Results for “teresa-torres”

Extract Kerberos tickets from LSASS memory, inject them into an attacker session, and perform lateral movement to access remote systems as the impersonated user.

Enumerate Active Directory service accounts, request Kerberos TGS tickets, and crack them offline to assess password strength and privilege escalation paths.

Provides Ktor server patterns including routing DSL, plugins, authentication, Koin DI, kotlinx.serialization, WebSockets, and testApplication testing.

Scan Tor hidden services, underground forums, paste sites, and dark web marketplaces to identify threats targeting an organization, including leaked credentials, data breaches, and threat actor discussions.

Build type-safe, testable Node.js/Deno backends using fp-ts with ReaderTaskEither, functional dependency injection, and service composition patterns.

Implement data access patterns, Scaling, Migrations, and ORM selection in NestJS. Use when implementing TypeORM/Prisma repositories, migrations, or database patterns in NestJS.

Migrates .NET Framework code using Thread.Abort to cooperative cancellation with CancellationToken in modern .NET 6+.

Enable MIPI/GMSL camera sensors on a Jetson Thor or Orin custom carrier by rendering a kernel-DT overlay from the in-tree sensor DTSI.

Detect Kerberoasting attacks by monitoring for anomalous Kerberos TGS requests targeting service accounts with SPNs for offline password cracking.

Escribe mensajes de commit, PRs e issues con tono humano en español rioplatense o técnico en inglés, siguiendo reglas de atomicidad, límite de 300 líneas y verificación previa de tests.

Create IEP templates for individualized education. TRIGGERS - Use when user needs help with iep-template related tasks.

Plan and execute a comprehensive red team engagement covering reconnaissance through post-exploitation using MITRE ATT&CK-aligned TTPs to evaluate an organization's detection and response capabilities.

Organizes PyTorch code with a Trainer class, automatic distributed training (DDP/FSDP/DeepSpeed), callbacks, and minimal boilerplate. Scales from laptop to supercomputer with the same code.

High-level PyTorch framework with Trainer class, automatic distributed training (DDP/FSDP/DeepSpeed), callbacks system, and minimal boilerplate. Scales from laptop to supercomputer with same code. Use when you want clean training loops with built-in best practices.

Builds and trains deep learning models with PyTorch, including tensors, autograd, and neural network modules.