CustomGPT

A CustomGPT is a tailored, specialized version of a Generative Pre-trained Transformer (GPT) model, such as those developed by OpenAI, that has been specifically configured and trained for a niche function or domain, often by uploading proprietary knowledge and connecting to external systems.

In the context of cybersecurity, a CustomGPT is an AI assistant specifically built and deployed to augment security operations, analysis, and defense mechanisms within an organization.

Customization Components

The power and risk of a CustomGPT lie in the specific elements that are added to the foundational large language model (LLM):

• Knowledge Base: The model is injected with specific, private, and relevant organizational data to form its specialized knowledge. In a cybersecurity context, this might include internal incident response playbooks, security policies, proprietary threat intelligence feeds, internal network diagrams, or logs. This knowledge allows the GPT to provide contextually accurate answers and perform specialized analysis that a general-purpose model cannot.

• Custom Instructions: Explicit, detailed instructions define the GPT's persona, its rules of engagement, its tone, and most importantly, its security-focused behavior. For instance, instructions might enforce the principle of least privilege when accessing external systems or mandate strict adherence to data handling policies.

• Actions (API Integrations): This is the ability to connect the CustomGPT to external applications or systems via APIs. In cybersecurity, Actions can enable the GPT to query a vulnerability database, retrieve real-time network logs from a Security Information and Event Management (SIEM) system, or trigger automated responses in an endpoint detection and response (EDR) platform.

Use Cases and Benefits in Cybersecurity

CustomGPTs are used to enhance and automate various security functions:

• Threat Intelligence and Analysis: Trained on internal and external threat data, a CustomGPT can rapidly summarize complex threat reports, link a detected Indicator of Compromise (IOC) to known threat actor groups, or analyze malware code snippets (safely using its code interpreter capability).

• Vulnerability Management: It can be used to prioritize vulnerabilities based on internal asset risk scores, regulatory compliance requirements, and real-time exploitability data by integrating with vulnerability scanners.

• Incident Response: A CustomGPT can serve as a "Security Operations Center (SOC) Copilot," providing analysts with instant access to relevant playbooks, summarizing incident timelines from log data, and generating standardized incident reports.

• Security Training and Awareness: It can act as a tailored educational tool, simulating phishing scenarios or explaining complex security concepts (like the steps of the MITRE ATT&CK framework) based on the organization's specific defenses.

Associated Cybersecurity Risks

While beneficial, the use of CustomGPTs introduces new vectors of risk that require careful management:

• Data Leakage/Exfiltration: Because the CustomGPT is trained on or given access to sensitive, proprietary data (e.g., PII, internal passwords, secret documents), an attacker who successfully manipulates the model through prompt injection could potentially bypass security controls and trick the GPT into revealing this sensitive information.

• Indirect Prompt Injection: This occurs when a malicious command is embedded in a data source (like a document or a web page) that the CustomGPT is instructed to process, leading the model to execute the attacker's instruction when it next interacts with a user.

• Misconfigured Actions/APIs: If the CustomGPT is granted overly permissive access via its connected Actions, a compromised or manipulated GPT could be used to execute unauthorized commands on critical internal systems, leading to severe compromise or data exfiltration. This emphasizes the need for strict access control and least privilege application.

• Supply Chain Risk: The security of the CustomGPT is dependent on the security practices of the underlying LLM provider (e.g., OpenAI) and any third-party APIs connected via Actions.

The ThreatNG platform, an all-in-one external attack surface management, digital risk protection, and security ratings solution , would help an organization externally identify risks associated with a CustomGPT by performing unauthenticated, outside-in discovery and assessment across various modules. This process essentially maps the digital footprint of the organization to uncover any publicly exposed artifacts related to its AI deployment.

External Discovery and Assessment

ThreatNG performs a purely external unauthenticated discovery to build a comprehensive inventory of the organization's digital assets, including its external attack surface. The platform's ability to identify the underlying technology stack and exposed subdomains is critical in pinpointing CustomGPT-related risks.

Technology Stack and Vendor Identification

The Domain Record Analysis within the Domain Intelligence module and the Technology Stack Investigation Module would be the primary mechanisms for identifying the platform hosting the CustomGPT.

• Vendor Identification: ThreatNG can externally identify AI Model & Platform Providers as part of its Vendors and Technology Identification. Specifically, its list includes OpenAI and CustomGPT , making it capable of recognizing if a foundational platform for CustomGPTs is being used.

• AI Development Tools: The platform also uncovers technologies used in the development and operation of the CustomGPT, such as those in the AI Development & MLOps sub-category, which includes vendors like LangChain and Pinecone. Uncovering these tools indicates a heavy reliance on custom AI development, suggesting a CustomGPT deployment.

