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 EresusSecurity/appsec-skills --skill eresus-serialization-reviewgit clone --depth 1 https://github.com/EresusSecurity/appsec-skillsWrote 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/eresussecurity/appsec-skills/eresus-serialization-review)<a href="https://agentmods.dev/skills/eresussecurity/appsec-skills/eresus-serialization-review"><img src="https://agentmods.dev/badge/skills/eresussecurity/appsec-skills/eresus-serialization-review/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/eresussecurity/appsec-skills/eresus-serialization-review"><img src="https://agentmods.dev/badge/skills/eresussecurity/appsec-skills/eresus-serialization-review.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 | $0.00100 | $0.00825 |
| Opus 5 | $0.00050 | $0.00413 |
| Sonnet 5 | $0.00020 | $0.00165 |
| Haiku 4.5 | $0.00010 | $0.00082 |
Grade A, and why
eresus-serialization-review 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 10d 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 — 127 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Serialization Security Review
Purpose
Find vulnerabilities caused by unsafe serialization, deserialization, object mapping, parser configuration, and cross-boundary state transfer. Focus on cases where untrusted bytes, JSON, YAML, XML, cookies, view state, cache blobs, or queue messages are turned into executable, privileged, or overly dynamic objects.
High-Risk Targets
Prioritize:
- Java native serialization and
ObjectInputStream - Jackson polymorphic typing and unsafe default typing
- Fastjson auto-type behavior
- .NET
BinaryFormatter,LosFormatter,NetDataContractSerializer - PHP
unserialize()and POP-chain entry points - Python
pickle,marshal, and unsafe YAML loaders - Node parsers that revive functions, prototypes, or constructors
- session cookies, view state, queue payloads, cache entries, and signed blobs crossing trust boundaries
Workflow
Step 1: Find Deserialization Boundaries
Locate where external or semi-trusted data is parsed, decoded, revived, or reconstructed:
- HTTP body parsers
- cookies and session stores
- file import handlers
- webhook processors
- message queue consumers
- cache/database blob readers
- mobile/app local state restores
Step 2: Classify the Input Trust Level
For each boundary, decide whether the input is:
- fully attacker-controlled
- user-controlled but signed/encrypted
- partner-controlled
- internal-only but reachable through weaker upstream systems
Do not assume "internal" means safe without an integrity guarantee.
Step 3: Identify Dangerous Parser Features
Look for:
- polymorphic type resolution
- class-name-based instantiation
- automatic object revival
- unsafe YAML/XML object construction
- magic methods, hooks, or callbacks triggered after deserialization
- prototype pollution or constructor abuse
- gadget-friendly libraries on the classpath or dependency tree
Step 4: Judge Exploitability
Confirm:
- the data crosses a trust boundary
- attacker influence reaches the parser
- type restrictions or integrity checks are absent, weak, or bypassable
- the resulting object graph has dangerous side effects or privileged behavior
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.
- 10d ago First seen · 127 lines · 100 tokens per session scan A 8725a80daaae
eresus-serialization-review is a skill published in the GitHub repository EresusSecurity/appsec-skills (7 stars, last pushed 5mo ago), licensed Apache-2.0. It adds 100 tokens to every session and 825 once invoked, about $0.0005 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 2026-08-31.
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