freshcrate
Home > AI Agents > vikramaditya

vikramaditya

Autonomous VAPT platform. Give it a target (FQDN, IP, CIDR) โ€” it hunts, it reports. Inspired by the Obsidian Order.

Description

Autonomous VAPT platform. Give it a target (FQDN, IP, CIDR) โ€” it hunts, it reports. Inspired by the Obsidian Order.

README

 โ–ˆโ–ˆโ•—   โ–ˆโ–ˆโ•—โ–ˆโ–ˆโ•—โ–ˆโ–ˆโ•—  โ–ˆโ–ˆโ•—โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ•—  โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ•— โ–ˆโ–ˆโ–ˆโ•—   โ–ˆโ–ˆโ–ˆโ•— โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ•— โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ•— โ–ˆโ–ˆโ•—โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ•—โ–ˆโ–ˆโ•—   โ–ˆโ–ˆโ•— โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ•—
 โ–ˆโ–ˆโ•‘   โ–ˆโ–ˆโ•‘โ–ˆโ–ˆโ•‘โ–ˆโ–ˆโ•‘ โ–ˆโ–ˆโ•”โ•โ–ˆโ–ˆโ•”โ•โ•โ–ˆโ–ˆโ•—โ–ˆโ–ˆโ•”โ•โ•โ–ˆโ–ˆโ•—โ–ˆโ–ˆโ–ˆโ–ˆโ•— โ–ˆโ–ˆโ–ˆโ–ˆโ•‘โ–ˆโ–ˆโ•”โ•โ•โ–ˆโ–ˆโ•—โ–ˆโ–ˆโ•”โ•โ•โ–ˆโ–ˆโ•—โ–ˆโ–ˆโ•‘โ•šโ•โ•โ–ˆโ–ˆโ•”โ•โ•โ•โ•šโ–ˆโ–ˆโ•— โ–ˆโ–ˆโ•”โ•โ–ˆโ–ˆโ•”โ•โ•โ–ˆโ–ˆโ•—
 โ–ˆโ–ˆโ•‘   โ–ˆโ–ˆโ•‘โ–ˆโ–ˆโ•‘โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ•”โ• โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ•”โ•โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ•‘โ–ˆโ–ˆโ•”โ–ˆโ–ˆโ–ˆโ–ˆโ•”โ–ˆโ–ˆโ•‘โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ•‘โ–ˆโ–ˆโ•‘  โ–ˆโ–ˆโ•‘โ–ˆโ–ˆโ•‘   โ–ˆโ–ˆโ•‘    โ•šโ–ˆโ–ˆโ–ˆโ–ˆโ•”โ• โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ•‘
 โ•šโ–ˆโ–ˆโ•— โ–ˆโ–ˆโ•”โ•โ–ˆโ–ˆโ•‘โ–ˆโ–ˆโ•”โ•โ–ˆโ–ˆโ•— โ–ˆโ–ˆโ•”โ•โ•โ–ˆโ–ˆโ•—โ–ˆโ–ˆโ•”โ•โ•โ–ˆโ–ˆโ•‘โ–ˆโ–ˆโ•‘โ•šโ–ˆโ–ˆโ•”โ•โ–ˆโ–ˆโ•‘โ–ˆโ–ˆโ•”โ•โ•โ–ˆโ–ˆโ•‘โ–ˆโ–ˆโ•‘  โ–ˆโ–ˆโ•‘โ–ˆโ–ˆโ•‘   โ–ˆโ–ˆโ•‘     โ•šโ–ˆโ–ˆโ•”โ•  โ–ˆโ–ˆโ•”โ•โ•โ–ˆโ–ˆโ•‘
  โ•šโ–ˆโ–ˆโ–ˆโ–ˆโ•”โ• โ–ˆโ–ˆโ•‘โ–ˆโ–ˆโ•‘  โ–ˆโ–ˆโ•—โ–ˆโ–ˆโ•‘  โ–ˆโ–ˆโ•‘โ–ˆโ–ˆโ•‘  โ–ˆโ–ˆโ•‘โ–ˆโ–ˆโ•‘ โ•šโ•โ• โ–ˆโ–ˆโ•‘โ–ˆโ–ˆโ•‘  โ–ˆโ–ˆโ•‘โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ•”โ•โ–ˆโ–ˆโ•‘   โ–ˆโ–ˆโ•‘      โ–ˆโ–ˆโ•‘   โ–ˆโ–ˆโ•‘  โ–ˆโ–ˆโ•‘
   โ•šโ•โ•โ•โ•  โ•šโ•โ•โ•šโ•โ•  โ•šโ•โ•โ•šโ•โ•  โ•šโ•โ•โ•šโ•โ•  โ•šโ•โ•โ•šโ•โ•     โ•šโ•โ•โ•šโ•โ•  โ•šโ•โ•โ•šโ•โ•โ•โ•โ•โ• โ•šโ•โ•   โ•šโ•โ•      โ•šโ•โ•   โ•šโ•โ•  โ•šโ•โ•

