'ploi' 검색 결과

Review concrete code for exploitable security defects, including missing access checks, unsafe input handling, and exposed secrets. Report verified issues with file locations, reachable attack paths, severity, and suggested fixes.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Review a code change for exploitable vulnerabilities
• Check authentication and access controls
• Trace unsafe input handling and secret exposure

Configure advanced Microsoft Defender protections on Windows, including rules that block risky behavior, protected folders, network filtering, and exploit defenses. Use audit modes to assess application impact, then deploy policies and monitor detections across an organization.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Strengthening Windows endpoint protection
• Assessing ASR rules in audit mode
• Configuring ransomware protection for folders

Assess whether stolen Kerberos tickets, credentials used for network authentication, can enable access to other systems during authorized testing. Guide ticket extraction and reuse, review detection indicators, and document evidence for security reports.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Authorized testing of access through reused tickets
• Checking detection of Kerberos ticket theft
• Collecting evidence for lateral movement reports

Assess Kubernetes security from an existing pod or API access point. Covers permission checks, exposed node services, secrets, host access, and cloud metadata to explain how configuration weaknesses can expand access across a cluster.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Review service account permissions and RBAC settings
• Assess host access and secrets exposure from pods
• Trace access paths from a cluster to cloud infrastructure

Assess Docker, containerd, and Podman environments for weaknesses that could expose the host system. The skill organizes checks for excessive permissions, exposed runtime sockets, and known vulnerabilities, alongside indicators defenders can monitor.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Assessing container isolation
• Reviewing permissions and exposed runtime sockets
• Checking known runtime vulnerabilities

Review Windows privilege escalation paths from a standard user session to Administrator or SYSTEM. Examine service permissions, token privileges, library loading, scheduled tasks, and stored credentials, with detection indicators for defensive validation.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Investigating privilege escalation in authorized Windows assessments
• Reviewing service and scheduled task permissions
• Checking detection coverage with attack and defense teams

Helps plan NetExec commands for penetration testing in Active Directory, the system used to manage Windows domain accounts. Covers authentication checks, shared resources, permissions, and information collection with examples organized by network protocol.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Checking NetExec authentication options
• Enumerating domain users and shared resources
• Collecting data for BloodHound

Assess server-side template injection, where user input is interpreted as template code. Identify template engines, evaluate information exposure and code execution risks, and organize evidence alongside detection and prevention measures.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Assessing template rendering endpoints
• Identifying the template engine in use
• Evaluating information exposure and code execution risks

Plan authorized security tests involving phone calls, text messages, physical access, and USB devices. Helps develop scenarios from public information, document interactions, and assess how staff verification procedures and physical controls respond.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Planning authorized phone and SMS security tests
• Reviewing visitor and badge verification procedures
• Designing USB device security exercises

Investigate TOCTOU flaws: race conditions where a checked property changes before an action uses it. The skill covers filesystem, kernel, web, and container testing, helping identify vulnerable sequences, reproduce timing issues, and document observed impact.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Reviewing file checks before privileged operations
• Testing access revocation during long-running requests
• Investigating duplicate payments from concurrent requests

Investigate Windows weaknesses that could let a standard user gain Administrator or SYSTEM access. Guides authorized penetration tests through system inspection, credential checks, escalation validation, and reports with remediation recommendations.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Investigating Windows privilege escalation paths
• Checking service permissions and stored credentials
• Assessing token privileges and missing patches

Assess AWS security through penetration testing, a process for checking exploitable weaknesses. Examine IAM permissions, storage, compute resources, and credential exposure to identify privilege escalation paths and document security audit findings.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Review IAM permissions for privilege escalation paths
• Assess S3 bucket access and exposed files
• Check credential exposure through EC2 metadata

Assess Linux systems for weaknesses that let a regular user gain administrator access. Guides inspection of permissions, scheduled tasks, and vulnerable components, with findings, evidence, and remediation recommendations documented for review.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Auditing Linux permissions and configuration
• Checking sudo and SUID privilege escalation paths
• Reviewing scheduled tasks and shared directories

Learn how to conduct an authorized penetration test, a security assessment that checks exploitable weaknesses. Follow guidance from initial research and scanning through validation, evidence collection, and reporting with remediation recommendations.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Learning the full penetration testing lifecycle
• Planning research and scanning for an authorized assessment
• Organizing vulnerability evidence

