feat: add forensic sample analysis

TODO.md

@@ -68,7 +68,7 @@ have no working implementation in the codebase yet.
   without affecting aggregate compliance statistics. Operators can configure forensic
   email-address and token redaction under Settings.
 - [x] Forensic report parsing
-- [ ] Failure sample analysis
+- [x] Failure sample analysis
 - [x] PII redaction options
 - [x] Detailed authentication failure views
 

backend/app/api/api_v1/endpoints/forensics.py

@@ -9,6 +9,7 @@ from app.core.database import get_db
 from app.core.security import require_admin_auth
 from app.models.domain import Domain
 from app.models.report import ForensicReport
+from app.services.forensic_analysis import analyze_forensic_report, summarize_forensic_samples
 from app.services.forensic_parser import ForensicParser, MAX_FORENSIC_REPORT_SIZE
 from app.services.forensic_persistence import (
     forensic_report_exists,
@@ -22,6 +23,45 @@ logger = logging.getLogger(__name__)
 router = APIRouter()
 
 
+class ForensicSampleAnalysisResponse(BaseModel):
+    id: int
+    report_id: str
+    domain: Optional[str] = None
+    source_ip: Optional[str] = None
+    auth_failure: str
+    delivery_result: Optional[str] = None
+    priority: str
+    diagnosis: str
+    recommendations: List[str] = Field(default_factory=list)
+    signals: List[str] = Field(default_factory=list)
+    authentication_results: Dict[str, str] = Field(default_factory=dict)
+    dkim_domain: Optional[str] = None
+    mail_from_domain: Optional[str] = None
+    privacy_note: str
+
+
+class ForensicAnalysisGroupResponse(BaseModel):
+    key: str
+    domain: str
+    source_ip: str
+    auth_failure: str
+    delivery_result: str
+    count: int
+    priority: str
+    latest_arrival: Optional[str] = None
+    diagnosis: str
+    recommendations: List[str] = Field(default_factory=list)
+
+
+class ForensicAnalysisResponse(BaseModel):
+    total: int
+    priority_counts: Dict[str, int] = Field(default_factory=dict)
+    failure_counts: Dict[str, int] = Field(default_factory=dict)
+    result_counts: Dict[str, int] = Field(default_factory=dict)
+    groups: List[ForensicAnalysisGroupResponse] = Field(default_factory=list)
+    samples: List[ForensicSampleAnalysisResponse] = Field(default_factory=list)
+
+
 class ForensicReportResponse(BaseModel):
     id: int
     report_id: str
@@ -44,6 +84,7 @@ class ForensicReportResponse(BaseModel):
     original_date: Optional[str] = None
     feedback_headers: Dict[str, Any] = Field(default_factory=dict)
     processed_at: Optional[str] = None
+    analysis: Optional[ForensicSampleAnalysisResponse] = None
 
 
 class ForensicListResponse(BaseModel):
@@ -79,6 +120,35 @@ def _validate_upload(file: UploadFile, content: bytes) -> None:
         )
 