Autonomous VAPT platform. Give it a target โ€” FQDN, IP, or CIDR range. It hunts, it reports.

"He who seeks the truth must be ready to face the fire." โ€” inspired by the legend of Vikramaditya

License: MITPython 3.10+ShellAI PoweredQuick Start ยท Architecture ยท Vulnerability Coverage ยท Reports ยท Installation ยท API Keys ยท Contributing


Recon โ†’ Tech fingerprinting โ†’ CVE mapping โ†’ Vulnerability scanning โ†’ AI analysis โ†’ Professional report


The Legend

Vikramaditya โ€” the legendary Indian emperor whose throne could only be ascended by one who sought truth fearlessly and judged without bias. His name means "valour of the sun".

This tool operates the same way. Give it a target. Walk away. Come back to a full VAPT report โ€” every vulnerability exposed, every weakness catalogued.

It was inspired by and evolved from claude-bug-bounty โ€” the original AI-assisted bug bounty automation platform that laid the recon pipeline, ReAct agent architecture, and AI analysis engine that powers this tool today.


What It Does

Vikramaditya is an autonomous VAPT tool built for professional security consultants. You give it a target โ€” a domain, a single IP, or an entire subnet. It runs the full assessment pipeline and produces a submission-ready report.

Stage What happens
๐Ÿ”ญ Recon Subdomain enumeration, DNS resolution, live host discovery, URL crawling, JS analysis, secret extraction
๐Ÿ”ฌ Fingerprint Tech stack detection (httpx), CVE risk scoring, priority host ranking
๐Ÿ” Scan SQLi, XSS, SSTI, RCE, file upload, CORS, JWT, cloud misconfigs, framework exposure
๐Ÿ’ฅ Exploit CMS exploit chains (Drupal, WordPress), Spring actuators, exposed admin panels
๐Ÿง  Analyze AI-powered triage โ€” finds chains, ranks by impact, kills noise
๐Ÿ“‹ Report Burp Suite-style HTML report: executive summary, CVSS scores, PoC evidence, remediation

Quick Start

git clone https://github.com/venkatas/vikramaditya.git
cd vikramaditya
chmod +x setup.sh && ./setup.sh      # installs all required tools
ollama pull gemma4:26b               # recommended brain model (17GB)

Infrastructure VAPT (domains, IPs, subnets)

# Full assessment on a domain
python3 hunt.py --target example.com

# Single IP address
python3 hunt.py --target 192.168.1.100

# Subnet (discovers live hosts first via nmap ping sweep)
python3 hunt.py --target 10.0.0.0/24

# Faster scan (fewer checks)
python3 hunt.py --target example.com --quick

# Autonomous mode โ€” AI drives all decisions
python3 hunt.py --target example.com --autonomous

Authenticated API VAPT (SPA + REST API targets)

# Brain-supervised autonomous scan (recommended)
python3 autopilot_api_hunt.py \
    --base-url https://api.target.com \
    --auth-creds "admin@target.com:password" \
    --login-url sign-in/ \
    --frontend-url https://app.target.com \
    --with-brain

# With second account for IDOR + privilege escalation testing
python3 autopilot_api_hunt.py \
    --base-url https://api.target.com \
    --auth-creds "admin@target.com:password" \
    --auth-creds-b "user@target.com:password" \
    --login-url sign-in/ \
    --with-brain

# Without brain (fully deterministic, no LLM needed)
python3 autopilot_api_hunt.py \
    --base-url https://api.target.com \
    --auth-creds "admin@target.com:password" \
    --login-url sign-in/

Individual Tools

# Authenticated API broken access control
python3 auth_api_tester.py --base-url URL --auth-creds user:pass --login-url sign-in/

