「across」の検索結果

Incident response workup for a lead in hand — an alert, an IOC, or a /dnr-hunt finding. Scopes the lead across the logs, verdicts whether the attack succeeded, quantifies blast radius, confirms root cause in source with a local PoC, and writes a proposed (never executed) containment/remediation/recovery plan. Use when asked to "respond to this alert", "work this incident", "how bad is this", or "run dnr-respond". /dnr-hunt is the no-alert entry to the same track.

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Hunts for the other instances of a bug already found — the variants of one root cause across a codebase. Use immediately after a vulnerability, logic bug, or bad pattern turns up in a specific file and the question becomes where else it occurs, including the bare conversational form ("are there others like this?", "is this the same bug?"). Also for generalizing one known instance into a CodeQL or Semgrep query for its whole pattern family, and for triaging a set of look-alike candidates against a known root cause. Not for initial discovery with no bug in hand.

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Validates cryptographic implementations against Project Wycheproof's test vectors, which encode known attacks and edge cases across AES, RSA, ECDSA, ECDH, and more. Covers loading test vectors, mapping result flags onto pass and fail expectations, and reading a failure. Use when testing a crypto implementation against known attacks, checking a library against standard test vectors, or investigating why two implementations disagree on the same input.

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Sets up and runs AFL++ for multi-core fuzzing of C/C++ projects built with afl-clang-fast or afl-gcc-fast. Covers instrumentation modes, parallel main and secondary campaigns, persistent mode, corpus minimization, and crash triage. Use when scaling fuzzing across cores, fuzzing a mature C/C++ codebase, reading the afl-fuzz status screen, or moving on after libFuzzer has plateaued.

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Builds and queries multi-language source and binary code graphs for security analysis. Includes pre-analysis passes for blast radius, taint propagation, privilege boundaries, entry point enumeration, proxy/unresolved-call tracking, type/reference queries, structural traversal, graph diffs, audit augmentation, declared cross-language/FFI/external links via `.trailmark/links.toml`, and SQL schema graphs. Use when analyzing call paths, mapping attack surface, finding complexity hotspots, enumerating entry points, tracing taint propagation, measuring blast radius, importing SARIF/weAudit/binary findings, linking source graphs across language or RPC boundaries, or building a code graph for audit prioritization. Feature-gate version-specific Trailmark APIs before using them; prefer `trailmark.parse.detect_languages()` or `--language auto` when the target language is unknown or polyglot.

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Validates security patches with reproducible baseline-versus-patched evidence, including original exploits, root-cause variants, behavior preservation, regressions, and newly introduced security failures. Use after a patch exists and before accepting, merging, or reporting it as fixed; also use when an AI-generated patch, remediation commit, pull request, or proposed upstream fix needs adversarial post-patch validation across any language.

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Interprets Culture Index (CI) surveys, behavioral profiles, and personality assessment data. Supports individual profile interpretation, team composition analysis (gas/brake/glue), burnout detection, profile comparison, hiring profiles, manager coaching, interview transcript analysis for trait prediction, candidate debrief, onboarding planning, and conflict mediation. Accepts extracted JSON or PDF input via OpenCV extraction script. Use when the user shares a Culture Index PDF or JSON profile, asks what someone's CI traits mean, compares Culture Index profiles across a team or against a hiring profile, or asks about burnout risk from Survey-versus-Job gaps.

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Comprehensive CI/CD pipeline exploitation methodology covering GitHub Actions injection vectors (expression injection via PR titles and issue bodies, workflow_run event abuse, GITHUB_TOKEN over-scoping, composite action supply chain compromise), Jenkins attack paths (Groovy sandbox escapes, script console remote code execution, Java remoting deserialization, credential store dumping, shared library injection), GitLab CI exploitation (YAML anchor injection, runner registration token abuse, CI variable extraction, protected branch bypass via merge request pipelines), and Azure DevOps pipeline agent compromise with service connection theft. Includes artifact poisoning techniques across all platforms, tooling guidance for gato and jenkins-attack-framework, and maps to MITRE ATT&CK T1195.002 (Supply Chain Compromise: Compromise Software Supply Chain). Covers enumeration of pipeline configurations, privilege escalation from contributor to code execution, lateral movement through pipeline trust boundaries, and persistence via modified workflow definitions. Each technique section provides working exploitation code, detection indicators, and defensive countermeasures.

