「attacks」の検索結果

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.

日本語の概要は準備中です。原文の説明を表示しています。

Deauthentication and disassociation attacks against 802.11 networks — targeted single-client deauth for handshake capture, broadcast deauth for DoS (with authorization), action-frame attacks bypassing 802.11w (PMF), beacon flooding, mdk4 / aireplay-ng tooling, and rate-limit / PMF-aware operation. Use to coerce client reconnection (handshake capture, evil-twin roaming), as targeted DoS, or to test PMF posture.

日本語の概要は準備中です。原文の説明を表示しています。

WPA/WPA2-PSK attack methodology — four-way handshake capture via targeted deauthentication, PMKID attacks (no client required), hcxdumptool / hcxpcapngtool conversion to hashcat hc22000 format, GPU-accelerated cracking with dictionary, mask, and rule-based attacks, vendor default-PSK generators (UPC, Sky, BT, etc.), 802.11r FT key cracking, opportunistic key cache analysis, and signal-level optimization. Use when the in-scope network is WPA/WPA2 Personal — the most common consumer/SMB encryption mode.

日本語の概要は準備中です。原文の説明を表示しています。

Wi-Fi reconnaissance methodology — adapter selection, monitor mode and packet injection setup, regulatory domain handling, multi-band airspace mapping, hidden SSID discovery, BSSID/ESSID/channel/PMF/encryption fingerprinting, client probe analysis, vendor OUI lookup, war-driving with Kismet/airodump-ng/Wigle, and structured airspace data capture for downstream attacks. Use at the start of any wireless engagement to build the target map before active attacks; covers 2.4 GHz, 5 GHz, and 6 GHz (Wi-Fi 6E) bands and adapter compatibility for each.

日本語の概要は準備中です。原文の説明を表示しています。

Social engineering attack techniques beyond email phishing for authorized red team and physical penetration testing engagements. Covers pretexting methodology (persona creation, authority and urgency psychological triggers, rapport building), vishing (voice phishing via caller ID spoofing, IVR system exploitation, VoIP infrastructure setup with Twilio/Asterisk), smishing (SMS-based phishing, carrier gateway abuse, short code impersonation), physical social engineering (tailgating and piggybacking, RFID badge cloning with Proxmark3, lock picking and bypass, dumpster diving for sensitive documents), USB drop attacks (Rubber Ducky keystroke injection, Bash Bunny multi-vector payloads, O.MG cable covert implants, BadUSB firmware attacks), watering hole attack planning and execution, and OSINT-driven targeting (LinkedIn harvesting, organizational chart reconstruction, employee pattern analysis). Integrates with the Social Engineering Toolkit for attack automation, Proxmark3 for RFID/NFC cloning, USB Rubber Ducky and Bash Bunny for physical payload delivery, and BeEF for browser exploitation. Maps to MITRE ATT&CK T1598 (Phishing for Information), T1566 (Phishing), T1091 (Replication Through Removable Media), and T1189 (Drive-by Compromise). All techniques require explicit written authorization and defined rules of engagement.

日本語の概要は準備中です。原文の説明を表示しています。

Deep-dive offensive methodology for dependency confusion and namespace attacks across all major package ecosystems. Covers npm scope confusion exploiting the gap between public and private scoped packages and .npmrc misconfigurations where registry mappings fail to pin internal scopes exclusively. Addresses PyPI namespace attacks through --extra-index-url resolution ordering, NuGet feed priority exploitation when multiple package sources are configured without clear directives, Maven and Gradle repository ordering where artifact resolution traverses repositories sequentially, Go module proxy abuse through GOPROXY misconfiguration, Ruby gems namespace squatting, and Docker image tag confusion with unqualified image references. Provides complete proof-of-concept methodology using safe callbacks including DNS canary via interactsh or Burp Collaborator and HTTP beacon with no destructive payload. Covers reconnaissance techniques for discovering internal package names through GitHub repository analysis, error message harvesting, JavaScript source map extraction, lock file parsing, job postings mentioning internal tools, and package manifest inspection. Directly references and builds upon Alex Birsan's seminal 2021 dependency confusion research. Each ecosystem section includes registry-specific exploitation mechanics, configuration vulnerabilities, and defensive countermeasures for engagement reporting.

