Skill UI

This tool parses API Gateway access logs from various providers (AWS, Kong, Nginx). It performs statistical analysis using pandas to detect critical security threats such as Broken Object Level Authorization (BOLA/IDOR), credential stuffing, rate limit bypass attempts, and injection vulnerabilities. Ideal for SOC analysts or security engineers investigating API abuse and building advanced threat detection rules.

This system deploys advanced AI, NLP, and behavioral analytics to detect sophisticated Business Email Compromise (BEC) attacks. Unlike traditional filters that rely on malicious links, this solution analyzes writing style, tone, grammatical patterns, and contextual anomalies to identify pure social engineering impersonation, providing a robust defense layer against advanced phishing and fraud.

This skill detects advanced cyber-physical attacks mimicking the Stuxnet pattern. It monitors for unauthorized modifications to PLC logic and detects discrepancies between reported sensor readings and actual physical process behavior. Ideal for high-security OT/ICS environments when hunting for APT lateral movement or validating process integrity against sophisticated threats.

This skill provides structured methods for detecting credential stuffing attacks by analyzing authentication logs. It focuses on identifying complex patterns such as login velocity anomalies, high IP diversity, password spray techniques, and suspicious geographical distributions of failed logins. It is essential for SOC analysts conducting threat hunting or building robust detection rules against account takeover attempts.

This skill provides comprehensive forensic analysis of cryptocurrency payment flows stemming from ransomware attacks. It leverages blockchain APIs and advanced techniques to identify wallet clusters, track fund movement through obfuscation methods like mixers and peel chains, and map funds to exchanges. It is crucial for law enforcement, incident responders, and threat intelligence analysts conducting ransomware attribution.

This skill provides a comprehensive framework for detecting NTLM relay attacks (T1557.001). It achieves this by correlating Windows Security Event 4624 (LogonType 3) to identify IP-to-hostname mismatches, detecting artifacts from Responder/LLMNR poisoning, and auditing SMB/LDAP protocol signing weaknesses. Use it for proactive threat hunting in Active Directory environments, investigating authentication anomalies, or building SIEM correlation rules.

Provides comprehensive guidelines for researchers packaging and releasing artifacts (data, code, instruments) derived from real communities in CSCW research. It emphasizes ethical constraints, de-identification techniques (such as quote search and join attacks), and best practices for protecting studied communities' privacy, ensuring responsible sharing.

A comprehensive guide for strengthening causal claims in corporate and empirical finance research. This resource details advanced econometric methods—including IV, DiD, RDD, and natural experiments—and provides strategies to preempt common methodological attacks (e.g., endogeneity, parallel-trends violations) required by top-tier academic journals like the Journal of Finance.

This skill calculates and documents the residual re-identification risk of de-identified datasets. It goes beyond simple direct identifier removal by assessing the risk posed by quasi-identifiers (age, ZIP, dates). It computes structural metrics like k-anonymity and l-diversity, and runs empirical linkage attacks to provide a defensible memo supporting HIPAA Expert Determination for determining if a dataset is safe for release.