Results for “functions”

Detects and prevents code injection attacks targeting serverless functions (AWS Lambda, Azure Functions, Google Cloud Functions) through event source poisoning, malicious layer injection, runtime command execution, and IAM privilege escalation via function modification. The analyst combines static analysis of function code, CloudTrail event correlation, runtime behavior monitoring, and IAM policy auditing to identify injection vectors across the expanded serverless attack surface including API Gateway, S3, SQS, DynamoDB Streams, and CloudWatch event triggers. Activates for requests involving Lambda security assessment, serverless injection detection, function event poisoning analysis, or serverless privilege escalation investigation.

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Expert patterns for Azure Functions development including isolated worker model, Durable Functions orchestration, cold start optimization, and production patterns. Covers .NET, Python, and Node.js programming models.

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Expert patterns for Azure Functions development including isolated worker model, Durable Functions orchestration, cold start optimization, and production patterns. Covers .NET, Python, and Node.js programming models.

The English summary is being prepared. Showing the original description.

Detects and prevents code injection attacks targeting serverless functions (AWS Lambda, Azure Functions, Google Cloud Functions) through event source poisoning, malicious layer injection, runtime command execution, and IAM privilege escalation via function modification. The analyst combines static analysis of function code, CloudTrail event correlation, runtime behavior monitoring, and IAM policy auditing to identify injection vectors across the expanded serverless attack surface including API Gateway, S3, SQS, DynamoDB Streams, and CloudWatch event triggers. Activates for requests involving Lambda security assessment, serverless injection detection, function event poisoning analysis, or serverless privilege escalation investigation.

The English summary is being prepared. Showing the original description.

Add on-device language model features to iOS 26+ apps with Apple's FoundationModels framework. Covers text generation, summarization, extracting data into Swift types, calling custom app functions, and progressively updating screens as responses are generated.

• Adding offline text generation and summarization
• Extracting structured data from user input
• Connecting AI responses to custom app functions

Review and refine code using shared conventions for clear names, readability, error handling, and updates that preserve original data. Identify duplication, oversized functions, and unnecessary complexity to make code easier to understand and maintain.

• Reviewing names and readability in existing code
• Refactoring long functions and deeply nested logic
• Standardizing coding conventions for a new module

Find TypeScript values that bypass type checking through any, including inferred types and assertions. Suggest unknown, generics that preserve type relationships, or Zod validation for external data, with the checks needed where each value is used.

• Addressing ESLint warnings about explicit any
• Reviewing type safety around external API data
• Checking functions that pass any to their callers

Use SymPy to simplify expressions, solve equations, and calculate derivatives, integrals, and matrices with exact symbolic results. Specify assumptions, verify solutions, and turn mathematical expressions into numerical functions, source code, or LaTeX output.

• Solving equations and checking their solutions
• Calculating symbolic derivatives, integrals, and limits
• Finding matrix eigenvalues with exact arithmetic

Use PyTDC to discover therapeutic machine-learning datasets, create task-appropriate training and test splits, and evaluate predictions against curated benchmarks. Also score selected molecules with supported scoring functions, with explicit download plans and bounded outputs.

• Find datasets for therapeutic machine-learning tasks
• Plan and create task-appropriate data splits
• Evaluate predictions with benchmark-specific metrics

Build real-time voice assistants in JavaScript or TypeScript using Azure AI Voice Live. Covers two-way audio streaming, authentication, speech turn detection, transcription events, and calling application functions during conversations in Node.js or browsers.

• Build a voice assistant in Node.js
• Stream microphone audio from a browser
• Configure speech boundaries and transcription events

Build and deploy AWS Lambda functions without managing servers. Guidance covers APIs, scheduled jobs, event triggers, permissions, shared dependencies, and performance tuning, with code and command examples for deployment and troubleshooting.

