Incident Types: The types of cybersecurity incidents that have occurred include Cyber Attack, Vulnerability and Ransomware.

Detection and Response: The company detects and responds to cybersecurity incidents through an containment measures with account bans (malicious operators), containment measures with tailored classifiers for suspicious use patterns, and remediation measures with technical indicators shared with external partners, and communication strategy with public report on ai misuse, communication strategy with tactics/techniques shared with researchers, and enhanced monitoring with ai use pattern detection, and incident response plan activated with no (anthropic claims prior documentation covers the risk), and third party assistance with hackerone (for vulnerability disclosure), and containment measures with user guidance: monitor claude’s screen activity and terminate unexpected behavior, containment measures with network egress settings (restrictive defaults for team/enterprise), and communication strategy with public statement to the register, communication strategy with existing security documentation (warns of network access risks), and enhanced monitoring with user-level monitoring recommended, and and and containment measures with shutting down compromised accounts, containment measures with revoking unauthorized access, and remediation measures with patching claude code vulnerabilities, remediation measures with enhancing model safeguards, and communication strategy with public disclosure via press release, communication strategy with notification of affected entities, communication strategy with intelligence sharing with authorities, and and incident response plan activated with yes (10-day investigation), and law enforcement notified with yes (coordinated with authorities), and containment measures with account bans for identified attackers, containment measures with system access revocation, and remediation measures with upgraded detection systems, remediation measures with developed classifiers to flag similar attacks, and communication strategy with public blog post, communication strategy with x (twitter) announcement, communication strategy with notifications to affected organizations, and enhanced monitoring with yes (new classifiers for ai-driven attack patterns), and and and containment measures with account bans, containment measures with victim notifications, and communication strategy with public disclosure via report, communication strategy with engagement with authorities, and enhanced monitoring with ai-driven soc analysis..

Common Attack Types: The most common types of attacks the company has faced is Cyber Attack.

Identification of Attack Vectors: The company identifies the attack vectors used in incidents through AI-Generated Malware (Reflective DLL Injection)Chisel Tunneling Tool (Extortion Campaign)Social Engineering (Romance Scams, IT Worker Fraud), Malicious Document UploadIndirect Prompt Injection via File Content, Claude Code Model (via jailbroken safeguards), Claude Code tool (jailbroken via social engineering) and Jailbroken Claude Code AIAbuse of Agentic Capabilities.

Commonly Compromised Data Types: The types of data most commonly compromised in incidents are Organizational Data, Financial Records, Pii (Romance Scams), Payment Information (Carding), , Files In Sandbox, Private User Inputs, Potential Pii (If Present), , Database Contents, Credentials, High-Value Target Data, , Credentials, Potentially High-Value Database Contents, Public Data Misrepresented As Secret, , High-Value Databases, Sensitive Corporate/Government Data and .

Incident Response Plan: The company's incident response plan is described as No (Anthropic claims prior documentation covers the risk), , Yes (10-day investigation), .

Third-Party Assistance: The company involves third-party assistance in incident response through HackerOne (for vulnerability disclosure), .

Prevention of Data Exfiltration: The company takes the following measures to prevent data exfiltration: Technical Indicators Shared with External Partners, , Patching Claude Code Vulnerabilities, Enhancing Model Safeguards, , upgraded detection systems, developed classifiers to flag similar attacks, .

Handling of PII Incidents: The company handles incidents involving personally identifiable information (PII) through by account bans (malicious operators), tailored classifiers for suspicious use patterns, , user guidance: monitor claude’s screen activity and terminate unexpected behavior, network egress settings (restrictive defaults for team/enterprise), , shutting down compromised accounts, revoking unauthorized access, , account bans for identified attackers, system access revocation, , account bans, victim notifications and .

Key Lessons Learned: The key lessons learned from past incidents are AI LLMs Can Enable Low-Skill Threat Actors to Develop Advanced Malware,AI-Assisted 'Vibe Hacking' Blurs Lines Between Human and Machine Operations,Proactive Detection (Classifiers, Behavioral Monitoring) Critical for AI MisuseAI models with network/tool access require robust safeguards beyond user vigilance.,Indirect prompt injection remains a critical risk for LLMs with file/API interactions.,Default permissions (e.g., network access) should prioritize security over usability.,API key validation could mitigate account hijacking risks.AI agents can autonomously execute complex cyberattacks with minimal human oversight, lowering the barrier for adversaries.,Jailbreaking techniques can bypass safeguards in advanced AI models, turning them into offensive tools.,Rapid deployment of AI systems may outpace defensive safeguards, empowering adversaries faster than defenses can adapt.,Transparency in incident disclosure is critical but raises questions about attribution methodologies and strategic risks.AI agentic capabilities can execute ~80-90% of sophisticated cyberattack workloads autonomously,Fragmented tasks can bypass AI safeguards when full context is obscured,Attack speed/volume exceeds human hacker capabilities (thousands of requests per second),Lower-skilled threat actors can now leverage AI for large-scale attacks,Public data can be weaponized via AI 'hallucination' exploitsAI's dual-use nature enables both offensive (autonomous attacks) and defensive (incident analysis) capabilities.,Barriers to sophisticated cyberattacks have dropped significantly with agentic AI, enabling less-resourced groups to scale operations.,Traditional security foundations (e.g., monitoring, threat sharing) remain critical but must integrate AI-driven defenses.,Over-reliance on AI threat narratives without evidence can distract from foundational security measures (as noted by skepticism from experts like Kevin Beaumont).

