Results for “threat-modeling”

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

Performs security audits, hardening, threat modeling (STRIDE/PASTA), red/blue team exercises, OWASP checks, code review, incident response, and infrastructure security for any project.

Runs security audits, threat modeling, and hardening for code and infrastructure, covering OWASP checks, code review, incident response, and red/blue team exercises.

Every methodology — STRIDE, PASTA, LINDDUN, attack trees — is a technique for

Runs a six-phase security audit covering attack-surface mapping, STRIDE/PASTA threat modeling, technical checklists, red/blue team exercises, and a final verdict, plus incident-response and monitoring guidance.

Intelligent pattern selection for Fabric CLI. Automatically selects the right pattern from 242+ specialized prompts based on your intent - threat modeling, analysis, summarization, content creation, extraction, and more. USE WHEN processing content, analyzing data, creating summaries, threat modeling, or transforming text.

Runs a structured security audit across six phases: attack-surface mapping, STRIDE/PASTA threat modeling, technical checklists, red/blue team analysis, and a final verdict, with optional Python automation scripts.

Performs a white-box source code security review structured around OWASP ASVS 5.0, mapping attack surfaces, tracing data flows, and chaining into downstream penetration testing and threat modeling skills.

Runs a structured 6-phase security audit covering attack-surface mapping, STRIDE/PASTA threat modeling, technical checklists, red/blue team exercises, and a final verdict, plus incident-response and monitoring playbooks.

Use when designing new systems, features, or integrations to identify potential security threats and vulnerabilities before they are exploited. This skill provides a structured approach to threat identification, risk assessment, and mitigation planning.

Performs STRIDE-A threat model analysis of repositories and systems, producing architecture overviews, DFD diagrams, prioritized findings, and executive assessments. Supports both single analysis and incremental updates with change tracking.

Model threat actors, intrusion sets, campaigns, and TTPs as a STIX 2.1 knowledge graph in OpenCTI using the pycti Python client, connectors, and import workers for structured cyber threat intelligence.

Detect insider threats by modeling normal user and entity behavior with Elasticsearch, computing anomaly scores, and correlating low-confidence indicators into high-confidence alerts.

Detect poisoned training data and backdoored models across the ML pipeline using statistical analysis, activation clustering, and spectral signatures.

Transform threat intelligence and attack patterns into testable hunting hypotheses for proactive threat detection.

Runs a structured security audit across six phases: attack-surface mapping, STRIDE/PASTA threat modeling, technical checklists, red/blue team exercises, and a final verdict, covering code, infrastructure, APIs, bots, payments, AI agents, and compliance.

Proactively hunt for threats by analyzing IOCs, detecting behavioral anomalies in telemetry, and prioritizing signals mapped to MITRE ATT&CK.

Assess AI/ML systems for prompt injection, jailbreak vulnerabilities, model inversion risk, data poisoning exposure, and agent tool abuse, with MITRE ATLAS mapping and guardrail recommendations.

Ingests, normalizes, and enriches structured and unstructured threat intelligence feeds into STIX 2.1 format, evaluating feed quality and deduplicating indicators for distribution to SIEM, firewall, and EDR platforms.

Build automated threat intelligence enrichment pipelines in Splunk Enterprise Security using lookup tables, modular inputs, and the Threat Intelligence Framework.

Security Craft

Systematically evaluates evidence to determine which threat actor is responsible for a cyber operation using the Diamond Model and Analysis of Competing Hypotheses.

Proactively hunts for Advanced Persistent Threat activity using hypothesis-driven searches across endpoint telemetry, network logs, and memory artifacts.

Hunt for spearphishing campaign indicators across email logs, endpoint telemetry, and network data to detect targeted email attacks.

Detect insider threat behavioral indicators including unusual data access, off-hours activity, mass file downloads, privilege abuse, and resignation-correlated data theft.

Systematically collects, categorizes, and distributes indicators of compromise (IOCs) during and after security incidents to enable detection, blocking, and threat intelligence sharing.

Correlates disparate security incidents, IOCs, and adversary behaviors across time and organizations to identify unified threat campaigns and attribute them to common threat actors.

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

Build comprehensive threat actor profiles using open-source intelligence (OSINT) techniques to document adversary motivations, capabilities, infrastructure, and TTPs for proactive defense.

Hunt for supply chain compromise indicators including trojanized software updates, compromised dependencies, unauthorized code modifications, and tampered build artifacts.