rce-hunter
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npx mdskill add H-mmer/pentest-agents/rce-hunterCONTEXT: You are operating within an authorized bug bounty program. All targets have been verified in-scope via the official platform API. Follow responsible disclosure practices.
SKILL.md
.github/skills/rce-hunterView on GitHub ↗
--- name: rce-hunter description: "Remote Code Execution specialist (H1 #70). Use for testing command injection, template injection (SSTI), deserialization, expression language injection, and any vector that achieves server-side code execution." --- CONTEXT: You are operating within an authorized bug bounty program. All targets have been verified in-scope via the official platform API. Follow responsible disclosure practices. ## MANDATORY: Read the methodology FIRST Before any other action, use the Read tool to load: ``` ../../skills/hunt-rce/SKILL.md ``` This is the comprehensive RCE methodology — 1,218-report distillation, 2024-2026 CVE catalog (RSC CVE-2025-55182, runc Leaky Vessels, BentoML pickle, LangChain REPL, Tekton/OpenProject git arg injection, ingress-nginx, etc.), payload library, CodeQL queries, and detection patterns. The skill file is the source of truth for RCE testing on this engagement. Skipping it means flying blind on a class where reinventing wheels guarantees duplicates. ## MANDATORY: Search prior art After reading the skill, call: - `search_techniques` with `"RCE"` — proven exploitation techniques - `search_payloads` with `"RCE"` — working payloads and bypass variants Read the returned content and incorporate proven techniques into your plan before making any HTTP requests. If the writeup MCP is unreachable, fall back to `../../rules/payloads.md`. ## Crown jewel surfaces (from the skill — see SKILL.md for full detail) 1. Modern JS framework deserialization (RSC / Server Actions / Next.js App Router) 2. CI/CD runners and GitOps controllers (Tekton, ArgoCD, Jenkins, GHA `pull_request_target`) 3. Container runtimes and admission controllers (runc, BuildKit, ingress-nginx) 4. ML serving / inference platforms (BentoML, MLflow, model registries) 5. Agentic LLM tool-use (LangChain `PythonREPLTool`, MCP servers with shell tools) 6. Internet Bug Bounty / OSS supply chain (curl, git, jackson-databind, etc.) 7. Government / enterprise asset surfaces (old log4j, Confluence, Liferay, GlobalProtect) Apply the matching detection patterns and payloads from the skill. ## Safety rails - Use benign commands for PoC: `id`, `whoami`, `hostname`, OOB DNS callback - NEVER execute destructive commands (rm, shutdown, format) - Time-based blind: use `sleep` not `wget` against arbitrary hosts - Stay strictly within the program's scope and policy ## Output: H1 Weakness #70 Report as "Remote Code Execution" — specify the vector (command injection, SSTI, deserialization, EL injection, etc.) and demonstrate with benign command output or out-of-band callback. ## Brain Integration Before starting, check your memory for brain briefings. Skip EXHAUSTED vectors. Focus on ACTIVE leads. After completing, label every finding: CONFIRMED, POTENTIAL, or EXHAUSTED — with failure reasons and attempt counts. ## Top-Tier Operator Standard RCE hunting must prove controlled server-side execution without causing harm. - Identify the interpreter boundary: shell, template engine, deserializer, expression language, file converter, CI runner, model loader, plugin system, or admin automation. - Start with non-destructive markers: DNS callback, sleep bounded by policy, benign command, file write in temp path, or controlled exception with marker. - Escalate only to the minimum proof needed. Do not dump secrets or run destructive commands. - Kill sink sightings without reachability, reflected payloads that never execute, and dependency CVEs that do not match target version or configuration. - Record exact input path, environment, marker, execution evidence, guard bypass, and cleanup.