Digital Risk Protection for AI
Digital Risk Protection (DRP) for AI is a specialized subset of the broader DRP discipline focused on proactively identifying, monitoring, and mitigating threats that target an organization's Artificial Intelligence (AI) assets and their associated digital footprint outside the corporate perimeter.
Unlike traditional perimeter security, DRP for AI assumes an attacker will leverage open-source intelligence (OSINT), public leaks, and shadow IT to compromise an AI system's integrity or leak proprietary data.
The primary focus areas for DRP in the AI context include:
AI Credential and Secret Leakage: Monitoring the open, deep, and dark web (including public code repositories, forums, and paste sites) for the unauthorized exposure of AI-specific secrets, such as API keys for Large Language Models (LLMs), service account credentials with access to model storage, and configuration files containing proprietary information.
Brand and Reputation Defense: Tracking for malicious or misleading domain name permutations, social media impersonations, or forum discussions that could lead to phishing attacks targeting employees with access to AI infrastructure, or that could compromise the trust in the organization's AI products.
Shadow AI and Endpoint Surveillance: Continuously discovering and mapping unmanaged or unauthorized AI endpoints, misconfigured cloud buckets, or publicly exposed development environments that pose a direct, unauthenticated risk to the AI supply chain or its training data.
Adversary Intelligence Gathering: Collecting intelligence on threat actor conversations, tactics, and ransomware events targeting AI infrastructure or specific AI vendors, providing preemptive insights that inform the organization’s defensive strategy.
By maintaining constant external vigilance, DRP for AI enables security teams to address threats originating from outside the firewall that could compromise the confidentiality, integrity, and availability of their AI assets.
ThreatNG, which is an all-in-one external attack surface management, digital risk protection, and security ratings solution, provides essential capabilities to mitigate Digital Risk Protection for AI by maintaining constant, unauthenticated vigilance outside the corporate perimeter. It is strategically focused on identifying the external exposures that enable credential theft, phishing, and brand compromise targeting AI assets.
External Discovery and Inventory
ThreatNG’s capability to perform purely external, unauthenticated discovery without connectors is fundamental to DRP for AI, as it maps public-facing AI assets and their associated exposures.
Technology Stack Identification: ThreatNG uncovers nearly 4,000 technologies, including the 265 technologies categorized as Artificial Intelligence, as well as vendors in AI Model & Platform Providers and AI Development & MLOps. This helps DRP teams inventory exposed AI assets and frameworks.
Domain Name Permutations: This module detects manipulations and additions to a domain, including homoglyphs and TLD swaps, using definable, packaged, targeted keywords (such as access and portal). This is critical for detecting phishing sites impersonating an organization's AI login or portal.
Example of ThreatNG Helping: ThreatNG discovers a domain permutation, ai-portal.com, that is deceptively similar to the organization's actual AI service login page. This immediate detection of a fraudulent asset is a core DRP function, preventing employee or customer credential theft.
External Assessment for Digital Risk
ThreatNG's security ratings quantify the external risks that are central to DRP for AI.
Non-Human Identity (NHI) Exposure: This critical governance metric quantifies vulnerability to threats from high-privilege machine identities, such as leaked API keys and service accounts. The discovery of exposed LLM access keys or service credentials is a primary concern for DRP.
BEC & Phishing Susceptibility: This rating is based on findings across Compromised Credentials (Dark Web Presence), Domain Name Permutations, and Domain Name Record Analysis (including missing DMARC and SPF records). These findings directly assess the organization's susceptibility to social engineering attacks targeting AI access.
Brand Damage Susceptibility: This rating is based on findings across Domain Name Permutations, Lawsuits, and Negative News. This helps DRP for AI teams monitor external chatter that could compromise the trust or reputation of their AI products.
Example of ThreatNG Helping: ThreatNG flags a high BEC & Phishing Susceptibility rating due to the discovery of leaked credentials and a missing DMARC record. This poor posture makes employees with access to AI infrastructure easy targets for credential-harvesting attacks.
Reporting and Continuous Monitoring
ThreatNG provides Continuous Monitoring of the external attack surface and digital risk, ensuring real-time awareness of exposures outside the firewall.
Reporting (Security Ratings and DRP Focus): ThreatNG provides the BEC & Phishing Susceptibility and Brand Damage Susceptibility ratings, which are direct measures of digital risk.
External Adversary View and MITRE ATT&CK Mapping: ThreatNG aligns the security posture with external threats by identifying how an adversary might achieve initial access (a key DRP concern) and establishes persistence, mapping these findings to MITRE ATT&CK techniques.
Investigation Modules
ThreatNG's Investigation Modules are essential DRP tools for locating leaked credentials and monitoring external chatter.
Dark Web Presence: This module proactively identifies organizational mentions of related people, places, or things, along with associated Compromised Credentials. This is vital for finding AI access credentials being traded or sold.
Sensitive Code Exposure: This module discovers public code repositories and explicitly looks for Access Credentials (various API Keys and Access Tokens) and Configuration Files. Finding a leaked LLM key here is a primary DRP success.
Social Media Investigation (Reddit and LinkedIn Discovery): Reddit Discovery transforms unmonitored public chatter into an early warning intelligence system for Narrative Risk, and LinkedIn Discovery identifies employees most susceptible to social engineering attacks.
Example of ThreatNG Helping: The Dark Web Presence module identifies a thread on a forum discussing an internal document leak. Simultaneously, Sensitive Code Exposure identifies a leaked GitHub Access Token belonging to a developer working on the AI pipeline, allowing the DRP team to immediately contain the credential and assess the potential for AI system compromise.
Intelligence Repositories
ThreatNG’s Intelligence Repositories (DarCache) provide the necessary contextual data to validate and prioritize digital risks.
Dark Web (DarCache Dark Web) and Compromised Credentials (DarCache Rupture): These repositories are the data sources for identifying leaked LLM keys and accounts used for AI access.
Ransomware Groups and Activities (DarCache Ransomware): Tracking over 70 ransomware gangs provides early warning if an AI vendor is targeted, which impacts your digital risk.
Complementary Solutions
ThreatNG's external discovery and risk intelligence provides verifiable evidence that enhances complementary solutions such as Threat Intelligence Platforms (TIPs) and Security Orchestration, Automation, and Response (SOAR) systems.
Complementary Solutions (TIPs): ThreatNG's discovery of leaked LLM keys via NHI Exposure or Sensitive Code Exposure provides high-fidelity, actionable threat intelligence. This external finding can be automatically fed into a TIP, enriching its intelligence feeds with contextually relevant, AI-specific risks that the organization needs to defend against.
Complementary Solutions (SOAR Systems): When ThreatNG identifies a high-risk event, such as a newly discovered phishing domain via Domain Name Permutations, the finding can trigger a SOAR playbook. The SOAR system automatically initiates a takedown request with the hosting registrar. It generates an internal alert to the IT team to blacklist the fraudulent domain, protecting employees from phishing attempts to obtain their AI access credentials.
