Investigate compromised Docker containers by analyzing images, layers, volumes, logs, and runtime artifacts to identify malicious activity and evidence.

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.

Analyzes malware C2 communication over HTTP, HTTPS, DNS, and custom protocols to reverse-engineer beacon patterns, command structures, data encoding, and infrastructure (primary servers, fallback domains, dead drops). Use after reverse engineering reveals network traffic needing protocol analysis or when building detection signatures for a framework like Cobalt Strike, Metasploit, or Sliver.

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.

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.

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.

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's web activity from a browser profile.

Analyzes bootkit and advanced rootkit malware infecting the Master Boot Record (MBR), Volume Boot Record (VBR), or UEFI firmware for below-OS persistence, covering boot sector analysis, UEFI module inspection, and anti-rootkit detection. Use when compromise survives OS reinstallation or antivirus/EDR fails to detect malware despite clear infection signs.

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' TTPs for detection-gap analysis. Use to compare threat-actor technique coverage, find gaps in detection engineering, or produce Navigator visualizations for threat-intel reporting.

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.

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.

Comprehensive OSINT methodology for external red-team operations and authorized attack-surface assessments. Covers the 6-stage recon pipeline (seed → asset expansion → enrichment → exposure analysis → convergence → operator-armed active validation) with connector-resilience and stage-vs-gating discipline, asset-graph discipline, severity rubric, confidence upgrade workflows, time budgeting, identity-fabric mapping, breach×identity correlation with per-person identity dossiers, detectability tagging, detection-aware probing, WAF/CDN bypass, vulnerability prioritization, phishing infrastructure planning, bug bounty submission, and client deliverable templates. Use when planning or executing reconnaissance against authorized targets, mapping an organization's external attack surface, investigating a person/entity, or producing client deliverables.

Operational arsenal for external red-team and bug-bounty reconnaissance. Concrete wordlists (28 Swagger paths, 13 GraphQL paths, 35 high-risk ports, 6 missing-header findings, 15 always-on HTTP checks, 5 SAML paths, cloud bucket permutations, JS guess-paths, vendor product fingerprints for Citrix/F5/Pulse/Fortinet/Cisco/PaloAlto/VMware/Exchange, cloud-native service fingerprints, container/K8s exposure paths, CI/CD platform paths, documentation/wiki leak paths, WHOIS/RDAP, DNS record catalog, Wayback CDX recipes), 80-pattern secret-regex catalog (incl. modern AI API keys: Anthropic/OpenAI/HuggingFace/Cloudflare/DigitalOcean/npm/PyPI/Docker Hub/Atlassian/DataDog/Sentry/ngrok; plus a provider-expansion tier: Postman PMAK/GitLab/Square/Shopify/Mailchimp/PagerDuty/Asana/Databricks/Grafana/Terraform Cloud/Fastly/Algolia/Segment/Airtable/GCP+Google OAuth/Azure AD/Facebook OAuth/RubyGems/JFrog/Okta/Slack app-level/Dropbox/Doppler/HashiCorp Vault/Firebase Cloud Messaging), 80+ dork corpus across 9 categories, GitHub code-search dorks, copy-paste curl/httpie probes for every check, post-discovery enumeration workflows (AWS/GitHub/Slack/JWT/PMAK/Anthropic/OpenAI), endpoint interest scoring rubric (0–100), mobile app ownership confidence + APK static-analysis pipeline (acquisition, apktool/aapt2/jadx/androguard decompile, manifest exported-component/deep-link/misconfig extraction, Firebase config, network-security-config, embedded-secret scan), identity-fabric endpoints (Entra/Okta/ADFS/Google/SAML/M365 Teams+SharePoint+OneDrive+OAuth + user-enum), GraphQL field-suggestion enumeration when introspection disabled, 9 read-only secret validators (Postman/AWS/GitHub/Slack/Anthropic/OpenAI/npm/Atlassian/DataDog), Postman workspace search (verified endpoint), Stack Exchange sweep, public SaaS dorks, email security analysis (SPF/DMARC/DKIM/BIMI/MTA-STS/DNSSEC), origin-discovery / CDN bypass techniques, TLS deep audit (sslyze/testssl.sh/JA3/JA4), reverse-DNS sweep + IPv6 enum, vulnerability prioritization data sources (NVD/EPSS/CISA KEV/ExploitDB/Metasploit), 27 attack-path hint templates, 80+ severity-matrix examples, LinkedIn employee enumeration, job posting tech-stack analysis, Slack/Discord workspace discovery, package registry leak hunting (npm/PyPI/Docker Hub/Quay/GHCR), sat imagery for physical recon, tooling quick-install one-liners, sector-specific recon notes (healthcare/finance/ICS-SCADA/IoT/government), runnable stdlib-only secret_scan.py helper, plus the existing tool references for username/email/phone/people/social/breach/infrastructure/crypto/media/geospatial/AI/archiving/automation. Use when you need concrete probe paths, regexes, payloads, scoring rules, curl one-liners, and tool URLs for an authorized external recon engagement.

Establishes a project's quality bar as a written contract and stops agents quietly lowering it. Interviews the user on which dimensions matter, supplies sane default thresholds when they have no number in mind, records everything in CONSTRAINTS.md, and watches the diff for a weakened bar — new @ts-ignore or eslint-disable suppressions, skipped or deleted tests, assertions stripped out, unimplemented stubs, thresholds edited down. Use when no quality bar is written down, when the user says "set up constraints" or "define our standards", when the user wants dimensions they care about — accessibility, web performance, coverage — set up as enforced constraints, when an agent keeps silencing checks or skipping tests to get to green, when you need a coverage or performance threshold and don't know what number to pick, or when an agent writes more code than anyone will read.

Reference for the Claude API / Anthropic SDK — model ids, pricing, params, streaming, tool use, MCP, agents, caching, token counting, model migration. TRIGGER — read BEFORE opening the target file; don't skip because it "looks like a one-liner" — whenever: the prompt names Claude/Anthropic in any form (Claude, Anthropic, Fable, Opus, Sonnet, Haiku, `anthropic`, `@anthropic-ai`, `claude-*`, `us.anthropic.*`, `[1m]`); the user asks about an LLM (pricing/model choice/limits/caching) — never answer from memory; OR the task is LLM-shaped with provider unstated (agent/MCP/tool-definition/multi-agent/RAG/LLM-judge/computer-use; generate/summarize/extract/classify/rewrite/converse over NL; debugging refusals/cutoffs/streaming/tool-calls/tokens). SKIP only when another provider is being worked on (overrides all triggers): OpenAI/GPT/Gemini/Llama/Mistral/Cohere/Ollama named in the query; OR `grep -rE 'openai|langchain_openai|google.generativeai|genai|mistralai|cohere|ollama'` over the project hits (run this grep FIRST if no provider named — don't Read the file).

Use this when the user asks to search memory, "did we already solve this?", "how did we do X last time?", or wants work from previous sessions.

Use this when setting up claude-mem on Grok Bot: local worker plus CMEM Pro observer (default), optional host-login observer, or remote cmem.ai. No Cursor required.

Use this when the user asks to search memory, "did we already solve this?", "how did we do X last time?", or wants work from previous sessions.

Use when writing or reviewing Go code in this repo that synthesizes audio with Speak v1 REST or Speak WebSockets. Route transcription work to deepgram-go-speech-to-text, voice conversation runtime work to deepgram-go-voice-agent, and repository maintenance work to deepgram-go-maintaining-sdk.

Implement a new POSIX command as a builtin in the safe shell interpreter