Security & Risk Management

PiraAI isn’t just about speed and alpha — it’s about resilience. In a world where honeypots, rugpulls, MEV attacks, and social manipulation are rampant, agents must be able to defend themselves like hardened war machines.

This module suite transforms PiraAI agents into on-chain firewalls, capable of detecting, avoiding, and reacting to malicious vectors in real time.

🛡️ Threat vs. Response Matrix

Threat Category	Example Attack Pattern	PiraAI Agent Response
Scam Token Deployments	Fake liquidity + locked token function	Contract risk scan → Block TX → Alert user
Honeypots	Cannot sell token after buy	Simulated TX → Flag sell lock → Auto-exit
MEV Sandwiching	Slippage spike before & after TX	MEV Monitor → Insert delay/cancel → Reprice
Rugpull LP Removals	Liquidity removed seconds after big pump	Watch LP pool → Auto-sell if below threshold
Social Manipulation	Influencer pumps → exits silently	KOL + Wallet tracking → Detect divergence

Scenario Simulation: Agent in the Wild

Scenario: A new memecoin launches on Solana. Twitter explodes.

🔻 What the average user does: Buys based on hype, unaware of token mechanics. Gets rugged or trapped in honeypot.

🛡️ What PiraAI agent does:

• Simulates the buy + sell cycle on devnet

• Checks token contract bytecode for:

  • Transfer taxes

  • LP lock status

  • Proxy upgradeability

• Monitors KOL wallet: buys but no sells → raises confidence

• Executes only after 3 security checkpoints pass

✅ Result: Agent buys early and exits before rug pull hits.

Agent Resilience Index

Category	PiraAI Agent Score	Traditional Bot
Scam Avoidance	High	❌ Low
Rugpull Protection	High	⚠️ Medium
Front-run Resistance	Moderate	❌ Low
Social Doxing Avoid	High	❌ None
Response Latency	Sub-second	⚡ Comparable

Portfolio Management

PiraAI agents are not just reactive bots. They're capital allocators — equipped with real-time, adaptive logic to size positions, preserve gains, and execute dynamic rebalancing across volatile asset classes (especially memes, microcaps, and low-liquidity tokens).

What Makes It Different?

Capability	Description
Position Sizing Algorithms	Implements strategies like Kelly Criterion, Volatility Sizing, and Adaptive VaR to determine optimal trade size per signal confidence.
Risk-Aware Execution Layer	Prevents overexposure during low-liquidity or high-slippage moments (common in meme launches).
P&L Anchoring Mechanism	Tracks session-based or rolling profit thresholds → auto-reduces risk once gain targets are met.
Stop-Loss Triggers (on-chain)	Agents can execute full or partial exits based on price deviations, liquidity drain, or KOL divergence.