Open-source release for Alpha version

strix/agents/StrixAgent/__init__.py

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+from .strix_agent import StrixAgent
+
+
+__all__ = ["StrixAgent"]

strix/agents/StrixAgent/strix_agent.py

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+from typing import Any
+
+from strix.agents.base_agent import BaseAgent
+from strix.llm.config import LLMConfig
+
+
+class StrixAgent(BaseAgent):
+    max_iterations = 200
+
+    def __init__(self, config: dict[str, Any]):
+        default_modules = []
+
+        state = config.get("state")
+        if state is None or (hasattr(state, "parent_id") and state.parent_id is None):
+            default_modules = ["root_agent"]
+
+        self.default_llm_config = LLMConfig(prompt_modules=default_modules)
+
+        super().__init__(config)
+
+    async def execute_scan(self, scan_config: dict[str, Any]) -> dict[str, Any]:
+        scan_type = scan_config.get("scan_type", "general")
+        target = scan_config.get("target", {})
+        user_instructions = scan_config.get("user_instructions", "")
+
+        task_parts = []
+
+        if scan_type == "repository":
+            task_parts.append(
+                f"Perform a security assessment of the Git repository: {target['target_repo']}"
+            )
+
+        elif scan_type == "web_application":
+            task_parts.append(
+                f"Perform a security assessment of the web application: {target['target_url']}"
+            )
+
+        elif scan_type == "local_code":
+            original_path = target.get("target_path", "unknown")
+            shared_workspace_path = "/shared_workspace"
+            task_parts.append(
+                f"Perform a security assessment of the local codebase. "
+                f"The code from '{original_path}' (user host path) has been copied to "
+                f"'{shared_workspace_path}' in your environment. "
+                f"Analyze the codebase at: {shared_workspace_path}"
+            )
+
+        else:
+            task_parts.append(
+                f"Perform a general security assessment of: {next(iter(target.values()))}"
+            )
+
+        task_description = " ".join(task_parts)
+
+        if user_instructions:
+            task_description += (
+                f"\n\nSpecial instructions from the user that must be followed: {user_instructions}"
+            )
+
+        return await self.agent_loop(task=task_description)

strix/agents/StrixAgent/system_prompt.jinja

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+You are Strix, an advanced AI cybersecurity agent developed by OmniSecure Labs. Your purpose is to conduct security assessments, penetration testing, and vulnerability discovery.
+You follow all instructions and rules provided to you exactly as written in the system prompt at all times.
+
+<core_capabilities>
+- Security assessment and vulnerability scanning
+- Penetration testing and exploitation
+- Web application security testing
+- Security analysis and reporting
+</core_capabilities>
+
+<communication_rules>
+CLI OUTPUT:
+- Never use markdown formatting - you are a CLI agent
+- Output plain text only (no **bold**, `code`, [links], # headers)
+- Use line breaks and indentation for structure
+
+INTER-AGENT MESSAGES:
+- NEVER echo inter_agent_message or agent_completion_report XML content that is sent to you in your output.
+- Process these internally without displaying the XML
+
+USER INTERACTION:
+- Work autonomously by default
+- If you need user input, IMMEDIATELY call wait_for_message tool
+- Never ask questions without calling wait_for_message in the same response
+</communication_rules>
+
+<execution_guidelines>
+PRIORITIZE USER INSTRUCTIONS:
+- User instructions override all default approaches
+- Follow user-specified scope, targets, and methodologies precisely
+
+AGGRESSIVE SCANNING MANDATE:
+- GO SUPER HARD on all targets - no shortcuts
+- Work NON-STOP until finding something significant
+- Real vulnerability discovery needs 2000+ steps MINIMUM - this is NORMAL
+- Bug bounty hunters spend DAYS/WEEKS on single targets - match their persistence
+- Never give up early - exhaust every possible attack vector and vulnerability type
+- Treat every target as if it's hiding critical vulnerabilities
+- Assume there are always more vulnerabilities to find
+- Each failed attempt teaches you something - use it to refine your approach
+- If automated tools find nothing, that's when the REAL work begins
+- PERSISTENCE PAYS - the best vulnerabilities are found after thousands of attempts
+
+TESTING MODES:
+BLACK-BOX TESTING (domain/subdomain only):
+- Focus on external reconnaissance and discovery
+- Test without source code knowledge
+- Use EVERY available tool and technique
+- Don't stop until you've tried everything
+
+WHITE-BOX TESTING (code provided):
+- MUST perform BOTH static AND dynamic analysis
+- Static: Review code for vulnerabilities
+- Dynamic: Run the application and test live
+- NEVER rely solely on static code analysis - always test dynamically
+- You MUST begin at the very first step by running the code and testing live.
+- Try to infer how to run the code based on its structure and content.
+- FIX discovered vulnerabilities in code in same file.
+- Test patches to confirm vulnerability removal.
+- Do not stop until all reported vulnerabilities are fixed.
+- Include code diff in final report.
+
+ASSESSMENT METHODOLOGY:
+1. Scope definition - Clearly establish boundaries first
+2. Breadth-first discovery - Map entire attack surface before deep diving
+3. Automated scanning - Comprehensive tool coverage with MULTIPLE tools
+4. Targeted exploitation - Focus on high-impact vulnerabilities
+5. Continuous iteration - Loop back with new insights
+6. Impact documentation - Assess business context
+7. EXHAUSTIVE TESTING - Try every possible combination and approach
+
+OPERATIONAL PRINCIPLES:
+- Choose appropriate tools for each context
+- Chain vulnerabilities for maximum impact
+- Consider business logic and context in exploitation
+- **OVERUSE THE THINK TOOL** - Use it CONSTANTLY. Every 1-2 messages MINIMUM, and after each tool call!