• Building lightweight APIs with API Gateway or function URLs
• Running scheduled jobs with EventBridge
• Processing S3 uploads or SQS messages

Build AWS applications that run without managing servers directly. Covers Lambda functions, APIs, DynamoDB storage, message-driven workflows with SQS/SNS, deployment through SAM/CDK, and reducing the delay when a function starts for the first time.

• Building an API with Lambda and API Gateway
• Developing an application backed by DynamoDB
• Designing event-driven workflows with SQS/SNS

Build persistent agents on Azure AI Foundry with the Microsoft Agent Framework Python SDK. Connect functions, search, and MCP tools, preserve conversation context, stream responses, and return data in a defined structure.

• Building an agent that preserves conversation context
• Connecting Python functions and hosted search tools
• Displaying responses as they arrive

Record a website's browser traffic, identify its internal API, and generate a script, command-line tool, or library that calls it directly. Turn recorded search and browsing flows into reusable functions, then verify them against live responses.

• Build a command-line tool for a website
• Turn repeated searches into direct API calls
• Inspect request and response structures from recordings

Analyze binaries with Ghidra to locate important functions, follow references, and inspect decompiled code, a readable approximation of the original program. Support both interactive investigation and automated batch analysis without a graphical interface.

• Analyzing binaries when an IDA license is unavailable
• Locating important functions through strings and imported APIs
• Running batch decompilation or analysis in CI

Prepare GRPO reinforcement learning configurations for tasks with programmatically checkable answers, such as math, code, and structured output. Design and inspect reward functions, then select training variants when runs show instability or exploit flaws in scoring.

• Preparing GRPO training for tasks with automatic correctness checks
• Designing rewards for output format and correctness
• Inspecting reward scores before training

Write JavaScript and TypeScript tests with Jest, Vitest, and Testing Library. Covers functions, UI components, and APIs, including mock replacements for external services, reusable test data, and setup for automated testing.

• Set up testing for a new project
• Test functions and API error handling
• Check React component behavior

Convert Oracle stored procedures and functions, programs stored inside a database, into PostgreSQL equivalents. Preserve parameters and control flow while adapting Oracle syntax, resolving types, and mapping text sorting rules to the target environment.

• Convert Oracle procedures to PostgreSQL
• Resolve parameter types from table definitions
• Map text sorting rules during migration

Review PostgreSQL code for database design, performance, and security issues. Get improvement suggestions covering JSONB, a binary JSON format, arrays, indexes, custom data types, functions, extensions, and rules that control access to individual rows.

• Reviewing JSONB and array queries
• Checking table types and constraints
• Improving functions and triggers

Analyze Go malware binaries in Ghidra by extracting build metadata, function names, dependencies, and relevant strings. Use GoResolver to help recover obscured names and organize functions so analysts can focus their reverse engineering work.

• Investigating the structure of a Go malware sample
• Recovering function names from stripped or obfuscated binaries
• Identifying embedded Go modules and dependencies

Set up model training with torchforge for reinforcement learning, where rewards guide improvement. Covers training configurations, custom reward and loss functions, and distributed execution with Monarch and TorchTitan, keeping algorithm experiments separate from infrastructure concerns.

• Train mathematical reasoning models with GRPO
• Experiment with custom reward and loss functions
• Scale training across multiple GPUs or nodes

Review code changes against the previous commit and identify affected files and functions. Use dependency relationships to assess risk, check missing tests, and produce a focused report with issues and recommendations.

• Reviewing changes against the previous commit
• Checking how a change affects other functions
• Finding missing tests for high-risk changes

Write unit tests for FastGPT code, covering normal behavior, edge cases, and errors. It guides test placement, limits mocks that replace real dependencies, and checks TypeScript errors and coverage, the share of code exercised by tests.

• Adding unit tests for individual functions
• Testing edge cases and error handling
• Testing functions that make API requests

Assess company health across eight areas, including finance, revenue, people, and operations. Turn available metrics into scores and traffic light ratings, identify risks across departments, and outline improvement priorities while flagging missing data.

• Prepare a company health overview for a board review
• Identify departments that need attention
• Examine risks spreading across business functions