「attacks」の検索結果

Exact detection thresholds for identifying malicious network patterns including port scans, DoS attacks, and beaconing behavior.

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Stress-test a finding against the choices you did not make. Enumerates the discrete forks a competent analyst could have taken (measure definition, sample filter, control set, clustering level, weighting, functional form), runs the specification grid, and reports the distribution rather than a point estimate — then attacks the identifying assumption with named, computable sensitivity statistics. Use when the user says "is this robust", "challenge this result", "specification curve", "multiverse", "how sensitive is this", "what if I'd used a different measure", "stress-test my estimate", or before a result becomes a headline claim. NOT a reviewer of prose or code — it challenges the CLAIM.

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Use when packaging ACM CCS artifacts for the artifact-evaluation committee and the ACM badges — Artifacts Available, Artifacts Evaluated Functional, Artifacts Evaluated Reusable, and Results Reproduced — covering what security evaluators inspect, how to make attacks and defenses turnkey, and how to justify withheld artifacts.

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Detect, respond to, and prevent software supply chain attacks on package registries, container images, and CI/CD pipelines with lockfile auditing, provenance verification, and emergency response playbooks.

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Defend AI systems against prompt injection and indirect prompt attacks using input controls, tool permissions, output validation, and isolation boundaries.

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Harden AI/LLM deployments against prompt injection, data exfiltration, model theft, and supply chain attacks. Covers input validation, output filtering, access control, model API security, and compliance controls for production AI systems.

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Deploy and tune Web Application Firewalls. Configure rules for OWASP Top 10 protection. Use when protecting web applications from common attacks.

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GitHub Actions security review for workflow exploitation vulnerabilities. Use when asked to "review GitHub Actions", "audit workflows", "check CI security", "GHA security", "workflow security review", or review .github/workflows/ for pwn requests, expression injection, credential theft, and supply chain attacks. Exploitation-focused with concrete PoC scenarios.

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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".

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Use when building or debugging UE5 gameplay: a character with double jump or dash, abilities with cooldowns, enemy AI that patrols, chases and attacks, a health bar or HUD; choosing Blueprint vs C++, GAS or not, StateTree vs Behavior Tree, EQS or Mass; setting up Enhanced Input, Common UI or UMG; replication, RepNotify, save games, World Partition state; "Blueprints are slow", Tick, casts and hard references; "ability won't activate", "enemy ignores the player"; or writing automated gameplay tests with injected input.

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Use when building or debugging Unity gameplay systems: enemy AI that patrols, chases and attacks, NavMesh baking and agents (AI Navigation 2), feet sliding on agents, state machines or behavior trees, physics projectiles that tunnel, the physics spiral, layers and the collision matrix, CharacterController vs Rigidbody characters, object pooling, 'hundreds of enemies', DOTS, Burst or Jobs decisions, Netcode for GameObjects multiplayer, audio mixers, snapshots, volume sliders and 3D combat sounds.

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Use when building gameplay systems in Godot 4.7: enemy AI that patrols, chases and attacks, state machines, behavior trees (LimboAI), NavigationAgent3D pathfinding and avoidance for 100 to 1000 enemies, 'agents stack up' or 'path is empty', hitbox and hurtbox combat, fast bullets going through walls, save and load, inventory, quests, dialogue (Dialogue Manager), input remapping, procedural dungeons, or measuring agent counts and frame time headless.

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This skill should be used when the user asks to "analyze logs for threats", "detect suspicious activity", "scan for brute force attempts", "identify injection attacks", or "audit access patterns for anomalies".

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Produces an adversarial attack on a legal argument that survives reply. Runs the opposing-counsel discipline twice: an unrestrained first pass, then the same instrument turned on that pass to cut every point that collapses under challenge - attacks on conceded facts, wrong-forum objections, speculation about documents and motives, gotchas with innocent explanations, overclaims, self-refuting assertions, and padding. The deliverable is one standalone attack containing only what can be defended, capped at five heads, not a discussion of the discarded draft. Use to attack, stress-test, red-team or rebut a submission, brief, motion, witness statement, letter or structured legal reasoning. Triggers on "attack this but only with points that hold", "no cheap shots", "what survives reply", "which points can I actually defend", "give me the version I can file", "double-pass adversarial review". Also use when an earlier adversarial review came back overlong or scattershot. Formal British English.

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Use for authorized Active Directory and Windows identity attacks including Kerberos, AD CS, BloodHound paths, NTLM relay, and domain privilege escalation research.

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Use when you need to apply Java secure coding best practices — including validating untrusted inputs, defending against injection attacks with parameterized queries, minimizing attack surface via least privilege, applying strong cryptographic algorithms, handling exceptions securely without exposing sensitive data, managing secrets at runtime, avoiding unsafe deserialization, and encoding output to prevent XSS. This should trigger for requests such as Review Java code for secure coding; Find input validation risks in Java code; Review Java code for injection vulnerabilities; Improve secure error handling in Java services; Harden Java code against common security flaws. Part of Plinth Toolkit

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Install-time cooldowns for npm/bun plus a sandboxed pre-install scan for bypasses. Use for supply-chain attacks or npm security.

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Use when assessing cryptography — TLS/PKI auditing, RSA/ECC key attacks, ECDSA nonce lattice recovery, symmetric/AEAD misuse, JWT/JOSE forgery, hash cracking, post-quantum migration review

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Foolbox operating guidance for wrapping vision models, running adversarial attacks, measuring clean and robust accuracy, handling NumPy/PyTorch/TensorFlow/JAX backends, and loading Foolbox-compatible model-zoo repositories.

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Use Adversarial Robustness Toolbox (ART) for estimator wrappers, adversarial attacks, defences, poisoning/privacy/extraction, metrics, and certification workflows.

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ICS/SCADA/OT exploitation - Modbus (502), S7comm (102), EtherNet/IP (44818), DNP3, OpenPLC, Node-RED SCADA, PLC/HMI/coil/holding-register attacks. Use when a target exposes industrial protocols or the goal is to drive a plant to a dangerous state (over-pressure/over-speed/disable interlock) and read the flag the HMI/CCTV reveals.

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Wiki-first "what do I use" lookup - pick the automated TOOL (wiki/tools/), then the PAYLOAD/technique (wiki/payloads/ + wiki/cheatsheets/), for a surface/service/vuln-class BEFORE hand-rolling or working from memory. Use for "tool for <service>", "automated tools for web/<service>", "what should I run on <surface>", "which tool for <X>", "payloads for <X>", "payload arsenal", "cheatsheet for <X>", "how do I exploit <tech/class>", "exploit/attack chain for <X>", "arsenal", any SSRF/XSS/SQLi/SSTI/LFI/JWT/XXE/IDOR/NoSQL/deserialization/CSRF/CORS/CRLF/GraphQL/smuggling/web-cache/OAuth/SAML/MFA/crypto/LDAP/XPath/WebAuthn/file-upload/IMDS/prompt-injection/Modbus ask, plus "privesc arsenal", "CVE arsenal", "default creds", "nuclei templates", "sqlmap/hydra/nmap/bloodhound", "password attacks".

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Harden AI/LLM deployments against prompt injection, data exfiltration, model theft, and supply chain attacks.

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Conducts privacy auditing of AI models including training data extraction testing, membership inference attacks, model inversion testing, and attribute inference assessment. Uses ML Privacy Meter and related tools to quantify privacy leakage. Keywords: model audit, membership inference, privacy meter, model inversion, training data extraction.

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。