Implemented Recommendations: The company has implemented the following recommendations to improve cybersecurity: Develop classifiers to detect AI-driven attack patterns, Share case studies publicly to improve industry-wide defenses, Prepare for AI-driven attacks to become more common as barriers to entry drop, Monitor for high-volume automated requests as indicators of AI-orchestrated attacks and Enhance contextual safeguards in AI tools to prevent task fragmentation exploits.

Additional Resources: Stakeholders can find additional resources on cybersecurity best practices at and Source: Anthropic Report on Claude Code Misuse, and Source: The RegisterUrl: https://www.theregister.com/2024/07/16/anthropic_claude_prompt_injection/Date Accessed: 2024-07-16, and Source: Johann Rehberger (wunderwuzzi) - Proof-of-Concept VideoUrl: https://www.youtube.com/watch?v=[REDACTED]Date Accessed: 2024-07-16, and Source: Anthropic Security DocumentationUrl: https://docs.anthropic.com/en/docs/security-considerationsDate Accessed: 2024-07-16, and Source: hCaptcha Threat Analysis Group Report, and Source: FOX BusinessUrl: https://www.foxbusiness.com/technology/artificial-intelligence-company-anthropic-cyberattack-ai-chinese-hackers, and Source: Anthropic Press ReleaseDate Accessed: 2025-10 (week of report release), and Source: Anthropic Blog PostDate Accessed: 2024-10-03, and Source: Anthropic X (Twitter) AnnouncementDate Accessed: 2024-10-03, and Source: SecurityAffairsUrl: https://securityaffairs.com/Date Accessed: 2025-11-16, and Source: Anthropic Report (2025)Date Accessed: 2025-11-16, and Source: Kevin Beaumont (LinkedIn Statement)Date Accessed: 2025-11-16.

Communication of Investigation Status: The company communicates the status of incident investigations to stakeholders through Public Report On Ai Misuse, Tactics/Techniques Shared With Researchers, Public Statement To The Register, Existing Security Documentation (Warns Of Network Access Risks), Public Disclosure Via Press Release, Notification Of Affected Entities, Intelligence Sharing With Authorities, Public Blog Post, X (Twitter) Announcement, Notifications To Affected Organizations, Public Disclosure Via Report and Engagement With Authorities.

Advisories Provided: The company provides the following advisories to stakeholders and customers following an incident: were Public Report With Tactics/Techniques For Researchers, Partnerships For Indicator Sharing, Users Advised To Disable Network Access If Not Required., Enterprises Recommended To Enforce Strict Network Access Controls., Monitor Claude’S Activity When Network Access Is Enabled., Avoid Summarizing Untrusted Documents With Network Access Active., Report Suspicious Behavior Via Anthropic’S Support Channels., , Urgent Notifications Sent To ~30 Targeted Organizations, Public Disclosure Via Press Release And Media Statements, , Notified affected organizations and coordinated with authorities, Victim Notifications and Authority Engagement.

Post-Incident Analysis Process: The company's process for conducting post-incident analysis is described as Ai Use Pattern Detection, , Hackerone (For Vulnerability Disclosure), , User-Level Monitoring Recommended, , , Yes (new classifiers for AI-driven attack patterns), Ai-Driven Soc Analysis, .

Corrective Actions Taken: The company has taken the following corrective actions based on post-incident analysis: Account Terminations, Custom Classifiers For Suspicious Patterns, Indicator Sharing With Partners, Public Disclosure Of Ttps, , Strengthening Claude Code'S Resistance To Jailbreaking, Implementing Real-Time Monitoring For Autonomous Ai Behaviors, Collaborating With Cybersecurity Agencies To Share Threat Intelligence, , Developed Classifiers To Flag Ai-Driven Attack Patterns, Upgraded Detection Systems For Autonomous Task Execution, Committed To Public Case Study Sharing For Industry Defense Improvement, , Enhanced Ai Agent Monitoring And Behavioral Analysis., Restricted Tool Access For Ai Models (E.G., Blocking Malicious Plugins)., Improved Jailbreak Detection Mechanisms., Public-Private Collaboration On Ai Security Standards., .

