724건 · 관련도순
Perform a focused security review of pending git changes to identify high-confidence security vulnerabilities with real exploitation potential. Use this skill when the user asks for a security review, security audit, vulnerability scan, or wants to check pending changes on a branch for security issues before merging. This is NOT a general code review.
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Writing, exploit ： 将原始素材逐段塑形为一篇文章。
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Writing, exploit ： 将原始素材组装成一段节拍之旅，在节拍使用每个术语之前先将其夯实。
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Research a specific CVE or vulnerability disclosure end-to-end — what version is affected, is your code reachable, is there a public PoC, is there a patch, what's the exposure window, what's the mitigation if you can't patch immediately. Use when the user mentions 'CVE,' 'vulnerability research,' 'is this CVE relevant,' 'zero-day,' 'CISA KEV,' 'GitHub Security Advisory,' 'reachability analysis,' 'patch analysis,' 'exploit availability,' 'EPSS,' 'CVSS,' or 'should we drop everything and patch this.'
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Use when gaining initial access to a target — phishing, payload delivery, HTML smuggling, ISO/IMG/MOTW bypass, supply-chain, credential stuffing, exposed-service exploitation
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Use when about to send a request to, scan, enumerate, exploit, or otherwise interact with any host, IP, URL, or asset — before the first packet reaches a target
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Use when attacking an AI/ML system or model — prompt injection & jailbreaks (Crescendo, Skeleton Key, Best-of-N), RAG/vector poisoning, agentic/MCP exploitation (CVE-2025-54136), ML supply-chain RCE (pickle CVE-2025-32434), model extraction / membership inference / adversarial suffixes (GCG)
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Use when starting an engagement, before exploitation, or whenever the attack surface changes — build/validate the threat model and detect drift (new unreviewed surface) before advancing
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Use when turning a memory-corruption bug into a working PoC — stack/ROP, glibc heap & FSOP, format strings, browser/JIT type confusion & UAF, Linux/Windows kernel LPE against ASLR/DEP/CFG/CET/V8-Sandbox
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Use when writing security tooling, exploits, scanners, or C2 in Python/C/Go/Rust/ASM — systems & network programming, automation, cryptography implementation
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Use when starting any offensive-security engagement or task — establishes how to find and invoke the right skill before any action (including clarifying questions, recon, exploitation, or reporting)
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Use when starting, planning, or running a multi-phase pentest or red-team engagement — to sequence the Cyber Kill Chain phases with quality gates instead of jumping straight to exploitation
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Use when bypassing a Windows exploit/platform mitigation — ASLR/DEP/CFG/XFG/CET, ACG/CIG, WDAC/App Control, ASR/AMSI/ETW, PPL/LSA Protection, BYOVD/VBS/HVCI
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Writing, exploit; assemble raw material into a journey of beats, grounding each term before a beat leans on it.
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Writing, exploit: shape raw material into an article, paragraph by paragraph.
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Fast PARALLEL wiki lookup engine over wiki/techniques + wiki/payloads + wiki/tools + wiki/cheatsheets for a surface/service/vuln-class. Two modes - quick (one qmd search, cheap, fire constantly) and deep (4 parallel subagents, one per area, merged ready-to-use arsenal card, cached). This is the fast path arsenal that `arsenal` delegates to; the hunt-* skills each inline their own qmd_query and can hand off here for a parallel lookup. Use for "what do I use against <surface>", "arsenal for <X>", "deep/full arsenal", "tool + payload + technique + cheatsheet for <X>", "fast wiki lookup", "parallel wiki search", any "how do I attack/exploit <service|vuln-class>" where you want the documented tooling + payloads before hand-rolling.
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Capture web-page / PoC screenshots into the engagement evidence (targets/<eng>/poc/) and embed them in walkthrough.md. Live pages + authenticated/exploited states (post-login dashboard, the flag page, an SSTI/cmdi render). Runs chromium on the Kali tooling host (VPN path to targets); hands off to the evidence skill for redaction before a real report. Use when building PoC evidence or asked to "take a screenshot / capture the PoC".
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Enterprise SSL VPN attack - vendor fingerprinting, CVE matrix (Cisco, Fortinet, Citrix, Palo Alto, Pulse/Ivanti), default credentials, pre-auth exploit commands. Wiki-first, FIND schema output.
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ICS/SCADA/OT exploitation - Modbus (502), S7comm (102), EtherNet/IP (44818), DNP3, OpenPLC, Node-RED SCADA, PLC/HMI/coil/holding-register attacks. Use when a target exposes industrial protocols or the goal is to drive a plant to a dangerous state (over-pressure/over-speed/disable interlock) and read the flag the HMI/CCTV reveals.
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RCE hunting - template injection, YAML/XML deserialization, dependency confusion, Kubernetes surfaces, CVE-specific exploits (Apache CVE-2021-41773, Spring CVE-2022-22963). OOB-mandatory for blind cases. Wiki-first, FIND schema output.
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Autonomous sub-agent hand-off for a fiddly, fully-specified exploit-compile / escalation RUN - the main agent stays on strategy and the board while a cheap sub-agent runs an exact copy-paste checklist behind a false-root/hostname guardrail. Use for "delegate", "offload", "hand this to a sub-agent", "spin a haiku", or the moment a foothold plus a working escalation vector is identified. Main agent dispatches, waits (no parallel duplicate), integrates the result.
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Provide comprehensive techniques for penetration testing AWS cloud environments. Covers IAM enumeration, privilege escalation, SSRF to metadata endpoint, S3 bucket exploitation, Lambda code extraction, and persistence techniques for red team operations.
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Provide comprehensive techniques for testing REST, SOAP, and GraphQL APIs during bug bounty hunting and penetration testing engagements. Covers vulnerability discovery, authentication bypass, IDOR exploitation, and API-specific attack vectors.
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Applies the reasoning of David Silver, lead researcher on AlphaGo and AlphaZero at DeepMind, to problems of AI design, reinforcement learning, and open-ended discovery. Use this skill whenever you are designing AI systems, evaluating learning algorithms, balancing exploration vs. exploitation, choosing research problems, or discussing how to break past human performance ceilings. Reach for this whenever the user asks about self-play, Monte-Carlo Tree Search, tabula rasa learning, AGI, or moving from human-curated data to autonomous experience. It helps shift the focus from hardcoding human knowledge to building systems that learn for themselves.
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