Communitygithub.com

building-malware-incident-communication-template

Build structured communication templates for malware incidents (ransomware,

Was ist building-malware-incident-communication-template?

building-malware-incident-communication-template is a Claude Code agent skill that build structured communication templates for malware incidents (ransomware,.

Funktioniert mit~Claude Code~Codex CLI~Cursor
npx skills add https://github.com/mukul975/Anthropic-Cybersecurity-Skills/tree/main/skills/building-malware-incident-communication-template

In Ihrer bevorzugten KI fragen

Öffnet einen neuen Chat, in dem dieser Agent-Skill bereits geladen ist.

Dokumentation

Building Malware Incident Communication Template

Overview

Effective communication during malware incidents is critical for coordinated response, stakeholder management, and regulatory compliance. A structured communication framework ensures the right people receive appropriate information at the right time, preventing panic while maintaining transparency. Communication templates should cover internal escalation, executive briefings, technical advisories for IT teams, customer notifications, regulatory disclosures, and media statements. The framework must account for different malware types (ransomware, wiper, trojan, worm) and severity levels that drive escalation speed and audience.

When to Use

  • When deploying or configuring building malware incident communication template capabilities in your environment
  • When establishing security controls aligned to compliance requirements
  • When building or improving security architecture for this domain
  • When conducting security assessments that require this implementation

Prerequisites

  • Familiarity with incident response concepts and tools
  • Access to a test or lab environment for safe execution
  • Python 3.8+ with required dependencies installed
  • Appropriate authorization for any testing activities

Communication Framework

Severity Classification

SeverityDescriptionNotification TimelineAudience
P1 - CriticalRansomware, wiper, or widespread infection affecting business operationsWithin 15 minutesCISO, CEO, Legal, Board (if applicable)
P2 - HighTargeted malware on critical systems, data exfiltration suspectedWithin 1 hourCISO, IT Director, Legal
P3 - MediumContained malware infection, limited spreadWithin 4 hoursSecurity Manager, IT Director
P4 - LowSingle endpoint infection, quickly containedWithin 24 hoursSecurity Team Lead

Communication Channels

ChannelUse CaseSecurity Level
Out-of-band phone callsInitial critical notificationsHighest
Encrypted messaging (Signal)Real-time IR team coordinationHigh
Secure email (encrypted)Formal notifications, documentationHigh
War room (physical/virtual)Ongoing incident coordinationMedium
Incident ticketing systemStatus tracking and documentationMedium
Company intranetBroad employee communicationStandard

Template 1: Initial Incident Notification (Internal)

SUBJECT: [SEVERITY] Malware Incident - Initial Notification - [DATE/TIME UTC]

CLASSIFICATION: CONFIDENTIAL - IR TEAM ONLY

INCIDENT ID: IR-[YEAR]-[NUMBER]
DETECTION TIME: [YYYY-MM-DD HH:MM UTC]
NOTIFICATION TIME: [YYYY-MM-DD HH:MM UTC]
SEVERITY: [P1/P2/P3/P4]

SUMMARY:
A malware incident has been detected affecting [NUMBER] systems in
[DEPARTMENT/LOCATION]. The malware has been identified as [TYPE] with
[KNOWN/UNKNOWN] characteristics.

CURRENT IMPACT:
- Systems affected: [COUNT and DESCRIPTION]
- Business functions impacted: [LIST]
- Data at risk: [DESCRIPTION]
- Current spread status: [CONTAINED/SPREADING/UNKNOWN]

IMMEDIATE ACTIONS TAKEN:
1. [ACTION - e.g., Affected endpoints isolated from network]
2. [ACTION - e.g., EDR containment policies activated]
3. [ACTION - e.g., Security team mobilized]

NEXT STEPS:
1. [PLANNED ACTION with TIMELINE]
2. [PLANNED ACTION with TIMELINE]

INCIDENT COMMANDER: [NAME]
CONTACT: [PHONE/ENCRYPTED CHANNEL]

NEXT UPDATE: [TIME] or sooner if situation changes

---
Do not forward this notification outside the IR team.

