Skill UI

Offensive cloud security methodology for AWS, Azure, and GCP. Covers identity discovery, credential harvesting, enumeration, privilege escalation, persistence, data exfiltration, lateral movement, serverless abuse, Kubernetes paths, and detection evasion during authorized assessments.

This skill uses Python and boto3 to analyze AWS CloudTrail logs. It establishes statistical baselines of normal API activity and detects various anomalies, such as unusual event sources, first-time API usage, geographic IP deviations, and high-frequency calls. This is critical for identifying credential compromise, privilege escalation, and unauthorized resource access in a security incident.

Deploy and operate Falco with the modern eBPF driver in Kubernetes and Docker. Covers driver selection, Helm installation, output channels, and the built-in ruleset that detects container escape, namespace abuse, privileged mounts, and anomalous syscalls. Ideal for enabling runtime security, routing alerts to SIEM or Falcosidekick, and upgrading existing deployments.

Implements a comprehensive defense-in-depth framework for autonomous AI agents that interact with external tools. It mitigates risks like prompt injection or tool misuse by enforcing strict tool allowlisting, binding tools to least-privilege identities, requiring human-in-the-loop approval for high-impact actions, and utilizing policy enforcement (like NeMo Guardrails) to bound the blast radius and ensure compliance.

This tool serves as a pre-flight safety check for legal prompts before submission to third-party AI surfaces (e.g., ChatGPT, Claude). It assesses whether the content risks compromising attorney-client privilege or work-product protection. The output provides a structured safety band (SAFE/CAUTION/STOP), detailed triggered risk factors, a discovery impact summary, and a legally safe, redacted rewrite.

This skill audits the security and integrity of legal AI components, including skills, prompts, workflows, and tools. It proactively detects prompt injection, malicious code, data exfiltration paths, and supply-chain risks before deployment or trust. Essential for maintaining confidentiality, privilege, and adhering to legal standards in AI environments.