日本語の概要は準備中です。原文の説明を表示しています。

Complete reference for 26 web2 bug classes with root causes, detection patterns, bypass tables, exploit techniques, and real paid examples. Covers IDOR, auth bypass, XSS (postMessage), SSRF (11 IP bypass techniques), SQLi, business logic, race conditions, OAuth/OIDC, file upload (10 bypass techniques), GraphQL, LLM/AI (ASI01-ASI10, MCP/RAG attacks), API misconfig (mass assignment, JWT, prototype pollution, CORS), ATO (9 paths), SSTI, subdomain takeover, cloud misconfig, HTTP smuggling, cache poisoning, MFA bypass (7 patterns), SAML attacks, error disclosure, CSS injection, LFI/RCE, insecure deserialization, dependency confusion, padding oracle. Use when hunting a specific vuln class or studying what makes bugs pay.

日本語の概要は準備中です。原文の説明を表示しています。

Terminal security analysis for shell environments. This skill should be used when checking commands for supply-chain attacks before execution, scanning repositories for hidden content or config poisoning, scoring URLs for homograph attacks, setting up AI tool protection, inspecting Python package artifacts, governing untrusted tasks or Web3 commands, auditing browser extensions, creating provenance receipts, downloading and executing scripts safely, investigating why tirith blocked a command, managing trusted patterns, running security audits, configuring MCP gateway proxies, or working with threat intelligence databases. Also use when the user mentions "tirith", "pipe-to-shell", "homograph", "ANSI injection", "zero-width", "punycode", "terminal security", "shell hook", "cloaking detection", "supply chain attack", "bidi override", "invisible unicode", or "config poisoning". Even if the user does not explicitly name tirith, use this skill when they ask about protecting shell environments, intercepting dangerous commands, or hardening AI agent tool execution.

日本語の概要は準備中です。原文の説明を表示しています。

Symmetric cipher attack playbook. Use when exploiting block cipher mode weaknesses (CBC padding oracle, ECB cut-and-paste, bit flipping), stream cipher key reuse, or meet-in-the-middle attacks.

日本語の概要は準備中です。原文の説明を表示しています。

Kerberos attack playbook for Active Directory. Use when targeting AD authentication via AS-REP roasting, Kerberoasting, golden/silver/diamond tickets, delegation abuse, or pass-the-ticket attacks.

日本語の概要は準備中です。原文の説明を表示しています。

DeFi attack pattern playbook. Use when analyzing flash loan attacks, price oracle manipulation, MEV sandwich attacks, governance exploits, bridge vulnerabilities, and token standard edge cases in decentralized finance protocols.

日本語の概要は準備中です。原文の説明を表示しています。

AI/ML security playbook. Use when assessing model supply chain attacks (pickle RCE, poisoned weights), adversarial examples, model poisoning, model stealing, data privacy attacks (membership inference, model inversion), and autonomous agent security risks.

日本語の概要は準備中です。原文の説明を表示しています。

Adversarial premortem for England & Wales civil litigation - builds the strongest version of a case, then attacks it from four angles to find where it loses before opposing counsel does. Runs an adversarial premortem on a UK litigation matter. Builds the strongest version of the case, then attacks it from four angles — procedural, substantive, evidentiary, strategic — to find where it actually loses. Returns a ranked stress-test brief: failure scenarios, evidence inconsistencies, blind spots, mitigations, and one brutal one-sentence verdict. Use before issue, before settlement negotiations, before a litigation-funder pitch, or before deciding whether to take a case.