 
+def _filtered_forensic_query(
+    db: Session,
+    *,
+    domain: Optional[str] = None,
+    source_ip: Optional[str] = None,
+    auth_failure: Optional[str] = None,
+    delivery_result: Optional[str] = None,
+):
+    query = db.query(ForensicReport).options(selectinload(ForensicReport.domain))
+    if domain:
+        normalized = domain.lower()
+        query = query.outerjoin(Domain).filter(
+            (Domain.name == normalized) | (ForensicReport.reported_domain == normalized)
+        )
+    if source_ip:
+        query = query.filter(ForensicReport.source_ip == source_ip.strip())
+    if auth_failure:
+        query = query.filter(ForensicReport.auth_failure == auth_failure.strip().lower())
+    if delivery_result:
+        query = query.filter(ForensicReport.delivery_result == delivery_result.strip().lower())
+    return query
+
+
+def _response_for_row(row: ForensicReport, redaction_policy) -> ForensicReportResponse:
+    data = forensic_report_to_dict(row, redaction_policy=redaction_policy)
+    data["analysis"] = analyze_forensic_report(row)
+    return ForensicReportResponse(**data)
+
+
 @router.post("/upload", response_model=ForensicUploadResponse)
 async def upload_forensic_report(
     file: UploadFile = File(...),
@@ -138,19 +208,13 @@ async def list_forensic_reports(
     _auth: dict = Depends(require_admin_auth),
 ):
     """List stored forensic reports, newest first."""
-    query = db.query(ForensicReport).options(selectinload(ForensicReport.domain))
-    if domain:
-        normalized = domain.lower()
-        query = query.outerjoin(Domain).filter(
-            (Domain.name == normalized) | (ForensicReport.reported_domain == normalized)
+    query = _filtered_forensic_query(
+        db,
+        domain=domain,
+        source_ip=source_ip,
+        auth_failure=auth_failure,
+        delivery_result=delivery_result,
     )
-    if source_ip:
-        query = query.filter(ForensicReport.source_ip == source_ip.strip())
-    if auth_failure:
-        query = query.filter(ForensicReport.auth_failure == auth_failure.strip().lower())
-    if delivery_result:
-        query = query.filter(ForensicReport.delivery_result == delivery_result.strip().lower())
-
     total = query.count()
     rows = (
         query.order_by(ForensicReport.arrival_date.desc().nullslast(), ForensicReport.id.desc())
@@ -165,13 +229,34 @@ async def list_forensic_reports(
         page=page,
         page_size=page_size,
         total_pages=total_pages,
-        reports=[
-            ForensicReportResponse(
-                **forensic_report_to_dict(row, redaction_policy=redaction_policy)
+        reports=[_response_for_row(row, redaction_policy) for row in rows],
     )
-            for row in rows
-        ],
+
+
+@router.get("/analysis", response_model=ForensicAnalysisResponse)
+async def analyze_forensic_reports(
+    domain: Optional[str] = Query(default=None),
+    source_ip: Optional[str] = Query(default=None),
+    auth_failure: Optional[str] = Query(default=None),
+    delivery_result: Optional[str] = Query(default=None),
+    page_size: int = Query(default=200, ge=1, le=500),
+    db: Session = Depends(get_db),
+    _auth: dict = Depends(require_admin_auth),
+):
+    """Summarize stored forensic samples into operator investigation groups."""
+    query = _filtered_forensic_query(
+        db,
+        domain=domain,
+        source_ip=source_ip,
+        auth_failure=auth_failure,
+        delivery_result=delivery_result,
     )
+    rows = (
+        query.order_by(ForensicReport.arrival_date.desc().nullslast(), ForensicReport.id.desc())
+        .limit(page_size)
+        .all()
+    )
+    return ForensicAnalysisResponse(**summarize_forensic_samples(rows))
 
 
 @router.get("/{report_id}", response_model=ForensicReportResponse)
@@ -192,4 +277,4 @@ async def get_forensic_report(
             status_code=status.HTTP_404_NOT_FOUND, detail="Forensic report not found"
         )
     redaction_policy = get_forensic_redaction_policy(db)
-    return ForensicReportResponse(**forensic_report_to_dict(row, redaction_policy=redaction_policy))
+    return _response_for_row(row, redaction_policy)