Provides binary exploitation techniques for CTF challenges. Use when you already have a vulnerable native target or service and need to turn memory corruption or low-level primitives into code execution or privilege escalation, such as buffer overflows, format strings, heap bugs, ROP, ret2libc, shellcode, kernel exploitation, seccomp bypass, sandbox escape, or Windows/Linux exploit chains. Do not use it when the main blocker is understanding what the binary does; use reverse engineering first. Do not use it for pure web bugs, disk or packet forensics, or standalone crypto/math challenges.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Linux kernel exploitation playbook. Use when exploiting kernel vulnerabilities (UAF, OOB, race condition, type confusion) for privilege escalation via commit_creds, modprobe_path overwrite, or kernel ROP chains in CTF and real-world scenarios.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Browser and V8 exploitation playbook. Use when exploiting JavaScript engine vulnerabilities including JIT type confusion, incorrect bounds elimination, and V8 sandbox bypass to achieve renderer RCE and sandbox escape in Chrome/Chromium.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Estimates tumor fraction (the genome-wide proportion of cfDNA molecules that are tumor-derived, the cfDNA analogue of bulk-tumor purity) from shallow whole-genome sequencing with ichorCNA, an HMM over 1 Mb bins that jointly EM-estimates tumor fraction, ploidy, and subclonal prevalence over a normal/ploidy grid. Encodes the load-bearing reframes: tumor fraction is the quantity that travels across assays and is NOT mutation VAF (clonal-het VAF approximately TF/2), CNA-based estimation has a hard ~3 percent limit-of-detection floor, and near-diploid or copy-neutral-LOH genomes return a falsely low value. Selects the estimator by data type (sWGS to ichorCNA, deep panel to max-VAF, methylation to deconvolution, sub-3 percent to fragmentomics or methylation). Use when quantifying tumor burden from a liquid biopsy, picking a tumor-fraction estimator for a given assay, or reconciling a TF estimate against a panel VAF.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Enforce "No Exploit, No Report" policy with PoC construction standards, false-positive filtering, and evidence collection per vulnerability class across backend, frontend, and mobile. Use when validating security findings, constructing exploit proofs, filtering false positives, or writing pentest findings.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Proof-of-concept development, payload crafting, shellcode analysis, and exploitation technique research for authorized security testing

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Apploi integration. Manage data, records, and automate workflows. Use when the user wants to interact with Apploi data.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

