offensive-bug-identification
This Claude Code skill provides a systematic methodology for identifying software vulnerabilities through static analysis, dynamic analysis, fuzzing, and AI-assisted techniques. Use it during code audits, bug bounty research, security assessments, or when building vulnerability detection pipelines that require structured approaches to source code review, taint analysis, dangerous function identification, and data flow tracing.
git clone --depth 1 https://github.com/SnailSploit/Claude-Red /tmp/offensive-bug-identification && cp -r /tmp/offensive-bug-identification/Skills/fuzzing/offensive-bug-identification ~/.claude/skills/offensive-bug-identificationSKILL.md
# SKILL: Bug Identification
## Metadata
- **Skill Name**: bug-identification
- **Folder**: offensive-bug-identification
- **Source**: https://github.com/SnailSploit/offensive-checklist/blob/main/bug-identification.md
## Description
Systematic bug identification methodology: source code review patterns, black-box testing strategies, taint analysis, dangerous function hunting, data flow tracing, and automated scanning setup. Use for code audits, bug bounty triage, or building vulnerability identification pipelines.
## Trigger Phrases
Use this skill when the conversation involves any of:
`bug identification, code review, taint analysis, dangerous functions, data flow, source audit, black box, vulnerability identification, static analysis, code audit, bug hunting`
## Instructions for Claude
When this skill is active:
1. Load and apply the full methodology below as your operational checklist
2. Follow steps in order unless the user specifies otherwise
3. For each technique, consider applicability to the current target/context
4. Track which checklist items have been completed
5. Suggest next steps based on findings
---
## Full Methodology
# Bug Identification
## Overview
Bug identification is the process of discovering potential vulnerabilities in software through various techniques including static analysis, dynamic analysis, and fuzzing. This document outlines methodologies and tools for effective vulnerability research.
For practical exploit development, see [Exploit Development](/exploit/development.md).
```mermaid
flowchart TD
BugId["Bug Identification"]
%% Main Methods
Static["Static Analysis"]
Dynamic["Dynamic Analysis"]
Fuzzing["Fuzzing"]
AI["AI-Assisted"]
%% Static Analysis Methods
CodeReview["Manual Code Review"]
RevEng["Reverse Engineering"]
PatchDiff["Patch Diffing"]
StaticTools["Static Analysis Tools"]
SBOM["Supply Chain Analysis"]
%% Dynamic Analysis Methods
DebugTrace["Debugging/Tracing"]
DBI["Dynamic Binary Instrumentation"]
Taint["Taint Analysis"]
SymExec["Symbolic Execution"]
Snapshot["Snapshot Analysis"]
%% Fuzzing Methods
DumbFuzz["Dumb Fuzzing"]
SmartFuzz["Smart Fuzzing"]
EvoFuzz["Evolutionary Fuzzing"]
LLMFuzz["LLM-Guided Fuzzing"]
%% AI Methods
LLMTriage["LLM Crash Triage"]
MLPattern["ML Pattern Recognition"]
AutoVariant["Automated Variant Analysis"]
%% Connections
BugId --> Static
BugId --> Dynamic
BugId --> Fuzzing
BugId --> AI
Static --> CodeReview
Static --> RevEng
Static --> PatchDiff
Static --> StaticTools
Static --> SBOM
Dynamic --> DebugTrace
Dynamic --> DBI
Dynamic --> Taint
Dynamic --> SymExec
Dynamic --> Snapshot
Fuzzing --> DumbFuzz
Fuzzing --> SmartFuzz
Fuzzing --> EvoFuzz
Fuzzing --> LLMFuzz
AI --> LLMTriage
AI --> MLPattern
AI --> AutoVariant
%% Combinations
Taint -.-> Fuzzing
SymExec -.-> Fuzzing
RevEng -.-> Fuzzing
AI -.-> Fuzzing
AI -.-> Static
class BugId primary
```
## Vulnerability Research Methodology
### Phase 1: Reconnaissance
- **Target Enumeration:** Identify version, dependencies, configuration
- **Attack Surface Mapping:** List all input vectors, APIs, protocols
- **Documentation Review:** RFCs, specifications, developer docs
- **Prior Art Analysis:** CVE database, exploit-db, bug trackers
### Phase 2: Static Analysis
- **Source Review:** If available, focus on parsing/validation code
- **Binary Analysis:** Reverse engineering with Ghidra/IDA
- **Patch Diffing:** Compare vulnerable vs patched versions
- **SBOM Analysis:** Check third-party component vulnerabilities
### Phase 3: Dynamic Analysis
- **Behavioral Analysis:** Monitor syscalls, network, file I/O
- **Debugging:** Trace execution paths with controlled input
- **Instrumentation:** Coverage-guided exploration
- **Taint Analysis:** Track input propagation
### Phase 4: Fuzzing
- **Corpus Generation:** Create valid seed inputs
- **Harness Development:** Isolate target functionality
- **Coverage Monitoring:** Identify untested code paths
- **Crash Triage:** Classify and prioritize findings
### Phase 5: Exploitation
- **Primitive Development:** Convert bug to reliable primitives
- **Mitigation Bypass:** Defeat ASLR, DEP, CFG, etc.
