'brute-force' 검색 결과

Analyze Windows authentication logs for repeated password guesses against Remote Desktop services. Group failures by source IP and account, check for later successful logins, and produce a JSON report highlighting attack patterns and possible compromise.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Investigate repeated login failures on exposed RDP services
• Identify accounts targeted by password guessing
• Check for successful logins after repeated failures

Expert guide for API rate limiting, bot protection, DDoS mitigation, brute-force prevention, and abuse detection / Panduan ahli untuk rate limiting API, perlindungan bot, mitigasi DDoS, pencegahan brute-force, dan deteksi penyalahgunaan.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Exploit GraphQL API architectural features to execute highly efficient brute-force, Credential Stuffing, and Denial of Service (DoS) attacks. Utilize Query Batching and Alias injection to bypass rate limits by packing thousands of requests into a single HTTP POST request.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Detect RDP brute force attacks by analyzing Windows Security Event Logs for failed authentication patterns (Event ID 4625), successful logons after failures (Event ID 4624), NLA failures, and source IP frequency analysis.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

JWT saldırıları — alg:none, HMAC brute-force, floating point bypass, CVE-2022-39227

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Detect RDP brute force attacks by analyzing Windows Security Event Logs for failed authentication patterns (Event ID 4625), successful logons after failures (Event ID 4624), NLA failures, and source IP frequency analysis.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Detect RDP brute force attacks by analyzing Windows Security Event Logs for failed authentication patterns (Event ID 4625), successful logons after failures (Event ID 4624), NLA failures, and source IP frequency analysis.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Develop network monitoring for signs that may precede ransomware encryption. Uses detection rules, linked log events, and threat intelligence to identify suspicious activity and define how alerts should be investigated, prioritized, and escalated.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Creating detection rules for activity before ransomware encryption
• Linking suspicious logins, scans, and file share access
• Investigating unusual internal network communications

Analyze authentication logs to spot suspicious sign-ins, password attacks, and possible account compromise. Statistical baselines and machine learning help compare login activity with normal user behavior, while example SIEM queries support security investigations.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Investigating suspicious sign-in alerts
• Detecting geographically inconsistent logins
• Finding brute force and password spraying

Analyze Apache and Nginx access logs for attack attempts, scanner activity, and repeated login requests. Add geographic context to source IP addresses and produce a prioritized findings report to support intrusion investigations and monitoring reviews.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Investigating suspicious requests in web access logs
• Finding injection attempts and unauthorized file access attempts
• Identifying scanners and repeated login attempts

Advanced API exploitation methodology focused on business logic abuse and sophisticated attack patterns that bypass traditional security controls. Covers business logic bypass through API call chaining and workflow manipulation. Addresses GraphQL-specific attacks including batching for credential brute-force, query depth exploitation, and introspection abuse. Includes pagination exploitation for data exfiltration, webhook hijacking for SSRF and data interception, and resource exhaustion through algorithmic complexity attacks. Covers race conditions in API transactions using parallel request techniques. Provides comprehensive JWT manipulation including algorithm confusion, kid injection, jku/x5u abuse, and claim tampering. Details API key leakage detection across source repositories, client-side code, and error messages. Covers undocumented endpoint discovery through predictable naming, debug routes, and source map analysis. Tooling includes Arjun, ParamSpider, jwt_tool, and GraphQL Voyager. Designed for authorized penetration testers targeting business logic layers that automated scanners miss.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

WPS (Wi-Fi Protected Setup) PIN attack methodology — Pixie Dust offline attack against vulnerable chipsets (Ralink, Realtek, Broadcom, MediaTek), online PIN brute-force with reaver/bully, lockout handling, time-of-day evasion, WPS push-button vulnerability windows, and PIN-to-PSK derivation. Use when a target SOHO router exposes WPS — common on consumer ISP gear, often left enabled by default even when WPS attacks have been known for over a decade.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Z-Wave attack methodology — sniffing with Z-Force / EZ-Wave / RTL-SDR + ZniffMobile, S0 (legacy) network-key derivation flaw and key reuse, S2 (modern) ECDH commissioning analysis, replay/injection on unauthenticated nodes, default-key brute-force on test deployments, and home-automation hub pivots. Use when targeting Z-Wave smart home devices (door locks, sensors, garage controllers) — common in mid-2010s smart home deployments still in production.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Hunt account takeover taxonomy — 9 distinct paths to ATO, plus chains. Paths: (1) password reset flaws (host-header injection redirects token, predictable/numeric token, Referer leak, no-expiry/reuse), (2) email change without re-auth, (3) OAuth account-link CSRF, (4) MFA bypass (per hunt-mfa-bypass), (5) session fixation, (6) JWT manipulation (forge token to another identity; crypto details → hunt-jwt-crypto), (7) password change without step-up (chain with login timing/length oracle), (8) social-recovery / security-question brute-force, (9) SSO subdomain takeover at OAuth redirect_uri. Chains: cookie theft + password oracle + no step-up = persistent ATO; lax redirect_uri = auth-code theft; dangling-CNAME takeover at redirect_uri = ATO. Validate: demonstrate real takeover of test account B from attacker A's session; OOB/Collaborator confirm blind token-leak steps. Use when hunting ATO chains, testing password reset / email change / MFA / OAuth / session / JWT, or chaining primitives toward Critical.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Hunt Missing/Weak Rate Limiting — login brute force, OTP/2FA brute force (10^6 keyspace), password-reset-token brute, credential stuffing, username/email enumeration via error-string / status-code / timing differences, weak password policy, missing CAPTCHA (CAPTCHA token replay / single-use / concurrency-window bypass specifics → hunt-captcha-bypass), IP-based rate-limit bypass via X-Forwarded-For and friends, ReDoS. Distinguishes hard lockout vs soft IP-throttle vs CAPTCHA-injection vs silent shadow-throttling (avoids false-negative 'no rate limit' conclusions). Medium to Critical depending on what the brute reaches (OTP→ATO = Critical).

