Decepticon is an autonomous red-team agent that coordinates AI agents, security tools, sandboxes, and supporting services for authorized cybersecurity assessments. Security researchers and red teams can run it through its Docker stack, cloud service, command-line interface, or Python SDK, with the catalogue entries representing its available skills.
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 skills add PurpleAILAB/Decepticon --skill pentest-task-treegit clone --depth 1 https://github.com/PurpleAILAB/DecepticonWrote 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/purpleailab/decepticon/pentest-task-tree)<a href="https://agentmods.dev/skills/purpleailab/decepticon/pentest-task-tree"><img src="https://agentmods.dev/badge/skills/purpleailab/decepticon/pentest-task-tree.svg" alt="Measured on agentmods" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to high
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- high YARA Match · line 29 YARA rule matched a hack tool or exploit indicator (offensive tools, reconnaissance, privilege escalation, or exploit frameworks).Fix: Remove offensive tool references and exploit code. Legitimate agent skills should not contain penetration testing tools, exploit frameworks, or reconnaissance utilities.
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 | $0.00044 | $0.02664 |
| Opus 5 | $0.00022 | $0.01332 |
| Sonnet 5 | $0.00009 | $0.00533 |
| Haiku 4.5 | $0.00004 | $0.00266 |
Grade A, and why
pentest-task-tree scanned grade A with 1 finding 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 4d 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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
Command: wget http://<target>/backup.zip -O backup.zip && unzip -l backup.zip How it starts
The opening of the file, as written. The whole thing — 243 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Pentest Task Tree (PTT) — Session Reasoning Playbook
Authorized use only. This methodology is for certified penetration testers operating under a signed scope-of-work, rules of engagement (RoE), and explicit written authorization. Do not apply to systems you do not own or have written permission to test.
What This Skill Does
The PTT methodology converts a live pentest into a session-stateful, LLM-reasoned task graph. Unlike static checklists, the PTT starts minimal, expands only on discovered evidence, and always exposes a single ranked "next node" to execute — preventing scope creep, cognitive overload, and wasted effort on unconfirmed attack surfaces.
This skill is the live-session reasoning complement to orchestration (multi-agent delegation) and kill-chain-analysis (post-recon vector scoring). Use it when you want a single operator driving a session with a maintained task tree rather than delegating to sub-agents.
PTT Format
1. Reconnaissance [to-do]
1.1 Passive information gathering [completed]
1.2 Active port scan (nmap -sV -sC -p-) [to-do]
1.3 Service fingerprinting [to-do]
2. Initial Access [to-do]
2.1 Web application testing (port 80/443) [to-do]
2.1.1 Directory enumeration (gobuster) [to-do]
2.1.2 CMS/version identification [to-do]
2.2 SSH brute-force (port 22) [not-applicable]
3. Privilege Escalation [to-do]
Rules:
- Layer depth:
1,1.1,1.1.1etc. Each child is a concrete sub-operation of its parent. - Status values:
to-do,completed,not-applicable. Never leave a node status-less. - Do NOT pre-generate nodes for unknown ports/services. Expand only on confirmed evidence.
- Remove/prune stale or invalidated nodes aggressively to control token budget.
- The tree is written to disk (
<engagement>/ptt.md) after every update.
Session Lifecycle
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.
- 4d ago First seen · 243 lines · 44 tokens per session scan A 1791eba40569
pentest-task-tree is a skill published in the GitHub repository PurpleAILAB/Decepticon (5,452 stars, last pushed 8d ago), licensed Apache-2.0. It adds 44 tokens to every session and 2,664 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.
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