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「detection」の検索結果

2,091 件 ・ 関連度順

概要と使いどころ

Detect abnormal access patterns in AWS S3, GCS, and Azure Blob Storage by analyzing CloudTrail Data Events, GCS audit logs, and Azure Storage Analytics. Identifies after-hours bulk downloads, access from new IP addresses, unusual API calls (GetObject spikes), and potential data exfiltration using statistical baselines and time-series anomaly detection.

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。

aniket2348823/Vul-Agent22026年6月9日 更新

Detect and analyze covert communication channels used by malware including DNS tunneling, ICMP exfiltration, steganographic HTTP, and protocol abuse for C2 and data exfiltration.

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。

aniket2348823/Vul-Agent22026年6月9日 更新

Perform static analysis of Android APK malware samples using apktool for decompilation, jadx for Java source recovery, and androguard for permission analysis, manifest inspection, and suspicious API call detection.

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。

aniket2348823/Vul-Agent22026年6月9日 更新

Use the Malpedia platform and API to research malware family relationships, track variant evolution, link families to threat actors, and integrate YARA rules for detection across malware lineages.

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。

aniket2348823/Vul-Agent22026年6月9日 更新

Queries Azure Monitor activity logs and sign-in logs via azure-monitor-query to detect suspicious administrative operations, impossible travel, privilege escalation, and resource modifications. Builds KQL queries for threat hunting in Azure environments. Use when investigating suspicious Azure tenant activity or building cloud SIEM detections.

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。

aniket2348823/Vul-Agent22026年6月9日 更新

Examine Linux system artifacts including auth logs, cron jobs, shell history, and system configuration to uncover evidence of compromise or unauthorized activity.

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。

aniket2348823/Vul-Agent22026年6月9日 更新

Analyzes RAM memory dumps from compromised systems using the Volatility framework to identify malicious processes, injected code, network connections, loaded modules, and extracted credentials. Supports Windows, Linux, and macOS memory forensics. Activates for requests involving memory forensics, RAM analysis, volatile data examination, process injection detection, or memory-resident malware investigation.

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。

aniket2348823/Vul-Agent22026年6月9日 更新

graphify

無料

Use for any question about a codebase, its architecture, file relationships, or project content — especially when graphify-out/ exists, where the question should be treated as a graphify query first. Turns any input (code, docs, papers, images, videos) into a persistent knowledge graph with god nodes, community detection, and query/path/explain tools.

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。

PP-Namias/Portfolio22026年10月13日 更新

Implements visual regression testing with screenshot comparison, diff detection, and CI integration using Playwright or Chromatic. Use when users request "visual testing", "screenshot testing", "UI regression", "visual diff", or "Chromatic setup".

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。

sathishssj3/Stereix-Engine22026年10月4日 更新

Detects leaked API keys, tokens, passwords, and credentials in code with pre-commit hooks, CI checks, scanning rules, and remediation procedures. Use for "secret scanning", "credential detection", "API key leaks", or "secret management".

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。

sathishssj3/Stereix-Engine22026年10月4日 更新

Optimizes CI pipelines for monorepos by detecting affected packages/apps and running only necessary builds and tests. Includes Turborepo/Nx strategies, caching, and parallel execution. Use for "monorepo CI", "affected detection", "incremental builds", or "workspace optimization".

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。

sathishssj3/Stereix-Engine22026年10月4日 更新

Implements content safety filters with PII redaction, policy constraints, prompt injection detection, and safe refusal templates. Use when adding "content moderation", "safety filters", "PII protection", or "guardrails".

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。

sathishssj3/Stereix-Engine22026年10月4日 更新

Defines database performance monitoring strategy with slow query detection, resource usage alerts, query execution thresholds, and automated alerting. Use for "database monitoring", "performance alerts", "slow queries", or "DB metrics".

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。

sathishssj3/Stereix-Engine22026年10月4日 更新

Implements complete dark/light mode theming systems using CSS variables, Tailwind dark mode, React context, and system preference detection. Use when users request "add dark mode", "theme toggle", "dark theme", "light mode switch", or "color scheme".

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。

sathishssj3/Stereix-Engine22026年10月4日 更新

Identifies API latency hotspots and bottlenecks with profiling tools, slow endpoint detection, suspected causes, and fix roadmap. Use for "latency profiling", "performance bottlenecks", "slow APIs", or "backend performance".

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。

sathishssj3/Stereix-Engine22026年10月4日 更新

Evil Twin / KARMA / Mana access point methodology — rogue AP construction with hostapd-mana / wifiphisher / airgeddon, KARMA universal probe response, Mana selective probe response, captive portal phishing, deauth-driven client coercion to attacker AP, MAC randomization defeat via PNL leak analysis, post-association MITM (DNS, ARP, transparent proxy), credential capture for portal/web/SMB, and detection-evasion tactics. Use to coerce client devices onto an attacker-controlled AP, intercept their traffic, harvest credentials, or deliver payloads via captive portal.