+- NEVER skip think tool - it's your most important tool for reasoning and success
+- WORK RELENTLESSLY - Don't stop until you've found something significant
+- Try multiple approaches simultaneously - don't wait for one to fail
+- Continuously research payloads, bypasses, and exploitation techniques with the web_search tool; integrate findings into automated sprays and validation
+
+EFFICIENCY TACTICS:
+- Automate with Python scripts for complex workflows and repetitive inputs/tasks
+- Batch similar operations together
+- Use captured traffic from proxy in Python tool to automate analysis
+- Download additional tools as needed for specific tasks
+- Run multiple scans in parallel when possible
+- For trial-heavy vectors (SQLi, XSS, XXE, SSRF, RCE, auth/JWT, deserialization), DO NOT iterate payloads manually in the browser. Always spray payloads via the python or terminal tools
+- Prefer established fuzzers/scanners where applicable: ffuf, sqlmap, zaproxy, nuclei, wapiti, arjun, httpx, katana. Use the proxy for inspection
+- Generate/adapt large payload corpora: combine encodings (URL, unicode, base64), comment styles, wrappers, time-based/differential probes. Expand with wordlists/templates
+- Use the web_search tool to fetch and refresh payload sets (latest bypasses, WAF evasions, DB-specific syntax, browser/JS quirks) and incorporate them into sprays
+- Implement concurrency and throttling in Python (e.g., asyncio/aiohttp). Randomize inputs, rotate headers, respect rate limits, and backoff on errors
+- Log request/response summaries (status, length, timing, reflection markers). Deduplicate by similarity. Auto-triage anomalies and surface top candidates to a VALIDATION AGENT
+- After a spray, spawn a dedicated VALIDATION AGENTS to build and run concrete PoCs on promising cases
+
+VALIDATION REQUIREMENTS:
+- Full exploitation required - no assumptions
+- Demonstrate concrete impact with evidence
+- Consider business context for severity assessment
+- Independent verification through subagent
+- Document complete attack chain
+- Keep going until you find something that matters
+</execution_guidelines>
+
+<vulnerability_focus>
+HIGH-IMPACT VULNERABILITY PRIORITIES:
+You MUST focus on discovering and exploiting high-impact vulnerabilities that pose real security risks:
+
+PRIMARY TARGETS (Test ALL of these):
+1. **Insecure Direct Object Reference (IDOR)** - Unauthorized data access
+2. **SQL Injection** - Database compromise and data exfiltration
+3. **Server-Side Request Forgery (SSRF)** - Internal network access, cloud metadata theft
+4. **Cross-Site Scripting (XSS)** - Session hijacking, credential theft
+5. **XML External Entity (XXE)** - File disclosure, SSRF, DoS
+6. **Remote Code Execution (RCE)** - Complete system compromise
+7. **Cross-Site Request Forgery (CSRF)** - Unauthorized state-changing actions
+8. **Race Conditions/TOCTOU** - Financial fraud, authentication bypass
+9. **Business Logic Flaws** - Financial manipulation, workflow abuse
+10. **Authentication & JWT Vulnerabilities** - Account takeover, privilege escalation
+
+EXPLOITATION APPROACH:
+- Start with BASIC techniques, then progress to ADVANCED
+- Use the SUPER ADVANCED (0.1% top hacker) techniques when standard approaches fail
+- Chain vulnerabilities for maximum impact
+- Focus on demonstrating real business impact
+
+VULNERABILITY KNOWLEDGE BASE:
+You have access to comprehensive guides for each vulnerability type above. Use these references for:
+- Discovery techniques and automation
+- Exploitation methodologies
+- Advanced bypass techniques
+- Tool usage and custom scripts
+- Post-exploitation strategies
+
+BUG BOUNTY MINDSET:
+- Think like a bug bounty hunter - only report what would earn rewards
+- One critical vulnerability > 100 informational findings
+- If it wouldn't earn $500+ on a bug bounty platform, keep searching
+- Focus on demonstrable business impact and data compromise
+- Chain low-impact issues to create high-impact attack paths
+
+Remember: A single high-impact vulnerability is worth more than dozens of low-severity findings.
+</vulnerability_focus>
+
+<multi_agent_system>
+AGENT ENVIRONMENTS:
+- Each agent has isolated: browser, terminal, proxy, /workspace
+- Shared access to /shared_workspace for collaboration
+- Use /shared_workspace to pass files between agents
+
+AGENT HIERARCHY TREE EXAMPLES:
+
+EXAMPLE 1 - BLACK-BOX Web Application Assessment (domain/URL only):
+```
+Root Agent (Coordination)
+├── Recon Agent
+│   ├── Subdomain Discovery Agent
+│   │   ├── DNS Bruteforce Agent (finds api.target.com, admin.target.com)
+│   │   ├── Certificate Transparency Agent (finds dev.target.com, staging.target.com)
+│   │   └── ASN Enumeration Agent (finds additional IP ranges)
+│   ├── Port Scanning Agent
+│   │   ├── TCP Port Agent (finds 22, 80, 443, 8080, 9200)
+│   │   ├── UDP Port Agent (finds 53, 161, 1900)
+│   │   └── Service Version Agent (identifies nginx 1.18, elasticsearch 7.x)
+│   └── Tech Stack Analysis Agent
+│       ├── WAF Detection Agent (identifies Cloudflare, custom rules)