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Hunt MFA / 2FA bypass — 7 distinct patterns. (1) MFA not enforced on sensitive endpoints (password change, email change accept without MFA challenge), (2) MFA-step skip via direct navigation to post-login URL, (3) MFA-token replay (same code accepted twice), (4) brute-force the 6-digit OTP without rate limit (10^6 attempts at server speed), (5) race condition on OTP validation, (6) recovery-code dump via /api/me, (7) backup factor downgrade (SMS factor with no rate limit). Plus the chain: cookie theft + password oracle + no step-up = ATO without MFA challenge. Detection: trace auth flow in Burp, find every state transition, check if MFA is middleware-gated vs per-endpoint, check OTP entropy and rate limit on OTP-validate. Validate: attacker session reaching post-MFA state. Use when hunting auth bypass, MFA flows, chaining primitives toward ATO.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Authentication bypass testing playbook. Use when assessing login flows, password reset logic, account recovery, MFA bypass, token predictability, brute-force resistance, and session boundary flaws.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Inspects and configures the web application firewall (WAF) in front of a Power Pages production site. Lists the current state, recommends enabling protection when it is off, and walks the user through adding, updating, or removing custom rules — IP blocks, country blocks, path blocks, and rate limits. Use when the user wants to turn on WAF, block traffic by IP or country, rate-limit login or signup pages, protect pages from brute-force attempts, restrict access to specific paths, review the current firewall configuration, or asks "is my site protected against bots / common web attacks?" — even if they say "add rate limit" or "protect login page" without mentioning "firewall" or "WAF".

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Implement cheat codes, hidden interactions, and unlockable meta-content via time-windowed input sequence buffers, spam thresholds, look-at (dot-product) detectors, progress-% unlocks, and meta persistence in user://secrets.cfg. Use when adding Konami-style codes, curiosity spam eggs, glimmer cues, lockout anti-brute-force, or gallery flags that must survive slot deletes. Keywords: Konami, sequence buffer, meta secrets.cfg, visibility detector, lockout, glimmer, spam threshold, progress unlock.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Implement cheat codes, hidden interactions, and unlockable meta-content via time-windowed input sequence buffers, spam thresholds, look-at (dot-product) detectors, progress-% unlocks, and meta persistence in user://secrets.cfg. Use when adding Konami-style codes, curiosity spam eggs, glimmer cues, lockout anti-brute-force, or gallery flags that must survive slot deletes. Keywords: Konami, sequence buffer, meta secrets.cfg, visibility detector, lockout, glimmer, spam threshold, progress unlock.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Applies the reasoning style of Ilya Sutskever (deep learning pioneer, co-founder of OpenAI and Safe Superintelligence Inc.) to problems involving AI architecture, scaling laws, alignment, and research strategy. Reach for this skill whenever discussing machine learning paradigms, the limits of compute and data, AGI timelines, superintelligence safety, or deciding between hardcoding vs. learning. Trigger this skill for questions about next-word prediction, reinforcement learning efficiency, generalization gaps, and transitioning from brute-force scaling to fundamental research, even if the user doesn't explicitly name him.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Detects attacks from server logs and blocks malicious IPs with CrowdSec, an open-source, crowd-sourced alternative to fail2ban. Use when a user asks to block brute force attempts, protect SSH or a web server, set up a community blocklist firewall, add a WAF, or install CrowdSec with Docker.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Applies the reasoning style of Ilya Sutskever (deep learning pioneer, co-founder of OpenAI and Safe Superintelligence Inc.) to problems involving AI architecture, scaling laws, alignment, and research strategy. Reach for this skill whenever discussing machine learning paradigms, the limits of compute and data, AGI timelines, superintelligence safety, or deciding between hardcoding vs. learning. Trigger this skill for questions about next-word prediction, reinforcement learning efficiency, generalization gaps, and transitioning from brute-force scaling to fundamental research, even if the user doesn't explicitly name him.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Apply ant colony optimization and foraging theory to resource search, exploration-exploitation tradeoffs, and distributed discovery. Covers scout deployment, trail reinforcement, diminishing returns detection, and adaptive foraging strategy selection. Use when searching a large solution space where brute-force enumeration is impractical, balancing investment between exploring new approaches and deepening known good ones, optimizing resource allocation across uncertain opportunities, or diagnosing premature convergence on local optima.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.