Results for “blind-injection”

SQL injection occurs when untrusted user input is interpolated directly into database queries, allowing attackers to alter query logic. Detect via single-quote errors, boolean-based blind responses (AND 1=1 vs AND 1=2), time-delay payloads (SLEEP, WAITFOR), UNION column enumeration, and error messages from MySQL, Oracle, MSSQL, PostgreSQL. Tools: sqlmap, sqlbftools, Burp Suite, wfuzz with SQLi fuzz strings.

JNDI injection playbook. Use when Java applications perform JNDI lookups with attacker-controlled names, especially via Log4j2, Spring, or any code path reaching InitialContext.lookup().

Detect and defend against prompt injection hidden in documents, web pages, and images consumed by an agent.

Vision-language pre-training framework bridging frozen image encoders and LLMs. Use when you need image captioning, visual question answering, image-text retrieval, or multimodal chat with state-of-the-art zero-shot performance.

Recommends that all diabetes insipidus patients wear an emergency bracelet or necklace to alert clinicians to their condition if incapacitated. Use when establishing care for a diabetes insipidus patient; triggers include diabetes insipidus diagnosis.

Vision-language pre-training framework bridging frozen image encoders and LLMs. Use when you need image captioning, visual question answering, image-text retrieval, or multimodal chat with state-of-the-art zero-shot performance.

Fine-tune and deploy CLIP vision-language models for zero-shot classification, image-text retrieval, and embedding extraction with ONNX and TensorRT support.

Fine-tune, evaluate, run inference, and export Cosmos-Embed1 video-text embedding models for tasks like text-to-video retrieval and semantic deduplication.

Wire Promptfoo and DeepTeam into CI/CD for automated regression red-teaming of LLM apps against OWASP LLM Top 10 and OWASP Agentic presets, failing the build when jailbreak or injection vulnerabilities regress.

Design a visual protest action that generates media coverage for a cause without requiring budget or platform access.

Approach an app, tool, codebase, website, or product as a genuine first-time user with zero insider context — try it out using only the information provided, get confused where a real newcomer would, and surface the "obvious" questions that people who built or use the thing daily can no longer see. Use this whenever the user wants a first-time-user test, a fresh perspective, a naive walkthrough, a cold read of their README/onboarding/docs/UI, or says things like "pretend you've never seen this", "would a new user get this?", "test my app like a beginner", "what would confuse someone new?", or "give me fresh eyes on this". Also use it when someone wants to find gaps in onboarding, docs, or first-run experience — even if they don't say "fresh eyes" explicitly.

Validates observable behavior of apps, CLIs, APIs, and generated artifacts against a prewritten contract without inspecting source code.

Configure Hilt dependency injection with proper scoping, modules, and constructor injection in Android. Use when changing the production Hilt graph; defer test overrides, Room wiring, navigation-specific scopes, and generic DI explanations to their specific skills.

Integrates endpoint health signals from CrowdStrike ZTA, Microsoft Intune, and Jamf into conditional access policies to enforce device compliance before granting resource access.

NIH grant research skill for clinical researchers. Grill-me intake (research idea + career stage + preliminary data + environment + submission posture + known institute targets) locks down the funding strategy before any search runs. Runs a 5-facet Consensus positioning analysis (with draft Significance/Innovation language), maps the research to the right NIH institutes and study sections via RePORTER, finds NOSIs and funded overlap, and produces an editable Word document (.docx) with budget/scope-aware mechanism recommendations, submission timelines, and a mandatory program officer recommendation. Use when the user asks about research funding or makes any grant-related request (e.g., 'grants for [topic]', 'find grants for my research idea', 'what grants match my research', 'help me find NIH funding', 'grant opportunities for my research'). NIH-only scope — non-NIH funders (PCORI, DOD CDMRP, VA, foundations) are out of scope and flagged at intake.

Team-Wiki Ingest

Clinicians educate adrenal insufficiency patients taking nondexamethasone glucocorticoids who initiate enzyme-inducing antiepileptic drugs about early signs of adrenal insufficiency. Trigger when an AI patient on nondexamethasone GC starts an enzyme-inducing AED such as phenytoin, carbamazepine, or oxcarbazepine.