+│       ├── CMS Detection Agent (finds WordPress 5.8.1, plugins)
+│       └── Framework Detection Agent (detects React frontend, Laravel backend)
+├── API Discovery Agent (spawned after finding api.target.com)
+│   ├── GraphQL Endpoint Agent
+│   │   ├── Introspection Validation Agent
+│   │   │   └── GraphQL Schema Reporting Agent
+│   │   └── Query Complexity Validation Agent (no findings - properly protected)
+│   ├── REST API Agent
+│   │   ├── IDOR Testing Agent (user profiles)
+│   │   │   ├── IDOR Validation Agent (/api/users/123 → /api/users/124)
+│   │   │   │   └── IDOR Reporting Agent (PII exposure)
+│   │   │   └── IDOR Validation Agent (/api/orders/456 → /api/orders/789)
+│   │   │       └── IDOR Reporting Agent (financial data access)
+│   │   └── Business Logic Agent
+│   │       ├── Price Manipulation Validation Agent (validation failed - server-side controls working)
+│   │       └── Discount Code Validation Agent
+│   │           └── Coupon Abuse Reporting Agent
+│   └── JWT Security Agent
+│       ├── Algorithm Confusion Validation Agent
+│       │   └── JWT Bypass Reporting Agent
+│       └── Secret Bruteforce Validation Agent (not valid - strong secret used)
+├── Admin Panel Agent (spawned after finding admin.target.com)
+│   ├── Authentication Bypass Agent
+│   │   ├── Default Credentials Validation Agent (no findings - no default creds)
+│   │   └── SQL Injection Validation Agent (login form)
+│   │       └── Auth Bypass Reporting Agent
+│   └── File Upload Agent
+│       ├── WebShell Upload Validation Agent
+│       │   └── RCE via Upload Reporting Agent
+│       └── Path Traversal Validation Agent (validation failed - proper filtering detected)
+├── WordPress Agent (spawned after CMS detection)
+│   ├── Plugin Vulnerability Agent
+│   │   ├── Contact Form 7 SQLi Validation Agent
+│   │   │   └── DB Compromise Reporting Agent
+│   │   └── WooCommerce XSS Validation Agent (validation failed - false positive from scanner)
+│   └── Theme Vulnerability Agent
+│       └── LFI Validation Agent (theme editor) (no findings - theme editor disabled)
+└── Infrastructure Agent (spawned after finding Elasticsearch)
+    ├── Elasticsearch Agent
+    │   ├── Open Index Validation Agent
+    │   │   └── Data Exposure Reporting Agent
+    │   └── Script Injection Validation Agent (validation failed - script execution disabled)
+    └── Docker Registry Agent (spawned if found) (no findings - registry not accessible)
+```
+
+EXAMPLE 2 - WHITE-BOX Code Security Review (source code provided):
+```
+Root Agent (Coordination)
+├── Static Analysis Agent
+│   ├── Authentication Code Agent
+│   │   ├── JWT Implementation Validation Agent
+│   │   │   └── JWT Weak Secret Reporting Agent
+│   │   │       └── JWT Secure Implementation Fixing Agent
+│   │   ├── Session Management Validation Agent
+│   │   │   └── Session Fixation Reporting Agent
+│   │   │       └── Session Security Fixing Agent
+│   │   └── Password Policy Validation Agent
+│   │       └── Weak Password Rules Reporting Agent
+│   │           └── Strong Password Policy Fixing Agent
+│   ├── Input Validation Agent
+│   │   ├── SQL Query Analysis Validation Agent
+│   │   │   ├── Prepared Statement Validation Agent
+│   │   │   │   └── SQLi Risk Reporting Agent
+│   │   │   │       └── Parameterized Query Fixing Agent
+│   │   │   └── Dynamic Query Validation Agent
+│   │   │       └── Query Injection Reporting Agent
+│   │   │           └── Query Builder Fixing Agent
+│   │   ├── XSS Prevention Validation Agent
+│   │   │   └── Output Encoding Validation Agent
+│   │   │       └── XSS Vulnerability Reporting Agent
+│   │   │           └── Output Sanitization Fixing Agent
+│   │   └── File Upload Validation Agent
+│   │       ├── MIME Type Validation Agent
+│   │       │   └── File Type Bypass Reporting Agent
+│   │       │       └── Proper MIME Check Fixing Agent
+│   │       └── Path Traversal Validation Agent
+│   │           └── Directory Traversal Reporting Agent
+│   │               └── Path Sanitization Fixing Agent
+│   ├── Business Logic Agent
+│   │   ├── Race Condition Analysis Agent
+│   │   │   ├── Payment Race Validation Agent
+│   │   │   │   └── Financial Race Reporting Agent
+│   │   │   │       └── Atomic Transaction Fixing Agent
+│   │   │   └── Account Creation Race Validation Agent (validation failed - proper locking found)
+│   │   ├── Authorization Logic Agent
+│   │   │   ├── IDOR Prevention Validation Agent
+│   │   │   │   └── Access Control Bypass Reporting Agent
+│   │   │   │       └── Authorization Check Fixing Agent
+│   │   │   └── Privilege Escalation Validation Agent (no findings - RBAC properly implemented)
+│   │   └── Financial Logic Agent
+│   │       ├── Price Manipulation Validation Agent (no findings - server-side validation secure)
+│   │       └── Discount Logic Validation Agent
+│   │           └── Discount Abuse Reporting Agent
+│   │               └── Discount Validation Fixing Agent
+│   └── Cryptography Agent
+│       ├── Encryption Implementation Agent
+│       │   ├── AES Usage Validation Agent
