From soundcheck
Detects RAG pipelines that ingest external documents into LLM context without sanitization or trust gating. Flag vulnerable patterns like direct concatenation, unbounded retrieval, and SSRF-through-fetch.
How this skill is triggered — by the user, by Claude, or both
Slash command
/soundcheck:rag-securityThe summary Claude sees in its skill listing — used to decide when to auto-load this skill
Prevents prompt injection through retrieved documents and uncontrolled content flooding
Prevents prompt injection through retrieved documents and uncontrolled content flooding into LLM context. Attacker-controlled documents can override system instructions, exfiltrate data, or manipulate model behavior when injected without guardrails.
Flag the vulnerable code and explain the risk. Then suggest a fix that establishes these properties. Translate each property into the audited file's language, HTTP client, and LLM API — use the documented secure primitives of that stack.
ssrf skill for outbound HTTP.prompt-injection
skill for the trust-tier pattern.Confirm the response:
npx claudepluginhub thejefflarson/soundcheck --plugin soundcheckDetects direct and indirect prompt injection in LLM applications. Flags user input or retrieved documents that could hijack model instructions, and enforces trust-tier separation, input screening, and output validation.
Probes RAG applications for prompt injection via poisoned retrieved context and embedding manipulation using garak, Promptfoo, and PyRIT.
Assesses AI/LLM application security including prompt injection, jailbreak resistance, OWASP LLM Top 10 (2025), RAG/agent security, and model supply chain risks. Maps findings to MITRE ATLAS and recommends mitigations.