Prevents AI-introduced regressions with sandbox-mode API testing, automated bug-check workflows, and patterns that catch blind spots where the same model writes and reviews code.

Rereads code, specs, plans, reviews, or skill edits with fresh eyes to catch blunders, oversights, and omissions before closure, reporting concrete evidence-backed findings.

Multimodal proposal brief intake — turns text, audio, or video into a structured, completeness-checked brief.md. Use when the user pastes a client brief, drops a voice memo or call recording, shares a video brief, asks to 'intake a proposal', 'structure this brief', or starts a new proposal run. Triggers: 'intake this brief', 'transcribe this recording', 'structure the brief', 'new proposal from voice memo', 'parse this RFP brief'.

info-to-ink

当需要进入高度专注、高效且愉悦的心流状态以完成创造性或学习性任务时

Cross-runtime 2-stage pipeline for Claude Code, Codex/OMX, and Gemini/Antigravity/OMA: trace causal hypotheses, inject evidence into deep-interview style requirements crystallization, then hand off to the right runtime planner/executor.

Run NVIDIA garak probe suites against an LLM endpoint to test for jailbreaks, prompt injection, data leakage, and toxic generation, then interpret the hit-rate report for triage and reporting.

Complete bedside prescribing reference for Mirago (mirabegron, beta-3 adrenoceptor agonist) for overactive bladder — covering contraindications, safety screening, drug interactions, dose selection in special populations, titration, and administration. Use when a clinician asks how to start mirabegron, what dose to use in renal or hepatic impairment, is mirabegron safe in this patient, mirabegron drug interactions, or Mirago for OAB.

Agent validation v4.3.0 — Make agents act effectively by disabling harmful actions, lowering gates, and injecting cross-run learning

Analyzes prompt injection, retrieval poisoning, memory contamination, planner drift, and tool-boundary abuse in agentic systems, mapping trust boundaries and proving exploit chains.

PUA Shot — compact all-in-one PUA reference for explicit injection into sub-agents or short sessions. Strong flavor, same evidence-first behavior.

Read-only OWASP LLM Top 10 audit of app-facing AI features: prompt injection, data leak, supply chain, poisoning, unsafe output, excessive agency, system-prompt leak, RAG/embedding risks, misinformation, unbounded consumption. Use when "audit LLM security", "prompt injection", "jailbreak my chatbot", "is my AI safe".

Suggests oral contraceptives over injectable contraceptives for women with BMI ≥27 kg/m2 with comorbidities or BMI ≥30 kg/m2 seeking contraception, provided they are well‑informed and oral contraceptives are not contraindicated. Triggers include clinician questions such as “Which contraceptive method is less likely to cause weight gain in this obese patient?” or “Should I recommend oral pills instead of depot injection for this patient with BMI 29 and hypertension?”.

Designs chaos experiments, creates failure injection frameworks, and facilitates game day exercises for distributed systems — producing runbooks, experiment manifests, rollback procedures, and post-mortem templates.

2-stage pipeline: trace (causal investigation) -> deep-interview (requirements crystallization) with 3-point injection

Instrument a shipped product's AI agents with tracing and observability so you can see what they did, why outputs happened, and what each run cost. Plain-language primer plus free-tier-first backend selection (Langfuse, Phoenix, LangSmith, Braintrust) and OpenTelemetry/OpenInference instrumentation. Load when the user asks to add observability, add tracing, instrument my agents, see what my agent is doing in production, set up Langfuse or Phoenix or LangSmith, debug why my agent gave a bad answer, or track LLM cost per request. Also fires when agent-system-architecture or setup-evaluation requires an observability plan for an agent-chain product. NOT for tracing the coding agent itself — that is run-trace. Precondition for runtime-learning-loop.

Executes Atomic Red Team tests mapped to MITRE ATT&CK techniques, performs coverage gap analysis, and runs detection validation loops to measure blue team visibility.