backend/app/services/forensic_analysis.py

@@ -0,0 +1,271 @@
+import json
+import re
+from collections import Counter
+from datetime import datetime
+from typing import Any, Dict, Iterable, List, Optional, Tuple
+
+from app.models.report import ForensicReport
+
+
+AUTH_RESULT_PATTERN = re.compile(r"\b(dkim|spf|dmarc)=([a-zA-Z0-9_-]+)", re.IGNORECASE)
+HEADER_DOMAIN_PATTERN = re.compile(r"\bheader\.d=([^;\s]+)", re.IGNORECASE)
+MAILFROM_DOMAIN_PATTERN = re.compile(r"\bsmtp\.mailfrom=([^;\s]+)", re.IGNORECASE)
+PRIORITY_ORDER = {"high": 3, "medium": 2, "low": 1}
+
+
+def _clean_value(value: Any) -> str:
+    return str(value or "").strip()
+
+
+def _normalize(value: Any) -> str:
+    return _clean_value(value).lower()
+
+
+def _feedback_headers(row: ForensicReport) -> Dict[str, Any]:
+    if not row.feedback_headers:
+        return {}
+    try:
+        parsed = json.loads(row.feedback_headers)
+    except (json.JSONDecodeError, TypeError):
+        return {}
+    return parsed if isinstance(parsed, dict) else {}
+
+
+def _parse_authentication_results(value: str) -> Dict[str, str]:
+    results: Dict[str, str] = {}
+    for mechanism, result in AUTH_RESULT_PATTERN.findall(value or ""):
+        results[mechanism.lower()] = result.lower()
+    return results
+
+
+def _first_match(pattern: re.Pattern[str], value: str) -> str:
+    match = pattern.search(value or "")
+    return match.group(1).lower().strip(".,") if match else ""
+
+
+def _failure_kind(row: ForensicReport, auth_results: Dict[str, str]) -> str:
+    reported = _normalize(row.auth_failure)
+    if reported in {"dkim", "spf", "dmarc", "both"}:
+        return reported
+    failed = {name for name, result in auth_results.items() if result in {"fail", "softfail"}}
+    if {"dkim", "spf"}.issubset(failed):
+        return "both"
+    for mechanism in ("dmarc", "dkim", "spf"):
+        if mechanism in failed:
+            return mechanism
+    return reported or "unknown"
+
+
+def _priority(row: ForensicReport, failure_kind: str) -> str:
+    delivery = _normalize(row.delivery_result)
+    if delivery in {"reject", "quarantine"}:
+        return "high"
+    if failure_kind in {"both", "dmarc"}:
+        return "high"
+    if failure_kind in {"dkim", "spf"}:
+        return "medium"
+    return "low"
+
+
+def _diagnosis(failure_kind: str, auth_results: Dict[str, str], delivery_result: str) -> str:
+    delivery = _normalize(delivery_result)
+    rejected = delivery in {"reject", "quarantine"}
+    suffix = " The receiver enforced the failure." if rejected else ""
+    if failure_kind == "both":
+        return "Both DKIM and SPF failed, so DMARC could not find an aligned pass." + suffix
+    if failure_kind == "dmarc":
+        return "DMARC failed after the receiver evaluated DKIM and SPF alignment." + suffix
+    if failure_kind == "dkim":
+        if auth_results.get("spf") == "pass":
+            return "DKIM failed while SPF passed; focus on DKIM signing and alignment." + suffix
+        return "DKIM failed for the reported message sample." + suffix
+    if failure_kind == "spf":
+        if auth_results.get("dkim") == "pass":
+            return (
+                "SPF failed while DKIM passed; focus on SPF authorization and alignment." + suffix
+            )
+        return "SPF failed for the reported message sample." + suffix
+    return "The receiver reported an authentication failure, but did not include a clear mechanism."
+
+
+def _recommendations(
+    failure_kind: str,
+    auth_results: Dict[str, str],
+    source_ip: str,
+    reported_domain: str,
+) -> List[str]:
+    actions: List[str] = []
+    if failure_kind in {"dkim", "both", "dmarc"}:
+        actions.append(
+            "Confirm the sending system signs mail with a DKIM domain aligned to the visible From domain."
+        )
+        actions.append(
+            "Check recent DKIM key, selector, and canonicalization changes for this sender."
+        )
+    if failure_kind in {"spf", "both", "dmarc"}:
+        actions.append(
+            "Verify the source IP or provider include is authorized in the domain SPF record."
+        )
+        actions.append(
+            "Review forwarding paths, because forwarding commonly breaks SPF while preserving DKIM."
+        )
+    if auth_results.get("spf") == "pass" and failure_kind == "dkim":
+        actions.append(
+            "If SPF is aligned and passing, this may be a DKIM-only repair rather than a sender authorization issue."
+        )
+    if auth_results.get("dkim") == "pass" and failure_kind == "spf":
+        actions.append(
+            "If DKIM is aligned and passing, treat SPF repair as lower risk before changing DMARC policy."
+        )
+    if source_ip:
+        actions.append(
+            f"Compare {source_ip} with known mail sources for {reported_domain or 'this domain'}."
+        )
+    actions.append(
+        "Keep using redacted forensic metadata; do not import or retain message bodies for this investigation."
+    )
+    return actions
+
+
+def _signals(
+    row: ForensicReport,
+    feedback_headers: Dict[str, Any],
+    auth_results: Dict[str, str],
+    header_domain: str,
+    mailfrom_domain: str,
+) -> List[str]:
+    signals = []
+    if row.source_ip:
+        signals.append(f"Source IP: {row.source_ip}")
+    if row.reported_domain:
+        signals.append(f"Reported domain: {row.reported_domain}")
+    if row.auth_failure:
+        signals.append(f"Failure: {row.auth_failure}")
+    if row.delivery_result:
+        signals.append(f"Delivery result: {row.delivery_result}")
+    if header_domain:
+        signals.append(f"DKIM header domain: {header_domain}")
+    if mailfrom_domain:
+        signals.append(f"SPF mail-from domain: {mailfrom_domain}")
+    identity_alignment = _clean_value(feedback_headers.get("identity_alignment"))
+    if identity_alignment:
+        signals.append(f"Identity alignment: {identity_alignment}")
+    for mechanism, result in sorted(auth_results.items()):
+        signals.append(f"{mechanism.upper()} result: {result}")
+    return signals
+
+
+def analyze_forensic_report(row: ForensicReport) -> Dict[str, Any]:
+    """Build a privacy-preserving operator analysis for one forensic sample."""
+    feedback_headers = _feedback_headers(row)
+    auth_results = _parse_authentication_results(row.authentication_results or "")
+    header_domain = _first_match(
+        HEADER_DOMAIN_PATTERN, row.authentication_results or ""
+    ) or _normalize(feedback_headers.get("dkim_domain"))
+    mailfrom_domain = _first_match(MAILFROM_DOMAIN_PATTERN, row.authentication_results or "")
+    failure_kind = _failure_kind(row, auth_results)
+    priority = _priority(row, failure_kind)
+    reported_domain = _clean_value(row.reported_domain or (row.domain.name if row.domain else ""))
+    source_ip = _clean_value(row.source_ip)
+
+    return {
+        "id": row.id,
+        "report_id": row.report_id,
+        "domain": reported_domain,
+        "source_ip": source_ip,
+        "auth_failure": failure_kind,
+        "delivery_result": _clean_value(row.delivery_result),
+        "priority": priority,
+        "diagnosis": _diagnosis(failure_kind, auth_results, row.delivery_result or ""),
+        "recommendations": _recommendations(
+            failure_kind,
+            auth_results,
+            source_ip,
+            reported_domain,
+        ),
+        "signals": _signals(row, feedback_headers, auth_results, header_domain, mailfrom_domain),
+        "authentication_results": auth_results,
+        "dkim_domain": header_domain,
+        "mail_from_domain": mailfrom_domain,
+        "privacy_note": "Analysis uses redacted headers and metadata only; message bodies are not stored.",
+    }
+
+
+def _group_key(row: ForensicReport) -> Tuple[str, str, str, str]:
+    return (
+        _clean_value(row.reported_domain or (row.domain.name if row.domain else "")) or "unknown",
+        _clean_value(row.source_ip) or "unknown",
+        _normalize(row.auth_failure) or "unknown",
+        _normalize(row.delivery_result) or "unknown",
+    )
+
+
+def _latest(left: Optional[datetime], right: Optional[datetime]) -> Optional[datetime]:
+    if left is None:
+        return right
+    if right is None:
+        return left
+    return max(left, right)
+
+
+def summarize_forensic_samples(rows: Iterable[ForensicReport]) -> Dict[str, Any]:
+    """Summarize forensic samples into investigation groups and top examples."""
+    reports = list(rows)
+    analyses = [analyze_forensic_report(row) for row in reports]
+    priority_counts = Counter(item["priority"] for item in analyses)
+    failure_counts = Counter(item["auth_failure"] for item in analyses)
+    result_counts = Counter(_normalize(row.delivery_result) or "unknown" for row in reports)
+    grouped: Dict[Tuple[str, str, str, str], Dict[str, Any]] = {}
+
+    for row, analysis in zip(reports, analyses):
+        key = _group_key(row)
+        group = grouped.setdefault(
+            key,
+            {
+                "key": "|".join(key),
+                "domain": key[0],
+                "source_ip": key[1],
+                "auth_failure": analysis["auth_failure"],
+                "delivery_result": key[3],
+                "count": 0,
+                "priority": analysis["priority"],
+                "latest_arrival": None,
+                "diagnosis": analysis["diagnosis"],
+                "recommendations": analysis["recommendations"][:3],
+            },
+        )
+        group["count"] += 1
+        group["latest_arrival"] = _latest(
+            group["latest_arrival"], row.arrival_date or row.processed_at
+        )
+        if PRIORITY_ORDER[analysis["priority"]] > PRIORITY_ORDER[group["priority"]]:
+            group["priority"] = analysis["priority"]
+            group["diagnosis"] = analysis["diagnosis"]
+            group["recommendations"] = analysis["recommendations"][:3]
+
+    groups = sorted(
+        grouped.values(),
+        key=lambda item: (
+            PRIORITY_ORDER[item["priority"]],
+            item["count"],
+            item["latest_arrival"] or datetime.min,
+        ),
+        reverse=True,
+    )
+    for group in groups:
+        if group["latest_arrival"] is not None:
+            group["latest_arrival"] = group["latest_arrival"].isoformat()
+
+    samples = sorted(
+        analyses,
+        key=lambda item: (PRIORITY_ORDER[item["priority"]], item["id"] or 0),
+        reverse=True,
+    )
+    return {
+        "total": len(reports),
+        "priority_counts": dict(priority_counts),
+        "failure_counts": dict(failure_counts),
+        "result_counts": dict(result_counts),
+        "groups": groups,
+        "samples": samples,
+    }