# Generic REST API IDOR scanner (two-token cross-user testing)
python3 api_idor_scanner.py --base-url URL --token-a TOKEN1 --token-b TOKEN2

# Business logic testing (score manipulation, rate limits, pagination abuse)
python3 business_logic_tester.py --base-url URL --auth-creds user:pass --login-url sign-in/

# OAuth/OIDC security testing
python3 oauth_tester.py --target target.com

# Finding validator (7-Question Gate โ€” kills weak findings before report)
python3 finding_validator.py findings/target/

# Chain builder (Aโ†’B exploit escalation)
python3 chain_builder.py findings/target/

# Generate VAPT report (HTML + Markdown with inline PoC)
python3 reporter.py findings/target/ --target target.com --client "Client Name"

Architecture

Target (FQDN / IP / CIDR)
        โ”‚
        โ–ผ
   hunt.py  โ—„โ”€โ”€ brain.py (AI analysis + multi-provider LLM)
        โ”‚         โ””โ”€โ”€ agent.py (autonomous ReAct loop)
        โ”‚
   โ”Œโ”€โ”€โ”€โ”€โ”ดโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”
   โ”‚                                         โ”‚
   โ–ผ                                         โ–ผ
recon.sh                               scanner.sh
  โ”‚                                       โ”‚
  โ”œโ”€โ”€ subfinder / assetfinder             โ”œโ”€โ”€ SQLi (sqlmap + verifier)
  โ”œโ”€โ”€ amass / dnsx                        โ”œโ”€โ”€ XSS (dalfox)
  โ”œโ”€โ”€ httpx (tech detect)                 โ”œโ”€โ”€ SSTI (math-canary probes)
  โ”œโ”€โ”€ katana / waybackurls / gau          โ”œโ”€โ”€ RCE (Log4Shell, Tomcat, JBoss)
  โ”œโ”€โ”€ nuclei (CVE templates)              โ”œโ”€โ”€ File upload bypass
  โ”œโ”€โ”€ nmap / naabu (port scan)            โ”œโ”€โ”€ Cloud exposure (Firebase, K8s, Docker)
  โ”œโ”€โ”€ subzy (takeover check)              โ”œโ”€โ”€ Framework exposure (Spring, GraphQL)
  โ””โ”€โ”€ trufflehog / gitleaks (JS secrets)  โ””โ”€โ”€ Race conditions (xargs -P 20)
        โ”‚
        โ–ผ
  prioritize.py (CVE risk scoring)
        โ”‚
        โ–ผ
   brain.py (AI triage)
        โ”‚
        โ–ผ
   reporter.py
     โ”œโ”€โ”€ vapt_report.html  (Burp Suite-style, self-contained)
     โ””โ”€โ”€ vapt_report.md    (Markdown summary)

Vulnerability Coverage

Category Checks
Injection SQLi (error/blind/time-based), SSTI (Jinja2/Freemarker/Thymeleaf/ERB), XXE, LDAP injection
XSS Reflected, stored, DOM โ€” via dalfox pipeline
RCE Log4Shell OOB, Tomcat PUT (CVE-2017-12615), JBoss deserialization, Spring4Shell
Auth JWT (alg=none, RS256โ†’HS256, weak secret), OAuth misconfig, session fixation
IDOR Object-level, field-level, GraphQL node() IDOR, UUID enumeration
File Upload Extension bypass, MIME confusion, polyglots, SVG XSS
Cloud Firebase open read/write, K8s API unauthenticated, Docker socket exposure, S3 bucket enum
Framework Spring actuators (env/heapdump), H2 console, GraphQL introspection, Swagger UI
CMS Drupalgeddon2 (CVE-2018-7600), WordPress user enum + xmlrpc, Joomla/Magento
Infrastructure Subdomain takeover (subzy), CORS misconfiguration, open redirect, HTTP smuggling
Secrets JS bundle secrets (trufflehog/gitleaks), .env exposure, .git/config leak
Race Conditions Concurrent probes on OTP, coupon, payment endpoints

Reports

The report output matches professional pentest engagement standards โ€” suitable for client submission.

