The application uses a default or weak authentication token for its API endpoints, which can be easily guessed or intercepted in transit.

The application does not implement any form of CSRF protection. This allows an attacker to perform actions on behalf of a legitimate user without their consent, such as changing the password or making transactions.

The application uses a hardcoded OpenAI API key, which is stored in the source code. An attacker can easily extract this key from the repository and use it to make unauthorized requests to the OpenAI service.

The application allows for the creation of indexes on a MongoDB collection without proper validation or authorization. An attacker can exploit this by crafting a malicious index specification, which could lead to denial of service (DoS) attacks or unauthorized data access.

The application exposes endpoints that perform sensitive operations without requiring authentication. This allows unauthenticated users to modify critical data or system configurations.

The code does not properly sanitize user input for prompt injection patterns. An attacker can bypass the detection mechanism by crafting a request message that contains disallowed patterns, which would then be executed in the context of the application without proper validation.

The application does not enforce authentication for operations that modify or access sensitive data. An attacker can exploit this by manipulating requests to perform actions such as creating, updating, or deleting records without proper authorization.

The function `fetch_video_url` retrieves a video URL from MongoDB using user-controlled input (`event` and `source_id`). An attacker can manipulate these inputs to retrieve arbitrary documents, potentially leading to unauthorized data exposure.

The function `change_value` uses a user-controlled input (`value`) without proper validation. An attacker can manipulate this value to bypass intended checks, leading to incorrect data interpretation and potential exploitation.

The function `get_graph_data` retrieves multiple documents from MongoDB using a user-controlled input (`source_id`), which can be manipulated by an attacker to retrieve unauthorized data.

The code allows deserialization of user-controlled input without proper validation, which can lead to arbitrary code execution or other malicious actions. This is particularly dangerous because it does not enforce any security checks on the deserialized data.

The `generate_sql_query` method constructs a SQL query using user-controlled input from the 'question' parameter without proper sanitization or parameterization. An attacker can manipulate this input to execute arbitrary SQL commands, leading to SQL injection.

The codebase contains hardcoded API keys in the configuration files. An attacker can easily exploit these by using Burp Suite or other tools to intercept and modify the requests, leading to unauthorized access to sensitive data.

The application allows external service access without proper authentication, exposing it to potential SSRF attacks where an attacker can manipulate the request to access internal services.

The application uses a hardcoded fallback time of 60 minutes for event searches if the extracted time from LLM is not available. This can lead to situations where an attacker can craft queries that default to a longer or shorter timeframe, potentially accessing more data than intended.

The application sends user-controlled input directly to an external LLM service without proper validation or sanitization, which can lead to command injection attacks.

The `process_event_query` method does not properly validate the user query, allowing for SSRF attacks. An attacker can craft a query that targets internal services or resources, potentially leading to unauthorized data exposure or system compromise.

The application uses a hardcoded API key for the Gemini service, which is stored in an environment variable. This makes it susceptible to attacks where an attacker can easily obtain and use this API key by accessing the source code.

The application allows user input to select the Gemini model, which is used without validation or sanitization. This can lead to command injection attacks if an attacker inputs malicious data.

The 'PromptResponse' model allows for the creation of new prompts without proper authentication. An attacker can exploit this by sending a crafted request to add arbitrary prompt data, leading to unauthorized access or manipulation of system data.

The application does not properly validate user input for SQL queries. An attacker can manipulate the `question` field in the `SqlQueryInput` model, which is used to construct a SQL query without proper sanitization or escaping. This can lead to SQL injection attacks where the attacker can execute arbitrary SQL commands on the database server.

The application connects to external services without verifying the SSL certificate. This allows an attacker to intercept and decrypt sensitive communications, including authentication tokens.

The application exposes sensitive operations without requiring authentication, which can be exploited by unauthenticated users to perform actions they should not have access to.

The application uses a default configuration for MongoDB, which is not secure. Attackers can exploit this by accessing the database without authentication through an unauthenticated network connection.

The application performs sensitive operations without requiring authentication. This includes administrative tasks that could be abused by an attacker.

The application transmits credentials in cleartext over unencrypted connections. This includes MongoDB connection strings and potentially other sensitive information.

The `execute_query` method constructs and executes SQL queries using user-controlled input without proper sanitization or parameterization. An attacker can manipulate the query string to perform SQL injection attacks, leading to unauthorized data access, manipulation, or deletion.

The application uses hardcoded credentials and default settings for the MySQL connection, which is insecure. An attacker can easily exploit these credentials to gain unauthorized access to the database.

The MySQL connection is configured to use cleartext communication without SSL/TLS encryption. This makes the data transmitted between the application and the database vulnerable to interception attacks.

The application allows user-controlled input to be directly included in SQL queries without proper sanitization or parameterization. An attacker can manipulate the query by injecting malicious SQL code, which could lead to unauthorized data access, modification, or deletion.

The application returns detailed error messages that include sensitive information such as database schema details, which can be exploited by an attacker to gain insights into the internal structure of the database.