backend/app/templates/forensic_report_detail.html

@@ -61,6 +61,42 @@
                 {% endcall %}
             </div>
 
+            {% call card() %}
+                {% call card_header() %}
+                    <div class="flex flex-col gap-2 md:flex-row md:items-start md:justify-between">
+                        <div>
+                            {% call card_title() %}Failure Sample Analysis{% endcall %}
+                            {% call card_description() %}Privacy-preserving diagnosis from the redacted failure sample{% endcall %}
+                        </div>
+                        <span class="badge uppercase" :class="priorityClass(report.analysis?.priority)" x-text="report.analysis?.priority || 'unknown'"></span>
+                    </div>
+                {% endcall %}
+                {% call card_content() %}
+                    <div class="space-y-4">
+                        <p class="font-medium" x-text="report.analysis?.diagnosis || 'No analysis is available for this sample.'"></p>
+                        <div class="grid grid-cols-1 lg:grid-cols-2 gap-4">
+                            <div>
+                                <p class="text-sm font-semibold mb-2">Recommended Actions</p>
+                                <ul class="text-sm space-y-1 list-disc pl-4">
+                                    <template x-for="action in report.analysis?.recommendations || []" :key="action">
+                                        <li x-text="action"></li>
+                                    </template>
+                                </ul>
+                            </div>
+                            <div>
+                                <p class="text-sm font-semibold mb-2">Signals</p>
+                                <ul class="text-sm space-y-1 list-disc pl-4">
+                                    <template x-for="signal in report.analysis?.signals || []" :key="signal">
+                                        <li x-text="signal"></li>
+                                    </template>
+                                </ul>
+                            </div>
+                        </div>
+                        <p class="text-xs text-base-content/60" x-text="report.analysis?.privacy_note"></p>
+                    </div>
+                {% endcall %}
+            {% endcall %}
+
             {% call card() %}
                 {% call card_header() %}
                     {% call card_title() %}Message Identity{% endcall %}
@@ -160,6 +196,11 @@ function forensicReportDetailApp(reportId) {
         labelize(value) {
             return String(value || '').replaceAll('_', ' ').replace(/\b\w/g, (char) => char.toUpperCase());
         },
+        priorityClass(priority) {
+            if (priority === 'high') return 'badge-error';
+            if (priority === 'medium') return 'badge-warning';
+            return 'badge-ghost';
+        },
     };
 }
 </script>