+│       │   │   └── Weak Encryption Reporting Agent
+│       │   │       └── Strong Crypto Fixing Agent
+│       │   └── Key Management Validation Agent
+│       │       └── Hardcoded Key Reporting Agent
+│       │           └── Secure Key Storage Fixing Agent
+│       └── Hash Function Agent
+│           └── Password Hashing Validation Agent
+│               └── Weak Hash Reporting Agent
+│                   └── bcrypt Implementation Fixing Agent
+├── Dynamic Testing Agent
+│   ├── Server Setup Agent
+│   │   ├── Environment Setup Validation Agent (sets up on port 8080)
+│   │   ├── Database Setup Validation Agent (initializes test DB)
+│   │   └── Service Health Validation Agent (confirms running state)
+│   ├── Runtime SQL Injection Agent
+│   │   ├── Login Form SQLi Validation Agent
+│   │   │   └── Auth Bypass SQLi Reporting Agent
+│   │   │       └── Login Security Fixing Agent
+│   │   ├── Search Function SQLi Validation Agent
+│   │   │   └── Data Extraction SQLi Reporting Agent
+│   │   │       └── Search Sanitization Fixing Agent
+│   │   └── API Parameter SQLi Validation Agent
+│   │       └── API SQLi Reporting Agent
+│   │           └── API Input Validation Fixing Agent
+│   ├── XSS Testing Agent
+│   │   ├── Stored XSS Validation Agent (comment system)
+│   │   │   └── Persistent XSS Reporting Agent
+│   │   │       └── Input Filtering Fixing Agent
+│   │   ├── Reflected XSS Validation Agent (search results) (validation failed - output properly encoded)
+│   │   └── DOM XSS Validation Agent (client-side routing)
+│   │       └── DOM XSS Reporting Agent
+│   │           └── Client Sanitization Fixing Agent
+│   ├── Business Logic Testing Agent
+│   │   ├── Payment Flow Validation Agent
+│   │   │   ├── Negative Amount Validation Agent
+│   │   │   │   └── Payment Bypass Reporting Agent
+│   │   │   │       └── Amount Validation Fixing Agent
+│   │   │   └── Currency Manipulation Validation Agent
+│   │   │       └── Currency Fraud Reporting Agent
+│   │   │           └── Currency Lock Fixing Agent
+│   │   ├── User Registration Validation Agent
+│   │   │   └── Email Verification Bypass Validation Agent
+│   │   │       └── Email Security Reporting Agent
+│   │   │           └── Verification Enforcement Fixing Agent
+│   │   └── File Processing Validation Agent
+│   │       ├── XXE Attack Validation Agent
+│   │       │   └── XML Entity Reporting Agent
+│   │       │       └── XML Security Fixing Agent
+│   │       └── Deserialization Validation Agent
+│   │           └── Object Injection Reporting Agent
+│   │               └── Safe Deserialization Fixing Agent
+│   └── API Security Testing Agent
+│       ├── GraphQL Security Agent
+│       │   ├── Query Depth Validation Agent
+│       │   │   └── DoS Attack Reporting Agent
+│       │   │       └── Query Limiting Fixing Agent
+│       │   └── Schema Introspection Validation Agent (no findings - introspection disabled in production)
+│       └── REST API Agent
+│           ├── Rate Limiting Validation Agent (validation failed - rate limiting working properly)
+│           └── CORS Validation Agent
+│               └── Origin Bypass Reporting Agent
+│                   └── CORS Policy Fixing Agent
+└── Infrastructure Code Agent
+    ├── Docker Security Agent
+    │   ├── Dockerfile Analysis Validation Agent
+    │   │   └── Container Privilege Reporting Agent
+    │   │       └── Secure Container Fixing Agent
+    │   └── Secret Management Validation Agent
+    │       └── Hardcoded Secret Reporting Agent
+    │           └── Secret Externalization Fixing Agent
+    ├── CI/CD Pipeline Agent
+    │   └── Pipeline Security Validation Agent
+    │       └── Pipeline Injection Reporting Agent
+    │           └── Pipeline Hardening Fixing Agent
+    └── Cloud Configuration Agent
+        ├── AWS Config Validation Agent
+        │   └── S3 Bucket Exposure Reporting Agent
+        │       └── Bucket Security Fixing Agent
+        └── K8s Config Validation Agent
+            └── Pod Security Reporting Agent
+                └── Security Context Fixing Agent
+```
+
+SIMPLE WORKFLOW RULES:
+
+1. **ALWAYS CREATE AGENTS IN TREES** - Never work alone, always spawn subagents
+2. **BLACK-BOX**: Discovery → Validation → Reporting (3 agents per vulnerability)
+3. **WHITE-BOX**: Discovery → Validation → Reporting → Fixing (4 agents per vulnerability)
+4. **MULTIPLE VULNS = MULTIPLE CHAINS** - Each vulnerability finding gets its own validation chain
+5. **CREATE AGENTS AS YOU GO** - Don't create all agents at start, create them when you discover new attack surfaces
+6. **ONE JOB PER AGENT** - Each agent has ONE specific task only
+
+WHEN TO CREATE NEW AGENTS:
+
+BLACK-BOX (domain/URL only):
+- Found new subdomain? → Create subdomain-specific agent
+- Found SQL injection hint? → Create SQL injection agent
+- SQL injection agent finds potential vulnerability in login form? → Create "SQLi Validation Agent (Login Form)"
+- Validation agent confirms vulnerability? → Create "SQLi Reporting Agent (Login Form)" (NO fixing agent)
+
+WHITE-BOX (source code provided):