Template 2: Executive Briefing

SUBJECT: Executive Briefing - Malware Incident IR-[YEAR]-[NUMBER]

FOR: [CEO / CISO / CIO / Board]
FROM: [Incident Commander]
DATE: [DATE]
UPDATE: [#]

SITUATION SUMMARY:
[2-3 sentences describing the incident in business terms]

BUSINESS IMPACT:
- Revenue impact: [ESTIMATED/NONE/UNDER ASSESSMENT]
- Operational impact: [DESCRIPTION]
- Customer impact: [DESCRIPTION]
- Regulatory implications: [DESCRIPTION]

CURRENT STATUS: [DETECTED / CONTAINED / ERADICATING / RECOVERING]

KEY DECISIONS NEEDED:
1. [DECISION with context and recommendation]
2. [DECISION with context and recommendation]

TIMELINE:
- [TIME]: Incident detected
- [TIME]: Containment initiated
- [TIME]: [MILESTONE]
- [TIME]: Estimated recovery (if known)

EXTERNAL COMMUNICATION STATUS:
- Regulatory notification: [REQUIRED/SUBMITTED/NOT REQUIRED]
- Customer notification: [REQUIRED/PLANNED/NOT REQUIRED]
- Law enforcement: [ENGAGED/PLANNED/NOT APPLICABLE]

RESOURCE REQUIREMENTS:
- [RESOURCE NEED - e.g., External IR firm engagement]
- [RESOURCE NEED - e.g., Additional hardware for rebuild]

NEXT UPDATE: [TIME]

Template 3: Technical Advisory for IT Teams

SUBJECT: TECHNICAL ADVISORY - [MALWARE NAME] - Immediate Action Required

SEVERITY: [CRITICAL/HIGH/MEDIUM]
DATE: [DATE/TIME UTC]
ADVISORY ID: TA-[YEAR]-[NUMBER]

THREAT DESCRIPTION:
[Technical description of the malware, behavior, and indicators]

AFFECTED SYSTEMS:
- Operating Systems: [LIST]
- Applications: [LIST]
- Network segments: [LIST]

INDICATORS OF COMPROMISE (IOCs):
File Hashes:
  MD5: [HASH]
  SHA256: [HASH]

File Names:
  [FILENAME]

Network Indicators:
  C2 Domains: [DOMAIN]
  C2 IPs: [IP ADDRESS]
  User-Agent: [STRING]

Registry Keys:
  [REGISTRY PATH]

DETECTION METHODS:
- EDR: [DETECTION RULE/SIGNATURE]
- SIEM: [CORRELATION RULE]
- Network: [IDS/IPS SIGNATURE]

REQUIRED ACTIONS:
Priority 1 (Immediate):
  [ ] Block IOCs at firewall/proxy
  [ ] Push EDR containment rules
  [ ] Scan all endpoints for IOCs

Priority 2 (Within 4 hours):
  [ ] Apply patches [KB/CVE NUMBER]
  [ ] Update antivirus signatures
  [ ] Review logs for historical indicators

Priority 3 (Within 24 hours):
  [ ] Conduct enterprise-wide hunt
  [ ] Validate backup integrity
  [ ] Update detection rules

CONTACT: SOC - [PHONE] | Security Engineering - [PHONE]

Template 4: Regulatory Notification

[ORGANIZATION LETTERHEAD]

[REGULATORY BODY]
[ADDRESS]

Date: [DATE]

RE: Data Security Incident Notification - [REFERENCE NUMBER]

Dear [TITLE/NAME],

Pursuant to [REGULATION - e.g., GDPR Article 33, State Breach Notification Law],
[ORGANIZATION] is providing notification of a data security incident.

INCIDENT SUMMARY:
On [DATE], [ORGANIZATION] detected a malware incident affecting systems containing
[TYPE OF DATA]. The incident was detected through [DETECTION METHOD].

