Results for “source-attribution”

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

Verify supply chain integrity for AI agent plugins, tools, and dependencies by generating SHA-256 manifests, detecting tampered files, auditing dependency pinning, and enforcing promotion gates.

Detect and exploit Broken Object Level Authorization (BOLA) and Insecure Direct Object Reference (IDOR) vulnerabilities in APIs and web applications.

Assess software supply chain security by generating SBOMs, scanning dependencies, auditing CI/CD pipelines, analyzing container images, and verifying vulnerability reachability.

Audits source code across C++, Android, iOS, and Web to classify files, detect embedded third-party libraries, and produce four-level verdicts with interactive HTML reports.

Orchestrator for the learn-from suite - auto-detects source type (academic paper, GitHub repo, blog/web article, or in-conversation learnings) and routes to the correct sub-skill for credibility check, security scan, insight extraction, and application. Load when the user says "learn from", "learn from this", "extract insights from", "apply learnings from", "what can we learn from", or provides a URL, file path, or pasted content that should be ingested as knowledge. Single entry point for all learning workflows.

Use when authorship order, CRediT contribution roles, or AI-assistance attribution must be recorded transparently for a manuscript, when an author dispute needs an evidence trail, or before a contributorship statement is required at submission; this skill maintains the human-attribution ledger of who contributed what and in which role (authorship order, CRediT taxonomy, revision responsibilities), which is distinct from the disclosure-metadata audit owned by ai-disclosure-auditor.

Develops comprehensive threat actor profiles for APT groups, criminal organizations, and hacktivist collectives by aggregating TTP documentation, historical campaign data, tooling fingerprints, and attribution indicators from multiple intelligence sources.