HTML report (vapt_report.html) โ€” single self-contained file:

  • Dark navy cover page with client name, consultant, date, and classification
  • Executive summary with risk breakdown bar
  • Vulnerability summary table (ID, name, severity, CVSS, host)
  • Per-finding detail: description, impact, PoC evidence, remediation, CWE/OWASP reference
  • Appendix: tools used, methodology, assessment timeline
# Generate report from a completed scan session
python3 reporter.py recon/example.com/sessions/20260325_120000_abc1/findings/ \
    --client "Acme Corp" \
    --consultant "Your Name" \
    --title "Web Application Penetration Test"

Output: reports/example.com/vapt_report.html + vapt_report.md


Autonomous Agent Mode

The --autonomous flag activates the ReAct agent (agent.py) which drives the entire assessment without manual intervention โ€” planning, choosing tools, analysing results, and pivoting to the next attack surface on its own.

# Autonomous hunt with a 4-hour budget
python3 hunt.py --target example.com --autonomous --time 4

# Watch live decisions as they happen
tail -f recon/example.com/sessions/<session_id>/agent_trace.jsonl

# Inject operator guidance mid-run without stopping the agent
python3 agent.py --bump recon/example.com/sessions/<session_id>/ \
    "Focus on /api/v2/ endpoints โ€” de-prioritize static assets"

The agent operates in a tight loop: Observe โ†’ Think (LLM) โ†’ Act (tool) โ†’ Observe. Every decision is logged to agent_trace.jsonl for post-engagement review.


Multi-Provider AI

brain.py supports five LLM backends. Set BRAIN_PROVIDER to force one, or let Vikramaditya auto-detect in priority order: Ollama โ†’ MLX โ†’ Claude โ†’ OpenAI โ†’ Grok.

Recommended Local Models (Benchmark-Tested)

Tested on MacBook Pro M4 Max (36GB) with a real VAPT findings set. Quality scored on: exploit chain identification, missed-test suggestions, and attack path analysis.

Rank Model Speed Quality RAM Best For
#1 gemma4:26b 25.6 tok/s 4/4 17GB Primary brain โ€” fastest with full quality, native tool calling, 262K context
#2 qwen3-coder-64k 10.2 tok/s 4/4 18GB Code analysis โ€” 64K context for large JS bundles
#3 vapt-qwen25 4.1 tok/s 4/4 19GB Deep analysis โ€” custom VAPT training data
#4 deepseek-r1:32b 3.9 tok/s 4/4 19GB Chain-of-thought reasoning (slow)
#5 baron-llm 14.2 tok/s 2/4 6.6GB Fast triage โ€” offensive security fine-tune
โ€” gemma4:e4b fast 3/4 9.6GB Lightweight โ€” laptops with 16GB RAM
# Recommended setup (one command):
ollama pull gemma4:26b

# Run fully local โ€” no API keys, no data leaves your machine
python3 hunt.py --target example.com

# Autopilot API VAPT (autonomous, no manual direction needed)
python3 autopilot_api_hunt.py --base-url https://api.target.com \
    --auth-creds user:pass --with-brain

All Supported Providers

Provider Env var required Notes
Ollama (local, default) โ€” CPU/GPU, all platforms, auto-detects best model
MLX (Apple Silicon) โ€” ~40 tok/s on M-series, SSD paging for large models
Claude (Anthropic) ANTHROPIC_API_KEY Best reasoning, cloud-only
OpenAI OPENAI_API_KEY gpt-4o, o3-mini
Grok (xAI) XAI_API_KEY grok-2-latest, grok-3-mini

Installation

Prerequisites

# macOS
brew install go python3 node jq nmap

# Debian/Ubuntu
sudo apt install golang python3 nodejs jq nmap

Install security tools

chmod +x setup.sh && ./setup.sh

setup.sh installs 25+ tools automatically:

Source Tools
Homebrew subfinder httpx nuclei ffuf nmap amass sqlmap trufflehog gitleaks whatweb
Go dnsx katana naabu cdncheck interactsh-client gau dalfox subzy waybackurls anew qsreplace assetfinder gf
Prebuilt binary gowitness (v3, Apple Silicon + Intel)
pip arjun httpx[cli] mlx-lm (arm64 only)
git clone โ†’ tools/ LinkFinder SecretFinder XSStrike drupalgeddon2
Auto nuclei-templates, gf patterns (~/.gf/), subfinder config scaffold

Python dependencies

pip install -r requirements.txt

See requirements.txt for LLM provider SDK details.


API Keys Setup

CHAOS API (ProjectDiscovery) โ€” Required for best subdomain coverage

The recon pipeline uses the Chaos dataset from ProjectDiscovery โ€” millions of pre-enumerated subdomains indexed per domain. Free key.