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Dense description covering Server-Side Template Injection across Jinja2, Twig, Freemarker, Velocity, Pebble, Smarty, Mako, Handlebars, ERB, Thymeleaf, EJS, Pug. Engine fingerprinting, filter bypass, blind exploitation, WAF evasion, SSTI-to-RCE chains. Tools: tplmap. CWE-1336. MITRE T1190. Use when testing template rendering endpoints or exploiting template injection for code execution.

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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.

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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.

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Comprehensive methodology for auditing and exploiting TLS/SSL implementations and misconfigurations across network services and mobile applications. Covers protocol downgrade attacks including POODLE (CVE-2014-3566) against SSLv3 CBC padding, DROWN (CVE-2016-0800) cross-protocol attack leveraging SSLv2 export ciphers to decrypt TLS sessions, and FREAK (CVE-2015-0204) forcing RSA export-grade key exchange. Addresses BEAST (CVE-2011-3389) exploiting CBC IV predictability in TLS 1.0, CRIME (CVE-2012-4929) and BREACH targeting TLS-level and HTTP-level compression oracles respectively, and Heartbleed (CVE-2014-0160) for OpenSSL memory disclosure. Covers certificate validation bypass techniques for applications with improper hostname verification or chain validation, certificate pinning bypass using Frida and Objection for mobile application interception, HSTS bypass via NTP manipulation and subdomain exploitation, TLS 1.3 0-RTT replay attacks against non-idempotent endpoints, mutual TLS (mTLS) authentication attacks including client certificate theft and relay, and Certificate Transparency log monitoring for reconnaissance. Primary tooling includes testssl.sh for comprehensive TLS auditing, sslyze for Python-integrated scanning, sslscan for quick cipher enumeration, and tlsx for high-speed TLS probing at scale. Maps to CWE-295 (Improper Certificate Validation), CWE-319 (Cleartext Transmission of Sensitive Information), and CWE-757 (Selection of Less-Secure Algorithm During Negotiation).

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Insecure deserialization exploitation across Java, PHP, .NET, Python, Node.js, and Ruby. Covers gadget chain construction with ysoserial/phpggc/ysoserial.net, ObjectInputStream and BinaryFormatter sink identification, pickle __reduce__ RCE, phar:// wrapper abuse, Jackson polymorphic typing, Json.NET TypeNameHandling, ViewState tampering, node-serialize IIFE injection, Ruby Marshal.load and YAML.load gadgets, framework-specific chains for Spring/Hibernate/Laravel/Symfony, modern attack surfaces including Kubernetes admission webhooks and message queue consumers, WAF bypass through encoding layers and content-type manipulation, and serialVersionUID/JMX/RMI vectors. Activate when the engagement involves deserialization sinks, serialized data in cookies or request bodies, gadget chain development, magic method abuse, ysoserial payload generation, or any review of marshalling and unmarshalling logic in target applications.

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Comprehensive secrets extraction methodology targeting CI/CD environments across all major platforms. Covers environment variable extraction from build contexts, exploitation of vault and secrets-manager misconfigurations (HashiCorp Vault, AWS Secrets Manager, Azure Key Vault, GCP Secret Manager), runner and agent token abuse for lateral movement, OIDC federation attacks exploiting trust relationships between CI/CD providers and cloud platforms, build log leakage analysis for inadvertently exposed credentials, cache poisoning techniques for credential exfiltration, platform-specific credential store exploitation (GitHub Actions secrets, GitLab CI variables, Jenkins credential providers), service connection and service account abuse in Azure DevOps and GCP, and Docker registry credential theft from build environments. Maps to MITRE ATT&CK T1552 (Unsecured Credentials) and its sub-techniques. Each section provides enumeration procedures, extraction techniques, and post-exploitation pivoting guidance for using recovered secrets to expand access.

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Comprehensive offensive methodology for software supply chain attacks covering the full kill chain from reconnaissance through exploitation. Addresses dependency confusion across npm, PyPI, and NuGet ecosystems where internal registry override allows an attacker to inject malicious packages that shadow private dependencies. Covers typosquatting techniques for popular packages, compromised package injection via maintainer account takeover or social engineering, and build system attacks through Makefile injection, setup.py install hooks, and npm postinstall scripts. Extends into CI/CD artifact tampering where build outputs are replaced or modified in transit, code signing abuse through stolen or self-signed certificates, upstream repository compromise via commit injection or force-push to trusted repos, and container image supply chain attacks including base image trojaning and registry confusion. Maps to MITRE ATT&CK T1195.001 (Supply Chain Compromise: Compromise Software Dependencies and Development Tools) and T1195.002 (Supply Chain Compromise: Compromise Software Supply Chain). Integrates tooling such as confused for dependency confusion scanning and dependency-check for known vulnerable component detection. Each technique section provides reproducible proof-of-concept patterns, detection guidance for defenders, and engagement-safe execution notes for authorized red team operations.