• Example of External Assessment: If ThreatNG detects the presence of the OpenAI vendor or a related AI Development & MLOps technology on a subdomain via its unauthenticated discovery, this immediately raises a red flag. The subsequent external assessment would focus on this subdomain to find potential exposures related to the CustomGPT itself.

Subdomain and Sensitive Code Exposures

The Subdomain Intelligence module is key to identifying improperly configured access points to the CustomGPT, which may reside on a subdomain.

• Subdomain Takeover Susceptibility: This assessment checks for CNAME records pointing to unclaimed third-party services that a CustomGPT might use for its knowledge base or external actions (e.g., a PaaS like Heroku or Vercel or a CDN like Cloudfront). If the CustomGPT's access point or associated resource has a "dangling DNS" state, it confirms a critical risk.

• Sensitive Code Exposure: The Code Repository Exposure module actively hunts for public code repositories containing exposed secrets. A CustomGPT's security relies heavily on API Keys and Access Credentials to connect to internal systems or its knowledge base. ThreatNG can uncover a vast array of exposed credentials, including Stripe API key, Google OAuth Key, AWS Access Key ID, and Slack Token. A leak of a Slack Webhook could expose the CustomGPT's integrated communication channel, while a leaked AWS Access Key ID could grant an attacker access to the knowledge base stored in an AWS S3 bucket.

Investigation Modules and Intelligence Repositories

ThreatNG’s advanced search capabilities and deep intelligence repositories provide the context needed to qualify and prioritize CustomGPT-related risks.

Investigation Modules

• Advanced Search and Reconnaissance Hub: The Reconnaissance Hub and Advanced Search allow security teams to pivot instantly on "CustomGPT" or "OpenAI" as search terms across all discovery and assessment results. For example, a security analyst could use Advanced Search to quickly filter all Cloud and SaaS Exposure findings to find open cloud buckets that also contain emails or document files that are part of the CustomGPT's training data, thus accelerating threat validation.

• Online Sharing Exposure: The platform actively discovers an organization's entity presence in code-sharing platforms like Pastebin and GitHub Gist. If an employee used a code-sharing platform to post a CustomGPT configuration file containing a proprietary API endpoint or a database connection string (a common source of sensitive code exposure ), ThreatNG would flag it immediately.

Intelligence Repositories

• Dark Web Presence (DarCache Dark Web): The platform continuously monitors the Dark Web for organizational mentions. This is vital for a CustomGPT as threat actors may discuss tactics to exploit a known, specific CustomGPT deployment or sell compromised credentials explicitly linked to an internal AI platform.

• Compromised Credentials (DarCache Rupture): By checking against its repository of compromised credentials , ThreatNG identifies if login data for employees with access to the CustomGPT's configuration or external integrations (e.g., an IT Admin ) has been leaked, which directly increases the risk of an account takeover used to manipulate the AI.

Reporting, Continuous Monitoring, and Prioritization

• Continuous Monitoring: ThreatNG provides continuous monitoring of the external attack surface. This ensures that any new subdomains or code exposures related to a CustomGPT development or deployment are caught immediately, rather than during periodic scans.

• Prioritized Reporting and Knowledgebase: Findings are delivered in Prioritized Reports (High, Medium, Low) , helping security leaders quickly focus on the most critical risks to the CustomGPT. The embedded Knowledgebase provides contextual Reasoning for the risk and Recommendations on how to reduce it, such as advice on securing the exposed cloud buckets used for the CustomGPT's knowledge base.

• Legal-Grade Attribution: ThreatNG's Context Engine™ provides Legal-Grade Attribution. This is crucial for a CustomGPT because it correlates a technical finding (like a leaked API key ) with legal or financial context , providing the absolute certainty security leaders need to justify the investment to remediate the leak before it allows an attacker to manipulate the CustomGPT.

Complementary Solutions

ThreatNG's external view can be significantly enhanced by the cooperation with complementary solutions.

• ThreatNG and a Security Information and Event Management (SIEM) Solution: ThreatNG identifies external risks like an exposed Git repository containing an internal CustomGPT API key. A SIEM solution, which monitors internal network and application logs, could then use this external finding as a high-fidelity alert. The SIEM could automatically search its internal logs for any unauthorized access attempts using that exposed API key, correlating the external threat with internal activity.

• ThreatNG and a Vulnerability and Risk Management (VRM) Solution: ThreatNG's Vulnerabilities repository includes data from NVD, EPSS, KEV, and Proof-of-Concept Exploits. If ThreatNG discovers a known vulnerability (KEV) on a web application hosting the CustomGPT's front-end interface, it can be flagged to a VRM solution. The VRM solution would then use that information to automatically ticket and prioritize the remediation of that specific vulnerability across the organization's entire portfolio, which ThreatNG's Overwatch can instantly assess.