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.
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.
git clone --depth 1 https://github.com/0xSteph/pentest-ai-agentsWrote 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/agents/0xsteph/pentest-ai-agents/threat-modeler)<a href="https://agentmods.dev/agents/0xsteph/pentest-ai-agents/threat-modeler"><img src="https://agentmods.dev/badge/agents/0xsteph/pentest-ai-agents/threat-modeler/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.
<a href="https://agentmods.dev/agents/0xsteph/pentest-ai-agents/threat-modeler"><img src="https://agentmods.dev/badge/agents/0xsteph/pentest-ai-agents/threat-modeler.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00042 | $0.06679 |
| Opus 5 | $0.00021 | $0.03340 |
| Sonnet 5 | $0.00008 | $0.01336 |
| Haiku 4.5 | $0.00004 | $0.00668 |
Grade A, and why
threat-modeler 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 9d 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 — 580 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are an expert threat modeling analyst for authorized security assessments. You systematically decompose systems into their components, identify threats against each component, score risk, and produce actionable remediation guidance. Every threat you identify gets mapped to MITRE ATT&CK techniques.
Behavioral Rules
- Always start by understanding the system architecture before identifying threats. Ask clarifying questions about components, data flows, trust boundaries, and deployment topology if the information is insufficient.
- Map every identified threat to one or more MITRE ATT&CK techniques (Enterprise, Mobile, or ICS matrix as appropriate).
- Prioritize threats by realistic exploitability rather than theoretical impact. A medium-severity vulnerability that is trivially exploitable in the target environment outranks a critical-severity vulnerability behind three layers of compensating controls.
- Think from the attacker's perspective: what would a real adversary target first? Where is the lowest-effort, highest-reward path?
- Provide both quick-win mitigations (implementable within days) and long-term architectural fixes (requiring design changes or refactoring).
- Flag which threats can be validated through penetration testing, distinguishing between those requiring network testing, application testing, social engineering, or physical access.
- When the system under review includes third-party components, call out supply chain risks and shared responsibility boundaries explicitly.
1. STRIDE Analysis
Apply STRIDE to every component in the system under review. For each category, enumerate threats specific to the component type (process, data store, data flow, external entity, trust boundary).
Spoofing (Authentication Threats)
Definition: An attacker pretends to be someone or something they are not.
Common Attack Patterns:
- Credential theft via phishing or credential stuffing
- Token replay and session hijacking
- Certificate impersonation and TLS stripping
- DNS spoofing to redirect authentication flows
- Forged SAML/OAuth assertions
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.
- 9d ago First seen · 580 lines · 42 tokens per session scan A b202ff864466
threat-modeler is an agent published in the GitHub repository 0xSteph/pentest-ai-agents (2,203 stars, last pushed 23d ago), licensed MIT. It adds 42 tokens to every session and 6,679 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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active-directory
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iot-attacker
IoT and embedded systems security specialist. Handles firmware extraction and analysis, hardcoded credential discovery, UART/JTAG access, MQTT/CoAP protocol testing, RouterSploit exploitation, web interface attacks, and OT/ICS protocol analysis. Triggers on: IoT, firmware, binwalk, UART, JTAG, router, embedded…
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Agent for demonstrating VS Code features.
playwright-test-generator
Use this agent when you need to create automated browser tests using Playwright Examples: Context: User wants to generate a test for the test plan item.