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。

ajtazer/heckit22026年10月7日 更新

hunt-ssti

無料

Arithmetic probes ({{7*7}}→49) confirm the injection point but are not proof of impact. The real goal is OS command execution. Arithmetic detection also fails silently when the app echoes the input back (e.g. inside an HTML attribute like <input value='{{7*7}}'>), producing a false negative even when injection exists.

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。

ajtazer/heckit22026年10月7日 更新

Hunt Session Management vulnerabilities — session fixation (no regeneration on login), insufficient invalidation on logout / password-change / email-change, predictable or low-entropy session IDs, JWT-as-session with no exp/revocation, refresh-token rotation/reuse-detection gaps, OAuth/SSO session linkage, device-bound-session (DBSC) downgrade, and cookie attribute issues (Secure/HttpOnly/SameSite/__Host-). Validate with TWO real sessions (attacker A + victim B), body-diff every 200, and OOB confirmation for theft chains. Medium to Critical (fixation→admin hijack, no-invalidation→persistent ATO).

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。

ajtazer/heckit22026年10月7日 更新

Comprehensive API security testing methodology covering REST, gRPC, and WebSocket attack surfaces. Addresses the full OWASP API Security Top 10 2023 including BOLA/IDOR, broken authentication, excessive data exposure, rate limiting bypass, BFLA, mass assignment, SSRF, and security misconfiguration. Includes REST-specific attacks such as HTTP verb tampering, content-type switching, and parameter pollution. Covers gRPC exploitation through protobuf interception, reflection API enumeration, and metadata injection. Addresses WebSocket vulnerabilities including origin bypass, message injection, and cross-site WebSocket hijacking. Provides tooling guidance for Burp Suite, Postman, grpcurl, websocat, and mitmproxy. Each technique includes detection signatures and defensive indicators so you understand what artifacts your testing leaves behind. Designed for authorized penetration testing engagements against API-driven architectures.

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。

ajtazer/heckit22026年10月7日 更新

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 a...

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。

ajtazer/heckit22026年10月7日 更新

HTTP request smuggling checklist: CL.TE, TE.CL, TE.TE variants, detection with timing and differential responses, WAF bypass, cache poisoning, credential hijacking, and request smuggling via HTTP/2. Use when testing reverse proxy/load balancer configurations.

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。

ajtazer/heckit22026年10月7日 更新

Business logic vulnerability testing for web/mobile/API engagements. Covers workflow bypass, state machine violations, multi-step process abuse, price/quantity/discount manipulation, currency confusion, coupon stacking, refund/chargeback abuse, race conditions on logic boundaries, parameter tampering for hidden flows, role/tenant boundary violations, time-of-check vs use, anti-automation defeat, fraud-detection evasion, and subscription/quota abuse. Use when scoping an application after surface-level OWASP Top 10 has been covered, or when the asset is a transactional/marketplace/fintech/e-commerce/SaaS app where logic flaws produce direct financial impact.

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。

ajtazer/heckit22026年10月7日 更新

Comprehensive OSINT methodology for external red-team operations and authorized attack-surface assessments. Covers the 5-stage recon pipeline (seed discovery, asset expansion, enrichment, exposure analysis, reporting), asset-graph discipline with 29 asset types, severity rubric (CRITICAL/HIGH/MEDIUM/LOW/INFO), confidence upgrade workflows, time budgeting, asset-level triage rules, scale-based tactics, identity-fabric mapping (Entra/Okta/ADFS/Google/SAML/M365 Teams+SharePoint+OAuth), API and auth-map methodology, JavaScript deep analysis, mobile attack surface, cloud attack surface, breach×identity correlation, detectability tagging, detection-aware probing (back-off, persona rotation), read-only validator discipline, WAF/CDN bypass + origin discovery, vulnerability prioritization (CVE/EPSS/KEV), phishing infrastructure planning + pretext development, bug bounty submission templates, client deliverable templates with risk translation, threat-actor investigation (incl. RU/CN pivots), cryptocurrency tracing,...

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。

ajtazer/heckit22026年10月7日 更新

Web2 recon pipeline — subdomain enumeration (subfinder, Chaos API, assetfinder), live host discovery (dnsx, httpx), URL crawling (katana, waybackurls, gau), directory fuzzing (ffuf), JS analysis (LinkFinder, SecretFinder), continuous monitoring (new subdomain alerts, JS change detection, GitHub commit watch). Use when starting recon on any web2 target or when asked about asset discovery, subdomain enum, or attack surface mapping.

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。

ajtazer/heckit22026年10月7日 更新