  1. Sign up at chaos.projectdiscovery.io
  2. Copy your API key
  3. Export before running:
export CHAOS_API_KEY="your-key-here"

# For persistence:
echo 'export CHAOS_API_KEY="your-key-here"' >> ~/.zshrc
source ~/.zshrc

recon.sh detects $CHAOS_API_KEY and auto-injects it into subfinder's provider config on first run. The key is never stored in any file in this repo.


Optional API Keys โ€” Better Subdomain Coverage

setup.sh creates a config scaffold at ~/.config/subfinder/provider-config.yaml. Uncomment and fill in any of these free/cheap keys:

Provider Free? Signup Benefit
VirusTotal โœ… Free virustotal.com +passive subdomain data
SecurityTrails โœ… Free tier securitytrails.com +historical DNS
Censys โœ… Free tier search.censys.io/account/api +certificate transparency
Shodan ๐Ÿ’ฒ ~$9/mo account.shodan.io +banner grab, port data
GitHub โœ… Free github.com/settings/tokens +source code subdomain leaks
# ~/.config/subfinder/provider-config.yaml
chaos:
  - YOUR_CHAOS_API_KEY
virustotal:
  - YOUR_VIRUSTOTAL_API_KEY
securitytrails:
  - YOUR_SECURITYTRAILS_API_KEY
censys:
  - YOUR_CENSYS_API_ID:YOUR_CENSYS_API_SECRET
shodan:
  - YOUR_SHODAN_API_KEY
github:
  - YOUR_GITHUB_TOKEN

See subfinder-config.yaml.example for the full template.


CLI Reference

hunt.py โ€” VAPT Orchestrator

Target input:
  --target example.com          FQDN
  --target 192.168.1.100        Single IP
  --target 10.0.0.0/24          CIDR range (nmap ping sweep first)

Scan modes:
  --quick                       Faster scan, fewer checks
  --full                        All checks including race conditions
  --autonomous                  AI-driven autonomous assessment
  --scope-lock                  Test exact target only (no subdomain expansion)

Selective phases:
  --recon-only                  Recon only
  --scan-only                   Scan only (requires prior recon)
  --js-scan                     JS analysis + secret extraction
  --param-discover              Parameter discovery (Arjun + ParamSpider)
  --api-fuzz                    API endpoint brute (Kiterunner)
  --secret-hunt                 TruffleHog + GitHound
  --cors-check                  CORS misconfiguration check
  --exploit                     CMS exploit chains (Drupal, WordPress)
  --rce-scan                    RCE: Log4Shell, Tomcat, JBoss, Spring
  --sqlmap                      sqlmap on discovered SQLi candidates
  --jwt-audit                   JWT algorithm confusion + weak secret crack

AI options:
  --no-brain                    Skip AI analysis (tools only)
  --brain-only                  AI analysis on existing recon data
  --brain-next                  Ask AI: what is the highest-impact next action?

Reporting:
  python3 reporter.py <findings_dir> [--client NAME] [--consultant NAME] [--title TITLE] [--target DOMAIN]

Utilities:
  --repair-tools                Auto-install missing tools
  --status                      Show current assessment progress
  --oob-setup                   Configure interactsh OOB token
  --resume SESSION_ID           Resume a previous session

Autopilot API VAPT (autopilot_api_hunt.py):
  --base-url URL                API base URL (required)
  --auth-creds user:pass        Primary account credentials (required)
  --auth-creds-b user:pass      Second account for IDOR/priv esc testing
  --login-url PATH              Login endpoint path (default: sign-in/)
  --frontend-url URL            Frontend URL for JS bundle scraping
  --with-brain                  Enable brain supervisor (local LLM)
  --rate-limit N                Max requests/sec (default: 5)
  --output DIR                  Output directory for findings

Autopilot API VAPT Engine

The autopilot_api_hunt.py module is a brain-supervised dynamic VAPT engine for modern SPA + REST API applications. It runs 12 attack phases autonomously with an AI supervisor that decides what to test next based on discoveries.