日本語の概要は準備中です。原文の説明を表示しています。

Provide comprehensive techniques for attacking Microsoft Active Directory environments. Covers reconnaissance, credential harvesting, Kerberos attacks, lateral movement, privilege escalation, and domain dominance for red team operations and penetration testing.

日本語の概要は準備中です。原文の説明を表示しています。

Kerberos-based Active Directory attacks driven by hand with standard tooling (Kerberoasting, AS-REP roasting, and delegation abuse: unconstrained, constrained/S4U, RBCD). Use when the target has SPN-bearing service accounts, accounts without pre-authentication, or delegation configured on computer/user objects, and you want the exact impacket/Rubeus/bloodyAD command, the hash format and hashcat mode, the Windows Event IDs that fire, and the remediation to write up.

日本語の概要は準備中です。原文の説明を表示しています。

Hunt JSON Web Token (JWT) vulnerabilities — alg=none bypass, RS256→HS256 key confusion, weak HMAC secret cracking, kid path traversal, JWKS injection, jku/x5u header attacks, embedded JWK confusion, expired-token acceptance, claim mutability, and token replay. Use when an app uses JWT for authentication or stateless sessions.

日本語の概要は準備中です。原文の説明を表示しています。

Use when the user asks about supply-chain attacks, third-party / vendor compromise (SolarWinds, Kaseya, 3CX, MOVEit, XZ-utils-style), software-bill-of-materials risks, or library / dependency-injection attacks. Self-updating knowledge cell.

日本語の概要は準備中です。原文の説明を表示しています。

DeFi attack pattern playbook. Use when analyzing flash loan attacks, price oracle manipulation, MEV sandwich attacks, governance exploits, bridge vulnerabilities, and token standard edge cases in decentralized finance protocols.

日本語の概要は準備中です。原文の説明を表示しています。

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.

日本語の概要は準備中です。原文の説明を表示しています。

Application-level business logic security testing for any domain. Takes an understanding-first approach: map the intended workflows before probing them. Covers: value/quantity logic abuse (negative, zero, overflow, rounding on any numeric field), workflow and state machine bypass (skipping required steps, forcing illegal state transitions, reusing one-time tokens), trust boundary violations (BOLA horizontal/vertical, BFLA, cross-tenant access, negative ownership attacks), idempotency and replay attacks (duplicate submissions, double-spend, same-reference reuse), multi-step flow integrity (checkout, registration, approval, verification), quota and rate limit bypass, time/date manipulation, and authorization code / reference number predictability. Domain-agnostic — applies to SaaS, e-commerce, banking, gaming, social platforms, APIs, or any multi-user application with stateful workflows. Chains from /pentester; chains into /param-fuzz when boundary violations or mass assignment are confirmed.

日本語の概要は準備中です。原文の説明を表示しています。

Kerberos attack playbook for Active Directory. Use when targeting AD authentication via AS-REP roasting, Kerberoasting, golden/silver/diamond tickets, delegation abuse, or pass-the-ticket attacks.

日本語の概要は準備中です。原文の説明を表示しています。

AI/ML security playbook. Use when assessing model supply chain attacks (pickle RCE, poisoned weights), adversarial examples, model poisoning, model stealing, data privacy attacks (membership inference, model inversion), and autonomous agent security risks.

日本語の概要は準備中です。原文の説明を表示しています。

Hunts for Active Directory credential and replication attacks — DCSync, Golden/Silver Ticket, and DCShadow — by analyzing directory-service-access (4662), Kerberos TGS (4769), and logon (4624) events for replication abuse and forged-ticket anomalies. Activates for requests to hunt DCSync, detect golden/silver tickets, or find Active Directory replication abuse.

日本語の概要は準備中です。原文の説明を表示しています。

Provide comprehensive techniques for attacking Microsoft Active Directory environments. Covers reconnaissance, credential harvesting, Kerberos attacks, lateral movement, privilege escalation, and domain dominance for red team operations and penetration testing.

日本語の概要は準備中です。原文の説明を表示しています。