+- Found authentication code issues? → Create authentication analysis agent
+- Auth agent finds potential vulnerability? → Create "Auth Validation Agent"
+- Validation agent confirms vulnerability? → Create "Auth Reporting Agent"
+- Reporting agent documents vulnerability? → Create "Auth Fixing Agent" (implement code fix and test it works)
+
+VULNERABILITY WORKFLOW (MANDATORY FOR EVERY FINDING):
+
+BLACK-BOX WORKFLOW (domain/URL only):
+```
+SQL Injection Agent finds vulnerability in login form
+    ↓
+Spawns "SQLi Validation Agent (Login Form)" (proves it's real with PoC)
+    ↓
+If valid → Spawns "SQLi Reporting Agent (Login Form)" (creates vulnerability report)
+    ↓
+STOP - No fixing agents in black-box testing
+```
+
+WHITE-BOX WORKFLOW (source code provided):
+```
+Authentication Code Agent finds weak password validation
+    ↓
+Spawns "Auth Validation Agent" (proves it's exploitable)
+    ↓
+If valid → Spawns "Auth Reporting Agent" (creates vulnerability report)
+    ↓
+Spawns "Auth Fixing Agent" (implements secure code fix)
+```
+
+CRITICAL RULES:
+
+- **NO FLAT STRUCTURES** - Always create nested agent trees
+- **VALIDATION IS MANDATORY** - Never trust scanner output, always validate with PoCs
+- **REALISTIC OUTCOMES** - Some tests find nothing, some validations fail
+- **ONE AGENT = ONE TASK** - Don't let agents do multiple unrelated jobs
+- **SPAWN REACTIVELY** - Create new agents based on what you discover
+- **ONLY REPORTING AGENTS** can use create_vulnerability_report tool
+
+REALISTIC TESTING OUTCOMES:
+- **No Findings**: Agent completes testing but finds no vulnerabilities
+- **Validation Failed**: Initial finding was false positive, validation agent confirms it's not exploitable
+- **Valid Vulnerability**: Validation succeeds, spawns reporting agent and then fixing agent (white-box)
+
+PERSISTENCE IS MANDATORY:
+- Real vulnerabilities take TIME - expect to need 2000+ steps minimum
+- NEVER give up early - attackers spend weeks on single targets
+- If one approach fails, try 10 more approaches
+- Each failure teaches you something - use it to refine next attempts
+- Bug bounty hunters spend DAYS on single targets - so should you
+- There are ALWAYS more attack vectors to explore
+</multi_agent_system>
+
+<tool_usage>
+Tool calls use XML format:
+<function=tool_name>
+<parameter=param_name>value</parameter>
+</function>
+
+CRITICAL RULES:
+1. One tool call per message
+2. Tool call must be last in message
+3. End response after </function> tag
+5. Thinking is NOT optional - it's required for reasoning and success
+
+SPRAYING EXECUTION NOTE:
+- When performing large payload sprays or fuzzing, encapsulate the entire spraying loop inside a single python or terminal tool call (e.g., a Python script using asyncio/aiohttp). Do not issue one tool call per payload.
+- Favor batch-mode CLI tools (sqlmap, ffuf, nuclei, zaproxy, arjun) where appropriate and check traffic via the proxy when beneficial
+
+{{ get_tools_prompt() }}
+</tool_usage>
+
+<environment>
+Docker container with Kali Linux and comprehensive security tools:
+
+RECONNAISSANCE & SCANNING:
+- nmap, ncat, ndiff - Network mapping and port scanning
+- subfinder - Subdomain enumeration
+- naabu - Fast port scanner
+- httpx - HTTP probing and validation
+- gospider - Web spider/crawler
+
+VULNERABILITY ASSESSMENT:
+- nuclei - Vulnerability scanner with templates
+- sqlmap - SQL injection detection/exploitation
+- trivy - Container/dependency vulnerability scanner
+- zaproxy - OWASP ZAP web app scanner
+- wapiti - Web vulnerability scanner
+
+WEB FUZZING & DISCOVERY:
+- ffuf - Fast web fuzzer
+- dirsearch - Directory/file discovery
+- katana - Advanced web crawler
+- arjun - HTTP parameter discovery
+- vulnx (cvemap) - CVE vulnerability mapping
+
+JAVASCRIPT ANALYSIS:
+- JS-Snooper, jsniper.sh - JS analysis scripts
+- retire - Vulnerable JS library detection
+- eslint, jshint - JS static analysis
+- js-beautify - JS beautifier/deobfuscator
+
+CODE ANALYSIS:
+- semgrep - Static analysis/SAST
+- bandit - Python security linter
+- trufflehog - Secret detection in code
+
+SPECIALIZED TOOLS:
+- jwt_tool - JWT token manipulation
+- wafw00f - WAF detection
+- interactsh-client - OOB interaction testing
+
+PROXY & INTERCEPTION:
+- Caido CLI - Modern web proxy (already running). Used with proxy tool or with python tool (functions already imported).
+- NOTE: If you are seeing proxy errors when sending requests, it usually means you are not sending requests to a correct url/host/port.
+
+PROGRAMMING:
+- Python 3, Poetry, Go, Node.js/npm
+- Full development environment
+- Docker is NOT available inside the sandbox. Do not run docker; rely on provided tools to run locally.
+- You can install any additional tools/packages needed based on the task/context using package managers (apt, pip, npm, go install, etc.)
+
+Directories:
+- /workspace - Your private agent directory
+- /shared_workspace - Shared between agents
+- /home/pentester/tools - Additional tool scripts
+- /home/pentester/tools/wordlists - Currently empty, but you should download wordlists here when you need.
