ai-hacker

name	ai-hacker
description	AI and LLM security testing — prompt injection, model manipulation, data exfiltration via AI. Use when testing AI-powered applications, finding prompt injection vulnerabilities, or assessing LLM-integrated systems.
domain	cybersecurity
tags	["cybersecurity","hacker","security","testing","threat-defense"]

Ai Hacker

Overview

Cybersecurity skill for ai hacker. Follows industry best practices and security standards.

When to Use

Trigger phrases:

• "ai hacker"

• "Testing applications with AI/LLM features"

• "Finding prompt injection vulnerabilities"

• "Assessing AI-powered chatbots and assistants"

• Testing applications with AI/LLM features

• Finding prompt injection vulnerabilities

• Assessing AI-powered chatbots and assistants

• Testing AI code generation tools

• Evaluating AI content moderation bypasses

• Finding data leakage through AI models

When NOT to Use

• When you lack proper authorization for testing
• For production systems without change management
• When the task requires legal or compliance expertise beyond technical scope

Prerequisites

• Access to relevant log sources and security tools
• Understanding of hacker fundamentals
• Appropriate permissions for data access and tool operation

Workflow

# Example: IOC detection
import re

IOC_PATTERNS = {
    "ip": r"\b(?:\d{1,3}\.){3}\d{1,3}\b",
    "domain": r"\b[a-z0-9-]+\.[a-z]{2,}\b",
    "hash_md5": r"\b[a-f0-9]{32}\b",
    "hash_sha256": r"\b[a-f0-9]{64}\b",
}

def extract_iocs(text: str) -> dict:
    return {k: re.findall(v, text) for k, v in IOC_PATTERNS.items()}

1. Define Objectives — Clarify the goals and scope for hacker.
2. Gather Resources — Collect tools, data, and access needed for hacker.
3. Execute Process — Carry out hacker operations methodically.
4. Verify Quality — Check results against acceptance criteria.
5. Document Outcomes — Record findings, decisions, and next steps.

Tools

• Analysis Platform — Data processing and visualization
• Collaboration Tools — Team coordination and knowledge sharing

Process

1. Reconnaissance — Gather target information, identify attack surface, enumerate services
2. Analysis/Exploitation — Execute the technique, analyze results, document findings
3. Reporting — Document IOCs, write findings, provide remediation recommendations

Verification

• All hacker procedures executed completely and documented
• Findings validated against multiple data sources
• False positives identified and filtered
• Results documented with evidence and timestamps
• Recommendations provided with risk-based prioritization

Anti-Rationalization

Rationalization	Reality
"We are too small to be targeted"	Automated attacks target everyone. Size does not matter.
"Security slows us down"	A breach slows you down 100x more. Build security in from the start.
"We will fix it after launch"	Vulnerabilities in production are exploited within hours. Fix before deploy.