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Command and Control framework deployment, configuration, and operational tradecraft for red team engagements. Covers Cobalt Strike (malleable C2 profiles, Beacon types HTTP/HTTPS/DNS/SMB, Beacon Object Files for in-memory execution, sleep and jitter tuning, named pipe pivoting), Sliver (implant generation across mTLS/WireGuard/DNS transport, operator multiplayer mode, armory extensions), Mythic (agent ecosystem with Apollo/Poseidon/Medusa, C2 profile configuration, translation containers), Havoc (Demon agent with sleep obfuscation via Ekko/Zilean, indirect syscalls, dotnet inline execution), Metasploit (msfvenom payload generation, multi/handler staging, Meterpreter post-exploitation modules), redirector architecture using Apache mod_rewrite and Nginx, domain fronting through CDN providers, DNS-based C2 for restrictive network egress, and TLS certificate management for infrastructure OPSEC. Tools: Cobalt Strike, Sliver, Mythic, Havoc, Metasploit Framework. Aligns to MITRE ATT&CK T1071 (Application Layer Protocol), T1573 (Encrypted Channel), T1090 (Proxy/Connection Proxy).

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Time-of-Check / Time-of-Use (TOCTOU) race condition exploitation methodology across binary, kernel, filesystem, web, and container layers. Covers symbolic-link races (open/access/stat split), file-descriptor races, fopen/realpath traversal races, /proc and procfs races, FUSE-backed slow-fs races to widen the window, ptrace and signal races, kernel double-fetch / userspace pointer races, container/runc/symlink escape primitives, kubernetes admission/authz TOCTOU, web auth-vs-authz TOCTOU, JWT-claim TOCTOU at gateway vs service, payment/idempotency races, and modern race-amplification techniques (single-packet attack, slow loris, FUSE pause, cgroup freeze, scheduler shaping). Use when you've identified a 'check then act' pattern in code, when fuzzing for race conditions, or when exploiting concurrency bugs in privileged binaries / kernel / orchestrators.

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Use when ending a turn, finishing a slice, blocked on another agent's work, or escalating to a human — durable work handoff via queue items so the system keeps moving across compactions, missed messages, and interruptions. Covers the hot-potato terminal-turn-rule (active work ends by passing the ball, not by going idle), default-nudge semantics, and when `--no-nudge` is appropriate for intentional cold park or human gate.

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Use when coordinating assignments, selected review boundaries, or blocked work across a rig.

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Use when the user wants to set up, scale, validate, or harden NVIDIA physical AI infrastructure for synthetic data generation workflows across local MicroK8s or Azure AKS, including Kubernetes clusters, inference endpoint deployment, OSMO deployment, workload submission readiness, and infrastructure failure recovery. Trigger keywords: physical ai infrastructure, resilient scaling, SDG infrastructure, microk8s, azure aks, NVCF deployment, NIM Operator, OSMO deploy, workflow scaling. Don't trigger for: OSMO log summarization or workload-only operations unless infrastructure setup, scaling, validation, or recovery is requested.

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Process, quality-control, annotate, and visualize single-cell or single-nucleus RNA-seq datasets across tissues and species. Use when Codex needs to build, adapt, or review a general scRNA-seq QC pipeline; choose dataset-appropriate cell-level filters from QC distributions; run required scDblFinder-based doublet and ambient-RNA filtering; annotate cells with matched references or marker-based fallbacks; or generate global and per-group UMAP visualizations for large scRNA-seq datasets.

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Research across Notion and synthesize into structured documentation; use when gathering info from multiple Notion sources to produce briefs, comparisons, or reports with citations.

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Route early browser-game work. Use when the user needs stack selection and workflow planning across design, implementation, assets, and playtesting before moving to a specialist skill.

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Triage macOS tests across Xcode and SwiftPM. Use when narrowing failures, explaining assertions or crashes, or separating setup from regressions.

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。