Results for “perigon”

Prüft Preisangaben nach PAngV 2022 auf Gesamtpreis, Grundpreis, Versandkosten und Streichpreis mit 30-Tage-Regel; liefert Checkliste, Prüfmemo und Musterauszeichnung.

Enumerating failure modes via pre-mortem analysis. Systematically identifies failure scenarios for plans, designs, and features, scoring them with RPN/AP. Does not write code.

Generates at most one token recommendation and one prediction-market pick per run, each with a falsifiable thesis, entry, sizing, and kill criterion. Returns NO_PICK when no candidate meets the bar.

Run a pre-mortem risk analysis on a PRD or launch plan, categorizing risks as Tigers (real problems), Paper Tigers (overblown concerns), and Elephants (unspoken worries), then classifying by urgency and creating action plans.

Run a pre-mortem risk analysis on a PRD or launch plan. Categorizes risks as Tigers (real problems), Paper Tigers (overblown concerns), and Elephants (unspoken worries), then classifies as launch-blocking, fast-follow, or track. Use when preparing for launch, stress-testing a product plan, or identifying what could go wrong.

Exploit the Zerologon vulnerability (CVE-2020-1472) in the Netlogon Remote Protocol to achieve domain controller compromise by resetting the machine account password to empty.

Automates multi-source enrichment of IPs, domains, URLs, and file hashes using VirusTotal, AbuseIPDB, Shodan, GreyNoise, URLScan.io, and MISP to provide contextual risk scoring and disposition recommendations for SOC analysts.

Provides guidance for performing causal interventions on PyTorch models using pyvene's declarative intervention framework. Use when conducting causal tracing, activation patching, interchange intervention training, or testing causal hypotheses about model behavior.

Provides guidance for performing causal interventions on PyTorch models using pyvene's declarative intervention framework. Use when conducting causal tracing, activation patching, interchange intervention training, or testing causal hypotheses about model behavior.

Cross-platform Python library for quantum computing, quantum machine learning, and quantum chemistry. Enables building and training quantum circuits with automatic differentiation, seamless integration with PyTorch/JAX/TensorFlow, and device-independent execution across simulators and quantum hardware (IBM, Amazon Braket, Google, Rigetti, IonQ, etc.). Use when working with quantum circuits, variational quantum algorithms (VQE, QAOA), quantum neural networks, hybrid quantum-classical models, molecular simulations, quantum chemistry calculations, or any quantum computing tasks requiring gradient-based optimization, hardware-agnostic programming, or quantum machine learning workflows.

Generates custom safety policies for NVIDIA Nemotron content-safety guardrails, producing a Markdown policy, JSON taxonomy, and inference prompts from rough user input.

Scans agent skills for security issues including prompt injection, malicious scripts, excessive permissions, secret exposure, and supply chain risks.

Audits project dependencies for supply chain risks including single maintainers, unmaintained packages, low popularity, high-risk features, past CVEs, and missing security contacts.

Reduces peak GPU memory in Megatron Bridge training by applying expandable segments, parallelism resizing, activation recompute, and CPU offloading constraints.

Detect and respond to Adversary-in-the-Middle (AiTM) phishing attacks that use reverse proxy kits like EvilProxy, Evilginx, and Tycoon 2FA to bypass MFA and steal session tokens.

Run a trademark clearance search before adopting a new brand name, mark, or logo and risk-rate it clear, caution, or high-risk with a proceed/modify/abandon recommendation.

Perform causal interventions on PyTorch models using pyvene's declarative framework for causal tracing, activation patching, and interchange intervention training.

Expert guidance for proactive threat hunting. Use this when the user asks to "hunt" for threads, IOCs, or specific TTPs.

Systematically collects, categorizes, and distributes indicators of compromise (IOCs) during and after security incidents to enable detection, blocking, and threat intelligence sharing.

Detect container escape attempts using runtime security tools like Falco, Sysdig, and custom seccomp/audit rules.

Detect and prevent public-over-private name resolution in npm, PyPI, and Maven dependency manifests.

Audits trending open-source repos for exploitable vulnerabilities using Semgrep, TruffleHog, osv-scanner, and Slither, then routes findings to responsible disclosure channels (PVR for code flaws, public PRs for dependency CVEs).

High-fidelity ASCII/Braille rendering via the Risomorphism-1911 pipeline — edge-aware downsampling, presets, quality gates, and eikon mirror workflows

Agent profile for PPC and paid-growth risk review before changing ads, budgets, bidding, tracking, or landing pages.

Detect insider threat behavioral indicators including unusual data access, off-hours activity, mass file downloads, privilege abuse, and resignation-correlated data theft.

Flag misspelled, brandjacked, and typosquatted package names across npm, PyPI, and crates.io before installation using edit-distance, keyboard-proximity, and known-target corpus matching with typomania, OSSGadget, and pypi-scan.

Calculate portfolio risk metrics including VaR, CVaR, Sharpe, Sortino, and drawdown analysis. Use when measuring portfolio risk, implementing risk limits, or building risk monitoring systems.

Higher-precedence research helper with risky setup.

Molecular machine learning toolkit. Property prediction (ADMET, toxicity), GNNs (GCN, MPNN), MoleculeNet benchmarks, pretrained models, featurization, for drug discovery ML.

Write and deploy Falco rules with the modern eBPF driver to detect container escape, namespace abuse, privileged mounts, and anomalous syscalls at runtime in Kubernetes and Docker.

Returns structured prediction-market data for Polymarket, Kalshi, Limitless, Opinion, Predict.Fun, dFlow, and UMA oracle via a local API, covering markets, cross-venue search, leaderboards, smart money, wallet analytics, identity clustering, and resolution status.

Assess Active Directory security posture using PingCastle, BloodHound, and Purple Knight to identify misconfigurations, privilege escalation paths, and attack vectors.

Utilize Shodan, the search engine for Internet-connected devices, to discover exposed assets, vulnerable ports, default credentials, and specific infrastructure configurations using advanced search queries (dorks).

Proactively hunt for threats by analyzing IOCs, detecting behavioral anomalies in telemetry, and prioritizing signals mapped to MITRE ATT&CK.

Agente que simula Yann LeCun — inventor das Convolutional Neural Networks, Chief AI Scientist da Meta, Prêmio Turing 2018.