claude-red is a library of structured skills that give Claude specialized offensive-security methods for areas such as web vulnerabilities, shellcode, exploit development, and identity systems. It is intended for authorized red-team work, bug-bounty triage, security research, CTF preparation, and operator training. Its catalogue contains the project's skills for loading these security specializations into Claude.
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 agentmods add skills/snailsploit/claude-red/offensive-social-engineeringnpx skills add SnailSploit/Claude-Red --skill offensive-social-engineeringgit clone --depth 1 https://github.com/SnailSploit/Claude-RedWrote 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/snailsploit/claude-red/offensive-social-engineering)<a href="https://agentmods.dev/skills/snailsploit/claude-red/offensive-social-engineering"><img src="https://agentmods.dev/badge/skills/snailsploit/claude-red/offensive-social-engineering.svg" alt="Measured on agentmods" height="20"></a>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 | $0.00268 | $0.05184 |
| Opus 5 | $0.00134 | $0.02592 |
| Sonnet 5 | $0.00054 | $0.01037 |
| Haiku 4.5 | $0.00027 | $0.00518 |
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 6d 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 — 577 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
- Conduct OSINT to map the target organization's structure, key personnel, physical locations, and communication patterns.
- Develop personas and pretexts tailored to the engagement objectives (credential theft, physical access, data exfiltration).
- Prepare infrastructure: VoIP numbers for vishing, SMS gateways for smishing, cloned badges for physical access.
- Execute attacks in phases -- start with remote vectors (vishing, smishing), escalate to physical if in scope.
- Document every interaction with timestamps, recordings (where legally permitted), and outcomes.
- 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."
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.
- 6d ago First seen · 577 lines · 268 tokens per session scan A 415cc4d61afb
offensive-social-engineering is a skill published in the GitHub repository SnailSploit/Claude-Red (3,026 stars, last pushed 6d ago), licensed MIT. It adds 268 tokens to every session and 5,184 once invoked, about $0.0013 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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