Results for “patterns”

Review PostgreSQL code for best practices, anti-patterns, and quality standards including JSONB, arrays, custom types, schema design, functions, and security features like Row Level Security.

Scans Cairo/StarkNet smart contracts for 6 critical vulnerability patterns including arithmetic overflow, L1-L2 messaging issues, and signature replay. Use when auditing StarkNet projects.

Hunt for Pass-the-Hash attacks by analyzing NTLM authentication patterns, identifying Type 3 logons where Kerberos is expected, and correlating with credential dumping indicators.

Parse Windows Prefetch files using the windowsprefetch Python library to reconstruct application execution history, detect renamed or masquerading binaries, and identify suspicious program execution patterns.

Parse NetFlow v9 and IPFIX records to detect volumetric anomalies, port scanning, data exfiltration, and C2 beaconing patterns using the Python netflow library.

Designs and implements backend systems including REST APIs, microservices, database architectures, authentication flows, and security hardening. Covers Node.js/Express/Fastify development, PostgreSQL optimization, API security, and backend architecture patterns.

Detect Kerberos Pass-the-Ticket attacks by analyzing Windows Event IDs 4768, 4769, and 4771 for anomalous ticket usage patterns in Splunk and Elastic SIEM.

Analyze Zeek conn.log and NetFlow data to detect ransomware network indicators including C2 beaconing, TOR exit node connections, data exfiltration, and suspicious DNS patterns.

Conduct a sector-specific threat landscape assessment by analyzing threat actor targeting patterns, common attack vectors, and industry-specific vulnerabilities to inform organizational risk management.

Detect and analyze heap spray attacks in memory dumps using Volatility3 plugins to identify NOP sled patterns, shellcode landing zones, and suspicious large allocations in process virtual address space.

Detect C2 beaconing patterns in network traffic using frequency analysis, jitter detection, and domain reputation to identify compromised endpoints communicating with adversary infrastructure.

Detect sandbox evasion techniques in malware samples by analyzing timing checks, VM artifact queries, user interaction detection, and sleep inflation patterns from Cuckoo/AnyRun behavioral reports.

Performs a full-stack security posture assessment with 0-100 risk scoring, scanning dependencies, code patterns, configuration, and data handling, then produces a prioritized report and routes to specialized skills.

Extracts indicators of compromise (IOCs) from malware samples, including file hashes, network indicators, host artifacts, and behavioral patterns for threat intelligence sharing and detection rule creation.

Captures and analyzes network packet data using Wireshark and tshark to identify malicious traffic patterns, diagnose protocol issues, extract artifacts, and support incident response investigations on authorized network segments.

Parse Apache and Nginx access logs to detect SQL injection, LFI, XSS, scanner fingerprints, and brute-force patterns using regex-based detection, GeoIP enrichment, and statistical anomaly analysis.

Monitors Modbus TCP traffic on SCADA and ICS networks to detect anomalous function code usage, unauthorized register writes, and suspicious communication patterns using deep packet inspection with pymodbus, Scapy, and Zeek.

Analyzes malware command-and-control (C2) communication protocols to understand beacon patterns, command structures, data encoding, and infrastructure for detection development and threat intelligence.

Deploy AI and NLP-powered detection systems to identify business email compromise attacks by analyzing writing style, behavioral patterns, and contextual anomalies that evade traditional rule-based filters.

Provides a security checklist and hardened Solidity patterns for auditing AMM contracts, liquidity pools, and swap flows, covering reentrancy, CEI ordering, donation attacks, oracle manipulation, slippage, admin controls, and integer math.

Parses Kubernetes API server audit logs (JSON lines) to detect exec-into-pod, secret access, RBAC modifications, privileged pod creation, and anonymous API access. Builds threat detection rules from audit event patterns.

Query AWS CloudTrail events with boto3, build statistical baselines of normal API activity, and detect anomalies such as unusual event sources, geographic anomalies, high-frequency API calls, and first-time API usage patterns.

Extract and catalog attack patterns from cyber threat intelligence reports into a structured STIX-based library mapped to MITRE ATT&CK for detection engineering and threat-informed defense.

Reverse-engineers custom JavaScript-based WASM virtual machines and risk-control engines by identifying DSL VM patterns, extracting opcodes, analyzing constant tables, and tracing exported functions through static analysis and runtime injection.

Audits codebases against PCI DSS v4.0, scanning for PAN patterns, CVV storage, and all 12 requirements including network security, encryption, access control, and logging. Estimates SAQ type for payment-handling systems.

Detect and exploit Server-Side Template Injection vulnerabilities across multiple template engines including Jinja2, Twig, Freemarker, and Velocity, with payloads for sandbox escape and remote code execution. Includes detection methodology, bypass techniques, and fix patterns.

Review this PR or diff for quality, security, and maintainability. Use when reviewing pull requests, examining a named change set, or the user asks for a code review of current work. Repo-wide anti-patterns → audit-code-quality. Bulk transform semantics → audit-codemod-safety.

Detect model stealing, model inversion, and membership inference performed through inference-API abuse by monitoring query patterns, applying output perturbation, and red-teaming your own model's extractability.

Identify command-and-control beaconing patterns in network traffic by applying statistical frequency analysis, jitter calculation, and coefficient of variation scoring to detect periodic callbacks from compromised endpoints.

Hunt for adversary abuse of Living Off the Land Binaries (LOLBins) by analyzing endpoint process creation logs for suspicious execution patterns of legitimate Windows system binaries used for malicious purposes.

Detects credential stuffing attacks by analyzing authentication logs for login velocity anomalies, ASN diversity, password spray patterns, and geographic distribution of failed logins using statistical analysis on Splunk or raw log data.

Detect compromised O365 and Google Workspace email accounts by analyzing inbox rule creation, suspicious sign-in locations, mail forwarding rules, and unusual API access patterns via Microsoft Graph and audit logs.

Detect compromised cloud credentials across AWS, Azure, and GCP by analyzing anomalous API activity, impossible travel patterns, unauthorized resource provisioning, and credential abuse indicators using GuardDuty, Defender for Identity, and SCC Event Threat Detection.

Detect NTLM relay attacks by analyzing Windows Event 4624 logon type 3 with NTLMSSP authentication, identifying IP-to-hostname mismatches, Responder traffic signatures, SMB signing status, and suspicious authentication patterns across the domain.

Guide for implementing GDPR-valid consent under Article 7 conditions and Article 4(11) definition. Covers five core requirements: freely given, specific, informed, unambiguous, and clear affirmative action. Includes pre-ticked boxes prohibition per Planet49 CJEU C-673/17, consent form audit checklist, and practical implementation patterns.

VS-Enhanced Academic Style Auditor - Academic Writing Quality Analysis Identifies 24+ writing patterns that reduce scholarly quality, adapted from Wikipedia AI Cleanup guidelines Use when: checking drafts before submission, improving academic writing quality, preparing for style improvement Triggers: writing quality, style audit, pattern check, writing review, academic style check