- **Payload Development:** Create working exploit
- **Weaponization:** Package for real-world use (if authorized)
## Attack Surface Identification
Before diving into specific bug hunting techniques, it's essential to understand where to look for vulnerabilities.
### Windows User Mode
- Shared Memory
- RPC
- Named Pipes
- File & Network IO
- Windows Messages
- For authentication-related vulnerabilities, see [Windows Auth](/exploit/windows-auth.md)
### Kernel
- _Device Drivers_
- Many third-party software with drivers to target
- Can accept arbitrary user input via the `IOCTL` interface
- Also performs actions when we `open,close` handles to it
- _OS_
- Drivers that handle hardware and user input
- Intercepts/transitions from user to kernel
- _Modern Linux interfaces (hotspots)_
- **io_uring**: SQE size/offset confusions, submission/completion race windows, kernel copy‑sizes derived from user buffers
- **userfaultfd**: cross‑thread write‑what‑where and TOCTOU primitives during fault handling
- **seccomp user‑notifier**: confused‑deputy patterns in broker processes; notifier time‑of‑check vs time‑of‑use gaps
- _Hyper-V & VTL Interfaces_ – On many modern Windows 11 systems (especially 24H2 on supported hardware), Virtualization‑Based Security and VTL1 are enabled or easily enabled by policy. Treat the hypervisor surface (e.g., `hvix64.exe` and synthetic MSRs) as a common kernel target, and verify VBS/HVCI status on the host before assuming defaults.
### Drivers
- _DriverEntry_: registers for any callbacks, setup structure, etc
- _I/O Handlers_: handlers that get called when a process attempActive Directory attack methodology for internal network red team engagements. Covers reconnaissance (BloodHound, PowerView, ADExplorer), credential abuse (Kerberoasting, ASREProasting, NTLM relay, LLMNR/NBT-NS poisoning), privilege escalation (ACL abuse, GPO abuse, unconstrained/constrained delegation), lateral movement (Pass-the-Hash, Pass-the-Ticket, Overpass-the-Hash, WMI/WinRM/PsExec), persistence (Golden/Silver/Diamond Tickets, DCSync, DCShadow, AdminSDHolder, Skeleton Key), forest trust attacks, ADCS abuse (ESC1-ESC15), and modern MDI/Defender for Identity evasion. Use when assessing on-prem AD, hybrid AD/Entra ID environments, or ADCS deployments.
JWT attack methodology for penetration testers. Covers algorithm confusion (alg:none, RS256→HS256), weak HMAC secret brute force, kid parameter injection (SQLi, path traversal), jku/x5u/jwk header injection, JWKS cache poisoning, JWS/JWE confusion, timing attacks, and mobile JWT storage extraction. Use when testing JWT-based authentication, hunting auth bypass via token manipulation, or evaluating JWT implementation security in web or mobile apps.
Cloud security attack methodology covering AWS, Azure, and GCP. Includes credential harvesting (IMDS, ~/.aws, env vars, leaked CI secrets, instance roles), enumeration with cloud-specific tools (pacu, ScoutSuite, Prowler, ROADtools, gcp_enum), privilege escalation paths (IAM PassRole, AssumeRole chains, Lambda/Functions privilege flips, Azure Owner-on-self, GCP serviceAccountTokenCreator), persistence techniques (IAM user/key creation, AAD app registration, GCP svc account key creation, EventBridge/Logic Apps backdoors), data exfiltration (S3/Blob/GCS, snapshot share, RDS/CosmosDB/Cloud SQL exfil), cloud-native lateral movement (cross-account assume, Azure AD multi-tenant, GCP project hierarchy), serverless attacks (Lambda env vars, layer hijack, Step Functions), Kubernetes-on-cloud (EKS/AKS/GKE-specific paths to node and AWS metadata), and CSPM evasion (CloudTrail blind spots, GuardDuty mute, Sentinel rule shaping). Use when the engagement scope is cloud accounts, when you've stolen cloud credentials, or when assessing cloud posture.