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 xs-leaksgit 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/xs-leaks)<a href="https://agentmods.dev/skills/purpleailab/decepticon/xs-leaks"><img src="https://agentmods.dev/badge/skills/purpleailab/decepticon/xs-leaks/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/skills/purpleailab/decepticon/xs-leaks"><img src="https://agentmods.dev/badge/skills/purpleailab/decepticon/xs-leaks.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00033 | $0.01007 |
| Opus 5 | $0.00016 | $0.00504 |
| Sonnet 5 | $0.00007 | $0.00201 |
| Haiku 4.5 | $0.00003 | $0.00101 |
Grade A, and why
xs-leaks 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 7d 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.
try { await fetch(url, {mode:'no-cors', credentials:'include'}); } catch {} Copies of this mod
1 near-identical copy found in the catalogue:
- xs-leaks — 98% identical, 2 lines differ
How it starts
The opening of the file, as written. The whole thing — 119 lines — stays where its author put it; the contents beside it link to each section on GitHub.
XS-Leaks (Cross-Site Leaks)
XS-Leaks abuse browser primitives that leak information ACROSS origins. Attacker page can observe whether a cross-origin GET returned different content based on victim's authenticated state. Smaller than full cross-origin read (which is blocked), but enough to enumerate identifiers, detect membership, learn search-result presence.
1. Categories
1.1 Timing oracles
Cross-origin fetch / image load timing varies by server response size. Attacker measures load time → infers content.
const start = performance.now();
const img = new Image();
img.onerror = () => console.log(performance.now() - start);
img.src = 'https://target.com/api/users/me/notifications';
1.2 Frame counting (window.frames.length)
Some pages embed N iframes when authenticated and 0 when not. Attacker
iframes target page and reads iframe.contentWindow.frames.length.
1.3 Window name / postMessage leak
iframe.contentWindow.name is preserved across navigation. Some pages
set it w/ user-identifying data.
1.4 Error-event oracle
<img src=target.com/api/user/{id}/data> triggers different onerror
behavior based on response code (403 vs 404 vs 200 w/ image content-type).
1.5 CSS injection style oracle
<link rel=stylesheet href=target.com/page> — different applied styles
leak state via getComputedStyle of attacker page.
1.6 Search result presence
Many search endpoints return cached/non-cached headers indicating hits. Attacker measures cache hit vs miss timing for guessed search terms.
1.7 ID guessability (XS-Search)
for (const guessed_id of guessable_set) {
const url = `https://target.com/api/user/${guessed_id}`;
// measure timing or frame-count differential
}
2. xsleaks.dev — canonical reference
Full taxonomy + browser-version compatibility matrix: https://xsleaks.dev/
Decepticon agents should consult this for current technique viability — browser mitigations evolve fast (COOP, COEP, Cross-Origin-Opener-Policy).
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.
- 7d ago First seen · 119 lines · 33 tokens per session scan A 4c6e793a5c45
xs-leaks is a skill published in the GitHub repository PurpleAILAB/Decepticon (5,482 stars, last pushed 11d ago), licensed Apache-2.0. It adds 33 tokens to every session and 1,007 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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