offensive-social-engineering

offensive-social-engineering is a skill for Claude Code, Codex from Miosa-osa/OSA. It costs 193 tokens per session (5,409 once invoked), scanned A, original, Apache-2.0.

A guide to social-engineering techniques used in authorized red-team and physical penetration tests. It covers manipulating people through pretexts, phone-based phishing, and related methods beyond email phishing.

In plain words
What is it for?
It is for planning authorized exercises involving personas, pretexting, voice phishing, caller-ID spoofing, and interactive voice-response systems.
Why use it?
It helps security teams examine how attackers may exploit trust, authority, urgency, or phone systems rather than software alone. Use it only with clear permission and safeguards.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Needs its repository: it runs a file that does not travel with it, so clone the repository first. The line is python3 /tools/responder/Responder.py -I usb0 -wrfb &.

Good fit It is for planning authorized exercises involving personas, pretexting, voice phishing, caller-ID spoofing, and interactive voice-response systems.

Compare 6 skills from other repositories ↓
Install

Getting it into your agent

It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.

Clone the repo
git clone --depth 1 https://github.com/Miosa-osa/OSA
agentmods
npx agentmods add skills/miosa-osa/osa/offensive-social-engineering

Made for: Claude Code, Codex.

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 offensive-social-engineering

README.md
[![agentmods](https://agentmods.dev/badge/skills/miosa-osa/osa/offensive-social-engineering/github.svg)](https://agentmods.dev/skills/miosa-osa/osa/offensive-social-engineering)
Your own site
<a href="https://agentmods.dev/skills/miosa-osa/osa/offensive-social-engineering"><img src="https://agentmods.dev/badge/skills/miosa-osa/osa/offensive-social-engineering/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.

agentmods 80×15 button for offensive-social-engineering

Your own site · 80×15
<a href="https://agentmods.dev/skills/miosa-osa/osa/offensive-social-engineering"><img src="https://agentmods.dev/badge/skills/miosa-osa/osa/offensive-social-engineering.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 193 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 5,409 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 $0.00193 $0.05409
Opus 5.5 $0.00077 $0.02164
Sonnet 5.5 $0.00039 $0.01082
Haiku 4.5 $0.00019 $0.00541

Measured 1mo ago against content hash 81edac63c8b9, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

offensive-social-engineering 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 1mo 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.

priv/skills/offensive-social-engineering/SKILL.md · 617 lines

How it starts

The opening of the file, as written. The whole thing — 617 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Offensive Social Engineering

Social engineering exploits human trust, authority bias, and procedural gaps rather than technical vulnerabilities. While phishing is the most common vector, a comprehensive red team engagement tests the full spectrum: voice calls, text messages, physical access, and planted devices. You are simulating an adversary who combines OSINT, psychological manipulation, and physical access techniques to breach an organization's defenses at the human layer.

Every technique described here requires explicit written authorization. Physical social engineering carries additional legal considerations -- trespassing, impersonation of officials, and recording laws vary by jurisdiction. Confirm your scope covers each vector before execution.

Quick Workflow

  1. Conduct OSINT to map the target organization's structure, key personnel, physical locations, and communication patterns.
  2. Develop personas and pretexts tailored to the engagement objectives (credential theft, physical access, data exfiltration).
  3. Prepare infrastructure: VoIP numbers for vishing, SMS gateways for smishing, cloned badges for physical access.
  4. Execute attacks in phases -- start with remote vectors (vishing, smishing), escalate to physical if in scope.
  5. Document every interaction with timestamps, recordings (where legally permitted), and outcomes.
  6. Debrief with the client; provide actionable recommendations for security awareness and procedural improvements.

Pretexting and Psychological Manipulation

Pretexting is the foundation of all social engineering. You construct a believable scenario that gives you a reason to request information or access. The pretext must hold up under casual scrutiny and, for high-value targets, under deliberate verification.

Persona Development

Build a persona with enough depth to answer follow-up questions. A thin pretext collapses under the first challenge.

Persona Template:
  Name:           [Realistic for the region and industry]
  Role:           [IT support, vendor account manager, building inspector]
  Organization:   [Real vendor the target uses, or plausible third party]
  Contact Info:   [Burner phone, spoofed email, LinkedIn profile]
  Backstory:      [Why you are calling/visiting today]
  Verification:   [What to say if they try to verify your identity]
  Fallback:       [Graceful exit if the pretext fails]

Example -- IT Support Persona:
  Name:           Mark Chen
  Role:           Senior Support Engineer, Contoso IT Services
  Backstory:      Contoso manages the target's endpoint security.
                  Calling about a critical vulnerability patch that
                  requires the user to verify their credentials on
                  a portal to receive the update.
  Verification:   "You can check our contract reference CON-2024-0847
                  with your procurement team."
  Fallback:       "No problem, I will have your account manager
                  Sarah reach out to coordinate instead."

Read the full file on GitHub · 617 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. 1mo ago First seen · 617 lines · 193 tokens per session scan A 81edac63c8b9

Subscribe to this mod's changes

offensive-social-engineering is a skill published in the GitHub repository Miosa-osa/OSA (78 stars, last pushed 11d ago), licensed Apache-2.0. It adds 193 tokens to every session and 5,409 once invoked, about $0.0008 per session on Opus 5.5. 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 2026-09-14.