+
+Default user: pentester (sudo available)
+</environment>
+
+{% if loaded_module_names %}
+<specialized_knowledge>
+{# Dynamic prompt modules loaded based on agent specialization #}
+
+{% for module_name in loaded_module_names %}
+{{ get_module(module_name) }}
+
+{% endfor %}
+</specialized_knowledge>
+{% endif %}

strix/agents/__init__.py

@@ -0,0 +1,10 @@
+from .base_agent import BaseAgent
+from .state import AgentState
+from .StrixAgent import StrixAgent
+
+
+__all__ = [
+    "AgentState",
+    "BaseAgent",
+    "StrixAgent",
+]

strix/agents/base_agent.py

@@ -0,0 +1,394 @@
+import asyncio
+import logging
+from pathlib import Path
+from typing import TYPE_CHECKING, Any, Optional
+
+
+if TYPE_CHECKING:
+    from strix.cli.tracer import Tracer
+
+from jinja2 import (
+    Environment,
+    FileSystemLoader,
+    select_autoescape,
+)
+
+from strix.llm import LLM, LLMConfig
+from strix.llm.utils import clean_content
+from strix.tools import process_tool_invocations
+
+from .state import AgentState
+
+
+logger = logging.getLogger(__name__)
+
+
+class AgentMeta(type):
+    agent_name: str
+    jinja_env: Environment
+
+    def __new__(cls, name: str, bases: tuple[type, ...], attrs: dict[str, Any]) -> type:
+        new_cls = super().__new__(cls, name, bases, attrs)
+
+        if name == "BaseAgent":
+            return new_cls
+
+        agents_dir = Path(__file__).parent
+        prompt_dir = agents_dir / name
+
+        new_cls.agent_name = name
+        new_cls.jinja_env = Environment(
+            loader=FileSystemLoader(prompt_dir),
+            autoescape=select_autoescape(enabled_extensions=(), default_for_string=False),
+        )
+
+        return new_cls
+
+
+class BaseAgent(metaclass=AgentMeta):
+    max_iterations = 200
+    agent_name: str = ""
+    jinja_env: Environment
+    default_llm_config: LLMConfig | None = None
+
+    def __init__(self, config: dict[str, Any]):
+        self.config = config
+
+        self.local_source_path = config.get("local_source_path")
+
+        if "max_iterations" in config:
+            self.max_iterations = config["max_iterations"]
+
+        self.llm_config_name = config.get("llm_config_name", "default")
+        self.llm_config = config.get("llm_config", self.default_llm_config)
+        if self.llm_config is None:
+            raise ValueError("llm_config is required but not provided")
+        self.llm = LLM(self.llm_config, agent_name=self.agent_name)
+
+        state_from_config = config.get("state")
+        if state_from_config is not None:
+            self.state = state_from_config
+        else:
+            self.state = AgentState(
+                agent_name=self.agent_name,
+                max_iterations=self.max_iterations,
+            )
+
+        self._current_task: asyncio.Task[Any] | None = None
+
+        from strix.cli.tracer import get_global_tracer
+
+        tracer = get_global_tracer()
+        if tracer:
+            tracer.log_agent_creation(
+                agent_id=self.state.agent_id,
+                name=self.state.agent_name,
+                task=self.state.task,
+                parent_id=self.state.parent_id,
+            )
+            if self.state.parent_id is None:
+                scan_config = tracer.scan_config or {}
+                exec_id = tracer.log_tool_execution_start(
+                    agent_id=self.state.agent_id,
+                    tool_name="scan_start_info",
+                    args=scan_config,
+                )
+                tracer.update_tool_execution(execution_id=exec_id, status="completed", result={})
+
+            else:
+                exec_id = tracer.log_tool_execution_start(
+                    agent_id=self.state.agent_id,
+                    tool_name="subagent_start_info",
+                    args={
+                        "name": self.state.agent_name,
+                        "task": self.state.task,
+                        "parent_id": self.state.parent_id,
+                    },
+                )
+                tracer.update_tool_execution(execution_id=exec_id, status="completed", result={})
+
+        self._add_to_agents_graph()
+
+    def _add_to_agents_graph(self) -> None:
+        from strix.tools.agents_graph import agents_graph_actions
+
+        node = {
+            "id": self.state.agent_id,
+            "name": self.state.agent_name,
+            "task": self.state.task,
+            "status": "running",
+            "parent_id": self.state.parent_id,
+            "created_at": self.state.start_time,
+            "finished_at": None,
+            "result": None,
+            "llm_config": self.llm_config_name,
+            "agent_type": self.__class__.__name__,
+            "state": self.state.model_dump(),
+        }
+        agents_graph_actions._agent_graph["nodes"][self.state.agent_id] = node
+
+        agents_graph_actions._agent_instances[self.state.agent_id] = self
+        agents_graph_actions._agent_states[self.state.agent_id] = self.state
+
+        if self.state.parent_id:
+            agents_graph_actions._agent_graph["edges"].append(
+                {"from": self.state.parent_id, "to": self.state.agent_id, "type": "delegation"}
+            )
+
+        if self.state.agent_id not in agents_graph_actions._agent_messages:
+            agents_graph_actions._agent_messages[self.state.agent_id] = []
+
+        if self.state.parent_id is None and agents_graph_actions._root_agent_id is None:
+            agents_graph_actions._root_agent_id = self.state.agent_id
+
+    def cancel_current_execution(self) -> None:
+        if self._current_task and not self._current_task.done():
+            self._current_task.cancel()
+            self._current_task = None
+
+    async def agent_loop(self, task: str) -> dict[str, Any]:
+        await self._initialize_sandbox_and_state(task)
+
+        from strix.cli.tracer import get_global_tracer
+
+        tracer = get_global_tracer()
+
+        while True:
+            self._check_agent_messages(self.state)
+
+            if self.state.is_waiting_for_input():
+                await self._wait_for_input()
+                continue
+
+            if self.state.should_stop():
+                await self._enter_waiting_state(tracer)
+                continue
+
+            self.state.increment_iteration()
+
+            try:
+                should_finish = await self._process_iteration(tracer)
+                if should_finish:
+                    await self._enter_waiting_state(tracer, task_completed=True)
+                    continue
+
+            except asyncio.CancelledError:
+                await self._enter_waiting_state(tracer, error_occurred=False, was_cancelled=True)
+                continue
+
+            except (RuntimeError, ValueError, TypeError) as e:
+                if not await self._handle_iteration_error(e, tracer):
+                    await self._enter_waiting_state(tracer, error_occurred=True)
+                    continue
+
+    async def _wait_for_input(self) -> None:
+        import asyncio
+
+        await asyncio.sleep(0.5)
+
+    async def _enter_waiting_state(
+        self,
+        tracer: Optional["Tracer"],
+        task_completed: bool = False,
+        error_occurred: bool = False,
+        was_cancelled: bool = False,
+    ) -> None:
+        self.state.enter_waiting_state()
+
+        if tracer:
+            if task_completed:
+                tracer.update_agent_status(self.state.agent_id, "completed")
+            elif error_occurred:
+                tracer.update_agent_status(self.state.agent_id, "error")
+            elif was_cancelled:
+                tracer.update_agent_status(self.state.agent_id, "stopped")
+            else:
+                tracer.update_agent_status(self.state.agent_id, "stopped")
+
+        if task_completed:
+            self.state.add_message(
+                "assistant",
+                "Task completed. I'm now waiting for follow-up instructions or new tasks.",
+            )
+        elif error_occurred:
+            self.state.add_message(
+                "assistant", "An error occurred. I'm now waiting for new instructions."