backend/app/templates/forensic_reports.html

@@ -101,6 +101,49 @@
         {% endcall %}
     </div>
 
+    {% call card() %}
+        {% call card_header() %}
+            <div class="flex flex-col gap-2 md:flex-row md:items-start md:justify-between">
+                <div>
+                    {% call card_title() %}Sample Analysis{% endcall %}
+                    {% call card_description() %}Grouped investigation hints from redacted forensic metadata{% endcall %}
+                </div>
+                <div class="flex gap-2">
+                    <span class="badge badge-error badge-outline">High <span x-text="analysis.priority_counts?.high || 0"></span></span>
+                    <span class="badge badge-warning badge-outline">Medium <span x-text="analysis.priority_counts?.medium || 0"></span></span>
+                </div>
+            </div>
+        {% endcall %}
+        {% call card_content() %}
+            <template x-if="analysis.groups.length === 0">
+                <p class="text-base-content/60">No failure samples are available for analysis.</p>
+            </template>
+            <div class="grid grid-cols-1 lg:grid-cols-3 gap-4" x-show="analysis.groups.length > 0">
+                <template x-for="group in analysis.groups.slice(0, 3)" :key="group.key">
+                    <div class="border border-base-300 rounded-md p-4 space-y-3">
+                        <div class="flex items-start justify-between gap-3">
+                            <div class="min-w-0">
+                                <p class="font-semibold break-words" x-text="group.domain"></p>
+                                <p class="text-sm font-mono text-base-content/70" x-text="group.source_ip"></p>
+                            </div>
+                            <span class="badge uppercase" :class="priorityClass(group.priority)" x-text="group.priority"></span>
+                        </div>
+                        <p class="text-sm" x-text="group.diagnosis"></p>
+                        <ul class="text-sm space-y-1 list-disc pl-4">
+                            <template x-for="action in group.recommendations.slice(0, 2)" :key="action">
+                                <li x-text="action"></li>
+                            </template>
+                        </ul>
+                        <div class="flex items-center justify-between text-xs text-base-content/60">
+                            <span><span x-text="group.count"></span> samples</span>
+                            <span class="uppercase" x-text="group.auth_failure"></span>
+                        </div>
+                    </div>
+                </template>
+            </div>
+        {% endcall %}
+    {% endcall %}
+
     {% call card() %}
         {% call card_header() %}
             <div class="flex items-center justify-between gap-4">
@@ -173,6 +216,7 @@ function forensicReportsApp() {
         uploadError: false,
         selectedFile: null,
         reports: [],
+        analysis: { groups: [], priority_counts: {}, failure_counts: {}, result_counts: {}, samples: [] },
         domainOptions: [],
         total: 0,
         filters: {
@@ -220,6 +264,7 @@ function forensicReportsApp() {
                 const data = await response.json();
                 this.reports = data.reports || [];
                 this.total = data.total || 0;
+                await this.fetchAnalysis(params);
                 if (!this.filters.domain) {
                     this.domainOptions = [...new Set(this.reports.map((report) => report.domain || report.reported_domain).filter(Boolean))].sort();
                 }
@@ -229,6 +274,11 @@ function forensicReportsApp() {
                 this.loading = false;
             }
         },
+        async fetchAnalysis(params) {
+            const response = await fetch(`/api/v1/forensics/analysis?${params.toString()}`);
+            if (!response.ok) throw new Error('Unable to analyze forensic reports');
+            this.analysis = await response.json();
+        },
         async uploadReport() {
             if (!this.selectedFile) return;
             this.uploading = true;
@@ -262,6 +312,11 @@ function forensicReportsApp() {
             const date = new Date(value);
             return Number.isNaN(date.getTime()) ? value : date.toLocaleString();
         },
+        priorityClass(priority) {
+            if (priority === 'high') return 'badge-error';
+            if (priority === 'medium') return 'badge-warning';
+            return 'badge-ghost';
+        },
     };
 }
 </script>

