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 prototype-pollutiongit 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/prototype-pollution)<a href="https://agentmods.dev/skills/purpleailab/decepticon/prototype-pollution"><img src="https://agentmods.dev/badge/skills/purpleailab/decepticon/prototype-pollution.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 | $0.00047 | $0.01198 |
| Opus 5 | $0.00023 | $0.00599 |
| Sonnet 5 | $0.00009 | $0.00240 |
| Haiku 4.5 | $0.00005 | $0.00120 |
Grade A, and why
prototype-pollution scanned grade A with 2 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 3d 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 -X POST https://target.com/api/settings \ Runs shell commandslowCapability
Expected in a hook, worth knowing in a rule or an instructions file.
- **`child_process.spawn(cmd, args, opts)`** — opts has a `shell` option. Copies of this mod
1 near-identical copy found in the catalogue:
- prototype-pollution — 88% identical, 3 lines differ
How it starts
The opening of the file, as written. The whole thing — 107 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Prototype Pollution Playbook
Prototype pollution is the JavaScript equivalent of a universal gadget:
plant a property on Object.prototype and it appears on every object in
the runtime. Worthless in isolation, deadly in chain (__proto__.isAdmin = true → auth bypass; __proto__.shell = "/bin/bash" → RCE via spawn).
1. Sinks — the libraries that still introduce sinks
Keep a running list per engagement. These continue to ship sinks in 2026:
- Deep-merge:
lodash.merge,deepmerge(pre-fix),merge-deep,deepExtend,hoek.merge,mixme - Deep-clone:
lodash.defaultsDeep,lodash.zipObjectDeep,set-value(pre-3.0.3) - URL-to-obj:
qs,express-fileupload,jquery.extend(true, ...) - Config loaders:
node-configrecursive merge,dotenv-extended,rc - Template engines: Handlebars helpers fed from untrusted ctx
# Every JS/TS project: sweep known-bad versions
jq '.dependencies,.devDependencies | to_entries[] | select(.key | test("merge|lodash|set-value|dot-object|dot-prop|node-pg"))' /workspace/src/package.json
npm ls lodash set-value dot-prop 2>/dev/null | grep -E '[0-9]'
2. Sources
Any user input deserialized into a nested object:
- JSON body parsers (
body-parser,express.json) - Query string parsers (
qswith default config parsesa[b][__proto__][c]=1) - YAML uploads
- Form-data / multipart
3. Audit workflow
- Find every deep merge call site.
- Trace each one backwards — is the right-hand object user-controlled?
- If yes: check the merge function's prototype-pollution fix version.
- Even if the merge is fixed, check whether a copy (lodash.set, dot-path-value, jsonpath.set) creates a pollution path.
4. Exploitation gadgets
Poisoning Object.prototype doesn't do anything by itself — you need
a gadget that reads a property that didn't exist before.
Classic gadgets:
child_process.spawn(cmd, args, opts)— opts has ashelloption. Poison__proto__.shell = "/bin/bash"then any subsequent spawn call executes through bash and interprets args as shell strings.- Express middleware — most middlewares check
options.someFlagwithif (opts.someFlag). Poisoning that flag flips security defaults. - Templating — Handlebars and EJS read
helpersandpartialsfrom the context object; pollution adds helpers that execute code. lodash.template— if the template source is built from_.template(tpl, ctx)you can inject via pollutedescape/evaluatekeys.mongoose— pollutingSchema.Typescauses subsequent schema definitions to use attacker-controlled types.
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.
- 3d ago First seen · 107 lines · 47 tokens per session scan A 4e3b2c7c5c1e
prototype-pollution is a skill published in the GitHub repository PurpleAILAB/Decepticon (5,452 stars, last pushed 7d ago), licensed Apache-2.0. It adds 47 tokens to every session and 1,198 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 2 findings (makes network calls, runs shell commands). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.
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