德州扑克策略 (德州扑克策略 (Texas Hold'em) — solver/GTO 时代的无限注德州扑克竞技打法，牌手/职业视角。覆盖: (a) 理论两极 — GTO 博弈论均衡 (不可剥削的基线策略) vs Exploitative 剥削打法 (针对对手漏洞偏离均衡最大化 EV)，以及二者的实战取舍; (b) solver 时代工作流 — PioSOLVER/GTO Wizard 跑解、范围构建、节点锁定 (node-locking) 做剥削、用 HUD+数据库 (Hold'em Manager/PokerTracker/Hand2Note) 复盘找漏洞 (leak finding); (c) 牌型分层 — 现金局 (cash game) vs 锦标赛 (MTT) 的根本差异，后者叠加 ICM (独立筹码模型) 与跳台/泡沫期博弈; (d) 核心概念栈 — 范围 (range)/权益 (equity)/EV/位置 (position)/翻前开池与 3-bet/4-bet/翻后下注理论 (c-bet、极化 vs 浓缩范围、MDF 最小防守频率、阻断牌 blockers、超池下注 overbet)、SPR、底池赔率; (e) 元层 — 资金管理 (bankroll management)、桌位选择 (table selection)、方差与心态 (mental game/tilt 控制)、抽水 (rake) 与场次选择对长期赢率 (winrate, bb/100) 的影响; (f) 智识演进 — 从 Sklansky 古典手牌价值 → Janda/Tipton 博弈论 → solver 普及 → GTO Wizard 民主化求解 → AI 超人 (Libratus/Pluribus) 对人类策略的反哺。学派分歧: GTO 派 vs 剥削派、现金局 vs 锦标赛、理论自上而下 vs 牌局自下而上、solver 纯学院派 vs 实战感觉派。不含: 线下牌场运营/发牌荷官、博彩合规与赌场管理、扑克之外的牌类 (桥牌/斗地主)、纯概率赌博 (老虎机/轮盘)。) Master OS — automated mastery of 德州扑克策略 (Texas Hold'em) — solver/GTO 时代的无限注德州扑克竞技打法，牌手/职业视角。覆盖: (a) 理论两极 — GTO 博弈论均衡 (不可剥削的基线策略) vs Exploitative 剥削打法 (针对对手漏洞偏离均衡最大化 EV)，以及二者的实战取舍; (b) solver 时代工作流 — PioSOLVER/GTO Wizard 跑解、范围构建、节点锁定 (node-locking) 做剥削、用 HUD+数据库 (Hold'em Manager/PokerTracker/Hand2Note) 复盘找漏洞 (leak finding); (c) 牌型分层 — 现金局 (cash game) vs 锦标赛 (MTT) 的根本差异，后者叠加 ICM (独立筹码模型) 与跳台/泡沫期博弈; (d) 核心概念栈 — 范围 (range)/权益 (equity)/EV/位置 (position)/翻前开池与 3-bet/4-bet/翻后下注理论 (c-bet、极化 vs 浓缩范围、MDF 最小防守频率、阻断牌 blockers、超池下注 overbet)、SPR、底池赔率; (e) 元层 — 资金管理 (bankroll management)、桌位选择 (table selection)、方差与心态 (mental game/tilt 控制)、抽水 (rake) 与场次选择对长期赢率 (winrate, bb/100) 的影响; (f) 智识演进 — 从 Sklansky 古典手牌价值 → Janda/Tipton 博弈论 → solver 普及 → GTO Wizard 民主化求解 → AI 超人 (Libratus/Pluribus) 对人类策略的反哺。学派分歧: GTO 派 vs 剥削派、现金局 vs 锦标赛、理论自上而下 vs 牌局自下而上、solver 纯学院派 vs 实战感觉派。不含: 线下牌场运营/发牌荷官、博彩合规与赌场管理、扑克之外的牌类 (桥牌/斗地主)、纯概率赌博 (老虎机/轮盘)。: top builders' mental models, tool stack, current workflows, jargon, and where to keep up. Trigger this skill when the user works on 德州扑克策略 (Texas Hold'em) — solver/GTO 时代的无限注德州扑克竞技打法，牌手/职业视角。覆盖: (a) 理论两极 — GTO 博弈论均衡 (不可剥削的基线策略) vs Exploitative 剥削打法 (针对对手漏洞偏离均衡最大化 EV)，以及二者的实战取舍; (b) solver 时代工作流 — PioSOLVER/GTO Wizard 跑解、范围构建、节点锁定 (node-locking) 做剥削、用 HUD+数据库 (Hold'em Manager/PokerTracker/Hand2Note) 复盘找漏洞 (leak finding); (c) 牌型分层 — 现金局 (cash game) vs 锦标赛 (MTT) 的根本差异，后者叠加 ICM (独立筹码模型) 与跳台/泡沫期博弈; (d) 核心概念栈 — 范围 (range)/权益 (equity)/EV/位置 (position)/翻前开池与 3-bet/4-bet/翻后下注理论 (c-bet、极化 vs 浓缩范围、MDF 最小防守频率、阻断牌 blockers、超池下注 overbet)、SPR、底池赔率; (e) 元层 — 资金管理 (bankroll management)、桌位选择 (table selection)、方差与心态 (mental game/tilt 控制)、抽水 (rake) 与场次选择对长期赢率 (winrate, bb/100) 的影响; (f) 智识演进 — 从 Sklansky 古典手牌价值 → Janda/Tipton 博弈论 → solver 普及 → GTO Wizard 民主化求解 → AI 超人 (Libratus/Pluribus) 对人类策略的反哺。学派分歧: GTO 派 vs 剥削派、现金局 vs 锦标赛、理论自上而下 vs 牌局自下而上、solver 纯学院派 vs 实战感觉派。不含: 线下牌场运营/发牌荷官、博彩合规与赌场管理、扑克之外的牌类 (桥牌/斗地主)、纯概率赌博 (老虎机/轮盘)。 problems and wants industry-grade thinking, tool selection, or workflow guidance. 触发词：「德州扑克」「德扑」「Texas Hold'em」「poker strategy」「扑克策略」

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Authorized exploit development and vulnerability research skill for lab environments, CTFs, owned software, crash analysis, memory corruption, exploitability assessment, fuzzing results, proof-of-concept design, and remediation. Use for defensive validation and education; avoid real-world weaponization, stealth, persistence, evasion, or unauthorized targets.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Identify and exploit vulnerabilities in the AI Supply Chain by injecting malicious models, datasets, or dependencies. Use this skill to simulate advanced persistent threats (APTs) compromising Hugging Face repositories, manipulating pre-trained weights (Model Poisoning), and exploiting insecure deserialization during model loading (e.g., Pickle files).

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.