Individual skill
ai-llm-dos
Unbounded-consumption / denial-of-wallet attacks on LLM apps — force runaway tokens, cost, or latency. Load when testing an LLM product's limits/billing, on "LLM DoS", cost amplification, or resource exhaustion. Signals: user-controlled prompts/max_tokens, agent loops, no rate/'cost caps'.
skills/ai-ml/ai-llm-dos/SKILL.md
Source commit ee0e0c50d2f6d941a14b73dd85a2b470d0ab976e
What was checked
- Matches the observed repository HEAD
- Yes
- Scanner rules are current
- No
- Repository scan complete
- No
- Skill scan complete
- Yes
- Observed behavior
- Not checked yet
- Last checked
- Nov 7, 2026
These are observations at the recorded commit, not a guarantee of safety. Review the source before running it.
Install this skill
Choose an agent in your Stack or copy a command below. Commands fetch the pinned commit and copy only this skill directory. Existing destinations are refused. Copying a command does not install anything.
An install command is unavailable: current rules, complete repository and skill scans, an eligible behavior level and a permitted license are required.
Repository context
- Repository stars (not skill ratings)
- 27
- Repository last updated
- Oct 14, 2026
- License
- MIT
Observed agent integration: No specific integration evidence. Standard SKILL.md installation does not imply verified compatibility.
- agent-skills Repository topic
- ai-agents Repository topic
- ai-security Repository topic
- application-security Repository topic
- blue-team Repository topic
- bug-bounty Repository topic
- claude-code Repository topic
- codex Repository topic
- detection-engineering Repository topic
- gemini Repository topic
- testing Derived category
Files and excerpt
File metadata and permitted, redacted excerpts come from the recorded scan. Source links are pinned to that commit.
Browse files
SKILL.mdcore · 2,393 bytes
Read excerpt
# LLM unbounded consumption (denial-of-wallet)
## When it applies
An LLM feature lets users drive expensive computation with weak limits. Unlike classic DoS, the
damage is often financial (the provider bills per token) — "denial of wallet" — plus latency/availability.
## Why it works
Inference cost scales with tokens and calls. If the app lets users control input size, output
length (`max_tokens`), recursion (agent loops, tool chains), or call volume without hard caps, an
attacker amplifies cost/latency far beyond normal use.
## Method
1. **Input amplification**: send very long inputs, or inputs that induce very long outputs
("repeat X 10000 times", "write an exhaustive…"); push `max_tokens` if client-controlled.