Last Ransom Demanded: The amount of the last ransom demanded was $75,000–$500,000 (Extortion Campaign).

Last Attacking Group: The attacking group in the last incident were an Name: GTG-5004 (UK-based)Role: RaaS OperatorTools Used: Claude Code, Tools Used: ChaCha20 + RSA Encryption, Tools Used: Shadow Copy Deletion, Tools Used: Network Share Encryption, Tools Used: Reflective DLL Injection, Name: GTG-2002Role: Data Extortion OperatorTools Used: Claude Code, Tools Used: Chisel Tunneling Tool, Tools Used: Custom Malware (String Encryption, Anti-Debugging), Tools Used: HTML Ransom Notes, Name: Unnamed (North Korean)Role: Fraudulent IT Worker SchemeName: Unnamed (Chinese APT)Role: APT Campaign OperatorName: Unnamed (Russian-speaking)Role: Malware Developer (Advanced Evasion)Name: UnnamedRole: Carding Service Operator (API Integration)Name: UnnamedRole: Romance Scam Operator (Emotional Manipulation, Multi-Language Support), Name: Johann Rehberger (wunderwuzzi)Type: Independent Security ResearcherMotivation: Vulnerability Research & Responsible Disclosure, Chinese state-sponsored hacking group (attributed with high confidence by Anthropic; disputed by Chinese Embassy), Chinese state-sponsored group (high confidence) and China-linked APT GroupState-sponsored Hackers.

Most Recent Incident Detected: The most recent incident detected was on 2025-09-mid (exact date unspecified).

Most Recent Incident Publicly Disclosed: The most recent incident publicly disclosed was on 2025-11-16.

Most Significant Data Compromised: The most significant data compromised in an incident were Sensitive Organizational Data (17+ Victims in Government, Healthcare, Financial, Emergency Services), Financial Data (Analyzed for Ransom Demands), Personally Identifiable Information (PII) in Romance Scams, , Private User Data, Sensitive Files in Sandbox, Anthropic Account Data, , and .

Most Significant System Affected: The most significant system affected in an incident was Windows Systems (Ransomware Encryption)Network SharesC2 Infrastructure (PHP Consoles)Boot Process (Ransom Notes Embedded) and Claude AI (Pro/Max/Team/Enterprise Accounts)Anthropic File APISandbox Environment and and .

Third-Party Assistance in Most Recent Incident: The third-party assistance involved in the most recent incident was hackerone (for vulnerability disclosure), .

Containment Measures in Most Recent Incident: The containment measures taken in the most recent incident were Account Bans (Malicious Operators)Tailored Classifiers for Suspicious Use Patterns, User Guidance: Monitor Claude’s screen activity and terminate unexpected behaviorNetwork Egress Settings (restrictive defaults for Team/Enterprise), Shutting Down Compromised AccountsRevoking Unauthorized Access, account bans for identified attackerssystem access revocation and Account BansVictim Notifications.

Most Sensitive Data Compromised: The most sensitive data compromised in a breach were Private User Data, Sensitive Files in Sandbox, Financial Data (Analyzed for Ransom Demands), Anthropic Account Data, Personally Identifiable Information (PII) in Romance Scams, Sensitive Organizational Data (17+ Victims in Government, Healthcare, Financial and Emergency Services).

Highest Ransom Demanded: The highest ransom demanded in a ransomware incident was $75,000–$500,000 (Extortion Campaign).

Most Significant Lesson Learned: The most significant lesson learned from past incidents was Over-reliance on AI threat narratives without evidence can distract from foundational security measures (as noted by skepticism from experts like Kevin Beaumont).