The code does not properly sanitize and validate user-controlled input when resolving file paths. An attacker can manipulate the 'key' parameter in the request to specify arbitrary directory traversal sequences, allowing them to read or write files outside of the intended data/queryNode/{module}/{sub_folder} directories.

The API does not require authentication for actions that modify or delete data, such as 'delete' and 'reactivate'. An attacker can send requests to these endpoints with arbitrary custId and processCd values to perform unauthorized operations on prompts.

The API exposes endpoints like `/prompts/action` and `/copy_prompt` without proper security configurations, allowing unauthenticated access. This includes missing authentication, authorization checks, and secure configuration settings.

The API endpoints '/get_summary' and '/get_analytic_summary' do not require authentication. An attacker can make unauthorized requests to these endpoints, potentially accessing sensitive information or performing actions that were intended for authorized users only.

The application contains a hardcoded API key in the source code. An attacker can easily discover this key and use it without any authorization, leading to unauthorized access and potential data leakage.

The application makes external requests without verifying the SSL certificate, which could be exploited by a man-in-the-middle attack. This exposes the system to potential eavesdropping and data manipulation.

The function `_validate_message` does not properly sanitize user-controlled input before passing it to the LLM service. An attacker can inject malicious payloads into the prompt, leading to command injection or other harmful effects.

The application accepts user input directly in the process of training an AI model without proper validation or sanitization. An attacker can provide malicious inputs that could lead to incorrect model predictions, data breaches, and system compromise.

The application exposes sensitive data through direct object references without proper authorization checks. An attacker can exploit this by manipulating URLs or request parameters to access unauthorized data.

The application performs sensitive operations without requiring authentication, exposing it to attacks that could manipulate critical data or functions.

The application uses a hardcoded API key for authentication, which is stored in the source code. An attacker can easily discover this key and use it to access the service without authorization.

The application performs sensitive operations without requiring authentication. This includes administrative tasks that could be exploited by an attacker to gain unauthorized access.

The application connects to a MongoDB database without any authentication or SSL verification. This configuration allows unauthenticated access to the database, which could be exploited by an attacker to gain unauthorized access to sensitive data.

The endpoint '/video-summary' accepts a user-controlled input for the 'source_req.videoFile' parameter, which is directly used in file download and processing without proper validation or sanitization. An attacker can provide a malicious URL to download arbitrary files from the server, potentially leading to unauthorized access, data leakage, or remote code execution if the Gemini API endpoint is exploitable.

The application configures MongoDB without authentication, exposing the database to unauthenticated users. Any attacker can connect to the MongoDB instance and perform any operations allowed by the user permissions in the database.

The API endpoints '/find_image' and '/find_events' do not require authentication. An attacker can send requests to these endpoints without any credentials, potentially leading to unauthorized access and data leakage.

The code logs the entire request body and response body without any filtering or sanitization. This includes potentially sensitive information such as user input, which could be logged in cleartext if not properly handled.

The application does not properly validate the API key provided in the request header. An attacker can provide any value as an API key, and it will be accepted by the system due to the use of a constant-time comparison function that does not reveal its length. This allows for unauthenticated access to the API.

The application uses a whitelist for IP addresses that is configured with hardcoded values from ALLOWED_IPS. This list includes localhost, 127.0.0.1, and ::1 which are not suitable for production environments where access should be restricted to specific networks or ranges.

The rate limiter is configured to use a global identifier for all requests, which can be easily bypassed. An attacker could repeatedly make requests with the same identifier (e.g., 'global') until the rate limit expires and bypasses the intended protection.

The middleware does not enforce authentication for requests to sensitive endpoints. An attacker can bypass the request ID generation and validation mechanisms by simply manipulating the 'X-Request-ID' header, leading to potential unauthorized access or data leakage.

The application uses a hardcoded API key for authentication, which exposes it to potential misuse and abuse if the key is discovered by an attacker.

The code allows for the creation of indexes on 'custId' and 'processCd' fields without proper validation or authentication. An attacker can exploit this by crafting a malicious document to insert into the collection, leading to unauthorized access and potential data breach.

The application contains a hardcoded API key in the source code, which can be easily accessed and used by anyone who gains access to the repository or the deployed application.

The application allows unrestricted access to a third-party service without proper authentication, which can be exploited by attackers to gain unauthorized access.

The application transmits credentials in cleartext over HTTP, which can be intercepted and read by an attacker using man-in-the-middle attacks.

The function `mask_api_key` does not provide adequate masking for API keys. It only masks the first 8 characters of the key, which can be easily reconstructed by an attacker with basic knowledge of the data format.

The function `sanitize_for_log` does not check the length of the sanitized data before logging it. This could lead to a situation where sensitive information is logged in full, potentially compromising security.

The application does not properly handle cases where the event graph is not found in MongoDB. It returns a generic error message without any specific details, which can be exploited by an attacker to infer information about the existence and structure of the data stored in the database.

[ { "vulnerability_name": "Insecure Content Security Policy Configuration", "cwe_id": "CWE-74", "owasp_category": "A05:2021-Security Misconfiguration", "severity": "High", "description": "The application sets a lax Content Security Policy (CSP) header which allows 'unsafe-inli...