries) > 2 {
queries = queries[:2]
}
seen := map[string]bool{canonicalResearchURL(nonempty(item.Document.CanonicalURL, item.Document.URL)): true}
out := []model.ResearchResult{}
for _, query := range queries {
if strings.TrimSpace(query) == "" || len(out) >= e.Cfg.SourceInboxSecurityResearchResults {
continue
}
var results []model.ResearchResult
err := e.withSharedResearchWork(ctx, "searxng.search", func() error {
var searchErr error
results, _, searchErr = e.Research.SearchDetailedLanguage(ctx, sanitizeSearchQuerySiteFilters(query), e.Cfg.SourceInboxSecurityResearchResults, nonempty(item.Document.Language, e.Cfg.ArticleLanguage))
return searchErr
})
if err != nil {
continue
}
for _, result := range results {
if len(out) >= e.Cfg.SourceInboxSecurityResearchResults {
break
}
key := canonicalResearchURL(result.URL)
if key == "" || seen[key] {
continue
}
seen[key] = true
var page research.FetchedPage
fetchErr := e.withSharedResearchWork(ctx, "web.fetch", func() error {
var inner error
page, _, inner = e.Research.FetchPage(ctx, result.URL, research.FetchOptions{MaxBytes: e.Cfg.ArticleResearchPageMaxBytes, MaxChars: e.Cfg.ArticleResearchPageMaxChars, Timeout: e.Cfg.ArticleResearchFetchTimeout, AllowPrivate: e.Cfg.ArticleResearchAllowPrivate})
return inner
})
if fetchErr != nil || strings.TrimSpace(page.Content) == "" {
continue
}
result.URL = nonempty(page.URL, result.URL)
result.Title = nonempty(page.Title, result.Title)
result.Content = page.Content
result.Snippet = clamp(page.Content, 1200)
result.ContentType = page.ContentType
result.Fetched = true
result.Relevant = true
result.Relevance = .65
result.SourceQuality = "supplemental_security"
result.SourceQualityScore = .72
result.AssessmentReason = "Gezielt nachgeladen, weil der Security-Candidate für einen belastbaren Faktensatz zusätzliche Details benötigte."
out = append(out, result)
}
}
if len(out) > 0 && e.Broker != nil {
e.Broker.Publish(model.Activity{Type: "source.security.research", Source: "searxng", Phase: "source-inbox-security", Message: fmt.Sprintf("Security-Candidate wurde mit %d gezielt nachgeladenen Volltextquellen ergänzt", len(out)), Strength: .62, Metadata: map[string]any{"run_id": sourceInboxMetadataString(item.Metadata, "proactive_run_id"), "inbox_id": item.ID, "title": item.Document.Title, "results": len(out), "queries": queries}})
}
return out
}
func securityAssessmentMetadata(a securityInboxAssessment) map[string]any {
return map[string]any{"security_relevant": a.SecurityRelevant, "security_confidence": a.Confidence, "security_event_type": a.EventType, "security_severity": a.Severity, "security_vendor": a.Vendor, "security_products": unique(a.Products), "security_cves": unique(a.CVEs), "security_affected_versions": unique(a.AffectedVersions), "security_fixed_versions": unique(a.FixedVersions), "security_summary": a.Summary, "security_facts": unique(a.Facts), "security_recommended_actions": unique(a.RecommendedActions), "security_research_needed": a.ResearchNeeded, "security_research_queries": unique(a.ResearchQueries), "security_assessment_reason": a.Reason}
}
func researchURLs(results []model.ResearchResult) []string {
values := make([]string, 0, len(results))
for _, result := range results {
if strings.TrimSpace(result.URL) != "" {
values = append(values, result.URL)
}
}
return unique(values)
}
func (e *Engine) learnProactiveSecurityNode(ctx context.Context, node model.Node) graph.MutationStats {
if e.Ollama == nil || strings.TrimSpace(node.ID) == "" {
return graph.MutationStats{}
}
text := strings.TrimSpace(node.Label + "\n" + clamp(node.Summary, 6000))
if text == "" {
return graph.MutationStats{}
}
cctx, cancel := context.WithTimeout(e.backgroundOllamaContext(ctx), 3*time.Minute)
vectors, err := e.Ollama.Embed(cctx, []string{text})
cancel()
if err != nil || len(vectors) != 1 || len(vectors[0]) == 0 {
return e.Graph.SetVectorWithStats(node.ID, hashEmbedding(text, 256))
}
return e.Graph.SetVectorWithStats(node.ID, vectors[0])
}
func (e *Engine) sourceInboxResearch(ctx context.Context, query string, limit int, freshnessSensitive bool) []model.ResearchResult {
if e.SourceInbox == nil || !e.Cfg.SourceInboxEnabled || limit < 1 {
return nil
}
maxAge := time.Duration(0)
if freshnessSensitive {
maxAge = e.Cfg.SourceInboxFreshMaxAge
}
items, err := e.SourceInbox.SearchCandidates(ctx, query, limit, maxAge)
if err != nil {
return nil
}
out := make([]model.ResearchResult, 0, len(items))
for _, item := range items {
if item.QueryScore < .18 {
continue
}
d := item.Document
out = append(out, model.ResearchResult{SourceInboxID: item.ID, Title: d.Title, URL: d.CanonicalURL, Snippet: clamp(d.Text, 1000), Content: d.Text, ContentType: d.ContentType, Query: query, Language: d.Language, Fetched: true, Relevant: true, Relevance: item.QueryScore, SourceQuality: "source_inbox", SourceQualityScore: .68, AssessmentReason: "Vorab durch Source-Agent gesammelt und vom Brain als thematisch passend zur Knowledgebase klassifiziert."})
}
if len(out) > 0 && e.Broker != nil {
e.Broker.Publish(model.Activity{Type: "article.research.inbox", Source: "brain", Phase: "knowledge-research-routing", Message: fmt.Sprintf("Source-Inbox liefert %d bereits gecrawlte Kandidaten vor SearXNG", len(out)), Strength: .56, Metadata: map[string]any{"query": query, "results": len(out), "freshness_sensitive": freshnessSensitive}})
}
return out
}