How the Brain Supervisor Works

Discover endpoints (JS bundle + Django debug + crawl)
  โ†’ Brain categorizes endpoints and creates prioritized test plan
  โ†’ Loop:
      Execute top-priority phase
      โ†’ Brain reviews findings
      โ†’ Brain decides: CONTINUE / INJECT / SKIP / PIVOT
      โ†’ Modify test queue based on decision
  โ†’ Chain building โ†’ Brain validation (FP removal) โ†’ Report

Attack Phases

Phase Tests
Auth Bypass No token, expired, tampered, alg=none
IDOR Sequential ID enum, Base64 decode, PII detection
Privilege Escalation Learner โ†’ admin endpoint access
Business Logic Score manipulation, workflow bypass, negative values
File Upload Double extension, MIME mismatch, polyglot, S3 arbitrary type
Injection SQLi (time + error), SSTI, command injection
Info Disclosure Django DEBUG, server headers, SMTP creds, AWS keys, DB schema
Rate Limiting Rapid login, password change, reset
Token Security JWT lifetime, refresh token abuse
Timing Oracles User enumeration via response time
Chain Building Cross-reference findings for escalation
Brain Validation FP removal + severity correction via LLM

Brain Model Stack

Role Model Speed Use
Decision engine baron-llm 14 tok/s Per-phase INJECT/SKIP/CONTINUE decisions
FP validation qwen3-coder-64k 10 tok/s JSON severity corrections
Chain analysis gemma4:26b 25 tok/s Final exploit chain + recommendations

New Modules (v5+)

Module Purpose
autopilot_api_hunt.py Brain-supervised autonomous API VAPT (12 phases)
auth_api_tester.py Broken access control testing (5 auth states per endpoint)
api_idor_scanner.py Generic two-token IDOR scanner (ID mutation + Base64 decode)
business_logic_tester.py Score manipulation, rate limits, pagination abuse
oauth_tester.py OAuth state entropy, redirect_uri bypass, host header injection
auth_utils.py JWT decode/tamper (no PyJWT), rate limiter, auth session
finding_validator.py 7-Question Gate + 28-pattern never-submit list
chain_builder.py 12-pattern Aโ†’B exploit chain discovery
scope_checker.py Deterministic domain matching (anchored suffix, IP rejection)
memory/ Hunt journal (JSONL), pattern DB, audit log with circuit breaker

Directory Structure

vikramaditya/
โ”œโ”€โ”€ hunt.py                  Main orchestrator (infrastructure VAPT)
โ”œโ”€โ”€ autopilot_api_hunt.py    Brain-supervised API VAPT engine
โ”œโ”€โ”€ brain.py                 AI analysis engine (Gemma 4, Ollama, MLX, Claude, OpenAI, Grok)
โ”œโ”€โ”€ agent.py                 Autonomous ReAct agent
โ”œโ”€โ”€ auth_api_tester.py       Authenticated API broken access control
โ”œโ”€โ”€ api_idor_scanner.py      Generic REST IDOR scanner
โ”œโ”€โ”€ business_logic_tester.py Score manipulation, rate limits, pagination
โ”œโ”€โ”€ oauth_tester.py          OAuth/OIDC security testing
โ”œโ”€โ”€ auth_utils.py            JWT helper, rate limiter, auth session
โ”œโ”€โ”€ finding_validator.py     7-Question Gate + never-submit list
โ”œโ”€โ”€ chain_builder.py         Aโ†’B exploit chain discovery
โ”œโ”€โ”€ scope_checker.py         Deterministic scope enforcement
โ”œโ”€โ”€ recon.sh                 Subdomain + URL discovery
โ”œโ”€โ”€ scanner.sh               Vulnerability scanner
โ”œโ”€โ”€ reporter.py              Report generator (HTML + Markdown + inline PoC)
โ”œโ”€โ”€ memory/                  Hunt journal, pattern DB, audit log
โ”œโ”€โ”€ prioritize.py        CVE risk scoring
โ”œโ”€โ”€ api_audit.py         OpenAPI/REST API auditing
โ”œโ”€โ”€ cve.py               CVE matcher
โ”œโ”€โ”€ fuzzer.py            Smart logic fuzzer
โ”œโ”€โ”€ validate.py          Finding validator (4-gate)
โ”œโ”€โ”€ intel.py             CVE + advisory intel
โ”œโ”€โ”€ mindmap.py           Attack surface mapper
โ”œโ”€โ”€ targets.py           Target management
โ”œโ”€โ”€ idor.py              IDOR scanner
โ”œโ”€โ”€ idor_mutator.py      GraphQL mutation IDOR
โ”œโ”€โ”€ oauth.py             OAuth misconfiguration tester
โ”œโ”€โ”€ race.py              Race condition tester
โ”œโ”€โ”€ payloads.py          Payload generator
โ”œโ”€โ”€ probe.py             HTTP prober
โ”œโ”€โ”€ browser_recon.js     Browser-side recon (Playwright)
โ”œโ”€โ”€ evasion.py           WAF bypass helpers
โ”œโ”€โ”€ zendesk_idor.py      Zendesk-specific IDOR
โ”œโ”€โ”€ setup.sh             Tool installer
โ”œโ”€โ”€ sqli_verify.sh       SQLi verification
โ”œโ”€โ”€ procs.sh             Pipeline process monitor
โ”œโ”€โ”€ requirements.txt     Python dependencies
โ”œโ”€โ”€ config.example.json  Configuration template
โ”œโ”€โ”€ skills/              Skill definitions
โ”œโ”€โ”€ wordlists/           Custom wordlists
โ”œโ”€โ”€ recon/               Scan output (gitignored)
โ”œโ”€โ”€ findings/            Validated findings (gitignored)
โ””โ”€โ”€ reports/             Generated reports (gitignored)