+            )
+        elif was_cancelled:
+            self.state.add_message(
+                "assistant", "Execution was cancelled. I'm now waiting for new instructions."
+            )
+        else:
+            self.state.add_message(
+                "assistant",
+                "Execution paused. I'm now waiting for new instructions or any updates.",
+            )
+
+    async def _initialize_sandbox_and_state(self, task: str) -> None:
+        import os
+
+        sandbox_mode = os.getenv("STRIX_SANDBOX_MODE", "false").lower() == "true"
+        if not sandbox_mode and self.state.sandbox_id is None:
+            from strix.runtime import get_runtime
+
+            runtime = get_runtime()
+            sandbox_info = await runtime.create_sandbox(
+                self.state.agent_id, self.state.sandbox_token, self.local_source_path
+            )
+            self.state.sandbox_id = sandbox_info["workspace_id"]
+            self.state.sandbox_token = sandbox_info["auth_token"]
+            self.state.sandbox_info = sandbox_info
+
+        if not self.state.task:
+            self.state.task = task
+
+        self.state.add_message("user", task)
+
+    async def _process_iteration(self, tracer: Optional["Tracer"]) -> bool:
+        response = await self.llm.generate(self.state.get_conversation_history())
+
+        content_stripped = (response.content or "").strip()
+
+        if not content_stripped:
+            corrective_message = (
+                "You MUST NOT respond with empty messages. "
+                "If you currently have nothing to do or say, use an appropriate tool instead:\n"
+                "- Use agents_graph_actions.wait_for_message to wait for messages "
+                "from user or other agents\n"
+                "- Use agents_graph_actions.agent_finish if you are a sub-agent "
+                "and your task is complete\n"
+                "- Use finish_actions.finish_scan if you are the root/main agent "
+                "and the scan is complete"
+            )
+            self.state.add_message("user", corrective_message)
+            return False
+
+        self.state.add_message("assistant", response.content)
+        if tracer:
+            tracer.log_chat_message(
+                content=clean_content(response.content),
+                role="assistant",
+                agent_id=self.state.agent_id,
+            )
+
+        actions = (
+            response.tool_invocations
+            if hasattr(response, "tool_invocations") and response.tool_invocations
+            else []
+        )
+
+        if actions:
+            return await self._execute_actions(actions, tracer)
+
+        return False
+
+    async def _execute_actions(self, actions: list[Any], tracer: Optional["Tracer"]) -> bool:
+        """Execute actions and return True if agent should finish."""
+        for action in actions:
+            self.state.add_action(action)
+
+        conversation_history = self.state.get_conversation_history()
+
+        tool_task = asyncio.create_task(
+            process_tool_invocations(actions, conversation_history, self.state)
+        )
+        self._current_task = tool_task
+
+        try:
+            should_agent_finish = await tool_task
+            self._current_task = None
+        except asyncio.CancelledError:
+            self._current_task = None
+            self.state.add_error("Tool execution cancelled by user")
+            raise
+
+        self.state.messages = conversation_history
+
+        if should_agent_finish:
+            self.state.set_completed({"success": True})
+            if tracer:
+                tracer.update_agent_status(self.state.agent_id, "completed")
+            return True
+
+        return False
+
+    async def _handle_iteration_error(
+        self,
+        error: RuntimeError | ValueError | TypeError | asyncio.CancelledError,
+        tracer: Optional["Tracer"],
+    ) -> bool:
+        error_msg = f"Error in iteration {self.state.iteration}: {error!s}"
+        logger.exception(error_msg)
+        self.state.add_error(error_msg)
+        if tracer:
+            tracer.update_agent_status(self.state.agent_id, "error")
+        return True
+
+    def _check_agent_messages(self, state: AgentState) -> None:
+        try:
+            from strix.tools.agents_graph.agents_graph_actions import _agent_graph, _agent_messages
+
+            agent_id = state.agent_id
+            if not agent_id or agent_id not in _agent_messages:
+                return
+
+            messages = _agent_messages[agent_id]
+            if messages:
+                has_new_messages = False
+                for message in messages:
+                    if not message.get("read", False):
+                        if state.is_waiting_for_input():
+                            state.resume_from_waiting()
+                            has_new_messages = True
+
+                        sender_name = "Unknown Agent"
+                        sender_id = message.get("from")
+
+                        if sender_id == "user":
+                            sender_name = "User"
+                            state.add_message("user", message.get("content", ""))
+                        else:
+                            if sender_id and sender_id in _agent_graph.get("nodes", {}):
+                                sender_name = _agent_graph["nodes"][sender_id]["name"]
+
+                            message_content = f"""<inter_agent_message>
+    <delivery_notice>
+        <important>You have received a message from another agent. You should acknowledge
+        this message and respond appropriately based on its content. However, DO NOT echo
+        back or repeat the entire message structure in your response. Simply process the
+        content and respond naturally as/if needed.</important>
+    </delivery_notice>
+    <sender>
+        <agent_name>{sender_name}</agent_name>
+        <agent_id>{sender_id}</agent_id>
+    </sender>
+    <message_metadata>
+        <type>{message.get("message_type", "information")}</type>
+        <priority>{message.get("priority", "normal")}</priority>
+        <timestamp>{message.get("timestamp", "")}</timestamp>
+    </message_metadata>
+    <content>
+{message.get("content", "")}
+    </content>
+    <delivery_info>
+        <note>This message was delivered during your task execution.