DATA POTENTIALLY AFFECTED:
- Types of data: [PERSONAL DATA, FINANCIAL, HEALTH, etc.]
- Number of individuals: [COUNT or ESTIMATE]
- Categories of individuals: [CUSTOMERS, EMPLOYEES, etc.]

TIMELINE:
- [DATE]: Incident occurred (estimated)
- [DATE]: Incident detected
- [DATE]: Containment achieved
- [DATE]: This notification

MEASURES TAKEN:
1. [CONTAINMENT ACTION]
2. [INVESTIGATION ACTION]
3. [REMEDIATION ACTION]

MEASURES TO MITIGATE ADVERSE EFFECTS:
1. [MITIGATION - e.g., Credit monitoring offered]
2. [MITIGATION - e.g., Password resets enforced]

CONTACT INFORMATION:
[DPO/PRIVACY OFFICER NAME]
[TITLE]
[EMAIL]
[PHONE]

Respectfully,
[SIGNATORY]
[TITLE]

Template 5: Customer/Public Notification

SUBJECT: Important Security Notice from [ORGANIZATION]

Dear [CUSTOMER/USER],

We are writing to inform you of a security incident that may have affected
your information.

WHAT HAPPENED:
On [DATE], we detected unauthorized activity on our systems involving
malicious software. We immediately activated our incident response procedures
and engaged leading cybersecurity experts to investigate.

WHAT INFORMATION WAS INVOLVED:
Based on our investigation, the following types of information may have
been affected: [LIST - e.g., names, email addresses, etc.]

WHAT WE ARE DOING:
- We have contained the incident and removed the malicious software
- We have engaged [FORENSIC FIRM] to conduct a thorough investigation
- We have enhanced our security controls to prevent similar incidents
- We have notified relevant regulatory authorities

WHAT YOU CAN DO:
- Change your password for your [ORGANIZATION] account
- Enable multi-factor authentication if not already active
- Monitor your accounts for unusual activity
- [Additional specific recommendations]

ADDITIONAL RESOURCES:
- [DEDICATED SUPPORT LINE]
- [FAQ PAGE URL]
- [CREDIT MONITORING ENROLLMENT - if applicable]

We sincerely apologize for any concern this may cause and remain committed
to protecting your information.

[SIGNATORY]
[TITLE]

Communication Workflow

Escalation Matrix

Malware Detected
  |
  v
[Classify Severity: P1/P2/P3/P4]
  |
  |-- P1: Notify within 15 min
  |     |-- Incident Commander
  |     |-- CISO (phone call)
  |     |-- CEO (phone call)
  |     |-- Legal Counsel
  |     |-- External IR firm
  |     |-- Law enforcement (if applicable)
  |
  |-- P2: Notify within 1 hour
  |     |-- CISO
  |     |-- IT Director
  |     |-- Legal Counsel
  |
  |-- P3: Notify within 4 hours
  |     |-- Security Manager
  |     |-- IT Director
  |
  |-- P4: Notify within 24 hours
        |-- Security Team Lead

References

  • NIST SP 800-61 Rev 2: Incident Communication Guidelines
  • GDPR Article 33: Data Breach Notification Requirements
  • SANS Incident Handler's Handbook: Communication Best Practices
  • CISA Incident Reporting Guidelines

Individual skills in this repo

This repo contains 20 individual skills — each has its own dedicated page.

abusing-dpapi-for-credential-access

Extract and decrypt Windows DPAPI-protected secrets (Credential Manager, browser logins/cookies, Wi-Fi credentials, KeePass keys) online or offline using SharpDPAPI, SharpChrome, Mimikatz, or Impacket

abusing-shadow-credentials-for-privesc

Take over Active Directory accounts by writing attacker-controlled public keys to msDS-KeyCredentialLink (Shadow Credentials) with pyWhisker, Whisker, or Certipy, then authenticate via PKINIT to recover the target

achieving-cmmc-level-2-compliance

>-

acquiring-disk-image-with-dd-and-dcfldd

Create forensically sound bit-for-bit disk images with dd or dcfldd on a Linux forensic workstation, preserving evidence integrity through hash verification (MD5/SHA) during acquisition. Use when imaging a suspect drive, USB device, or memory card for investigation, preserving volatile disk evidence during incident response, or producing a verified copy for legal or law-enforcement proceedings before any destructive analysis.

