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Abnormal Security Cases

Use this skill when working with Abnormal Security abuse mailbox cases - user-reported emails, case triage, remediation actions, case lifecycle, and phishing simulation management. Covers case statuses, judgments, bulk actions, and MSP workflows for managing user-reported suspicious emails. Essential for MSP security analysts triaging abuse mailbox submissions in Abnormal Security.

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Atualizado há 4 meses

Ver no GitHub ↗ Licença: Apache-2.0

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Abnormal Security Abuse Mailbox Cases

Overview

Abnormal Security's Abuse Mailbox automatically processes user-reported suspicious emails. When users forward or report emails to a designated abuse mailbox address, Abnormal analyzes the reported message and creates a case with an AI-generated judgment. This skill covers case lifecycle, triage workflows, remediation actions, and bulk operations.

Case Lifecycle

User Reports Email
       |
       v
  Case Created (status: Open)
       |
       v
  AI Analysis (judgment generated)
       |
       +---> Malicious   ---> Auto-Remediate (if configured)
       |
       +---> Suspicious  ---> Analyst Review Required
       |
       +---> Spam         ---> Auto-Dismiss (if configured)
       |
       +---> Safe         ---> Auto-Dismiss (if configured)
       |
       v
  Analyst Action
       |
       +---> Remediate (quarantine/delete across org)
       |
       +---> Mark Not Spam (release to inbox)
       |
       +---> Dismiss (close case, no action)
       |
       v
  Case Closed (status: Done)

Case Field Reference

Core Fields

| Field | Type | Description | |-------|------|-------------| | caseId | string | Unique case identifier | | severity | string | Severity level of the case | | affectedEmployee | string | Email address of the user who reported | | firstReported | datetime | When the case was first reported |

Judgment Fields

| Field | Type | Description | |-------|------|-------------| | overallStatus | string | Case status: Open, Acknowledged, Done | | judgmentStatus | string | AI judgment: Malicious, Spam, Safe, No Action Needed | | customerVisibleTime | datetime | When the case became visible in portal |

Reported Message Fields

| Field | Type | Description | |-------|------|-------------| | reportedMessage.subject | string | Subject of the reported email | | reportedMessage.senderAddress | string | Sender of the reported email | | reportedMessage.senderName | string | Display name of the sender | | reportedMessage.recipientAddress | string | Recipient of the reported email | | reportedMessage.receivedTime | datetime | When the reported email was received | | reportedMessage.attackType | string | Detected attack type (if malicious) |

Case Judgments

| Judgment | Description | Recommended Action | |----------|-------------|-------------------| | Malicious | Confirmed threat (BEC, phishing, malware) | Remediate across organization | | Spam | Unsolicited bulk email, marketing | Dismiss or move to junk | | Safe | Legitimate email, no threat detected | Dismiss, notify user it is safe | | No Action Needed | Phishing simulation or already remediated | Dismiss |

MCP Tools

| Tool | Description | Key Parameters | |------|-------------|----------------| | abnormal_cases_list | List abuse mailbox cases | pageSize, pageNumber, filter, fromDate, toDate | | abnormal_cases_get | Get detailed case by ID | caseId | | abnormal_cases_actions | Get available actions for a case | caseId | | abnormal_cases_action | Take action on a case | caseId, action |

Tool Usage Examples

List open cases:

{
  "tool": "abnormal_cases_list",
  "parameters": {
    "filter": "overallStatus eq 'Open'",
    "pageSize": 25
  }
}

Get case details:

{
  "tool": "abnormal_cases_get",
  "parameters": {
    "caseId": "12345"
  }
}

Remediate a case:

{
  "tool": "abnormal_cases_action",
  "parameters": {
    "caseId": "12345",
    "action": "REMEDIATE"
  }
}

Triage Workflows

Standard Triage Workflow

  1. List open cases - Get all cases with overallStatus eq 'Open'
  2. Sort by severity - Address critical and high severity first
  3. Review AI judgment:
  4. If Malicious: verify and remediate across organization
  5. If Spam: dismiss or move to junk
  6. If Safe: dismiss and respond to reporter
  7. If No Action Needed: dismiss (likely phishing simulation)
  8. Take action - Remediate, dismiss, or mark not spam
  9. Close case - Case moves to Done status after action

Bulk Triage Workflow

  1. Filter cases by judgment - Start with cases judged as Malicious
  2. Batch remediate - Remediate all confirmed Malicious cases
  3. Review Suspicious - Manually review cases without clear judgment
  4. Auto-dismiss Safe/Spam - Close remaining low-risk cases

Escalation Criteria

Escalate a case when:

  • Multiple users report the same email
  • The reported email impersonates an executive
  • The email contains active malware or ransomware
  • Credentials may have been entered on a phishing page
  • The sender is a known vendor or partner (supply chain risk)

Case Actions

| Action | Description | When to Use | |--------|-------------|-------------| | REMEDIATE | Remove the email from all recipients' inboxes | Confirmed malicious email | | MARK_NOT_SPAM | Release email back to inbox | False positive, legitimate email | | DISMISS | Close case without action | Safe email, phishing simulation, spam |

Error Handling

Common API Errors

| Code | Message | Resolution | |------|---------|------------| | 400 | Invalid filter | Check OData filter syntax | | 401 | Unauthorized | Check API token | | 403 | Insufficient permissions | Token needs abuse mailbox scope | | 404 | Case not found | Verify case ID | | 409 | Case already actioned | Case was already remediated/dismissed | | 429 | Rate limited | Wait and retry |

Best Practices

  1. Triage daily - Review abuse mailbox cases at least once per day
  2. Trust the AI judgment - Abnormal's accuracy is high; use it to prioritize
  3. Remediate org-wide - When a threat is confirmed, remediate for all recipients
  4. Respond to reporters - Let users know their report was reviewed
  5. Track phishing simulation reports - Monitor security awareness training effectiveness
  6. Correlate with threats - Check if reported emails match known threat campaigns
  7. Monitor false positive rate - High FP rates may indicate policy tuning needed

Related Skills

  • [Abnormal Threats](../threats/SKILL.md) - Threat detection and analysis
  • [Abnormal Messages](../messages/SKILL.md) - Message analysis
  • [Abnormal API Patterns](../api-patterns/SKILL.md) - API authentication and usage
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