social-engineer

social-engineer is an agent for Claude Code from 0xSteph/pentest-ai-agents. It costs 40 tokens per session (3,861 once invoked), scanned A, original, MIT.

A security-testing agent focused on human behavior, including phishing, pretexting, voice scams, physical social engineering, and security-awareness assessments. Social engineering means manipulating people into revealing information or taking an action.

In plain words
What is it for?
Use it to plan authorized phishing and other human-factor tests, evaluate organizational resilience, and design security-awareness assessments.
Why use it?
It helps organizations test whether people and processes resist realistic attacks and shows where awareness or resilience needs improvement. Its work assumes written authorization for the assessment.

Agent for Claude Code

Written for Claude Code: shipped in a Claude Code plugin. Also seen: model in frontmatter.

Part of the pentest-ai-agents plugin — 3 commands, 52 agents shipped together

Good fit Use it to plan authorized phishing and other human-factor tests, evaluate organizational resilience, and design security-awareness assessments.

Compare 6 agents from other repositories ↓
Install with agentmods
npx agentmods add agents/0xsteph/pentest-ai-agents/social-engineer
About the project

0xSteph/pentest-ai-agents is a collection of Claude Code specialist agents for authorized penetration testing and security research, covering areas such as reconnaissance, web systems, cloud, reverse engineering and detection. Security researchers and penetration testers use it to plan engagements, investigate findings, build detections and write reports. The catalogue entries are the project's own agents, commands and plugin components.

0xSteph/pentest-ai-agents · 2,203 stars · on GitHub · pentestai.xyz

Install

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.

Clone the repo
git clone --depth 1 https://github.com/0xSteph/pentest-ai-agents

Made for: Claude Code.

Or install pentest-ai-agents, the plugin that ships this one along with the rest of its 3 commands, 52 agents.

Wrote 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.

agentmods badge for social-engineer

README.md
[![agentmods](https://agentmods.dev/badge/agents/0xsteph/pentest-ai-agents/social-engineer.svg)](https://agentmods.dev/agents/0xsteph/pentest-ai-agents/social-engineer)
Your own site
<a href="https://agentmods.dev/agents/0xsteph/pentest-ai-agents/social-engineer"><img src="https://agentmods.dev/badge/agents/0xsteph/pentest-ai-agents/social-engineer.svg" alt="Measured on agentmods" height="20"></a>
Per session 40 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 3,861 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00040 $0.03861
Opus 5 $0.00020 $0.01930
Sonnet 5 $0.00008 $0.00772
Haiku 4.5 $0.00004 $0.00386

Measured 8d ago against content hash dff8f9f7f31a, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-08, from the pricing page.

Security

Grade A, and why

social-engineer 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 8d 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.

agents/social-engineer.md · 347 lines

How it starts

The opening of the file, as written. The whole thing — 347 lines — stays where its author put it; the contents beside it link to each section on GitHub.

You are an expert social engineering methodologist supporting authorized red team engagements and security awareness assessments. You provide detailed guidance on human-factor attack techniques, campaign design, and organizational resilience testing.

You operate under the assumption that the user has explicit written authorization (signed rules of engagement, defined scope, legal review) for all social engineering activities. Your role is to be a knowledgeable technical reference for authorized testing.

Core Capabilities

1. Phishing Campaigns (Authorized Testing Only)

ATT&CK: T1566.001 (Spearphishing Attachment), T1566.002 (Spearphishing Link), T1566.003 (Spearphishing via Service)

Infrastructure Setup

Domain Selection:

  • Typosquatting: Character transposition, omission, insertion (e.g., examp1e.com, exampel.com)
  • Homoglyph: Unicode lookalikes, IDN homograph attacks (e.g., Cyrillic а vs Latin a)
  • Keyword domains: Combining target brand with plausible terms (targetcorp-sso.com, targetcorp-secure.com)
  • Expired/aged domains: Acquiring domains with established reputation to bypass domain-age filters
  • Register domains 2-4 weeks before campaign launch to build domain age and reputation

Email Authentication for Deliverability:

  • Configure SPF records for sending infrastructure
  • Set up DKIM signing on the mail server
  • Implement DMARC with appropriate policy
  • Warm up sending IP addresses gradually to build sender reputation
  • Test deliverability against target email gateway before campaign launch

Email Server/Platform:

  • GoPhish: Open-source phishing framework, campaign tracking, template management, landing page hosting
  • King Phisher: Campaign management with geolocation tracking, calendar invites as delivery mechanism
  • Evilginx2: Reverse-proxy phishing framework for MFA bypass testing via session token capture
  • Modlishka: Real-time HTTP reverse proxy for credential and 2FA token interception

Read the full file on GitHub · 347 lines

Changes

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.

  1. 8d ago First seen · 347 lines · 40 tokens per session scan A dff8f9f7f31a

Subscribe to this mod's changes

social-engineer is an agent published in the GitHub repository 0xSteph/pentest-ai-agents (2,203 stars, last pushed 23d ago), licensed MIT. It adds 40 tokens to every session and 3,861 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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