analyzing-active-directory-acl-abuse

Detect dangerous ACL misconfigurations in Active Directory using ldap3

analyzing-android-malware-with-apktool

Perform static analysis of Android APK malware using apktool for resource decompilation, jadx for Java source recovery, and androguard for manifest inspection, dangerous permission-combination detection, and identification of obfuscated code, dynamic code loading, and reflection-based API calls. Use to statically triage a suspicious APK without executing it or to build mobile malware detection rules.

analyzing-api-gateway-access-logs

Parses API Gateway access logs (AWS API Gateway, Kong, Nginx) to detect

analyzing-apt-group-with-mitre-navigator

Query ATT&CK data with attackcti, mitreattack-python, and stix2, then build MITRE ATT&CK Navigator layers and multi-layer heatmap overlays mapping one or more APT groups

analyzing-azure-activity-logs-for-threats

Queries Azure Monitor activity logs and sign-in logs via azure-monitor-query

analyzing-bootkit-and-rootkit-samples

Analyzes bootkit and advanced rootkit malware infecting the Master

analyzing-browser-forensics-with-hindsight

Parse Chromium-based browser databases with Hindsight to extract and correlate browsing history, downloads, cookies, cached content, autofill data, saved passwords, and extensions from Chrome, Edge, Brave, Opera, and Vivaldi into a unified timeline (XLSX, JSON, or SQLite output). Use during incident response, insider-threat investigations, or criminal cases when you need to reconstruct a user

analyzing-campaign-attribution-evidence

Systematically evaluate cyber-campaign evidence to attribute an operation to a threat actor, using the Diamond Model and Analysis of Competing Hypotheses (ACH) to weigh infrastructure overlaps, TTP consistency, malware code similarity, and timing/language artifacts into confidence-weighted attribution assessments. Use when an incident investigation needs a defensible attribution confidence level.

analyzing-certificate-transparency-for-phishing

Monitor Certificate Transparency logs using crt.sh and Certstream to

analyzing-cloud-storage-access-patterns

Detect abnormal access in AWS S3, GCS, and Azure Blob Storage by analyzing CloudTrail Data Events, GCS audit logs, and Azure Storage Analytics for after-hours bulk downloads, new-IP access, and API-call spikes (e.g. GetObject) via statistical baselines and time-series anomaly detection. Use when investigating suspected cloud data exfiltration or building related detection rules.

analyzing-cobalt-strike-beacon-configuration

Extract and analyze Cobalt Strike beacon configuration from PE files

analyzing-cobaltstrike-malleable-c2-profiles

Parse and analyze Cobalt Strike Malleable C2 profiles with dissect.cobaltstrike (profiles and beacon-payload configs) and pyMalleableC2 (AST parsing) to extract HTTP/DNS transforms, URIs, headers, sleep/jitter, and injection behavior, then generate network detection signatures. Use when reverse-engineering a captured malleable profile or building detections against Cobalt Strike Beacon traffic.

analyzing-command-and-control-communication

Analyzes malware C2 communication over HTTP, HTTPS, DNS, and custom

analyzing-cyber-kill-chain

Analyzes intrusion activity against the Lockheed Martin Cyber Kill Chain

analyzing-disk-image-with-autopsy

Perform comprehensive forensic analysis of raw (dd), E01, or AFF disk images with Autopsy and The Sleuth Kit, recovering deleted files, examining metadata and embedded artifacts, keyword searching, and building investigation timelines with visual reports. Use for structured analysis of a forensic disk image or when stakeholders need visual reports from evidence.

analyzing-dns-logs-for-exfiltration

Analyzes DNS query logs to detect data exfiltration via DNS tunneling,

Verwandte Skills