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llm-security

Authorized security assessment of LLM applications and AI agents: prompt injection, tool abuse, RAG exposure, memory poisoning, system-prompt extraction, and agent-compliance engineering

SKILL.md metadata excerpt. This is the source’s description, not an instruction to this site.

sickn33/agentic-awesome-skillsskills/llm-security/SKILL.md

Before you use it

Input
Not independently summarized. Check the source’s scope and examples.
Expected output
Not independently summarized; do not assume a ready-to-use artifact.
Prerequisites
Review the source instructions, scripts, accounts and tools in your intended environment.

Installation guidance is not individually established for this example. Read the source and confirm its requirements.

Publisher documentation, static file observations and environment tests are different kinds of evidence. Runtime behavior has not been observed.

Study the method

Start with the task scope and instructions, then inspect supporting files and examples. Compare the workflow with your own inputs, constraints and intended result.

File and folder counts are unknown, not zero.

The supporting file list has not been read for this source. Open the source directory to inspect it.

Zero files in scripts/ does not mean no execution, network access or file writes. Markdown and other folders may describe or contain executable behavior.

Source version and requirements

Observed
2026-09-12T10:44:01.656Z
Source commit
bdfbf79ccaabdc31f60ce60ef1703a9abe95f9c3
Content SHA-256
9dedaad267d44a048d2a2d9a6e4646c717b8e81fb12f287affb04a9aaace784d
License
Unknown
Author attribution
Repository owner: sickn33. Individual authorship is not independently established.

This page describes a pinned source snapshot, not the latest repository state. Changes after this commit have not been reconciled here. A repository license does not necessarily cover external models, datasets or services.

Open current repository ↗
Reference note and manual copy