Configuration

Copy and edit the example config:

cp config.example.json config.json

Key settings:

{
  "brain_provider": "ollama",
  "ollama_model": "qwen2.5:14b",
  "interactsh_token": "YOUR_INTERACTSH_TOKEN",
  "rate_limit": 50,
  "threads": 10,
  "timeout": 30,
  "user_agent": "Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36"
}

Contributing

PRs welcome. This tool was originally inspired by and built on top of shuvonsec/claude-bug-bounty โ€” the original AI-assisted bug bounty platform. Contributions that advance its mission are appreciated.

Good contributions:

  • New vulnerability scanners or detection modules for scanner.sh
  • Payload additions to skills/ and wordlists/
  • New agent tool definitions in agent.py
  • Report template improvements โ€” better HTML, better Markdown
  • New AI provider support in brain.py
  • Real-world methodology improvements (with evidence from authorized engagements)
  • IP / network scanning improvements (better CIDR handling, IPv6)
  • Platform-specific modules (Jira, Confluence, GitLab, cloud consoles)

How to contribute:

git checkout -b feature/your-contribution
# ... make your changes ...
git commit -m "Add: short description"
git push origin feature/your-contribution

Then open a pull request describing what you added and why it's useful.

Commit message conventions:

Prefix Use for
Add: New scanner, module, or feature
Fix: Bug fix
Improve: Enhancement to existing functionality
Refactor: Code cleanup, no behaviour change
Docs: README, comments, docs only

Legal

For authorized security testing only.

Only use this tool against systems you own or have explicit written authorization to test. Vikramaditya is designed for professional VAPT consultants working under signed engagement letters. Unauthorized use against systems you do not have permission to test is illegal in most jurisdictions.

The authors accept no liability for misuse.


Credits

Vikramaditya evolved from claude-bug-bounty by @shuvonsec โ€” an AI-assisted bug bounty automation framework that pioneered the recon pipeline, ReAct agent loop, and AI-driven analysis engine that form the core of this tool.

Named after Emperor Vikramaditya โ€” whose legendary throne tested every claimant with 32 trials of truth before granting the seat of judgment. Like the emperor's court: thorough, relentless, and no weakness goes unexamined.


MIT License ยท Built for professional VAPT consultants

"In the end, the Order sees all."

Release History

VersionChangesUrgencyDate
main@2026-04-20Latest activity on main branchHigh4/20/2026
0.0.0No release found โ€” using repo HEADHigh4/11/2026

Dependencies & License Audit

Loading dependencies...

Similar Packages

claude-bug-bountyAI-powered bug bounty hunting from your terminal - recon, 20 vuln classes, autonomous hunting, and report generation. All inside Claude Code.v4.0.0
Phantom Autonomous Offensive Security Intelligence AI-powered multi-agent penetration testingv0.8.0
tsunamiautonomous AI agent that builds full-stack apps. local models. no cloud. no API keys. runs on your hardware.main@2026-04-21
ps2-recomp-Agent-SKILLEnable autonomous reverse engineering and recompilation of PlayStation 2 games using a structured OS for LLM agents with persistent memory and workflowsmain@2026-04-21
jobclawStreamline hiring by connecting AI agents that evaluate, negotiate, and schedule interviews to reduce time and improve candidate fit.main@2026-04-21