investigate

[Skill Scanner] Outbound data post or form upload via curl/wget detected BENIGN with caution. The fragment describes a legitimate incident investigation workflow intended to guide an AI agent through reproducible, auditable root-cause analysis and documentation. No hardcoded secrets or suspicious payloads are evident. The pattern of invoking external tooling is standard for this domain, but should be executed under strict access controls and with validated inputs to avoid leakage of logs or credentials. Security risk is moderate due to potential exposure of environment/log data through automated tooling, but the stated purpose remains coherent and proportionate. LLM verification: This skill is a legitimate incident investigation playbook rather than malware, but it contains multiple operational and supply-chain risks that could be abused: unguarded listing of production envs, outbound probes to attacker-supplied endpoints, unpinned third-party CLIs, and insufficient redaction and approval controls for sensitive outputs. Recommend applying mitigations before automating: require explicit human approval for env listings and external probes, enforce automated redaction of se