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 skill provides a systematic method to map observed Indicators of Compromise (IOCs) and threat actor TTPs to the global MITRE ATT&CK framework. It guides users in building technique coverage heatmaps using the ATT&CK Navigator, identifying critical detection gaps, and generating actionable threat intelligence reports across Enterprise, Mobile, and ICS domains. Ideal for SOC analysts, threat hunters, and security researchers seeking structured threat analysis.

Timesketch is a powerful, open-source tool for security teams to build collaborative forensic timelines. It ingests, normalizes, and analyzes multi-source event data—including logs, artifacts, and Plaso outputs—to reconstruct complex attack chains and document incident investigations. Ideal for joint analysis and deep dive DFIR work.

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.

Conducts comprehensive, sector-specific threat landscape assessments by profiling key threat actors, mapping attack vectors, and detailing associated MITRE ATT&CK TTPs (covering financial, healthcare, energy, etc.). Utilizing sophisticated data analysis via Python stacks and integrating real-time threat intelligence feeds (ISAC, CVEs), this tool generates highly actionable intelligence for risk management, security investment prioritization, and high-level board-level reporting on industry exposure.

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.

AWS Detective automatically analyzes log data from CloudTrail, VPC Flow Logs, GuardDuty, and EKS audit logs to build interactive behavior graphs. This tool enables security analysts to investigate suspicious activity, trace lateral movement across accounts, profile compromised entities (IAM users, EC2 instances), and reconstruct complex attack timelines without manual log parsing. Ideal for triaging GuardDuty findings or investigating suspected AWS compromises.

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.