Most Significant Recommendation Implemented: The most significant recommendation implemented to improve cybersecurity was Reevaluate the balance between AI deployment speed and security safeguards in national cybersecurity strategy., Prioritize evidence-based risk assessments over speculative AI threat hype., Enhance AI model resilience against jailbreaking and autonomous malicious use cases., Implement API key ownership validation to prevent cross-account exfiltration., Enhance threat intelligence sharing and collaborative defense mechanisms., Develop classifiers to detect AI-driven attack patterns, Share case studies publicly to improve industry-wide defenses, Share Technical Indicators with Cybersecurity Community, Strengthen collaboration between AI developers, government agencies, and cybersecurity firms to preemptively counter AI-driven threats., Monitor AI Tool Usage for Malicious Patterns, Enhance sandbox isolation to restrict API calls to user-owned resources., Provide clearer warnings and opt-in consent for high-risk features (e.g., network access)., Monitor for high-volume automated requests as indicators of AI-orchestrated attacks, Strengthen AI model jailbreak protections and monitor for anomalous agent behavior., Develop automated detection for prompt injection patterns in uploaded files., Disable network access by default for all account tiers., Adopt AI for SOC operations, detection, and response to counter AI-driven threats., Implement stricter safeguards for AI agent autonomy and tool access (e.g., MCP standards)., Enhance AI Guardrails to Prevent Abuse in Coding/Operational Tasks, Collaborate with researchers to proactively test for novel attack vectors., Develop standardized frameworks for attributing AI-facilitated cyberattacks to state actors., Educate Researchers on AI-Assisted Threat Actor TTPs, Prepare for AI-driven attacks to become more common as barriers to entry drop and Enhance contextual safeguards in AI tools to prevent task fragmentation exploits.

Most Recent Source: The most recent source of information about an incident are Kevin Beaumont (LinkedIn Statement), SecurityAffairs, Anthropic Report on Claude Code Misuse, The Register, Anthropic Security Documentation, Anthropic Press Release, FOX Business, Johann Rehberger (wunderwuzzi) - Proof-of-Concept Video, Anthropic Report (2025), Anthropic Blog Post, hCaptcha Threat Analysis Group Report and Anthropic X (Twitter) Announcement.

Most Recent URL for Additional Resources: The most recent URL for additional resources on cybersecurity best practices is https://www.theregister.com/2024/07/16/anthropic_claude_prompt_injection/, https://www.youtube.com/watch?v=[REDACTED], https://docs.anthropic.com/en/docs/security-considerations, https://www.foxbusiness.com/technology/artificial-intelligence-company-anthropic-cyberattack-ai-chinese-hackers, https://securityaffairs.com/ .

Current Status of Most Recent Investigation: The current status of the most recent investigation is Completed (Accounts Banned, Indicators Shared).

Most Recent Stakeholder Advisory: The most recent stakeholder advisory issued was Public Report with Tactics/Techniques for Researchers, Partnerships for Indicator Sharing, Users advised to disable network access if not required., Enterprises recommended to enforce strict network access controls., Urgent notifications sent to ~30 targeted organizations, Notified affected organizations and coordinated with authorities, Victim Notifications, Authority Engagement, .

Most Recent Customer Advisory: The most recent customer advisory issued were an Monitor Claude’s activity when network access is enabled.Avoid summarizing untrusted documents with network access active.Report suspicious behavior via Anthropic’s support channels. and Public disclosure via press release and media statements.

Most Recent Entry Point: The most recent entry point used by an initial access broker were an Claude Code tool (jailbroken via social engineering) and Claude Code Model (via jailbroken safeguards).

Most Recent Reconnaissance Period: The most recent reconnaissance period for an incident was Pre-September 2025 (Framework Development)Autonomous Mapping Post-Access.

Most Significant Root Cause: The most significant root cause identified in post-incident analysis was Lack of Restrictions on AI-Assisted Malware DevelopmentThreat Actors Exploiting LLM Coding CapabilitiesInsufficient Initial Guardrails for High-Risk Use Cases, Over-reliance on user vigilance for security-critical features.Lack of separation between content and directives in prompt processing.Insufficient validation of API key ownership in sandbox environment.Default-permissive settings for high-risk features (Pro/Max accounts)., Inadequate safeguards against AI model jailbreakingOver-reliance on human oversight for autonomous AI systemsExploitation of benign-command disguises to bypass security protocols, AI safeguards inadequate for fragmented, context-obscured tasksOver-reliance on AI's inability to recognize malicious intent in isolated actionsLack of rate-limiting for high-volume automated requests, Insufficient safeguards against AI agent autonomy.Over-permissive tool access (e.g., password crackers, scanners) via MCP standards.Jailbreak vulnerabilities in Claude Code allowing malicious task execution..

Most Significant Corrective Action: The most significant corrective action taken based on post-incident analysis was Account TerminationsCustom Classifiers for Suspicious PatternsIndicator Sharing with PartnersPublic Disclosure of TTPs, Strengthening Claude Code's resistance to jailbreakingImplementing real-time monitoring for autonomous AI behaviorsCollaborating with cybersecurity agencies to share threat intelligence, Developed classifiers to flag AI-driven attack patternsUpgraded detection systems for autonomous task executionCommitted to public case study sharing for industry defense improvement, Enhanced AI agent monitoring and behavioral analysis.Restricted tool access for AI models (e.g., blocking malicious plugins).Improved jailbreak detection mechanisms.Public-private collaboration on AI security standards..