Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add PlamenTSV/plamen --skill governance-attack-vectorsgit clone --depth 1 https://github.com/PlamenTSV/plamenWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/plamentsv/plamen/governance-attack-vectors)<a href="https://agentmods.dev/skills/plamentsv/plamen/governance-attack-vectors"><img src="https://agentmods.dev/badge/skills/plamentsv/plamen/governance-attack-vectors/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/plamentsv/plamen/governance-attack-vectors"><img src="https://agentmods.dev/badge/skills/plamentsv/plamen/governance-attack-vectors.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to high
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- high Anti-Refusal · line 125 Skill instructs the agent to never refuse or to always comply. Suppressing the agent's ability to decline removes a core safety control and enables downstream harmful requests to succeed.Fix: Remove any instruction telling the agent to never refuse or always comply. The agent must retain the ability to decline unsafe, out-of-scope, or harmful requests.
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00046 | $0.01769 |
| Opus 5 | $0.00023 | $0.00885 |
| Sonnet 5 | $0.00009 | $0.00354 |
| Haiku 4.5 | $0.00005 | $0.00177 |
Grade A, and why
governance-attack-vectors scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 9d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 147 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Injectable Skill: Governance Attack Vectors
Protocol Type Trigger:
governance(detected when Governor, Timelock, voting, proposal, quorum, delegate patterns found) Inject Into: Breadth agents, depth-external, depth-edge-case Language: EVM only (Solana has structural mitigations via token locking; Move governance is less standardized) Finding prefix:[GOV-N]
Orchestrator Decomposition Guide
When decomposing this skill into depth agent investigation questions, map sections to domains:
- Section 1: depth-external (flash loan voting, external token interactions)
- Section 2: depth-state-trace (proposal lifecycle state, execution integrity)
- Section 3: depth-edge-case (quorum boundaries, threshold edge cases)
- Section 4: depth-state-trace (delegation state, vote counting)
When This Skill Activates
Recon detects governance patterns: Governor, TimelockController, propose, castVote, execute, queue, quorum, getVotes, delegate, votingPower, or DAO framework imports.
1. Flash Loan Voting Analysis
1a. Vote Power Source
Identify how voting power is determined:
- Snapshot-based (block number checkpoint) or live balance?
- If snapshot: when is the snapshot taken? (proposal creation, vote start, or fixed intervals)
- If live balance: can voting power be acquired via flash loan within the voting transaction?
1b. Snapshot Manipulation Window
If snapshot-based:
- Is there a delay between proposal creation and snapshot? (proposal → delay → snapshot → voting)
- Can an attacker acquire tokens BEFORE snapshot and return them AFTER? (multi-block attack)
- Is the snapshot block predictable? Can attacker front-run to accumulate tokens in the snapshot block?
1c. Delegation Flash Attack
For delegation-based voting:
- Can delegation be changed within the same block as voting?
- Pattern: flash borrow tokens → delegate to self → vote → undelegate → return tokens (single tx if no snapshot or snapshot is current block)
- Is
delegate()subject to the same snapshot asgetVotes()?
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 9d ago First seen · 147 lines · 46 tokens per session scan A 84955d46f85f
governance-attack-vectors is a skill published in the GitHub repository PlamenTSV/plamen (294 stars, last pushed today), licensed MIT. It adds 46 tokens to every session and 1,769 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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