backend/app/tests/test_forensics_api.py

@@ -90,6 +90,54 @@ def test_list_forensic_reports_filters_failure_fields(authed_client, db_session)
     assert data["reports"][0]["report_id"] == "ruf-spf-filter-test"
 
 
+def test_forensic_analysis_groups_failure_samples(authed_client, db_session):
+    dkim = ForensicParser.parse_bytes(SAMPLE_FORENSIC_EMAIL)
+    spf = dict(dkim)
+    spf.update(
+        {
+            "report_id": "ruf-spf-analysis-test",
+            "reported_domain": "example.com",
+            "source_ip": "198.51.100.23",
+            "auth_failure": "spf",
+            "delivery_result": "quarantine",
+            "authentication_results": (
+                "mx.example.net; dkim=pass header.d=example.com; "
+                "spf=fail smtp.mailfrom=example.com; dmarc=fail"
+            ),
+        }
+    )
+    save_forensic_report(db_session, dkim)
+    save_forensic_report(db_session, spf)
+    db_session.commit()
+
+    response = authed_client.get("/api/v1/forensics/analysis?domain=example.com")
+
+    assert response.status_code == 200
+    data = response.json()
+    assert data["total"] == 2
+    assert data["priority_counts"]["high"] == 2
+    assert data["failure_counts"]["dkim"] == 1
+    assert data["failure_counts"]["spf"] == 1
+    assert data["groups"][0]["priority"] == "high"
+    assert "redacted headers and metadata only" in data["samples"][0]["privacy_note"]
+    assert any("SPF" in action for action in data["samples"][0]["recommendations"])
+
+
+def test_forensic_report_responses_include_sample_analysis(authed_client):
+    authed_client.post(
+        "/api/v1/forensics/upload",
+        files={"file": ("report.eml", SAMPLE_FORENSIC_EMAIL, "message/rfc822")},
+    )
+
+    list_response = authed_client.get("/api/v1/forensics")
+
+    assert list_response.status_code == 200
+    item = list_response.json()["reports"][0]
+    assert item["analysis"]["priority"] == "high"
+    assert "DKIM" in item["analysis"]["diagnosis"]
+    assert item["original_subject"] not in item["analysis"]["signals"]
+
+
 def test_forensic_api_applies_configured_redaction_policy(authed_client, db_session):
     authed_client.post(
         "/api/v1/forensics/upload",
@@ -216,6 +264,7 @@ def test_forensic_html_pages_render():
     assert "Authentication Failures" in list_response.text
     assert detail_response.status_code == 200
     assert "Forensic Investigation" in detail_response.text
+    assert "Failure Sample Analysis" in detail_response.text
 
 
 def test_save_forensic_report_duplicate_and_invalid_domain_paths(db_session):

docs/milestones.md

@@ -175,9 +175,7 @@ Delivered:
 - Keep forensic reports out of aggregate report statistics and ReportStore rollups.
 - Expose authenticated forensic upload/list/detail APIs.
 - Provide dedicated forensic report list/detail views for authentication failure investigation.
-
-Planned:
-- Add richer failure investigation workflows.
+- Add privacy-preserving failure sample analysis with grouped causes, priorities, signals, and recommended actions.
 
 Exit criteria:
 - A security analyst can inspect individual failure reports without mixing them into aggregate statistics.