Individual skill
prompt-injection
Hunt LLM prompt injection and tool-call hijacking in modern AI-integrated applications (CWE-1427). Covers indirect injection via RAG, tool abuse, exfiltration chains, and jailbreak-to-RCE pivots on agentic systems.
packages/decepticon/decepticon/skills/standard/analyst/prompt-injection/SKILL.md
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- Last checked
- Nov 8, 2026
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- Nov 7, 2026
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- Apache-2.0
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- agent Repository topic
- ai Repository topic
- cybersecurity Repository topic
- hacking Repository topic
- langchain Repository topic
- langgraph Repository topic
- llm Repository topic
- generative-ai Repository topic
- pentesting Repository topic
- pentest Repository topic
- engineering Derived category
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# Prompt Injection Playbook
Every product shipping an LLM interface in 2026 has this surface. The
bug bounty payouts are high because nobody has a clean defense, and the
chain impact is unbounded (prompt injection → tool call → exfil → RCE
in the agent's sandbox).
## 1. Target inventory — what counts as an LLM application
- Chatbots with document upload / RAG
- IDE copilots and code-review bots
- Email assistants (classic indirect-injection vector)
- Browser agents / AI-powered scraping tools
- Customer support bots with CRM tool access