Results for “pattern”

Provides expert patterns for implementing Clerk authentication in Next.js, including middleware, server components, client hooks, organizations, and webhooks.

Performs comprehensive SQL code review across all major databases, analyzing security, performance, maintainability, and anti-patterns.

Detect abuse of service accounts through anomalous interactive logons, privilege escalation, lateral movement, and unauthorized access patterns.

Implements secure API design patterns including authentication, authorization, input validation, rate limiting, and protection against common vulnerabilities.

Detect suspicious PowerShell execution patterns including encoded commands, download cradles, AMSI bypass attempts, and constrained language mode evasion.

Guides implementing authentication, authorization, input validation, and OWASP Top 10 prevention with secure code patterns and validation checkpoints.

Reverse engineers stripped Go and Rust binaries by recovering runtime metadata, symbols, panic strings, and idiomatic decompilation patterns.

Manages BIND9 DNS servers by discovering zones, validating configuration, checking DNSSEC status, and reporting query patterns and statistics.

Production-quality Bash scripts for Solana vanity generation, keypair verification, batch operations, dependency auditing, and test orchestration — with security-hardened patterns including file permissions, input validation, and cleanup traps.

Quick reference for PostgreSQL best practices covering query optimization, schema design, indexing, Row Level Security, and connection pooling.

age file encryption reference — the modern, simple alternative to GPG. Covers key generation, X25519 encryption, SSH key support, passphrase mode, pipe patterns, SOPS integration, YubiKey plugins, and security considerations. By Filippo Valsorda.

age file encryption reference — the modern, simple alternative to GPG. Covers key generation, X25519 encryption, SSH key support, passphrase mode, pipe patterns, SOPS integration, YubiKey plugins, and security considerations. By Filippo Valsorda.

Master smart contract security best practices to prevent common vulnerabilities and implement secure Solidity patterns. Use when writing smart contracts, auditing existing contracts, or implementing security measures for blockchain applications.

Analyzes token implementations and integrations for ERC20/ERC721 conformity, weird token patterns, contract composition, owner privileges, and on-chain scarcity.

Analyzes email security including phishing dissection, SPF/DKIM/DMARC authentication checks, BEC fraud patterns, and OAuth token abuse research for authorized reviews.

Covers Firebase Authentication, Firestore, Realtime Database, Cloud Functions, Storage, and Hosting, with patterns for security rules, data modeling, and real-time listeners.

Hardens code against vulnerabilities by applying threat modeling, OWASP Top 10 prevention patterns, and secure coding practices for web applications.

Investigate AWS account compromises by querying CloudTrail logs to reconstruct attacker activity, identify compromised credentials, and analyze API call patterns.

Runs Semgrep static analysis with custom YAML rules, supporting taint tracking, metavariable comparisons, and pattern-not-inside exclusions for precise vulnerability detection.

Blocks Claude from finishing a session until deterministic quality checks pass: learning library freshness, disk space, and rationalization pattern detection.

Hunt for adversary persistence via Windows Scheduled Tasks by analyzing task creation events, suspicious task actions, and unusual scheduling patterns.

Hunt for unusual network connections by analyzing outbound traffic patterns, rare destinations, non-standard ports, and anomalous connection frequencies from endpoints.

Production-grade multi-threaded Rust vanity address generator for Solana — 100K+ keys/sec using Rayon parallel iterators with solana-sdk, Base58 pattern matching, prefix/suffix support, security-hardened file output, and Criterion benchmarks.

Provides comprehensive security patterns for Perl applications covering taint mode, input validation, safe file operations, SQL injection prevention, and web security.

Reviews and hardens GitHub Actions workflows against injection, privilege escalation, supply-chain, and token-scoping risks that pattern matchers miss.

Analyzes smart contract codebases against Trail of Bits' secure development guidelines, generating documentation, reviewing architecture and upgradeability patterns, assessing implementation quality, identifying pitfalls, and providing prioritized recommendations.

Hunt for web shell deployments on internet-facing servers by analyzing file creation in web directories, suspicious process spawning from web servers, and anomalous HTTP patterns.

Detect and prevent API enumeration attacks including BOLA and IDOR exploitation by monitoring sequential identifier access patterns and authorization failures.

Scan files, directories, and memory dumps using YARA rules to identify malware families, suspicious patterns, and IOC matches.

Detects prompt injection attacks targeting LLM-based applications using regex pattern matching, heuristic scoring, and DeBERTa transformer classification.

Automatically discover, classify, and protect sensitive data in S3 buckets using machine learning and pattern matching for PII, financial data, and credentials detection.

Secure Perl applications against injection, taint, and web vulnerabilities with validated patterns for input handling, file operations, process execution, and DBI queries.

Scans Python and JavaScript codebases for bugs, security vulnerabilities, code smells, and anti-patterns, producing a prioritized fix list with line numbers, severity ratings, and suggested corrections.

Hunt for adversary persistence and execution via Windows scheduled tasks by analyzing task creation events, suspicious task properties, and unusual execution patterns.

Build network traffic baselines from NetFlow/IPFIX data using Python pandas for statistical analysis, z-score anomaly detection, and hourly/daily traffic pattern profiling.

Detect and prevent privilege escalation in Kubernetes pods by monitoring security contexts, capabilities, and syscall patterns with Falco and OPA policies.