external/anthropic-cybersecurity-skills/skills/implementing-end-to-end-encryption-for-messaging/SKILL.md
Implements a simplified Signal Protocol-style end-to-end encryption scheme for messaging, covering key exchange, forward secrecy, and the core cryptographic components so no server or intermediary can decrypt messages. Use when designing or building E2EE messaging, or evaluating forward-secrecy and key-management tradeoffs for a messaging system.
npx skillsauth add seikaikyo/dash-skills implementing-end-to-end-encryption-for-messagingInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
3 of 9 scanners reported clean
Some scanners were skipped, did not run, or reported a non-clean status. Review each row below.
End-to-end encryption (E2EE) ensures that only the communicating parties can read messages, with no intermediary (including the server) able to decrypt them. This skill implements a simplified version of the Signal Protocol's Double Ratchet algorithm, using X25519 for key exchange, HKDF for key derivation, and AES-256-GCM for message encryption.
| Component | Purpose | Algorithm | |-----------|---------|-----------| | X3DH | Initial key agreement | X25519 | | Double Ratchet | Ongoing key management | X25519 + HKDF + AES-GCM | | Sending Chain | Per-message encryption keys | HMAC-SHA256 chain | | Receiving Chain | Per-message decryption keys | HMAC-SHA256 chain | | Root Chain | Derives new chain keys on DH ratchet | HKDF |
Each message uses a unique encryption key derived from a ratcheting chain. After a key is used, it is deleted, ensuring that compromise of the current state does not reveal previously sent/received messages.
tools
Conduct comprehensive GDPR compliance assessments by evaluating data processing activities against EU Regulation 2016/679, including Article 30 records of processing, lawful basis validation, data subject rights implementation, Data Protection Impact Assessments (DPIAs) under Article 35, breach notification procedures, international transfer safeguards (SCCs, adequacy decisions), and technical/organizational measures under Article 32. Use when processing personal data of EU residents, preparing for supervisory authority audits, implementing privacy-by-design for new systems, scoping compliance gaps for M&A due diligence, assessing third-party processors, or responding to data subject access requests at scale. Incorporates 2026 guidance from ICO, EDPB, and post-Data (Use and Access) Act 2025 UK-GDPR considerations. Do not use for implementing specific Article 32 controls — use implementing-gdpr-data-protection-controls; or for DSAR automation — use implementing-gdpr-data-subject-access-request.
tools
Parse Windows forensic artifacts—$MFT/$J (MFTECmd), Prefetch (PECmd), registry hives (RECmd), shellbags, and Amcache—into normalized CSV/JSON with Eric Zimmerman's EZ Tools, then load results into Timeline Explorer for analysis. Use during DFIR/incident-response investigations, after triage collection (e.g. with KAPE), to establish program execution, file/folder access, and persistence evidence from acquired forensic images.
development
Build automated multi-turn adversarial attacks against conversational LLM targets using Microsoft PyRIT's RedTeamingOrchestrator, CrescendoOrchestrator (gradual escalation), and TreeOfAttacksWithPruningOrchestrator (adaptive branching), with scorer feedback loops and persisted conversation memory. Use when single-shot LLM scanning is insufficient and you need multi-turn, scorer-driven AI red-team campaigns against a chatbot or agent.
testing
Stand up MISP, enable and cache curated threat feeds (CIRCL, abuse.ch, Feodo Tracker), apply warninglists to suppress false positives, query indicators with PyMISP, and export attributes as auto-generated Suricata/Sigma/Wazuh detection rules. Use when maturing a MISP instance to actively drive detection, curating threat feeds with quality controls, or automating IOC-to-detection pipelines for the SIEM/IDS.