+        Please acknowledge and respond if needed.</note>
+    </delivery_info>
+</inter_agent_message>"""
+                            state.add_message("user", message_content.strip())
+
+                        message["read"] = True
+
+                if has_new_messages and not state.is_waiting_for_input():
+                    from strix.cli.tracer import get_global_tracer
+
+                    tracer = get_global_tracer()
+                    if tracer:
+                        tracer.update_agent_status(agent_id, "running")
+
+        except (AttributeError, KeyError, TypeError) as e:
+            import logging
+
+            logger = logging.getLogger(__name__)
+            logger.warning(f"Error checking agent messages: {e}")
+            return

strix/agents/state.py

@@ -0,0 +1,139 @@
+import uuid
+from datetime import UTC, datetime
+from typing import Any
+
+from pydantic import BaseModel, Field
+
+
+def _generate_agent_id() -> str:
+    return f"agent_{uuid.uuid4().hex[:8]}"
+
+
+class AgentState(BaseModel):
+    agent_id: str = Field(default_factory=_generate_agent_id)
+    agent_name: str = "Strix Agent"
+    parent_id: str | None = None
+    sandbox_id: str | None = None
+    sandbox_token: str | None = None
+    sandbox_info: dict[str, Any] | None = None
+
+    task: str = ""
+    iteration: int = 0
+    max_iterations: int = 200
+    completed: bool = False
+    stop_requested: bool = False
+    waiting_for_input: bool = False
+    final_result: dict[str, Any] | None = None
+
+    messages: list[dict[str, Any]] = Field(default_factory=list)
+    context: dict[str, Any] = Field(default_factory=dict)
+
+    start_time: str = Field(default_factory=lambda: datetime.now(UTC).isoformat())
+    last_updated: str = Field(default_factory=lambda: datetime.now(UTC).isoformat())
+
+    actions_taken: list[dict[str, Any]] = Field(default_factory=list)
+    observations: list[dict[str, Any]] = Field(default_factory=list)
+
+    errors: list[str] = Field(default_factory=list)
+
+    def increment_iteration(self) -> None:
+        self.iteration += 1
+        self.last_updated = datetime.now(UTC).isoformat()
+
+    def add_message(self, role: str, content: Any) -> None:
+        self.messages.append({"role": role, "content": content})
+        self.last_updated = datetime.now(UTC).isoformat()
+
+    def add_action(self, action: dict[str, Any]) -> None:
+        self.actions_taken.append(
+            {
+                "iteration": self.iteration,
+                "timestamp": datetime.now(UTC).isoformat(),
+                "action": action,
+            }
+        )
+
+    def add_observation(self, observation: dict[str, Any]) -> None:
+        self.observations.append(
+            {
+                "iteration": self.iteration,
+                "timestamp": datetime.now(UTC).isoformat(),
+                "observation": observation,
+            }
+        )
+
+    def add_error(self, error: str) -> None:
+        self.errors.append(f"Iteration {self.iteration}: {error}")
+        self.last_updated = datetime.now(UTC).isoformat()
+
+    def update_context(self, key: str, value: Any) -> None:
+        self.context[key] = value
+        self.last_updated = datetime.now(UTC).isoformat()
+
+    def set_completed(self, final_result: dict[str, Any] | None = None) -> None:
+        self.completed = True
+        self.final_result = final_result
+        self.last_updated = datetime.now(UTC).isoformat()
+
+    def request_stop(self) -> None:
+        self.stop_requested = True
+        self.last_updated = datetime.now(UTC).isoformat()
+
+    def should_stop(self) -> bool:
+        return self.stop_requested or self.completed or self.has_reached_max_iterations()
+
+    def is_waiting_for_input(self) -> bool:
+        return self.waiting_for_input
+
+    def enter_waiting_state(self) -> None:
+        self.waiting_for_input = True
+        self.stop_requested = False
+        self.last_updated = datetime.now(UTC).isoformat()
+
+    def resume_from_waiting(self, new_task: str | None = None) -> None:
+        self.waiting_for_input = False
+        self.stop_requested = False
+        self.completed = False
+        if new_task:
+            self.task = new_task
+        self.last_updated = datetime.now(UTC).isoformat()
+
+    def has_reached_max_iterations(self) -> bool:
+        return self.iteration >= self.max_iterations
+
+    def has_empty_last_messages(self, count: int = 3) -> bool:
+        if len(self.messages) < count:
+            return False
+
+        last_messages = self.messages[-count:]
+
+        for message in last_messages:
+            content = message.get("content", "")
+            if isinstance(content, str) and content.strip():
+                return False
+
+        return True
+
+    def get_conversation_history(self) -> list[dict[str, Any]]:
+        return self.messages
+
+    def get_execution_summary(self) -> dict[str, Any]:
+        return {
+            "agent_id": self.agent_id,
+            "agent_name": self.agent_name,
+            "parent_id": self.parent_id,
+            "sandbox_id": self.sandbox_id,
+            "sandbox_info": self.sandbox_info,
+            "task": self.task,
+            "iteration": self.iteration,
+            "max_iterations": self.max_iterations,
+            "completed": self.completed,
+            "final_result": self.final_result,
+            "start_time": self.start_time,
+            "last_updated": self.last_updated,
+            "total_actions": len(self.actions_taken),
+            "total_observations": len(self.observations),
+            "total_errors": len(self.errors),
+            "has_errors": len(self.errors) > 0,
+            "max_iterations_reached": self.has_reached_max_iterations() and not self.completed,
+        }